Jean-Pierre Patrice

Rodney Philip Gauthier

Jean Charles

Jérémy Agnès

Olivier Sébastien

Eric Jacques

Assia François

Jean Paul

Malliaras Georges

Jacques Moutte

Cr

Laurent Navarro

Gilles Neubert

Mines Saint-E ´ tienne Martha Orellano Carrasquilla

Mines Saint-E ´ tienne Martha Orellano
email: martha.orellano@emse.fr

Moutte Jacques

E ´ Tienne

Carrasquilla Vi

Anastasia Fabien

Nahla

Zeinab Benjamin

Marie Jérémy

Safi Camilo

Audrey

Omar Souraya

Maty, Cleo Jairo Papi

Carrasquilla Mines Saint-E ´ Tienne

Mines Saint-E ´ tienne Martha Orellano Carrasquilla

NEUBERT NIKOLOVSKI NORTIER

Keywords: SUBCRITERION 2, User resistance SUBCRITERION 2, availability

I have many people to thank, and I will try to summarize it into a few worlds. First, I would like to thank the jury for being able to review my thesis manuscript. Thanks to the reviewers, Maria Franca Norese and Tim McAloone for sharing with me years of expertise throughout their valuable remarks that provide me a critical regard of my work. Thanks for doing it with such an extraordinary kindness. Particularly, thanks to Maria Franca for submerging me in the discipline of multi-criteria decision aiding during my stage in Politecnico di Torino.

Thanks to the examiners, Giuditta Pezzotta, and Lilia Gzara

Auvergne Rhone-Alpes Region (France) supports this research through a doctoral thesis allocation into the ARC 8. The sponsors of this research within the framework of the PEAK Cluster: THESAME, Funds F2I/UIMM, French Plan d'Investissement d'Avenir and its financial operator Caisse des Dépôts, the ACE project of PFA (French Automotive Industry).

Introduction

La création de valeur durable traduit l'interêt des entreprises envers les objectifs du développement durable a ` travers des modèles économiques innovants.

Au-delà des interêts l'économiques, les entreprises dites durables, sont de plus en plus soucieuses de la protection de l'environnement et de la garantie du bien-être social. En accord avec la recherche academique, la creation de valeur durable peut être analysée a ` trois niveaux différents : l'entreprise, la chaîne logistique, et la société au sens large [START_REF] Boons | Business models for sustainable innovation: state-of-the-art and steps towards a research agenda[END_REF][START_REF] Bocken | A literature and practice review to develop sustainable business model archetypes[END_REF]. Tout d'abord, au niveau de l'entreprise, l'adoption d'une stratégie axée sur le développement durable représente une opportunité de s'aligner sur les tendances actuelles du marché, ainsi qu'une source precieuse d'avantage competitive [START_REF] Hart | Creating sustainable value[END_REF][START_REF] Matinheikki | From the profi of one toward benefitting many -Crafting a vision of shared value creation[END_REF][START_REF] Brown | Why do companies pursue collaborative circular oriented innovation?[END_REF]. Deuxièmement, au niveau de la chaîne logistique, la création de valeur durable nécessite de l'alignement stratégique des acteurs dans une dynamique de collaboration étroite, ayant pour but le partage des ressources et des responsabilités vis-a `-vis des besoins de durabilité [START_REF] Maestrini | Supply chain performance measurement systems: A systematic review and research agenda[END_REF][START_REF] Arnold | Fostering sustainability by linking co-creation and relationship management concepts[END_REF]. Enfin, la société comprend les acteurs non-économiques qui sont impactés par l'activité économique. Cela représente les pressions externes qui poussent les entreprises à adopter des pratiques plus vertueuses, favorisant la préservation de l'environnement et le bien-être commun [START_REF] Bocken | A literature and practice review to develop sustainable business model archetypes[END_REF][START_REF] Boons | Business models for sustainable innovation: state-of-the-art and steps towards a research agenda[END_REF][START_REF] Baldassarre | Bridging sustainable business model innovation and user-driven innovation: A process for sustainable value proposition design[END_REF].

Bien que l'adoption de pratiques durables semble fondamentale dans le milieu industriel actuel, elle nécessite des transformations radicales aux niveaux interne et externe des entreprises. Par exemple, les entreprises sont amenées a ` innover dans leurs produits, leurs processus, et leurs modèles d'aff pour atteindre le triple objectif de la durabilité (i.e., croissance economique, protection de l'environnement et bien-étre social) [START_REF] Ballantyne | Industrial Marketing Management Value propositions as communication practice : Taking a wider view[END_REF][START_REF] Baldassarre | Bridging sustainable business model innovation and user-driven innovation: A process for sustainable value proposition design[END_REF]. Par conséquence, le ro ˆle de l'entreprise dans la création d'une société plus durable est un défi complexe mais puissant, qui peut transformer les modes de production et de consommation de la societé.

Des nombreuses recherches academiques ont traité la question de la création de valeur, analysée du point de vue de plusieurs domaines de la conaissance, en dégageant des Mines Saint-E ´ tienne Martha Orellano Carrasquilla viii pistes prometteuses [START_REF] Ueda | Value creation and decision-making in sustainable society[END_REF][START_REF] Bocken | A literature and practice review to develop sustainable business model archetypes[END_REF][START_REF] Joyce | The triple layered business model canvas: A tool to design more sustainable business models[END_REF][START_REF] Aquilani | The challenging transition to bio-economies: Towards a new framework integrating corporate sustainability and value co-creation[END_REF]. En soulignant les travaux de Bocken et al. (2014), ces auteurs mettent en lumière le potentiel durable des modèles économiques innovants tels que les systèmes produits-services (PSS), l'économie de la fonctionnalité, et l'économie circulaire. Dans la même direction, [START_REF] Pieroni | Business model innovation for circular economy and sustainability: A review of approaches[END_REF] démontre le lien existant entre les modèles économiques en boucle fermée et la réalisation de la valeur durable. Cependant, en dépit de l'importance de transformer les modèles d'entreprise envers le développement durable, il n'existent toujours pas de mécanismes concrets pour y parvenir. La recherche académique a mis en évidence deux grands défis pour la suite : premièrement, il est nécessaire de trouver un consensus sur le concept de valeur durable a travers la construction d'un cadre conceptuel général [START_REF] Kaihara | Value creation in production: Reconsideration from interdisciplinary approaches[END_REF]. Deuxièmement, des recherches supplémentaires sont nécessaires pour développer des méthodologies opérationnelles, permettant d'orienter les entreprises vers la durabilité [START_REF] Bocken | Value mapping for sustainable business thinking[END_REF].

Cette thèse, a donc pour objectif de répondre à ces besoins relevés dans la littérature. D'abord un cadre méthodologique pour soutenir la création de valeur durable a été proposé. Concrètement, ce travail propose en prémier lieu une conceptualisation de la valeur durable basée sur une vaste revue de la littérature. Ensuite, un cadre méthodologique pour aider à la prise de décisions dans la conception d'offres innovantes, tenant compte de la durabilité, est proposé. L'ensemble des contributions s'inscrit dans une perspective stratégique de relations de collaboration entre plusieurs acteurs industriels. Enfin, la méthodologie proposée a été en partie construite et appliquée suivant une démarche de recherche-intervention dans le cas d'une entreprise Franc ¸aise (Groupe EDF -Electricité de France).

Organisation du manuscrit et contenu des chapitres

Le manuscrit est structuré en quatre parties (y compris la partie introductoire I) et composé par un total de sept chapitres. La deuxième partie présente l'état de l'art en appui de cette recherche, et se divise en trois chapitres. La troisième partie présente le cadre méthodologique proposé et illustre son application a ` travers un cas industriel, comprenant les chapitres 5 et 6. Enfin, la quatrième partie présente les conclusions, en distinguant les contributions scientifiques de celles managériales, ainsi que les perspectives de recherche.

Dans la Partie II, le chapitre 2 concerne la caractérisation de la création de valeur durable. Une vaste revue de la littérature sur le concept de création de valeur dans différentes disciplines et au fi du temps est developpée. Cette revue de littérature a pour objectif de parvenir à une conceptualisation structurée de la création de valeur dans le contexte actuel autour de la durabilité et de l'innovation des entreprises. A ` la fi du chapitre, un cadre conceptuel pour caractériser la valeur durable est fourni, contribuant ainsi au prémier axe de recherche de ce travail de thèse. Ensuite, le chapitre 3 a pour objectif de montrer ix le lien entre l'innovation collaborative et la création de valeur durable dans les relations inter-organisationnelles. A ` la fi de ce chapitre, les éléments permettant d'analyser et de modéliser les relations collaboratives entre plusieurs acteurs industriels sont mises en lumière. Enfin, le chapitre 4 explore a ` la fois les approches de modélisation des systèmes et des méthodes d'analyse multicritères. D'un côté, les méthodes de modélisation de systèmes sont explorées pour comprendre les relations menées entre les acteurs a ` travers leurs échanges de valeur. De l'autre côté, les approches d'analyse multicritères sont étudiées pour aboutir a ` des pistes pour l'évaluation de la valeur dans le contexte de la conception collaborative d'off innovantes.

Concernant la Partie III de cette thèse, le chapitre 5 développe le cadre méthodologique proposé. Suivant une approche progressive, les éléments retenus dans la littérature, et adaptés au contexte de création de valeur durable, sont couplés dans un cadre méthodologique global composé de quatre phases : i) analyse de la création de valeur, ii) modèle d'alignement de la valeur, iii ) la modélisation des préférences, et iv) le processus de consensus. En fi de ce chapitre, la reproductibilité de la méthodologie proposée est discutée. En complément, le chapitre 6 detaille l'application du cadre méthodologique à un cas industriel. Dans ce chapitre, l'évolution méthodologique de la proposition est illustrée a ` travers le cas d'étude. Les résultats obtenus lors de la mise en ouvre de la proposition sont analysés et débouchent sur un ensemble d'implications en matière de gestion et de perspectives pour l'entreprise, en soulignant les effets sur la stratégie des achats, pour favoriser les politiques RSE (Responsabilité Societale des Entreprises) de l'entreprise.

La dernière Partie IV est consacrée au chapitre 7, contenant les conclusions et les perspectives de recherche degagées de ce travail de thèse. Cette partie présente donc, les principales contributions vis-a `-vis de l'état de l'art. Ensuite, les limites de la recherche concernant l'approche méthodologique et les théories et méthodes mobilisées sont spécifiées. A ` partir de l'étude de cas, les implications managériales sont discutées. Enfin, les sujets non couverts sont pésentés en tant que perspectives de recherche.

Conclusions

Ce travail de thèse contribue a ` la littérature sur la durabilité, l'innovation et la création de valeur. Plus précisément, le cadre proposé contribue a ` la conceptualisation, a ` la modélisation et à l'évaluation de la création de valeur durable dans les contextes d'innovation collaborative entre plusieurs acteurs industriels. Le cadre a été construit a ` partir d'une solide base conceptuelle obtenue d'une revue de la littérature dans les domaines de la création de valeur, la gestion de l'innovation, la modélisation des systèmes et l'aide a la décision. Notre proposition est donc le résultat de la convergence de plusieurs disciplines, démontrant ainsi la complexité autour du sujet de la création de valeur durable. 6. 12 Results aggregation at the beginning of life according to decisional profi 6. 13 Results aggregation at the middle of life according to decisional profi . 6. 14 Results aggregation at the end of life according to decisional profi . .

List of Tables

Chapter 1

Introduction

Research context

Value creation is undergoing profound transformations in current industry, going beyond economics and increasingly concerned with environmental and social aspects. In academic research, such a transformation is known as sustainable value creation [START_REF] Boons | Business models for sustainable innovation: state-of-the-art and steps towards a research agenda[END_REF][START_REF] Bocken | A literature and practice review to develop sustainable business model archetypes[END_REF], and can be analysed from three diff t levels: the fi the supply chain and the society. Firstly, from the firm level, adopting a sustainability-oriented strategy could represent an opportunity to fi the current market trends and to get competitive advantage [START_REF] Hart | Creating sustainable value[END_REF][START_REF] Matinheikki | From the profi of one toward benefitting many -Crafting a vision of shared value creation[END_REF][START_REF] Brown | Why do companies pursue collaborative circular oriented innovation?[END_REF]. Secondly, at the supply chain level, creating sustainable value requires the entailment of collaborative relationships between the actors, seeking for sharing resources and responsibilities [START_REF] Maestrini | Supply chain performance measurement systems: A systematic review and research agenda[END_REF][START_REF] Arnold | Fostering sustainability by linking co-creation and relationship management concepts[END_REF]. Finally, the society comprehends non-economic actors, and represents the external pressures that push companies towards sustainability-oriented practices, seeking for environment preservation and people well-being [START_REF] Bocken | A literature and practice review to develop sustainable business model archetypes[END_REF][START_REF] Boons | Business models for sustainable innovation: state-of-the-art and steps towards a research agenda[END_REF][START_REF] Baldassarre | Bridging sustainable business model innovation and user-driven innovation: A process for sustainable value proposition design[END_REF].

Although the adoption of sustainable practices appears to be fundamental in today's businesses, it requires drastic transformations of the internal and external organisations of a any company. For instance, companies should be able to innovate in their products, processes, and business models to achieve the triple bottom line of sustainability. 1 Introduction Furthermore, sustainable value creation necessitates a collaborative integration of several and heterogeneous actors, which increase the business complexity in terms of relationships management [START_REF] Ballantyne | Industrial Marketing Management Value propositions as communication practice : Taking a wider view[END_REF][START_REF] Baldassarre | Bridging sustainable business model innovation and user-driven innovation: A process for sustainable value proposition design[END_REF]. Hence, the role of the company to achieve a more sustainable society is complex and powerful, since it can transform the current patterns of production and consumption.

A plethora of academic researches have treated the question of sustainable value creation drawing out some promising directions [START_REF] Ueda | Value creation and decision-making in sustainable society[END_REF][START_REF] Bocken | A literature and practice review to develop sustainable business model archetypes[END_REF][START_REF] Joyce | The triple layered business model canvas: A tool to design more sustainable business models[END_REF][START_REF] Aquilani | The challenging transition to bio-economies: Towards a new framework integrating corporate sustainability and value co-creation[END_REF]. For instance, [START_REF] Bocken | A literature and practice review to develop sustainable business model archetypes[END_REF] highlight the potential of product-service systems (PSS), functional economy, and circular economy as sustainable business archetypes. In the same perspective, [START_REF] Pieroni | Business model innovation for circular economy and sustainability: A review of approaches[END_REF] demonstrate the existing link between circular oriented business models and the achievement of sustainable value. Other authors propose generic frameworks for the evolution of business models towards sustainability [START_REF] Boons | Business models for sustainable innovation: state-of-the-art and steps towards a research agenda[END_REF][START_REF] Joyce | The triple layered business model canvas: A tool to design more sustainable business models[END_REF].

Although several contributions demonstrate the importance of transforming business models towards sustainability, concrete mechanisms to achieve it are still missing. Two main challenges have been highlighted in academic research, fi , it is necessary to build a consensus about the concept of sustainable value [START_REF] Kaihara | Value creation in production: Reconsideration from interdisciplinary approaches[END_REF]. Secondly, further research is needed to build holistic and operational methodologies for guiding companies in the pursuit of sustainability [START_REF] Bocken | Value mapping for sustainable business thinking[END_REF]. Concretely, while the economic aspect is well mastered, environmental, social, and other intangible aspects are still hardly integrated into the business mindset. Throughout this thesis, a methodological framework to support sustainable value creation has been proposed. Concretely, this work proposes fi a conceptualization of sustainable value based on literature review. Then, a methodological framework to support decision-making at early development phases of innovative offers. The entire contribution is framed into a strategic perspective of collaborative relationships between industrial actors.

Research questions and objectives

The main objective of this thesis work is to guide companies in their transition towards sustainable value creation. Certainly, such a transformation impacts the organisation at internal and external levels, needing the development of new activities and skills, and entailing collaborative relationships with the external actors. As a potential answer to the challenges that a company faces, this thesis provides a methodological framework to support sustainable value creation in collaborative business innovation. The proposed framework enables the visualization of the value creation process in a collaborative context. A focus on sustainability is adopted, considering the life cycle of innovative offers development.

In this thesis, a strategic positioning is adopted with respect to value creation, rather than studying the productive processes of a company. Thus, from a strategic point of view, we analyse and model the relationships between several actors, considering 1 Introduction

• We apply a multi-criteria decision approach in early phases of innovative offers design, by integrating sustainability criteria. Concretely, we propose the implementation of Analytic Hierarchy Process (AHP) to prioritize the diff t dimensions of value creation, considering multiple actors points of view (Orellano et al., 2019b). Then, we couple AHP with clustering techniques and stakeholderbased methodologies to facilitate the consensus process between actors.

From a practical point of view, this research is built within the frame of a French project called ICOVET (Innovation Collaborative dans les Vêtements de Travail, in French). The project represents an initiative of collaborative innovation applied to the supply system of safety clothing in EDF (Electricité de France, in French), the fi producer and distributor of energy in France. The project consists in the transformation of a product-purchasing model into a service-based offer of safety clothes. The aim of the project is to manage the entire life cycle of the safety clothes, to reduce the economic expenses, and to mitigate environmental and social impacts. The three theoretical approaches, explained above, were applied to the case study, providing valuable evidence about the support of sustainable value creation in B2B contexts. From a scientific perspective, the case study contributes to enrich theory about sustainable value creation in a context of collaborative innovation.

Structure of the manuscript

The manuscript is structured in four parts (including the preliminary part I) and a total of seven chapters. Part II introduces the state of the art supporting this research, divided into three chapters. Part III presents the methodological framework proposed through this research and its application to an industrial case, comprehending chapters 5 and 6. Part IV reports the conclusions, diff tiating between scientific and managerial contributions, and research perspectives.

Part II: Theoretical Background

Chapter 2: Characterization of sustainable value creation. This chapter presents a literature review about the concept of value creation from diff t disciplines along the time. The aim of the literature review is to reach a structured conceptualization of value creation regarding the current context of sustainability and business innovation. At the end of the chapter, a conceptual framework to characterise sustainable value is provided, contributing to the fi research axe of this thesis work. development. The aim of this chapter is to identify a typology of collaborative relationships enabling sustainable value creation in innovative businesses. At the end of this chapter, the elements to analyse collaborative relationships are identified.

Chapter 4: Decision making in multidimensional and multi-stakeholder value creation. This chapter explores both system modelling and multi-criteria analysis approaches to support the process of collaborative value creation. On the one side, system modelling methods are explored to understand actors' relationships with respect to their value exchanges. On the other side, multi-criteria analysis approaches are investigated for value assessment in early stages of innovation development, considering multiple actors perspectives.

Part III: Proposal Development

Chapter 5: Framework to support sustainable value creation in collaborative innovation. This chapter presents the methodological proposal for the analysis and decision-making around the creation of sustainable value in collaborative businesses. 1 Introduction Following a step-by-step approach, the elements retained from the literature and adapted to the context of sustainable value creation are integrated into a holistic methodological framework composed by four main phases: i) value creation analysis, ii) value alignment model, iii) preference modelling, and iv) consensus process. At the end of the chapter, the robustness and reproducibility of the proposed methodology is discussed.

Chapter 6: Case study application -ICOVET project. In this chapter the methodological development of the proposal is illustrated through a real case study at EDF (Electricité de France, in French), a big-sized company in France. The results obtained from the proposal implementation are analysed, leading into a set of managerial implications, and perspectives for the company, pointing out its purchasing strategy.

Part IV: General conclusion

Chapter 7: Conclusions and research perspectives. This part outlines the main contributions of the thesis regarding the state of the art and the research question. Then, it presents the limits of the research regarding the methodological approach and the mobilised theories and methods. From the case study, the managerial implications are discussed. Finally, the uncovered topics are mentioned as research perspectives.

Part II

Introduction

The increase of environmental and social needs demands the adoption of more sustainable practices in the industry, which should focus on the creation of value other than economic [START_REF] Brown | Why do companies pursue collaborative circular oriented innovation?[END_REF]. For international institutions, as the United Nations, the European Union, and the World Business Council for Sustainable Development (WBCSD), the sustainability approach seeks for a trade-off between the environmental, social and economic pillars. Some companies adopt this approach in 2 Characterisation of sustainable value creation their CSR strategy (Corporate Social Responsibility), as an opportunity to fi with the market trends and to diff tiate themselves from competitors [START_REF] Hart | Creating sustainable value[END_REF]. From an academic perspective, value creation is considered as the principal objective of any business activity, and it is generally addressed as both an economic and marketing issue. In economics, the defi of value is narrowly linked to the market price of products and services [START_REF] Bowman | Value creation versus value capture: towards a coherent defi of value in strategy[END_REF]. Historically, the notion of value has been studied in marketing literature [START_REF] Payne | A Review of the 'Value' Literature and Implications for Relationship Marketing[END_REF], which explains the strong customer orientation observed until the last decade [START_REF] Eggert | Value creation in the relationship life cycle: A quasi-longitudinal analysis[END_REF][START_REF] Xing | A sustainability-oriented multidimensional value assessment model for product-service development[END_REF][START_REF] Patala | Sustainable value propositions: Framework and implications for technology suppliers[END_REF][START_REF] Eggert | Conceptualizing and communicating value in business markets : From value in exchange to value in use[END_REF]. Here, value is defi as the trade-off between benefits and sacrifices perceived by the customer with respect to an offer [START_REF] Eggert | Value creation in the relationship life cycle: A quasi-longitudinal analysis[END_REF][START_REF] Eggert | Conceptualizing and communicating value in business markets : From value in exchange to value in use[END_REF]. During the 2000s', the concept of "value in use" appeared with the growing importance of the service in the global market as a source of competitiveness, focusing on the customer experience [START_REF] Vargo | Service-dominant logic: continuing the evolution[END_REF]. Currently, businesses are evolving in accordance with the global need for sustainability, integrating economic, environmental and social objectives to their strategies [START_REF] Bocken | Value mapping for sustainable business thinking[END_REF][START_REF] Patala | Sustainable value propositions: Framework and implications for technology suppliers[END_REF][START_REF] Baldassarre | Bridging sustainable business model innovation and user-driven innovation: A process for sustainable value proposition design[END_REF][START_REF] Hankammer | Degrowth and collaborative value creation: Reflections on concepts and technologies[END_REF]. Moreover, sustainability businesses require the integration of several stakeholders into the value creation process [START_REF] Bocken | Value mapping for sustainable business thinking[END_REF][START_REF] Lacoste | Sustainable value co-creation in business networks[END_REF][START_REF] Reypens | Leveraging value in multi-stakeholder innovation networks: A process framework for value co-creation and capture[END_REF]. The literature makes it evident that the concept of value is in constant evolution, according to the market context. Therefore, in the current industrial context, increasingly concerned with environmental and social needs, a re-conceptualization of value creation is required.

The aim of this literature review is fi to analyse the evolution of the concept of value in business-to-business (B2B) relationships throughout the time; then, to characterise the value from a sustainability approach. The following research questions guide this review:

• RQ1. How has the notion of value been approached in different research fields since 2000?

• RQ2. What does the notion of sustainable value mean in B2B relationships?

• RQ3. What are the research challenges about sustainable value creation?

Following a systematic literature review methodology, 50 papers published after 2000 in peer-reviewed journals in the fi of industrial engineering, management, marketing and environmental sciences have been analysed. Two principal features were taken into account to conduct this literature review. First, we included papers providing a conceptualization of value and a description of the value creation process. Second, we included studies addressing sustainable business models in B2B contexts. The literature analysis revealed four main categories of the conceptualization of value: economic, customer, sustainable, and multi-stakeholder value. The results were discussed and synthesize into a structured framework for sustainable value characterisation in B2B contexts. The conclusions elucidate the main directions for this research fi Mines Saint-E ´ tienne Martha Orellano Carrasquilla 2.2 Literature review methodology 13

Literature review methodology

To address the research questions, a systematic literature review has been conducted. Systematic literature review methodology is a replicable, scientific, and transparent process that makes it possible to retain a reliable sample of scientific publications [START_REF] Maestrini | Supply chain performance measurement systems: A systematic review and research agenda[END_REF]. The research methodology has been structured in three main steps: i) identification of sources, ii) selection fi by inclusion criteria, and iii) descriptive and content analysis of articles. Figure 2.1 summarizes the entire process of the systematic literature review, showing the results at each stage.

Identification of sources

The selected databases to perform the research were Web of Science (WOS) and Science Direct (SD). The criteria for selecting the databases were the quality of the sources based on the impact factor of the journal and the scope of research of the databases, including management, engineering and environmental sciences [START_REF] Harzing | Google Scholar, Scopus and the Web of Science: a longitudinal and cross-disciplinary comparison[END_REF]. The research was limited to peer-reviewed papers published from 2000 to 2018, considering that from the year 2000 on, the concept of value creation has gained greatly in importance in research thanks to the emerging fi of business models innovation [START_REF] Chesbrough | The role of the business model in capturing value from innovation: evidence from Xerox Corporation's technology spinoff companies[END_REF]. This research was conducted through searching by "topic" in WOS and by "title, abstract and keywords" in SD. The single keyword used to start the research was "value creation" in order to address the notion of value in business and industrial contexts, further developed in the subsequent fi steps. As for the results, 661 papers from WOS and 963 from SD were found, a total of 1 624 potential papers. These papers belong to the general fi of engineering and management, which correspond to our scope of research. Thus, the research domains focusing on natural sciences, agriculture, operations research, tourism, fi nce and civil engineering were 2 Characterisation of sustainable value creation discarded by using the fi options of the databases. Hence, 306 papers from WOS and 337 papers from SD were selected, totalling 643 papers for further analysis. Figure 2.2 shows the number of publications over time in both databases, demonstrating that the subject under study has gained in importance in research since the last decade. We obtained 27 journals from WOS and 14 from SD, with six journals overlapping in both databases. The resulting journals come from a variety of disciplines: marketing, management, environmental sciences, and operations management.

Selection filtering

643 peer-reviewed papers constitute the initial sample to start the fi process. First, the analysis of the abstract and the objectives of each article was effectuated, leading to a sample of 127 articles. The papers related exclusively to the fi defi of value (e.g., accounting) and the ones addressing the value from the production point of view (e.g., value stream mapping) were excluded. Then, the articles selection was effectuated according to two criteria of inclusion:

• Conceptualization of value: papers discussing the nature of the value concept from diff t historical contexts and disciplines.

• Value creation process: papers discussing the organisational configurations and drivers to enable value creation in B2B relationships.

During this step, new keywords were identified: "business models innovation", "sustainable business models", "value co-creation" and "sustainable value". Accordingly, we retained some papers referring to these topics to have a broader scope of literature about value creation in relation to sustainability. Finally, 50 peer-reviewed articles were retained for further analysis.

Mines Saint-E ´ tienne Martha Orellano Carrasquilla 2. 2 Literature review methodology 15

Descriptive analysis

The 50 selected articles belong to 23 diff t international journals, classified into four research domains and according to the WOS suggested categories. Figure 2.3 illustrates the distribution of articles over time according to the research domains. The domain of marketing management focuses on customer value and represents 37% of the sample. The domain of operations, production and technology management comprehends 23% of the selected articles. This domain mainly focuses on supply chain management. The domain of management, business and economics, focusing on the strategic perspective of value creation, represents 21% of the contributions. The fi of environmental sciences covers 18% of the sample, and shows a growth on the integration of sustainability issues within the value creation literature between 2014 and 2018. This domain focuses on the integration of environmental and social impacts to economic activities.

Content analysis

Regarding the conceptualization of value, four diff t approaches were identified over time: Firstly, value has been studied as an economic concept [START_REF] Bowman | Value creation versus value capture: towards a coherent defi of value in strategy[END_REF]. Secondly, being highly infl by the relational marketing perspective, the concept of value has been studied in relation with the customer, known as customer value [START_REF] Vargo | Service-dominant logic: continuing the evolution[END_REF]. Thirdly, over the last two decades, the notion of value has been addressed from a sustainability perspective, going beyond economics and integrating environmental and social aspects into its defi known as sustainable value [START_REF] Hart | Creating sustainable value[END_REF]. Finally, the multi-stakeholder defi of value defends the idea that value is always co-created from the interaction of several actors [START_REF] Baldassarre | Bridging sustainable business model innovation and user-driven innovation: A process for sustainable value proposition design[END_REF]. Table 2.1 lists the retained articles from the literature review, classified into the four approaches to value conceptualization. 2 Characterisation of sustainable value creation [START_REF] Buxel | Strategic sustainability: Creating business value with life cycle analysis[END_REF] BH 24 [START_REF] Bocken | Value mapping for sustainable business thinking[END_REF] JIPE 25 [START_REF] Coutelle-Brillet | Perceived value of service innovation : a conceptual framework[END_REF] JBIM 26 Gr önroos and Voima (2013) JAMS 27 [START_REF] Ford | Service and value in the interactive business landscape[END_REF] IMM 28 [START_REF] Jaakkola | Value co-creation in solution networks[END_REF] IMM 29 Dominguez-Pér y et al. (2013) IJPE 30 [START_REF] Xing | A sustainability-oriented multidimensional value assessment model for product-service development[END_REF] IJPR 31 [START_REF] Haas | Creating value in business relationships: The role of sales[END_REF] IMM 32 [START_REF] Corsaro | The impact of network configurations on value constellations in business markets -The case of an innovation network[END_REF] IMM 33 [START_REF] Hsieh | Strategy and process of value creation and appropriation in service clusters[END_REF] T echnov. 34 [START_REF] Ballantyne | Industrial Marketing Management Value propositions as communication practice : Taking a wider view[END_REF] IMM 35 [START_REF] Wagner | Creating and appropriating value in collaborative relationships[END_REF] JBR 36 Westerlund and Sv ahn (2008) IMM 37 [START_REF] Vargo | Service-dominant logic: continuing the evolution[END_REF] JAMS 38 [START_REF] Payne | Managing the co-creation of value[END_REF] JAMS 39 [START_REF] Kumar | Value flow characterization during product lifecycle to assist in recovery decisions[END_REF] IJPR 40 [START_REF] Huemer | Supply Management. Value Creation, Coordination and Positioning in Supply Relationships[END_REF] LRP 41 [START_REF] Eggert | Value creation in the relationship life cycle: A quasi-longitudinal analysis[END_REF] IMM 42 [START_REF] Prahalad | Co-creating unique value with customers[END_REF] S&L 43 [START_REF] Harmsen | Identifying the determinants of value creation in the market: A competence-based approach[END_REF] JBR 44 [START_REF] Hart | Creating sustainable value[END_REF] AME 45 Möller and T önen (2003) IMM 46 [START_REF] Kothandaraman | The Future of Competition: Value-Creating Networks[END_REF] IMM 47 [START_REF] Walter | Value Creation in Buyer-Seller Relationships: Theoretical Considerations and Empirical Results from a Supplier's Perspective[END_REF] IMM 48 [START_REF] Dumond | Value management: an underlying framework[END_REF] IJOPM 49 [START_REF] Lapierre | Customer-perceived value in industrial contexts[END_REF] JBIM 50 [START_REF] Bowman | Value creation versus value capture: towards a coherent defi of value in strategy[END_REF] BJM

Conceptualization of value

The notion of value throughout the time 2.3.1 Economic value

The seminal defi of value has its origins in classical economics theory coming into use at the end of 18th century. The value of something was defi by the amount of labour required to produce it [START_REF] Bowman | Value creation versus value capture: towards a coherent defi of value in strategy[END_REF]. During the 1990's, resources management became the dominant paradigm in enterprise management. For instance, the resource-based view (RBV) motivated a more sophisticated vision of the economic value [START_REF] Bowman | Value creation versus value capture: towards a coherent defi of value in strategy[END_REF]Mo ¨ller and Tönen, 2003;[START_REF] Huemer | Supply Management. Value Creation, Coordination and Positioning in Supply Relationships[END_REF]. In this paradigm, a valuable thing is anything that generates or economizes money, or that improves the company's efficiency. Indeed, the resources of a company are its main source of value if they are managed strategically, in a way that they provide competitive advantages. In line with the classical economic theory of value, [START_REF] Bowman | Value creation versus value capture: towards a coherent defi of value in strategy[END_REF] highlight that the value should be understood from two perspectives, value in exchange and value in use. The former, created during the sales-purchasing process, and the latter, during the customer consumption process. In both cases, value is defi as the marginal utility.

Besides, considering customer-supplier relationships, [START_REF] Walter | Value Creation in Buyer-Seller Relationships: Theoretical Considerations and Empirical Results from a Supplier's Perspective[END_REF] integrate non-monetary attributes to the defi of economic value, as market positioning and competitiveness. In this logic, the authors defi economic value from the supplier perspective as a function of customer-supplier relationships. Here, the economic value for a supplier depends on how much a customer is profitable in terms of purchasing volume, cash-flow, and loyalty [START_REF] Walter | Value Creation in Buyer-Seller Relationships: Theoretical Considerations and Empirical Results from a Supplier's Perspective[END_REF]. Several authors agree that supplier's value depends on having good relationships with the customers [START_REF] Möller | Business suppliers' value creation potential: A capability-based analysis[END_REF][START_REF] Wagner | Creating and appropriating value in collaborative relationships[END_REF][START_REF] Hsieh | Strategy and process of value creation and appropriation in service clusters[END_REF][START_REF] Corsaro | The impact of network configurations on value constellations in business markets -The case of an innovation network[END_REF][START_REF] Haas | Creating value in business relationships: The role of sales[END_REF][START_REF] Lages | VCW Value Creation Wheel: Innovation, technology, business, and society[END_REF]. Nevertheless, the supplier potential of value creation also depends on internal drivers, for instance, price level, efficient processes, diversity of the customer portfolio, innovation capabilities, access to resources, and market positioning. For instance, [START_REF] Harmsen | Identifying the determinants of value creation in the market: A competence-based approach[END_REF], demonstrate throughout an empirical study, that economic value creation depends on the company's fl y to fi market changes, and to rapidly develop new products and skills. Besides, [START_REF] Lages | VCW Value Creation Wheel: Innovation, technology, business, and society[END_REF] considers that economic value results from the ability of a company to capture new customers throughout business model innovation. Finally, for [START_REF] Corsaro | The impact of network configurations on value constellations in business markets -The case of an innovation network[END_REF] and [START_REF] Haas | Creating value in business relationships: The role of sales[END_REF] economic value not only depends on the provider understanding of the customer behaviour, but it is created only by integrating resources, activities and knowledge with the customer. These authors observe value as the result of a mirror process, in which the value is created for the provider as for the customer simultaneously.

In conclusion, from the economic perspective, value can be characterised as market value and fi value, and it depends on the level of knowledge a supplier company has about its customers. Market value corresponds to the profi generated from innovation and ability to fit market trends; while fi value concerns the utility margins generated from the routine company's sales. Economic value is created by the 2 Characterisation of sustainable value creation provider through a transactional relationship between the provider and the customer. Afterwards, with the evolution of services in the early 2000s', a strong customer orientation was adopted by the companies, introducing the idea that value is a subjective construction depending on the customer perception [START_REF] Eggert | Value creation in the relationship life cycle: A quasi-longitudinal analysis[END_REF][START_REF] Eggert | Conceptualizing and communicating value in business markets : From value in exchange to value in use[END_REF]. This research stream focused on the customer, represents a counterpart of the supplier orientation, which is predominant in the conceptualization of economic value.

Customer value

With the increase of market competitiveness, the concept of value evolved, integrating the perception of the customer in its defi

In marketing, value has been strongly studied from the customer perspective, known as customer value, which constitutes a research priority in this fi [START_REF] Kothandaraman | The Future of Competition: Value-Creating Networks[END_REF][START_REF] Eggert | Value creation in the relationship life cycle: A quasi-longitudinal analysis[END_REF][START_REF] Westerlund | A relationship value perspective of social capital in networks of software SMEs[END_REF][START_REF] Corsaro | The impact of network configurations on value constellations in business markets -The case of an innovation network[END_REF][START_REF] Haas | Creating value in business relationships: The role of sales[END_REF][START_REF] Coutelle-Brillet | Perceived value of service innovation : a conceptual framework[END_REF][START_REF] Eggert | Conceptualizing and communicating value in business markets : From value in exchange to value in use[END_REF]. Two streams of customer value were identified through the literature review, one from the marketing perspective, and the other one infl ed by service development theories.

Firstly, the marketing literature defi customer value as the trade-off between customer's perceived benefits and sacrifices associated to an offer purchasing [START_REF] Dumond | Value management: an underlying framework[END_REF][START_REF] Kothandaraman | The Future of Competition: Value-Creating Networks[END_REF][START_REF] Eggert | Value creation in the relationship life cycle: A quasi-longitudinal analysis[END_REF]Ha ¨nninen and Karjaluoto, 2017;[START_REF] Eggert | Conceptualizing and communicating value in business markets : From value in exchange to value in use[END_REF]. According to this defi the value created by any business is subjectively perceived by the customer rather than objectively defined by the seller. In this logic, value creation depends narrowly on the attributes of the offer that provides customer satisfaction, for instance, the product quality, the level of customization and the responsiveness of the provider company [START_REF] Lapierre | Customer-perceived value in industrial contexts[END_REF][START_REF] Prahalad | Co-creating unique value with customers[END_REF]. Nevertheless, some researchers in marketing consider that this vision does not capture the full meaning of customer value, and need to be further developed. For instance, [START_REF] Coutelle-Brillet | Perceived value of service innovation : a conceptual framework[END_REF] evoke the idea that value is characterised by several intangible dimensions, as efficiency, emotions, and altruism. In the same perspective, [START_REF] Ford | Service and value in the interactive business landscape[END_REF] sustain that customer value results from the aggregation of psychological, functional, and economics benefits perceived by the customer. [START_REF] Hänninen | Environmental values and customer-perceived value in industrial supplier relationships[END_REF] propose a characterisation of customer value by a set of technical, economic, social, and image benefits. Considering the idea of the multidimensionality of value, [START_REF] Hänninen | Environmental values and customer-perceived value in industrial supplier relationships[END_REF] highlight the importance of defi customer criteria to measure the level of value obtained from a business transaction.

Secondly, with the emergence of Service-Dominant Logic (SDL) proposed by [START_REF] Vargo | Service-dominant logic: continuing the evolution[END_REF], the defi of customer value was infl by the relational nature of services. In this context, the main source of value is the knowledge generated from the interaction between the customer and the provider instead of the transactional exchange [START_REF] Payne | Managing the co-creation of value[END_REF][START_REF] Gro ¨nroos | Critical service logic: Making sense of value creation and co-creation[END_REF][START_REF] Ballantyne | Industrial Marketing Management Value propositions as communication practice : Taking a wider view[END_REF][START_REF] Ekman | Service network value cocreation: Defining the roles of the generic actor[END_REF]. SDL reinforced the idea of "value in use", claiming that any form of value is exclusively created by the customer during the consumption process (Vargo and Mines Saint-E ´ tienne Martha Orellano Carrasquilla 2. 3 The notion of value throughout the time 19 [START_REF] Vargo | Service-dominant logic: continuing the evolution[END_REF]Grönroos and Voima, 2013;[START_REF] Ekman | Service network value cocreation: Defining the roles of the generic actor[END_REF]. From this perspective, the main challenge for companies is meeting several customers' value expectations through customized value propositions [START_REF] Ballantyne | Industrial Marketing Management Value propositions as communication practice : Taking a wider view[END_REF][START_REF] Zacharias | Effective configurations of value creation and capture capabilities: Extending Treacy and Wiersema's value disciplines[END_REF].

To summarize, customer value is based on marketing and service development literature. From these perspectives, the value created by any offer is an individual and cognitive construction of the customer, and takes place during the consumption process. The value depends on the set of attributes of an offer, observed by customers with respect to their own needs, and comparing with similar offers in the market. From this vision, three fundamental characteristics defi the notion of value: subjectivity, multidimensionality and competition [START_REF] Eggert | Value creation in the relationship life cycle: A quasi-longitudinal analysis[END_REF][START_REF] Eggert | Conceptualizing and communicating value in business markets : From value in exchange to value in use[END_REF].

Sustainable value

With the infl of marketing research, the idea of value multidimensionality opened new debates about the conceptualization and assessment of value. Besides, the global challenges, including climate change, resource depletion and extreme poverty, have pushed the industrial transformation towards the consideration of environmental and social benefits in their business strategies [START_REF] Bocken | Value mapping for sustainable business thinking[END_REF][START_REF] Buxel | Strategic sustainability: Creating business value with life cycle analysis[END_REF][START_REF] Schenkel | Creating integral value for stakeholders in closed loop supply chains[END_REF][START_REF] Patala | Sustainable value propositions: Framework and implications for technology suppliers[END_REF][START_REF] Ekman | Service network value cocreation: Defining the roles of the generic actor[END_REF][START_REF] Manda | Value creation with life cycle assessment: an approach to contextualize the application of life cycle assessment in chemical companies to create sustainable value[END_REF][START_REF] Aquilani | The challenging transition to bio-economies: Towards a new framework integrating corporate sustainability and value co-creation[END_REF]. This panorama triggered a re-definition of the concept of value regarding the sustainability issues.

In general, sustainable value is defi as the simultaneous creation of economic, environmental and social benefits from a business activity [START_REF] Bocken | Value mapping for sustainable business thinking[END_REF]. Nevertheless, a plethora of authors still consider that the major challenge regarding sustainable value is achieving a clear conceptualization. For instance, [START_REF] Bocken | Value mapping for sustainable business thinking[END_REF] propose a mapping tool that describes economic, environmental and social dimensions of value in terms of value destroyed and value opportunities for diff nt actors. Besides, [START_REF] Schenkel | Creating integral value for stakeholders in closed loop supply chains[END_REF] determine some strategic factors of success to achieve sustainable value. Finally, [START_REF] Volschenk | Creation and appropriation of socio-environmental value in coopetition[END_REF] consider that sustainable value supposes the integration of several actors, therefore, a knowledge dimension should be considered for its characterisation. In spite of the conceptual effort verified in the literature, there is not a clear consensus between the authors about the concept of sustainable value. Furthermore, the authors point out the need for formal methods to assess the sustainable value created by a company [START_REF] Schenkel | Creating integral value for stakeholders in closed loop supply chains[END_REF][START_REF] Kaihara | Value creation in production: Reconsideration from interdisciplinary approaches[END_REF]. In the literature, two main streams to assess sustainable value has been identified.

Firstly, from a compensatory vision, the three dimensions of sustainable value are considered interchangeable (known as Triple Bottom Line or weak sustainability) [START_REF] Pope | Conceptualising sustainability assessment[END_REF][START_REF] Patala | Sustainable value propositions: Framework and implications for technology suppliers[END_REF]. In this case, the degradation of one dimension is considered acceptable since it is compensated by the improvement on another one. From this approach, sustainable value creation is often translated into monetary benefits. For instance, [START_REF] Hart | Creating sustainable value[END_REF] propose a strategic framework to improve sustainable value in companies by implementing technology innovation, waste reduction strategies, and 2 Characterisation of sustainable value creation stakeholders integration. Besides, [START_REF] Patala | Sustainable value propositions: Framework and implications for technology suppliers[END_REF] propose a monetisation-based method that translates economic, environmental and social benefits and impacts, into economic gains, expenses and fi risks. Although monetisation-based methods are attractive for business decisions, some metrics can be selected arbitrary (e.g., price per Kg. of CO 2 ), which could provide unrealistic results. Moreover, these kind of approaches has been largely criticised since they focus on avoiding non-sustainability and extra-costs, rather than on researching real sustainable solutions [START_REF] Pope | Conceptualising sustainability assessment[END_REF].

Secondly, non-compensatory approaches defend a clear multidimensional concept of sustainable value, rejecting any monetisation approach (for instance eco-efficiency and societal approaches) [START_REF] Pope | Conceptualising sustainability assessment[END_REF][START_REF] Vezzoli | Product-Service System Design for Sustainability[END_REF]. In this line, [START_REF] Xing | A sustainability-oriented multidimensional value assessment model for product-service development[END_REF] propose a coupling of diff t methods to evaluate efficiency, costs and environmental impacts derived from an offer development in an independent way. Besides, [START_REF] Buxel | Strategic sustainability: Creating business value with life cycle analysis[END_REF] and [START_REF] Manda | Value creation with life cycle assessment: an approach to contextualize the application of life cycle assessment in chemical companies to create sustainable value[END_REF] propose the implementation of Life Cycle Assessment (LCA) to determine the sustainable value procured by a given offer expressed in terms of environmental quality. In general, non-compensatory approaches aim at confronting the economic mind-set of the industry with the urgency of the environmental and social needs, encouraging a reliable adoption of sustainable practices [START_REF] Lacoste | Sustainable value co-creation in business networks[END_REF]. Nevertheless, these authors point out the complexity of conducting a proper assessment of sustainable value, given the heterogeneity of the metrics, the involvement of non-tangible attributes (e.g., social well-being), the diffi y to collect reliable data (e.g., biodiversity degradation), the context dependency of the results (e.g., resource depletion, employment, society growth, among others). Particularly, LCA-based methods are very time-consuming and data-intensive, not always suitable to be implemented for guiding business decisions [START_REF] Manda | Value creation with life cycle assessment: an approach to contextualize the application of life cycle assessment in chemical companies to create sustainable value[END_REF].

An important aspect highlighted in recent literature on sustainable value creation is the need for collaboration between a broader set of stakeholders [START_REF] Reypens | Leveraging value in multi-stakeholder innovation networks: A process framework for value co-creation and capture[END_REF]. Therefore, sustainable value is not only a multidimensional concern, but also implies multiple stakeholders [START_REF] Ekman | Service network value cocreation: Defining the roles of the generic actor[END_REF]. For companies, creating sustainable value represents a source of competitiveness, being an opportunity to improve the company's reputation. From the academic point of view, a clear definition of sustainable value creation, and the development of value assessment methods constitute important research streams in management and engineering fi s [START_REF] Xing | A sustainability-oriented multidimensional value assessment model for product-service development[END_REF][START_REF] Ueda | Value creation and decision-making in sustainable society[END_REF][START_REF] Kaihara | Value creation in production: Reconsideration from interdisciplinary approaches[END_REF].

Multi-stakeholder value

Recent literature evidences that sustainable value creation requires including relevant stakeholders, who are diff t from the customer and the provider [START_REF] Ballantyne | Industrial Marketing Management Value propositions as communication practice : Taking a wider view[END_REF][START_REF] Bocken | Value mapping for sustainable business thinking[END_REF][START_REF] Reypens | Leveraging value in multi-stakeholder innovation networks: A process framework for value co-creation and capture[END_REF][START_REF] Lacoste | Sustainable value co-creation in business networks[END_REF][START_REF] Joyce | The triple layered business model canvas: A tool to design more sustainable business models[END_REF][START_REF] Baldassarre | Bridging sustainable business model innovation and user-driven innovation: A process for sustainable value proposition design[END_REF][START_REF] Hankammer | Degrowth and collaborative value creation: Reflections on concepts and technologies[END_REF][START_REF] Aquilani | The challenging transition to bio-economies: Towards a new framework integrating corporate sustainability and value co-creation[END_REF][START_REF] Best | Examining networked ngo services: reconceptualising value co-creation[END_REF]. As cited by [START_REF] Aquilani | The challenging transition to bio-economies: Towards a new framework integrating corporate sustainability and value co-creation[END_REF], sustainable value is always co-created with actors inside and outside a company's boundaries, and should be equitably appropriated by all the stakeholders. Moreover, [START_REF] Ballantyne | Industrial Marketing Management Value propositions as communication practice : Taking a wider view[END_REF] and [START_REF] Eggert | Conceptualizing and communicating value in business markets : From value in exchange to value in use[END_REF] that a company co-develops value propositions with its external partners envisioning a reciprocal and fair exchange of the value created. Here, each actor determines what value is in its own terms. The term "reciprocal" evokes the collaborative character of value creation, and the term "fair" is associated with the symmetry in the distribution of value between the diff t actors concerned. Two main knowledge streams have study the notion of multi-stakeholder value, the resource-based view (RBV) and the relational marketing.

On the one side, from RBV perspective, value in relationships is determined by the access to new resources, which include knowledge, experience, and skills [START_REF] Westerlund | A relationship value perspective of social capital in networks of software SMEs[END_REF][START_REF] Jaakkola | Value co-creation in solution networks[END_REF][START_REF] Kähko ¨nen | Key dimensions of value creation ability of supply management[END_REF]. Moreover, value creation takes place during creative interaction processes, which allows developing new products, services or more sophisticated knowledge. [START_REF] Dominguez-Péry | A service science framework to enhance value creation in service innovation projects. An RFID case study[END_REF] evoke the necessity of inter-organisational relationships to achieve tangible and intangible forms of value, for instance, the access to new physical and fi assets, human capital, knowledge, brand image, and market position. Besides, [START_REF] Schenkel | Creating integral value for stakeholders in closed loop supply chains[END_REF] name the value created from stakeholders interaction as informational value, which is defi as the ability to learns and to collect and share information thought the supply chain. For the authors, informational value can enable the acquisition of other types of value (e.g., economic, environmental, social) [START_REF] Schenkel | Creating integral value for stakeholders in closed loop supply chains[END_REF].

On the other side, from the relational marketing perspective, each stakeholder represents a social actor, whose relationships are infl by power interdependencies [START_REF] Reypens | Leveraging value in multi-stakeholder innovation networks: A process framework for value co-creation and capture[END_REF]. In this literature stream, relationships are a means to achieve some sort of value and not a by value itself [START_REF] Coutelle-Brillet | Perceived value of service innovation : a conceptual framework[END_REF][START_REF] Reypens | Leveraging value in multi-stakeholder innovation networks: A process framework for value co-creation and capture[END_REF][START_REF] Arnold | Fostering sustainability by linking co-creation and relationship management concepts[END_REF]. [START_REF] Coutelle-Brillet | Perceived value of service innovation : a conceptual framework[END_REF] distinguish four value dimensions created from multiple actors interactions, named as efficiency, social, emotional and ethical. Similarly, [START_REF] Reypens | Leveraging value in multi-stakeholder innovation networks: A process framework for value co-creation and capture[END_REF] consider relationships as a means to achieve innovation, knowledge and relational outcomes. The fi can be translated into process improvement, the second one into technological and managerial improvements, and the last one into powerful positioning. In contrast, [START_REF] Ekman | Service network value cocreation: Defining the roles of the generic actor[END_REF] conducted an empirical study, fi that relationships are considered as a form of value by itself, known in industry as brand value.

In general, both RBV and relational marketing perspectives consider multi-stakeholder value mostly as a means than as an objective itself. One of the biggest challenges on multi-stakeholder value creation in B2B markets is to guarantee the reciprocity and fairness in the value distribution among the actors [START_REF] Reypens | Leveraging value in multi-stakeholder innovation networks: A process framework for value co-creation and capture[END_REF][START_REF] Aquilani | The challenging transition to bio-economies: Towards a new framework integrating corporate sustainability and value co-creation[END_REF]. Although there exist several frameworks in the literature addressing this research question, there is not proper measurements mechanisms to operationalize them. Under this panorama, current research should be oriented to propose collaborative mechanisms to create, assess and distribute value in multi-actor relationships.

Sustainable value creation in B2B markets

Value creation process. Past research, in economic and marketing fi considered the value creation as a delivery activity from the provider to the customer [START_REF] Bowman | Value creation versus value capture: towards a coherent defi of value in strategy[END_REF][START_REF] Eggert | Value creation in the relationship life cycle: A quasi-longitudinal analysis[END_REF]. Currently, two main approaches to value creation are observed in the industry from the process perspective: the dyadic co-creation between the provider and the customer, and the networked collaboration. In dyadic value co-creation processes, value is classified into value in exchange and value in use [START_REF] Vargo | Service-dominant logic: continuing the evolution[END_REF]. From the perspective of the value in exchange, the provider creates value in monetary terms. Value in use, in contrast, is associated to the customer perception according to the fulfilment of its needs during the use phase, translated into customer satisfaction. According to the Service-Dominant Logic, fi 2.4 illustrates the process of value co-creation from a dyadic relationship between provider and customer. [START_REF] Vargo | Service-dominant logic: continuing the evolution[END_REF] In current business configurations, value is created and perceived by a networked set of actors, and not only by dyadic provider-customer relationships [START_REF] Corsaro | The impact of network configurations on value constellations in business markets -The case of an innovation network[END_REF][START_REF] Reypens | Leveraging value in multi-stakeholder innovation networks: A process framework for value co-creation and capture[END_REF][START_REF] Aquilani | The challenging transition to bio-economies: Towards a new framework integrating corporate sustainability and value co-creation[END_REF]. Actually, Integrating sustainability within a company's value creation process, needs the participation of economic and non-economic Mines Saint-E ´ tienne Martha Orellano Carrasquilla 2. 4 Sustainable value creation in B2B markets 23 actors (i.e., suppliers, public actors, research entities, local communities, customers, among others), triggering the organizational transformation of the company [START_REF] Schenkel | Creating integral value for stakeholders in closed loop supply chains[END_REF][START_REF] Joyce | The triple layered business model canvas: A tool to design more sustainable business models[END_REF][START_REF] Lacoste | Sustainable value co-creation in business networks[END_REF][START_REF] Geissdoerfer | The circular economy -a new sustainability paradigm?[END_REF][START_REF] Baldassarre | Bridging sustainable business model innovation and user-driven innovation: A process for sustainable value proposition design[END_REF]. The level of sustainability achieved is conditioned by the engagement of each individual stakeholder, who evaluates diff tly the importance of environmental and social issues within the process of value creation [START_REF] Ballantyne | Industrial Marketing Management Value propositions as communication practice : Taking a wider view[END_REF][START_REF] Schenkel | Creating integral value for stakeholders in closed loop supply chains[END_REF][START_REF] Baldassarre | Bridging sustainable business model innovation and user-driven innovation: A process for sustainable value proposition design[END_REF][START_REF] Aquilani | The challenging transition to bio-economies: Towards a new framework integrating corporate sustainability and value co-creation[END_REF]. Moreover, multiple stakeholder integration takes place at different levels, enabling diff t confi of the value creation process [START_REF] Schenkel | Creating integral value for stakeholders in closed loop supply chains[END_REF][START_REF] Jaakkola | Value co-creation in solution networks[END_REF][START_REF] Lacoste | Sustainable value co-creation in business networks[END_REF]. For instance, demand and supply networks (Yan et al., 2017) (figure 2.5); and business ecosystems [START_REF] Bocken | Value mapping for sustainable business thinking[END_REF] (figure 2.6). Sustainable value propositions development. Sustainable value propositions refer to offers of products or services, which are designed by for the reduction of resource consumption, emissions to the environment, and human damage [START_REF] Manda | Value creation with life cycle assessment: an approach to contextualize the application of life cycle assessment in chemical companies to create sustainable value[END_REF]. Although there is not a standard pathway to develop sustainable value propositions, the literature proposes various sustainability-oriented solutions such as product-service systems, functional economy, circular economy, industrial symbiosis, among others [START_REF] Bocken | A literature and practice review to develop sustainable business model archetypes[END_REF]. Several studies focused on the value proposition as the core element on the business exchange [START_REF] Wang | Logistics Service Providers and Value Creation Through Collaboration: A Case Study[END_REF][START_REF] Ballantyne | Industrial Marketing Management Value propositions as communication practice : Taking a wider view[END_REF][START_REF] Lacoste | Sustainable value co-creation in business networks[END_REF]. To develop sustainable value proposition, suppliers should collaborate with their customers, involving them into the diff t stages of the offer development.

The offer co-development favours knowledge sharing, and the monitoring of the offer performance during the use phase.

Relational ambiguities in value creation. Taking into account the need for collaboration between several actors, the systematic review revealed the risk of relational ambiguities in value co-creation processes. The greater the number of stakeholders, the greater the risk of relational ambiguities and misunderstandings of individual expectations [START_REF] Ballantyne | Industrial Marketing Management Value propositions as communication practice : Taking a wider view[END_REF][START_REF] Sjo ¨din | Value co-creation process of integrated product-services: Effect of role ambiguities and relational coping strategies[END_REF] propose a set of relational ambiguities that can occur when sharing sensitive information and resources in an intensive relational context. These ambiguities can render the value co-creation process diffi Such ambiguities can involve some subsequent relational risks, namely, opportunistic behaviours and conflicts of interest, which can affect the stability of the relationships. To reduce the risk of confl and ambiguity, Kohtama ¨ki and Rajala (2016) propose establishing the roles and the relational governance between actors before the start of the value co-creation process. In this regard, in a multi-stakeholder context, value creation becomes a question of trust between actors, depending on the ethics each actor [START_REF] Coutelle-Brillet | Perceived value of service innovation : a conceptual framework[END_REF][START_REF] Reypens | Leveraging value in multi-stakeholder innovation networks: A process framework for value co-creation and capture[END_REF].

Mines Saint-E ´ tienne Martha Orellano Carrasquilla 2. 5 Proposed framework for the characterisation of sustainable value creation 25

Proposed framework for the characterisation of sustainable value creation

Considering the literature background, sustainable value is mainly constituted by the three classical dimensions contained into the triple bottom line approach to sustainability (i.e., economic, environmental, and social dimensions). Nevertheless, the value in sustainable oriented businesses also integrates a relational dimension. This fourth dimension is a fundamental element to access to resources and knowledge from the diff t key stakeholders concerned with sustainability. Additionally, integrating the marketing and engineering perspectives of value, the main intend of a business activity is creating value to their customers. Certainly, customer value is achieved throughout the provision of functionalities that fi the customer expectations. Considering the above, fi e dimensions have been proposed to characterize the creation of sustainable value in current business models.

(E) Economics: this dimension of value is determined by the benefits and cost savings achieved by the stakeholders involved in the offer development. Achieving the expected economic benefits involves integration of fi risks, uncertainties and return on investments in long-term horizons.

(N) Environmental: this dimension explains the environmental impact of an offer throughout its life cycle. There is the need to perform an input-output analysis of the offer during its life cycle. Input analysis addresses resource consumption, while output analysis addresses emissions of substances to the environment (air, soil, water, biodiversity).

(S) Social : explains the impact of an offer on the well-being of the economic and non-economic stakeholders. The social value is defi in terms of respect for the human rights, dignifi employment conditions, and development of local economies.

(R) Relational: this dimension explains the value derived from the relationships maintained between the actors, going beyond a simple monetary transaction, and which are based on the level of trust and commitment. The value is derived from the quality of the relationships between the actors, enabling the common construction of knowledge.

(F) Functional: this dimension focuses on the functional purpose of the offering, that is, the provision of product and service functionalities that meet the customer needs.

Conclusion

This chapter presented a review of the value concept in business-to-business (B2B) relationships as a multidisciplinary subject, which has evolved over time. We conduct a content analysis of 50 papers published between 2000 and 2018. Three principal features about the concept of the value. Firstly, value is a multidimensional concept, involving economic, environmental, social and other forms of value as knowledge and customer satisfaction. Secondly, achieving sustainable value needs a close collaboration between a broaden set of actors in the value chain. Thirdly, one of the main underpinnings of the multi-stakeholder context is the subjective character of value. Regarding the research questions proposed at the beginning of the chapter, the fi can be detailed as follows:

• RQ1. How has the notion of value been approached in different fields since 2000?

The subject of value creation has been studied mostly in marketing and operations management literature, in which value is an important topic of research, since the 1990s. Moreover, over the last fi e years, the literature on value creation has integrated issues concerning sustainability and actors' collaboration as research priorities.

• RQ2. What does the notion of sustainable value mean in B2B relationships? Value creation in B2B relationships continues to be an area of relevance and interest to academics and practitioners. Recent studies recognize the multi-dimensional character of the value and the need for multi-stakeholder participation in the value creation process. Recently, researches in industrial marketing adopted the triple bottom line approach, integrating economic, environmental, and social dimensions to assess sustainable value. Through the thematic analysis, we concluded that the notion of value is multidimensional, subjective and contextual. Then, we proposed an extended characterization of the value concept according to fi e dimensions: economic, environmental, social, relational and functional (section 2.5).

• RQ3. What are the research challenges about sustainable value creation? Current literature demonstrates that the main challenge on value research is to defi formal frameworks that make it possible to perceive, evaluate and communicate value among a broader set of stakeholders. In this sense, this thesis work aims at contributing to this challenge, integrating multidimensional and multi-stakeholder perspective of value creation. In this chapter, the conceptualization of value has been treated, providing a fi scheme to characterise value creation.

Chapter 3

Collaborative innovation for sustainable value creation

Introduction

According to the literature, any company has the sufficient skills to fulfil by its own the current market requirements related to sustainability issues [START_REF] Rohrbeck | Collaborative business modelling for systemic and sustainability innovations[END_REF][START_REF] Hellström | Collaboration mechanisms for business models in distributed energy ecosystems[END_REF][START_REF] Baldassarre | Bridging sustainable business model innovation and user-driven innovation: A process for sustainable value proposition design[END_REF][START_REF] Aquilani | The challenging transition to bio-economies: Towards a new framework integrating corporate sustainability and value co-creation[END_REF][START_REF] Hankammer | Degrowth and collaborative value creation: Reflections on concepts and technologies[END_REF][START_REF] Brehmer | Sustainable business models as boundary-spanning systems of value transfers[END_REF][START_REF] Brown | Why do companies pursue collaborative circular oriented innovation?[END_REF]. In this sense, companies are pushed to collaborate with other actors in the business ecosystem (i.e., customers, suppliers, competitors, research institutions, among others) to develop competent and sustainable value offers [START_REF] Chesbrough | Business model innovation: it's not just about technology anymore[END_REF][START_REF] Geum | Development of dual technology roadmap (TRM) for open innovation: Structure and typology[END_REF][START_REF] Baldassarre | Bridging sustainable business model innovation and user-driven innovation: A process for sustainable value proposition design[END_REF][START_REF] Jugend | Relationships among open innovation, innovative performance, government support and fi size: Comparing Brazilian fi embracing diff t levels of radicalism in innovation[END_REF]. However, the collaboration between multiple actors is a complex process that implies the understanding of actors' expectations, the efficient management of the relationships, and setting up collaborative decision-making processes [START_REF] Ueda | Value creation and decision-making in sustainable society[END_REF]. Indeed, collaboration between several actors goes beyond of simply putting resources together, instead, it refers to the co-creation of value thought strategic alignment [START_REF] Chester Goduscheit | Paths toward radical service innovation in manufacturing companies-a service-dominant logic perspective[END_REF][START_REF] Grimm | Critical factors for sub-supplier management: A sustainable food supply chains perspective[END_REF][START_REF] Nudurupati | Strategic sourcing with multi-stakeholders through value co-creation: An evidence from global health care company[END_REF][START_REF] Kohtama ¨ki | Theory and practice of value co-creation in B2B systems[END_REF][START_REF] Baldassarre | Bridging sustainable business model innovation and user-driven innovation: A process for sustainable value proposition design[END_REF][START_REF] Brown | Why do companies pursue collaborative circular oriented innovation?[END_REF]. One of the main objectives of multiple actors collaboration is the development of unique innovations, achieved through the strategic combination of resources and knowledge [START_REF] Neutzling | Linking sustainability-oriented innovation to supply chain relationship integration[END_REF]. Such innovations are key drivers in the creation of sustainable value [START_REF] Neutzling | Linking sustainability-oriented innovation to supply chain relationship integration[END_REF][START_REF] Calabrese | Fostering sustainability-oriented service innovation (SOSI) through business model renewal: The SOSI tool[END_REF][START_REF] Brown | Why do companies pursue collaborative circular oriented innovation?[END_REF]. The objective of this chapter is to show and analyse the link between collaboration and sustainable value creation throughout the lens of innovation in B2B contexts. To fulfil this aim, the research questions guiding this chapter are the following:

• RQ1. Why do companies collaborate in B2B?

• RQ2. What is the meaning of collaborative innovation in B2B?

• RQ3. How do companies collaborate in B2B?

• RQ4. How does collaboration enable the creation of sustainable value in B2B?

Literature review methodology

A bibliometric analysis was conducted to identify the linkage points between diff t disciplines of the literature with respect to a specific research subject [START_REF] Geissdoerfer | The circular economy -a new sustainability paradigm?[END_REF]. Moreover, this methodology allows representing the conceptual evolution of the subject, facilitating the identification of the current research interests and gaps [START_REF] Aria | bibliometrix: An r-tool for comprehensive science mapping analysis[END_REF]. The aim of this research is to identify papers related to collaborative innovation as a driver of sustainable value creation. We performed the research methodology following three main phases: i) sources identification, ii) conceptual structure representation, and iii) thematic analysis. The research framework used to structure the literature review is represented in Figure 3 illustrates the two triggers for adopting a collaborative approach in companies (technology-push and demand-pull). Then, the aim of the collaborative process is to perform a type of innovation, necessary for achieving sustainable value creation.

Sources identification

Following a classic methodology of literature review, we performed a research by generic keywords in the fi of interest. We crossed the key words "collab*" AND "innovat*" AND "sustainab*" in Web of Sciences (WOS). We obtained a fi sample of 1 813 papers published between 1975 and 2019. We fi ered the contributions, choosing only peer-reviewed journals, then reducing the sample to 944 papers. We excluded all the papers corresponding to the fi of art, ergonomics, archaeology, chemistry, and biology. As a result, we obtained a sample of 291 contributions corresponding to engineering, environmental sciences, and management, which are in line with the scope of this research.

Conceptual structure

With the base of the pre-selected 291 articles, a clustering technique based on Multiple Correspondence Analysis (MCA) of the articles' keywords was performed. The results lead to the representation of the conceptual structure of the research subject [START_REF] Aria | bibliometrix: An r-tool for comprehensive science mapping analysis[END_REF]. This analysis was performed using the package bibliometrix in R Studio developed by [START_REF] Aria | bibliometrix: An r-tool for comprehensive science mapping analysis[END_REF]. Five clusters were identified, corresponding to diff t topic areas in which the subjects of collaboration, innovation and sustainability have been studied together between 1975 and 2019 (Figure 3.2). C1 is related to the strong sustainability approach, characterised by an ecological and normative perspective. C2 corresponds to the topic of sustainable development through organisational innovation and networking. C3 corresponds to product innovation development as a means to improve fi competitive advantage. C4 refers to the role of R&D in the improvement of technological innovation. Finally, C5 corresponds to the collaborative practices implemented in supply chain management. Regarding the conceptual structure of the subject, the clusters C2 and C5 are selected for further 3 Collaborative innovation for sustainable value creation analysis in this chapter, since they consider the notion of collaboration from an organisational point of view. The three remaining clusters are considered out of our research scope. This process resulted in 40 articles, in which 35 correspond original researches and fi e are literature reviews in innovation management [START_REF] Di Stefano | Technology push and demand pull perspectives in innovation studies: Current fi and future research directions[END_REF][START_REF] West | Open innovation: current status and research opportunities[END_REF][START_REF] Edwards-Schachter | The nature and variety of innovation[END_REF], value creation [START_REF] Kaihara | Value creation in production: Reconsideration from interdisciplinary approaches[END_REF], and supply chain collaboration [START_REF] Chen | Supply chain collaboration for sustainability: A literature review and future research agenda[END_REF].

Thematic analysis

A thematic analysis of the selected sample was performed. A co-word analysis was performed by means of the bibliometrix package in R Studio [START_REF] Aria | bibliometrix: An r-tool for comprehensive science mapping analysis[END_REF]. This technique allows representing a thematic map of the selected papers (Figure 3.3). The thematic map allows classifying the articles according to the two dimensions of centrality and density, resulting in four quadrants of characterisation. The interpretation of each quadrant is as follows: i) upper-right quadrant indicates the motor-themes; ii) lower-right quadrant refers to the basic themes; iii) lower-left quadrant contains the emerging or disappearing themes; and iv) upper-left quadrant covers the very specialized themes [START_REF] Cobo | An approach for detecting, quantifying, and visualizing the evolution of a research fi A practical application to the Fuzzy Sets Theory[END_REF]. Five clusters were obtained, indicating diff t themes or research fi Value creation, collaboration networks, innovation management, supply chain integration and sustainable oriented innovation. Given the conceptual proximity of the themes of value creation and collaborative networks, we decided to considered them as a single theme. We obtained 37% of the articles addressing value creation and collaborative business models, which are considered basic themes in the research on collaborative innovation for sustainability [START_REF] Payne | Managing the co-creation of value[END_REF][START_REF] Rohrbeck | Collaborative business modelling for systemic and sustainability innovations[END_REF][START_REF] Hallikas | Service purchasing and value creation: Towards systemic purchases[END_REF][START_REF] Hellström | Collaboration mechanisms for business models in distributed energy ecosystems[END_REF][START_REF] Kohtama ¨ki | Theory and practice of value co-creation in B2B systems[END_REF][START_REF] Matinheikki | From the profi of one toward benefitting many -Crafting a vision of shared value creation[END_REF][START_REF] Hankammer | Degrowth and collaborative value creation: Reflections on concepts and technologies[END_REF][START_REF] Brehmer | Sustainable business models as boundary-spanning systems of value transfers[END_REF]. 26% of the contributions belongs to the fi of innovation management, which is a motor theme [START_REF] Huizingh | Open innovation: State of the art and future perspectives[END_REF][START_REF] Shaw | Innovation-sharing across a supply network: barriers to collaboration[END_REF][START_REF] Geum | Development of dual technology roadmap (TRM) for open innovation: Structure and typology[END_REF][START_REF] Maine | Radical innovation from the confluence of technologies: Innovation management strategies for the emerging nanobiotechnology industry[END_REF][START_REF] Lancker | The organizational innovation system: A systemic framework for radical innovation at the organizational level[END_REF][START_REF] Chester Goduscheit | Paths toward radical service innovation in manufacturing companies-a service-dominant logic perspective[END_REF][START_REF] Jugend | Relationships among open innovation, innovative performance, government support and fi size: Comparing Brazilian fi embracing diff t levels of radicalism in innovation[END_REF]. 26% of the articles addresses the collaborative practices in supply chain management, which is a specialized theme [START_REF] Schiele | How to distinguish innovative suppliers? identifying innovative suppliers as new task for purchasing[END_REF][START_REF] Walker | Fostering sustainability through sourcing from small businesses: public sector perspectives[END_REF][START_REF] Derrouiche | B2B relationship management: a framework to explore the impact of collaboration[END_REF][START_REF] Kang | Do external knowledge sourcing modes matter for service innovation? empirical evidence from south korean service fi[END_REF][START_REF] Nudurupati | Strategic sourcing with multi-stakeholders through value co-creation: An evidence from global health care company[END_REF][START_REF] Wang | Logistics Service Providers and Value Creation Through Collaboration: A Case Study[END_REF]. Finally, Sustainable-Oriented Innovation (SOI) is an emerging theme constituting the 11% of the total of analysed articles [START_REF] Hellström | Dimensions of environmentally sustainable innovation: the structure of eco-innovation concepts[END_REF][START_REF] Neutzling | Linking sustainability-oriented innovation to supply chain relationship integration[END_REF][START_REF] Calabrese | Fostering sustainability-oriented service innovation (SOSI) through business model renewal: The SOSI tool[END_REF][START_REF] Brown | Why do companies pursue collaborative circular oriented innovation?[END_REF]. A detailed content analysis of the articles was performed to obtain more precise insights about the relationship between collaborative innovation and sustainable value creation. Table 3.1 shows the list of the articles classified by theme, specifying the elements of collaborative innovation (i.e., trigger, collaboration approach, and innovation object), which impact on the dimensions of value creation (c.f., Chapter 2) indicated by "X". The results obtained are developed in the next sections.

Collaborative innovation: key concepts

Innovation has been traditionally defi as the set of technical, industrial and commercial improvements that enables organisations to perform efficiently their economic activities [START_REF] Rothwell | Developments towards the fi generation model of innovation[END_REF]. In general terms, innovation means the introduction of "something new" in a specific context [START_REF] Schiele | How to distinguish innovative suppliers? identifying innovative suppliers as new task for purchasing[END_REF]. Although the defi of innovation has not changed significantly with respect to the object (i.e., product, process, organisation, etc.), the way to develop it has changed drastically along the time [START_REF] Huizingh | Open innovation: State of the art and future perspectives[END_REF]. In this sense, innovation has shifted from a closed process inside a company's boundaries to a complex process of collaboration between multiple actors [START_REF] Chesbrough | Business model innovation: it's not just about technology anymore[END_REF][START_REF] Huizingh | Open innovation: State of the art and future perspectives[END_REF][START_REF] Hsieh | Strategy and process of value creation and appropriation in service clusters[END_REF][START_REF] Lancker | The organizational innovation system: A systemic framework for radical innovation at the organizational level[END_REF][START_REF] Jugend | Relationships among open innovation, innovative performance, government support and fi size: Comparing Brazilian fi embracing diff t levels of radicalism in innovation[END_REF]. For instance, [START_REF] Lancker | The organizational innovation system: A systemic framework for radical innovation at the organizational level[END_REF] consider innovation as the iterative process of learning, which needs intensive collaboration between a broader set of actors to improve a company value creation.

From the content analysis of the selected articles, (c.f., subsection 3.2.3) four main themes were identified in which the notion of collaborative innovation has been studied. Those are value creation, innovation management, supply chain management, and sustainable oriented innovation. Literature on value creation addresses customer satisfaction and sustainability issues through business models innovation (e.g., Kohtama ¨ki and Rajala ( 2016)). In innovation management, the collaboration between several actors focuses on the exchange and generation of knowledge (e.g., [START_REF] Huizingh | Open innovation: State of the art and future perspectives[END_REF]). In supply chain management there is an increasing interest in the integration of sustainability criteria in supply chain decisions. Here, the purchasing function has a fundamental role in pursuing sustainable practices (e.g., [START_REF] Chen | Supply chain collaboration for sustainability: A literature review and future research agenda[END_REF]). Finally, sustainability oriented innovation, is a new stream that establishes the link between innovation and value creation, referring to sustainable policies and corporate social responsibility applied to offers, processes and organisations (e.g., [START_REF] Brown | Why do companies pursue collaborative circular oriented innovation?[END_REF]).

Crossing these four research fi s, we explored the three features that contribute to answer our research questions in this chapter: i) the triggers of collaborative innovation, ii) the type of innovation, and iii) the collaboration approach adopted by a given company.

Firstly, the triggers of collaborative innovation address the fi research question of this chapter, concerning to the motivation of companies to perform collaborative innovation. The literature develops two major triggers of collaborative innovation referred as the technology-push and demand-pull approaches, respectively [START_REF] Di Stefano | Technology push and demand pull perspectives in innovation studies: Current fi and future research directions[END_REF]. Secondly, diff t types of innovation can be identified according to the object, the strategy and the degree of collaboration. According to the object, it can be the offer, the process, or the organisation [START_REF] Neutzling | Linking sustainability-oriented innovation to supply chain relationship integration[END_REF][START_REF] Edwards-Schachter | The nature and variety of innovation[END_REF]. According to the adopted strategy, innovation can be incremental or radical, and modular or systemic [START_REF] Shaw | Innovation-sharing across a supply network: barriers to collaboration[END_REF][START_REF] Edwards-Schachter | The nature and variety of innovation[END_REF]. Finally, depending on the openness of the focal company to external actors, there is a continuum between closed and collaborative innovation [START_REF] Chesbrough | Business model innovation: it's not just about technology anymore[END_REF][START_REF] Huizingh | Open innovation: State of the art and future perspectives[END_REF]. In the following, these key concepts are further developed.

Mines Saint-E ´ tienne Martha Orellano Carrasquilla 3.4 Triggers of collaborative innovation (why?) 35

Triggers of collaborative innovation (why?)

Technology-push approach

The technology-push approach highlights the key role of technology and the existing company's knowledge as major triggers of innovation, which is initiated by a provider company [START_REF] Di Stefano | Technology push and demand pull perspectives in innovation studies: Current fi and future research directions[END_REF]. This approach defends the idea that technology is the main source of innovation development, aiming at pushing an innovative offer to the market [START_REF] Di Stefano | Technology push and demand pull perspectives in innovation studies: Current fi and future research directions[END_REF]. In this case, the customer demand is taken into account as a complement to guide the innovation in the right economic direction. From the technology-push perspective, collaboration in B2B consists of exchanges between the supplier network and the customer. In general, the customer participates at last stages the process of innovation as a resource integrator (c.f., Resource-based view [START_REF] Barney | Firm resources and sustained competitive advantage[END_REF][START_REF] Möller | Business suppliers' value creation potential: A capability-based analysis[END_REF]). According to the literature review performed by Di Stefano et al. ( 2012), the technology-push approach is mostly related to technology development, product innovation, and technological diff in the market. In the technology-push approach, the principal motivations that push to adopt collaborative innovation strategy are: increasing the customer satisfaction with innovative offers [START_REF] Payne | Managing the co-creation of value[END_REF][START_REF] Chester Goduscheit | Paths toward radical service innovation in manufacturing companies-a service-dominant logic perspective[END_REF]; achieving competitive advantage [START_REF] Derrouiche | B2B relationship management: a framework to explore the impact of collaboration[END_REF][START_REF] Kohtama ¨ki | Theory and practice of value co-creation in B2B systems[END_REF][START_REF] Neutzling | Linking sustainability-oriented innovation to supply chain relationship integration[END_REF][START_REF] Chester Goduscheit | Paths toward radical service innovation in manufacturing companies-a service-dominant logic perspective[END_REF][START_REF] Jugend | Relationships among open innovation, innovative performance, government support and fi size: Comparing Brazilian fi embracing diff t levels of radicalism in innovation[END_REF]; capitalization of knowledge [START_REF] Huizingh | Open innovation: State of the art and future perspectives[END_REF][START_REF] Geum | Development of dual technology roadmap (TRM) for open innovation: Structure and typology[END_REF][START_REF] Brown | Why do companies pursue collaborative circular oriented innovation?[END_REF]; sharing resources, risks and costs [START_REF] Shaw | Innovation-sharing across a supply network: barriers to collaboration[END_REF][START_REF] Maine | Radical innovation from the confluence of technologies: Innovation management strategies for the emerging nanobiotechnology industry[END_REF]; and, recently, addressing sustainability issues [START_REF] Hellström | Collaboration mechanisms for business models in distributed energy ecosystems[END_REF][START_REF] Neutzling | Linking sustainability-oriented innovation to supply chain relationship integration[END_REF][START_REF] Hankammer | Degrowth and collaborative value creation: Reflections on concepts and technologies[END_REF][START_REF] Brehmer | Sustainable business models as boundary-spanning systems of value transfers[END_REF][START_REF] Calabrese | Fostering sustainability-oriented service innovation (SOSI) through business model renewal: The SOSI tool[END_REF][START_REF] Brown | Why do companies pursue collaborative circular oriented innovation?[END_REF].

Demand-pull approach

In the demand-pull approach, innovation is the result of market demand, which directly triggers the development of innovations to respond to unmet customer needs [START_REF] Di Stefano | Technology push and demand pull perspectives in innovation studies: Current fi and future research directions[END_REF]. The principal actors in demand-pull approach are the ones directly involved in customer-provider relationships (e.g., the purchasing function in B2B markets) [START_REF] Di Stefano | Technology push and demand pull perspectives in innovation studies: Current fi and future research directions[END_REF]. Given the predominance of the technology-push approach in theory and practice, the literature review reveals a lack of knowledge concerning the collaborative practices when the innovation initiative comes from the customer side (Yan et al., 2017).

The demand-pull approach to innovation is seen as a complement to the technology-push one, which help to fi the real market needs. According to [START_REF] Möller | Business suppliers' value creation potential: A capability-based analysis[END_REF], the main features of the demand-pull approach are the central role of the customer, the complex relationships with old and new actors in the value chain [START_REF] Nudurupati | Strategic sourcing with multi-stakeholders through value co-creation: An evidence from global health care company[END_REF], the intensive knowledge exchange between the actors [START_REF] Kang | Do external knowledge sourcing modes matter for service innovation? empirical evidence from south korean service fi[END_REF][START_REF] Reypens | Leveraging value in multi-stakeholder innovation networks: A process framework for value co-creation and capture[END_REF], and the radical transformation of internal and external value chains [START_REF] Möller | Business suppliers' value creation potential: A capability-based analysis[END_REF][START_REF] Nudurupati | Strategic sourcing with multi-stakeholders through value co-creation: An evidence from global health care company[END_REF]. The literature reveals that in a demand-pull approach is often diffi to distinguish the exact role of the customer 3 Collaborative innovation for sustainable value creation from that of the supplier in the value co-creation process [START_REF] Möller | Business suppliers' value creation potential: A capability-based analysis[END_REF]. Some of the motivations of the demand-pull approach found in the literature are: increasing customer value in use [START_REF] Hallikas | Service purchasing and value creation: Towards systemic purchases[END_REF][START_REF] Nudurupati | Strategic sourcing with multi-stakeholders through value co-creation: An evidence from global health care company[END_REF]; creating societal value [START_REF] Matinheikki | From the profi of one toward benefitting many -Crafting a vision of shared value creation[END_REF]; sharing resources and risks [START_REF] Kang | Do external knowledge sourcing modes matter for service innovation? empirical evidence from south korean service fi[END_REF]; creating sustainable value [START_REF] Hellström | Dimensions of environmentally sustainable innovation: the structure of eco-innovation concepts[END_REF][START_REF] Walker | Fostering sustainability through sourcing from small businesses: public sector perspectives[END_REF][START_REF] Rohrbeck | Collaborative business modelling for systemic and sustainability innovations[END_REF][START_REF] Calabrese | Fostering sustainability-oriented service innovation (SOSI) through business model renewal: The SOSI tool[END_REF][START_REF] Brown | Why do companies pursue collaborative circular oriented innovation?[END_REF]; and knowledge capitalization [START_REF] Hellström | Dimensions of environmentally sustainable innovation: the structure of eco-innovation concepts[END_REF]. It is noticed that sustainability issues is a major preoccupation in the demand-pull approach. Usually, the need to integrate sustainability aspects in a company's strategy comes from governmental policies [START_REF] Brown | Why do companies pursue collaborative circular oriented innovation?[END_REF], which implies the involvement of actors from the public sector (i.e., policy-oriented partnerships) [START_REF] Hellström | Dimensions of environmentally sustainable innovation: the structure of eco-innovation concepts[END_REF][START_REF] Walker | Fostering sustainability through sourcing from small businesses: public sector perspectives[END_REF][START_REF] Matinheikki | From the profi of one toward benefitting many -Crafting a vision of shared value creation[END_REF][START_REF] Calabrese | Fostering sustainability-oriented service innovation (SOSI) through business model renewal: The SOSI tool[END_REF].

Types of innovation (what?)

According to the innovation object

In a recent literature review, Edwards-Schachter (2018) explains the multidimensionality of the concept of innovation, and highlights the diffi y to get a clear conceptualization of the term. Nevertheless, innovation has been traditionally associated with "a new way to do something", supposing a technological change in a given context [START_REF] Edwards-Schachter | The nature and variety of innovation[END_REF]. Moreover, there exist three well-established types of innovation corresponding to product, process, and organisation, derived from the seminal Schumpeterian innovation theory [START_REF] Ueda | Value creation and decision-making in sustainable society[END_REF].

Firstly, product innovation is the oldest approach to innovation, highly studied in the literature of New Product Development (NPD) [START_REF] Schiele | How to distinguish innovative suppliers? identifying innovative suppliers as new task for purchasing[END_REF][START_REF] Edwards-Schachter | The nature and variety of innovation[END_REF]. It corresponds to the improvements on a given product, allowing completely new usages [START_REF] Shaw | Innovation-sharing across a supply network: barriers to collaboration[END_REF][START_REF] Geum | Development of dual technology roadmap (TRM) for open innovation: Structure and typology[END_REF][START_REF] Maine | Radical innovation from the confluence of technologies: Innovation management strategies for the emerging nanobiotechnology industry[END_REF], or enabling the management of environmental impacts (e.g., eco-innovation) [START_REF] Hellström | Dimensions of environmentally sustainable innovation: the structure of eco-innovation concepts[END_REF][START_REF] Garcia | Challenges of creating and capturing value in open eco-innovation: Evidence from the maritime industry in denmark[END_REF].

Secondly, process innovation refers to the new ways to perform organisational and production activities into a company [START_REF] Shaw | Innovation-sharing across a supply network: barriers to collaboration[END_REF][START_REF] Geum | Development of dual technology roadmap (TRM) for open innovation: Structure and typology[END_REF][START_REF] Maine | Radical innovation from the confluence of technologies: Innovation management strategies for the emerging nanobiotechnology industry[END_REF][START_REF] Wang | Logistics Service Providers and Value Creation Through Collaboration: A Case Study[END_REF][START_REF] Edwards-Schachter | The nature and variety of innovation[END_REF][START_REF] Brown | Why do companies pursue collaborative circular oriented innovation?[END_REF]. The change can be produced from the introduction of new technologies or from activity optimization. It is closely related to product innovation, since the product is the result of a process.

Finally, organisational innovation corresponds to a complex level of innovation that implies a holistic transformation in a company's internal and external structures [START_REF] Chesbrough | Business model innovation: it's not just about technology anymore[END_REF][START_REF] Shaw | Innovation-sharing across a supply network: barriers to collaboration[END_REF][START_REF] Chester Goduscheit | Paths toward radical service innovation in manufacturing companies-a service-dominant logic perspective[END_REF][START_REF] Jugend | Relationships among open innovation, innovative performance, government support and fi size: Comparing Brazilian fi embracing diff t levels of radicalism in innovation[END_REF][START_REF] Brown | Why do companies pursue collaborative circular oriented innovation?[END_REF]). Company's internal and external structure refers to the relationships between the actors and the diff t processes taking place at the systemic level. [START_REF] Huizingh | Open innovation: State of the art and future perspectives[END_REF][START_REF] Shaw | Innovation-sharing across a supply network: barriers to collaboration[END_REF][START_REF] Lancker | The organizational innovation system: A systemic framework for radical innovation at the organizational level[END_REF][START_REF] Chester Goduscheit | Paths toward radical service innovation in manufacturing companies-a service-dominant logic perspective[END_REF][START_REF] Jugend | Relationships among open innovation, innovative performance, government support and fi size: Comparing Brazilian fi embracing diff t levels of radicalism in innovation[END_REF]. Business model innovation is a form of organisational innovation [START_REF] Chesbrough | Business model innovation: it's not just about technology anymore[END_REF][START_REF] Rohrbeck | Collaborative business modelling for systemic and sustainability innovations[END_REF][START_REF] Hellström | Collaboration mechanisms for business models in distributed energy ecosystems[END_REF][START_REF] Hankammer | Degrowth and collaborative value creation: Reflections on concepts and technologies[END_REF][START_REF] Brehmer | Sustainable business models as boundary-spanning systems of value transfers[END_REF], and deals with the transformation in the way a company creates and captures value.

According to the innovation strategy

Traditionally, the output of the innovation process has been categorised as incremental or radical [START_REF] Rothwell | Developments towards the fi generation model of innovation[END_REF][START_REF] Shaw | Innovation-sharing across a supply network: barriers to collaboration[END_REF][START_REF] Edwards-Schachter | The nature and variety of innovation[END_REF][START_REF] Chester Goduscheit | Paths toward radical service innovation in manufacturing companies-a service-dominant logic perspective[END_REF], and modular or systemic (Hellstro ¨m, 2007;[START_REF] Shaw | Innovation-sharing across a supply network: barriers to collaboration[END_REF]. On the one side, this categorisation is related to the level of disruptiveness a company is aiming to achieve [START_REF] Maine | Radical innovation from the confluence of technologies: Innovation management strategies for the emerging nanobiotechnology industry[END_REF][START_REF] Edwards-Schachter | The nature and variety of innovation[END_REF]. On the other side, this refers to the scope of the innovation [START_REF] Shaw | Innovation-sharing across a supply network: barriers to collaboration[END_REF].

From incremental to radical innovation. Incremental innovation refers to small and cumulative improvements in the object of innovation (i.e., offer, process, organisation) [START_REF] Chester Goduscheit | Paths toward radical service innovation in manufacturing companies-a service-dominant logic perspective[END_REF][START_REF] Edwards-Schachter | The nature and variety of innovation[END_REF]. Incremental innovation is often related with the exploitation of company's internal knowledge and resources [START_REF] Chester Goduscheit | Paths toward radical service innovation in manufacturing companies-a service-dominant logic perspective[END_REF][START_REF] Edwards-Schachter | The nature and variety of innovation[END_REF]. Radical innovation, in contrast, needs the integration of external knowledge, since it refers to the development of completely new offers, processes or organisations with the aim to create new markets [START_REF] Chester Goduscheit | Paths toward radical service innovation in manufacturing companies-a service-dominant logic perspective[END_REF][START_REF] Edwards-Schachter | The nature and variety of innovation[END_REF]. In both cases, the innovation effort relies on the capability of the company to exploit knowledge in order to create higher value than in the current situation.

From modular to systemic innovation. Innovation can be also modular or systemic [START_REF] Hellström | Dimensions of environmentally sustainable innovation: the structure of eco-innovation concepts[END_REF][START_REF] Shaw | Innovation-sharing across a supply network: barriers to collaboration[END_REF]. Modular innovation addresses one or some parts of a system to be innovated, without changing the entire system. It could take places when, for example, one or more modules nested within a larger system are replaced to improve the system performance. Besides, systemic innovation implies a complete transformation of the object of innovation, which is translated into a completely diff nt functioning of the system. In general, modular and systemic innovation correspond to incremental and radical innovation, respectively. Nevertheless, in some cases, a modular innovation can derive into the transformation of the whole system functioning [START_REF] Shaw | Innovation-sharing across a supply network: barriers to collaboration[END_REF].

According to the degree of collaboration

According to [START_REF] Lancker | The organizational innovation system: A systemic framework for radical innovation at the organizational level[END_REF], innovation involves an evolutionary, non-linear and iterative learning process, which requires intense communication and collaboration between diff t actors in the value system. This assumption has its antecedents from the well-known Stakeholder Theory [START_REF] Freeman | Stakeholder Theory: The State of the Art[END_REF], which defi economic and non-economic actors as part of the business ecosystem. Adopting a collaborative 3 Collaborative innovation for sustainable value creation approach has some implications to the internal company's configuration and its relationship with the external environment [START_REF] Freeman | Stakeholder Theory: The State of the Art[END_REF]. Indeed, adopting an innovation strategy needs the focal company to entail internal and external collaboration processes [START_REF] Schiele | How to distinguish innovative suppliers? identifying innovative suppliers as new task for purchasing[END_REF][START_REF] Huizingh | Open innovation: State of the art and future perspectives[END_REF][START_REF] Yoon | Typology and success factors of collaboration for sustainable growth in the it service industry[END_REF]. According to the willingness of a company to collaborate with its environment, several configurations can take place going from closed to open innovation strategies. [START_REF] Huizingh | Open innovation: State of the art and future perspectives[END_REF] proposes four types of innovation according to the degree of openness of the focal company to the external environment:

Closed innovation. As stated on previous work [START_REF] Rothwell | Developments towards the fi generation model of innovation[END_REF], closed innovation development is based on the internal R&D capabilities of the focal fi in isolation. It is the oldest innovation model, corresponding to the mass production era, in which the main issues are R&D efficiency, intellectual property and technological development. In this model, value creation depends on the company ability to capitalize and exploit its own knowledge to create diff tiated products compared to the competitors. In this context, company's intellectual property is a critical driver of value creation, while collaboration is absent from the managerial concerns .

Out-bound open innovation. Refers to the ability of a company to commercialize internal knowledge in the external environment [START_REF] Huizingh | Open innovation: State of the art and future perspectives[END_REF]. This model requires some degree of collaboration of the focal fi with external actors, which are the customers of the innovation. Here, collaborative practices are key value drivers, which allows the focal company to understand the external needs and processes.

In-bound open innovation. Corresponds to the sourcing and acquisition of expertise from outside the focal company, and the ability to exploit it internally [START_REF] Huizingh | Open innovation: State of the art and future perspectives[END_REF]. In this case there is a need for an intensive internal collaboration coupled with a strategic external collaboration. The internal collaboration is crucial to align the fi culture and capabilities to the external knowledge, allowing the integration into the company processes.

Collaborative innovation. It is a general notion covering all the relationships based on the collaboration and the long-term engagement between two or more industrial actors. [START_REF] Neutzling | Linking sustainability-oriented innovation to supply chain relationship integration[END_REF] affirm that inter-organisational collaboration is essential to achieve effective innovation development in a given industrial sector. There exist several sub-categories going from dyadic collaboration (i.e., provider-customer value co-creation) [START_REF] Schiele | How to distinguish innovative suppliers? identifying innovative suppliers as new task for purchasing[END_REF][START_REF] Payne | Managing the co-creation of value[END_REF][START_REF] Derrouiche | B2B relationship management: a framework to explore the impact of collaboration[END_REF][START_REF] Grimm | Critical factors for sub-supplier management: A sustainable food supply chains perspective[END_REF][START_REF] Kohtama ¨ki | Theory and practice of value co-creation in B2B systems[END_REF] to networked approaches [START_REF] Romero | Collaborative networked organisations and customer communities: value co-creation and co-innovation in the networking era[END_REF][START_REF] Shaw | Innovation-sharing across a supply network: barriers to collaboration[END_REF][START_REF] Nudurupati | Strategic sourcing with multi-stakeholders through value co-creation: An evidence from global health care company[END_REF][START_REF] Hellström | Collaboration mechanisms for business models in distributed energy ecosystems[END_REF][START_REF] Reypens | Leveraging value in multi-stakeholder innovation networks: A process framework for value co-creation and capture[END_REF][START_REF] Wang | Logistics Service Providers and Value Creation Through Collaboration: A Case Study[END_REF][START_REF] Lancker | The organizational innovation system: A systemic framework for radical innovation at the organizational level[END_REF], in which several actors on the extended value chain are integrated, including economic and non-economic ones (i.e., customer, suppliers, competitors, governmental organisations, communities, etc.). The Mines Saint-E ´ tienne Martha Orellano Carrasquilla 3. 6 Collaborative innovation in today's business to business relationships (how?) 39 literature reveals that one of the most updated approaches of collaborative innovation is known as open innovation [START_REF] Chesbrough | Business model innovation: it's not just about technology anymore[END_REF][START_REF] Geum | Development of dual technology roadmap (TRM) for open innovation: Structure and typology[END_REF][START_REF] Maine | Radical innovation from the confluence of technologies: Innovation management strategies for the emerging nanobiotechnology industry[END_REF][START_REF] Jugend | Relationships among open innovation, innovative performance, government support and fi size: Comparing Brazilian fi embracing diff t levels of radicalism in innovation[END_REF], referring to inside-out and out-side in flows of knowledge between the actors in a long term engagement strategy.

3.6

Collaborative innovation in today's business to business relationships (how?)

The requisites for successful collaborative innovation

The basis of collaborative innovation is the management of the relationships between actors [START_REF] Shaw | Innovation-sharing across a supply network: barriers to collaboration[END_REF][START_REF] Maine | Radical innovation from the confluence of technologies: Innovation management strategies for the emerging nanobiotechnology industry[END_REF][START_REF] Matinheikki | From the profi of one toward benefitting many -Crafting a vision of shared value creation[END_REF][START_REF] Hellström | Dimensions of environmentally sustainable innovation: the structure of eco-innovation concepts[END_REF]. The major aspect to focus on is to characterise relationships in a collaborative context [START_REF] Derrouiche | B2B relationship management: a framework to explore the impact of collaboration[END_REF][START_REF] Lancker | The organizational innovation system: A systemic framework for radical innovation at the organizational level[END_REF][START_REF] Yoon | Typology and success factors of collaboration for sustainable growth in the it service industry[END_REF]. Relationships between the customer and the providers implies relational elements beyond a simple transactional process (e.g., trusts and commitment). [START_REF] Derrouiche | B2B relationship management: a framework to explore the impact of collaboration[END_REF] propose to characterise relationships through some criteria related to relational quality, for instance, the degree of commitment between the actors, the long-term vision on the relationships, and the balance on the inter-dependency. In general, collaboration needs an initial effort of the actors at the strategic level which corresponds to defi mutual objectives, establishing integrated policies and performing collaborative decision-making processes [START_REF] Ueda | Value creation and decision-making in sustainable society[END_REF][START_REF] Derrouiche | B2B relationship management: a framework to explore the impact of collaboration[END_REF][START_REF] Reypens | Leveraging value in multi-stakeholder innovation networks: A process framework for value co-creation and capture[END_REF]. The willingness of the companies to collaborate is essential but not sufficient. In this sense, some operational prerequisites that make collaboration possible are highlighted in t he literature and can be classified as preliminary, internal collaboration and external collaboration requisites.

Preliminary requisites. First, it is necessary identify the focal fi which is the company initiating the innovation project. Inside the company, it is necessary to identify a corresponding "leader" or "champion" and a leading group formed by internal key actors [START_REF] Nudurupati | Strategic sourcing with multi-stakeholders through value co-creation: An evidence from global health care company[END_REF][START_REF] Reypens | Leveraging value in multi-stakeholder innovation networks: A process framework for value co-creation and capture[END_REF]. The leading group coordinates and monitor the project development inside and outside the company boundaries. Once the focal fi and the respective champion and leading group are set, it is necessary to prepare the company to collaborate inside (cross-functional collaboration) and outside its boundaries (inter-organisational collaboration).

Internal collaboration requisites.

It is necessary to establish the conditions for collaboration at the company's internal level. Intra-organisational collaboration involves a cross-functional approach that depends very much on the company culture [START_REF] Huizingh | Open innovation: State of the art and future perspectives[END_REF][START_REF] Reypens | Leveraging value in multi-stakeholder innovation networks: A process framework for value co-creation and capture[END_REF][START_REF] Yoon | Typology and success factors of collaboration for sustainable growth in the it service industry[END_REF]. First, the focal company should be able to recognise and forecast the value opportunity in the collaboration. Second, it is required to be aware to invest on internal competences and resources [START_REF] Neutzling | Linking sustainability-oriented innovation to supply chain relationship integration[END_REF].

Finally, the focal company should provoke an inter-functional collaboration with the aim 3 Collaborative innovation for sustainable value creation of achieving internal goal-alignment [START_REF] Grimm | Critical factors for sub-supplier management: A sustainable food supply chains perspective[END_REF][START_REF] Yoon | Typology and success factors of collaboration for sustainable growth in the it service industry[END_REF]. In line with [START_REF] Schiele | How to distinguish innovative suppliers? identifying innovative suppliers as new task for purchasing[END_REF], a robust and organised internal collaboration is the base of a successful external collaboration.

External collaboration requisites.

Inter-organisational collaboration is much more complex than internal collaboration, since it involves heterogeneous actors with their own organisational culture and interests [START_REF] Romero | Collaborative networked organisations and customer communities: value co-creation and co-innovation in the networking era[END_REF][START_REF] Reypens | Leveraging value in multi-stakeholder innovation networks: A process framework for value co-creation and capture[END_REF][START_REF] Baldassarre | Bridging sustainable business model innovation and user-driven innovation: A process for sustainable value proposition design[END_REF]. The main motivation for the actors to collaborate in a value network is the expected value to be captured, which is superior to the invested efforts [START_REF] Romero | Collaborative networked organisations and customer communities: value co-creation and co-innovation in the networking era[END_REF][START_REF] Hellström | Collaboration mechanisms for business models in distributed energy ecosystems[END_REF]. Inter-organisational collaboration has its antecedents in the Resource-based view [START_REF] Barney | Firm resources and sustained competitive advantage[END_REF], referring to the strategic management of external resources. For [START_REF] Hallikas | Service purchasing and value creation: Towards systemic purchases[END_REF] and [START_REF] Neutzling | Linking sustainability-oriented innovation to supply chain relationship integration[END_REF], collaboration is much more than putting resources together, instead, it is creating unique capabilities from resources and knowledge integration. Thus, the actors in the value network should be conscious about being part of a network, and not isolated actors looking exclusively for its own benefit.

Indeed, some of the requisites for successful external collaboration are, fi , having the capability to integrate external knowledge into the internal know-how, which is known as "absorption capacity" [START_REF] Huizingh | Open innovation: State of the art and future perspectives[END_REF][START_REF] Yoon | Typology and success factors of collaboration for sustainable growth in the it service industry[END_REF]. Secondly, good quality of actors relationships, determined by the level of trust, adaptation, communication, participation, problem-solving orientation, among others [START_REF] Schiele | How to distinguish innovative suppliers? identifying innovative suppliers as new task for purchasing[END_REF][START_REF] Yoon | Typology and success factors of collaboration for sustainable growth in the it service industry[END_REF]. Thridly, a clear understanding of the value expected for each actor, as well as the interdependence relationships between the actors (i.e., goals, resources, capabilities, activities, etc.) [START_REF] Hellström | Collaboration mechanisms for business models in distributed energy ecosystems[END_REF]. Finally, it is necessary to identify the potential sources of conflicts (e.g., information asymmetry, opportunistic behaviour) [START_REF] Spekman | Strategic supplier selection: Understanding long-term buyer relationships[END_REF][START_REF] Yoon | Typology and success factors of collaboration for sustainable growth in the it service industry[END_REF].

The most critical point for a successful collaborative innovation is to ensure the alignment of the actors' objectives at internal and external levels [START_REF] Derrouiche | B2B relationship management: a framework to explore the impact of collaboration[END_REF][START_REF] Reypens | Leveraging value in multi-stakeholder innovation networks: A process framework for value co-creation and capture[END_REF][START_REF] Baldassarre | Bridging sustainable business model innovation and user-driven innovation: A process for sustainable value proposition design[END_REF][START_REF] Matinheikki | From the profi of one toward benefitting many -Crafting a vision of shared value creation[END_REF]. This condition supposes a cognitive alignment between actors that are highly heterogeneous. To this end, it is necessary to recognise the opportunity to create superior value from joint innovation development instead of isolated value creation [START_REF] Matinheikki | From the profi of one toward benefitting many -Crafting a vision of shared value creation[END_REF]. The way in which the collaboration process is hold by the actors depends on the individual need for engaging the collaboration (i.e., related to the company progress), the constraints linked to the confi tiality information (i.e., risk of information asymmetries), and the stage of the development life cycle of the innovation (i.e., idea generation, conceptualization, development, etc.) [START_REF] Lancker | The organizational innovation system: A systemic framework for radical innovation at the organizational level[END_REF]. The analysis of the evolution of the relationships in B2B with a extended vision is indispensable to understand value creation within complex collaborative business ecosystems.

The process of collaborative innovation

Any process of collaborative innovation starts with the recognition of an opportunity to create high value in a networked organisation [START_REF] Kang | Do external knowledge sourcing modes matter for service innovation? empirical evidence from south korean service fi[END_REF]. Then, the opportunity recognition is translated into an innovation project. However, there exist diff t configurations in the collaborative innovation process, depending on the industrial context, the origin of the innovation project, the investment capabilities of the actors, among others factors [START_REF] Schiele | How to distinguish innovative suppliers? identifying innovative suppliers as new task for purchasing[END_REF]. It should be noted that the healthcare industry is a rich source of collaborative innovation practices, since it involves a high level of actor's heterogeneity in terms of knowledge, financial structure and governance [START_REF] Walker | Fostering sustainability through sourcing from small businesses: public sector perspectives[END_REF][START_REF] Nudurupati | Strategic sourcing with multi-stakeholders through value co-creation: An evidence from global health care company[END_REF][START_REF] Reypens | Leveraging value in multi-stakeholder innovation networks: A process framework for value co-creation and capture[END_REF]. For instance, [START_REF] Schweizer | Guiding principles of value creation through collaborative innovation in pharmaceutical research[END_REF] performed an empirical study in the pharmaceutical industry, which leads to the identification of three main phases that characterise any process of collaborative innovation, described below.

Inception. The focal company (i.e., initiator of innovative project of value creation) identifies an innovative opportunity for value creation. Similarly, the need to collaborate into a mutual interest project with external actors is identified. Then, it is necessary to draw out the synergistic values between the potential collaborators, which determines the motivations to adhering the project [START_REF] Reypens | Leveraging value in multi-stakeholder innovation networks: A process framework for value co-creation and capture[END_REF]. At this stage, the focal company entails a strong internal communication with the aim of unlocking the cultural barriers to collaborate with external actors. The output of this stage is the general goal of the collaborative innovation project, the identification of the potential external actors to collaborate with, the anticipation of the value to be created, and an initial set of actions to deal with the intra-organisational barriers to the project development [START_REF] Reypens | Leveraging value in multi-stakeholder innovation networks: A process framework for value co-creation and capture[END_REF][START_REF] Schweizer | Guiding principles of value creation through collaborative innovation in pharmaceutical research[END_REF].

Ignition. The aim of this step is to perform a goal alignment between the diff t actors regarding the main goal of the project [START_REF] Reypens | Leveraging value in multi-stakeholder innovation networks: A process framework for value co-creation and capture[END_REF][START_REF] Baldassarre | Bridging sustainable business model innovation and user-driven innovation: A process for sustainable value proposition design[END_REF]. The expected benefits of the actors and the individual investments should be discussed, achieving a fair agreement between the parties. The outputs of this phase are the list of actors to participate in the collaborative process, and a synthesis of the actor's value expectations. Parties should be ready for full collaboration in intellectual and contractual terms [START_REF] Reypens | Leveraging value in multi-stakeholder innovation networks: A process framework for value co-creation and capture[END_REF].

Implementation.

In line with the model proposed by [START_REF] Rohrbeck | Collaborative business modelling for systemic and sustainability innovations[END_REF], this phase corresponds to the launch of the innovation in operational and commercial terms. The collaboration takes place on the operational planning alignment in terms of resources and activities needed for joint production. This phase is concerned with the offer commercialization and the value capture. At the end it is possible to conduct an assessment of the value created for each actor.

Collaborative innovation and sustainable value creation in the supply chain

An important body of literature recognises the importance of collaborative approach in the supply chain as a key driver to create sustainable value [START_REF] Chen | Supply chain collaboration for sustainability: A literature review and future research agenda[END_REF]. Here, the role of the purchaser is fundamental to enable innovation development [START_REF] Spekman | Strategic supplier selection: Understanding long-term buyer relationships[END_REF][START_REF] Schiele | How to distinguish innovative suppliers? identifying innovative suppliers as new task for purchasing[END_REF]. In B2B markets, sourcing has been considered as an strategic activity that allows the access to new resources and knowledge that enables innovation in the buyer company [START_REF] Spekman | Strategic supplier selection: Understanding long-term buyer relationships[END_REF][START_REF] Nudurupati | Strategic sourcing with multi-stakeholders through value co-creation: An evidence from global health care company[END_REF]. In the context of sustainable business models, the role of the purchaser has gained in importance [START_REF] Grimm | Critical factors for sub-supplier management: A sustainable food supply chains perspective[END_REF].

In past literature [START_REF] Spekman | Strategic supplier selection: Understanding long-term buyer relationships[END_REF], the role of the purchaser appears to be strictly prescriptive. The purchaser was limited to establish a set of requirements, and looking for a competent supplier able to fulfil them. The criteria of supplier selection in that context were the classical triad quality, price and delivery time [START_REF] Spekman | Strategic supplier selection: Understanding long-term buyer relationships[END_REF]. In that context, the purchaser adopted an "adversary approach" face of its suppliers, using the power positioning to get the best cost-benefit relation in the business transaction [START_REF] Spekman | Strategic supplier selection: Understanding long-term buyer relationships[END_REF]. In the current industrial context, the role of the purchasing function has been drastically transformed [START_REF] Schiele | How to distinguish innovative suppliers? identifying innovative suppliers as new task for purchasing[END_REF][START_REF] Nudurupati | Strategic sourcing with multi-stakeholders through value co-creation: An evidence from global health care company[END_REF]. The purchaser is facing a context in which the price is not the only element of the negotiation with its key suppliers, entailing a discussion about perceived value from diff t actors' perspective [START_REF] Nudurupati | Strategic sourcing with multi-stakeholders through value co-creation: An evidence from global health care company[END_REF]. Besides, external exigencies, related to the management of the environmental impacts and the strategic need of being socially responsible, push companies to transform the sourcing strategies in B2B contexts [START_REF] Walker | Fostering sustainability through sourcing from small businesses: public sector perspectives[END_REF][START_REF] Seuring | Sustainability management beyond corporate boundaries: from stakeholders to performance[END_REF][START_REF] Chen | Supply chain collaboration for sustainability: A literature review and future research agenda[END_REF]. This panorama makes it possible to entail a conversation around the innovation as a source of sustainability.

In the context of collaborations, the purchaser takes the role of "integrator" or "mediator" in the interactions between the actors along the value network [START_REF] Hallikas | Service purchasing and value creation: Towards systemic purchases[END_REF]. The integrator is at the centre of the collaborative project, being able to coordinate the relationships and the information sharing during the entire process of co-creation. In B2B relationships, the purchasing function is the direct link between suppliers and manufacturers with the customer needs [START_REF] Kang | Do external knowledge sourcing modes matter for service innovation? empirical evidence from south korean service fi[END_REF]. The integrators should have the skills to manage the project at the relational level, which means to establish a dialogue between actors from diff t domains of expertise, facilitating the alignment of their objectives. In this context, the role of the purchaser requires the ability to identify innovative suppliers and provoke an opportunity for collaboration [START_REF] Schiele | How to distinguish innovative suppliers? identifying innovative suppliers as new task for purchasing[END_REF]. Identifying innovative suppliers is a necessary but not sufficient condition. The purchaser should be also a facilitator of the fi to integrate and exploit external knowledge and resources.

In this context, the activity of sourcing becomes a central element in the organisational strategy to achieve sustainable value [START_REF] Grimm | Critical factors for sub-supplier management: A sustainable food supply chains perspective[END_REF]. For these authors, managing sourcing appropriately increases the efficiency of innovation development. Some of the aspects to be considered in sourcing strategies in the context of collaborative innovation are summarized as follows:

Mines Saint-E ´ tienne Martha Orellano Carrasquilla

7 Conclusions 43

• Considering the offer life cycle: from a supply management perspective, it allows increasing the knowledge about the functioning of the actors in the supply chain, enabling the design a robust and holistic prescription [START_REF] Nudurupati | Strategic sourcing with multi-stakeholders through value co-creation: An evidence from global health care company[END_REF].

• Identifying actors interdependencies: concerns to the primary tasks of objective alignment between the diff t actors. The collaborative relationship should be based on declared interdependencies and not in one sense dependency. This aspect avoid, for example, the technical dependency of the purchaser to a single supplier [START_REF] Nudurupati | Strategic sourcing with multi-stakeholders through value co-creation: An evidence from global health care company[END_REF][START_REF] Matinheikki | From the profi of one toward benefitting many -Crafting a vision of shared value creation[END_REF].

• Dynamic supplier selection: instead of having a static panel of suppliers, the purchasing function should be and perform a fl and extended panel of stakeholders depending on a specific purpose. This leads to the management of multiple stakeholders sourcing strategies [START_REF] Rohrbeck | Collaborative business modelling for systemic and sustainability innovations[END_REF][START_REF] Grimm | Critical factors for sub-supplier management: A sustainable food supply chains perspective[END_REF].

• Integrative role: instead of the traditional and exclusive negotiation role, the purchaser should be an mediator of the collaboration process, integrating a heterogeneous panel of stakeholders into a common goal. The purchasing focus should change from a cost-benefit discussion to a value-based one [START_REF] Hallikas | Service purchasing and value creation: Towards systemic purchases[END_REF][START_REF] Huizingh | Open innovation: State of the art and future perspectives[END_REF][START_REF] Kang | Do external knowledge sourcing modes matter for service innovation? empirical evidence from south korean service fi[END_REF].

Conclusions

Pursuing sustainable value creation needs the collaboration between multiple actors in a orchestrated network. Through this chapter, we mobilized an important amount of literature addressing the notion of collaborative innovation from four diff t research streams: value creation, innovation management, supply chain management and sustainable oriented innovation. The classical theories infl the current literature on collaborative innovation are the stakeholder theory [START_REF] Freeman | Stakeholder Theory: The State of the Art[END_REF] and the resource-based view [START_REF] Barney | Firm resources and sustained competitive advantage[END_REF]. Some insights contributing to research questions guiding this chapter are summarized as follows:

• RQ1. Why do companies collaborate in B2B?. Adopting a collaborative approach is motivated by the access to resources and knowledge. The aim is to perform radical and systemic innovations, oriented towards sustainable solutions, at the offer, process or organisational level, that a single company cannot achieve. The main requisite for a successful collaboration concerns to the strategic alignment of actors' goals. Several forms of collaboration can take place depending on the trigger of innovation (i.e., technology push or demand pull), the type of actor involved in the collaborative process (i.e., public actors, manufacturers, ONG's, research centres, among others), and the quality of the relationships between them.

• RQ4. How does collaboration enable the creation of sustainable value in B2B?. In the context of collaborative innovation, sustainable value is defi as the improvements in the offer, process, or organisation that simultaneously create economic, environmental, social, relational and functional value. The aim is ensuring economic growth and advanced social well-being. In B2B markets, the role of the purchasing function becomes central, being the key actor in sustainable sourcing strategies.

For the development of the chapters corresponding to the proposed framework (Part III; chapters 5 and 6), the elements retained from this chapter can be summarize as follows:

• Adopting a focus on the collaborative innovation at the supply chain level.

• The external triggers of collaborative innovation (demand-pull and technologypush) and its impacts on the organisation.

• The requisites for entailing a process of collaborative innovation with external actors, classified as preliminary, internal and external.

• The three main phases of the collaborative innovation process: inception, ignition, and implementation.

• The role of the purchaser as integrative actor in the process of collaboration.

Chapter 4

Decision making in multidimensional and multi-stakeholder value creation

Introduction

Sustainable value creation is a major issue in current industry [START_REF] Thabrew | Environmental decision making in multistakeholder contexts: applicability of life cycle thinking in development planning and implementation[END_REF][START_REF] Bostro ¨m | Sustainable and responsible supply chain governance: challenges and opportunities[END_REF][START_REF] Scho ¨ggl | Sustainability assessment in automotive and electronics supply chains-a set of indicators defi in a multi-stakeholder approach[END_REF][START_REF] Brown | Why do companies pursue collaborative circular oriented innovation?[END_REF]. The systemic nature of sustainability requires multifaceted knowledge, only achieved through the collaboration between several economic and non-economic actors [START_REF] Govindan | Evaluating the drivers of corporate social responsibility in the mining industry with multi-criteria approach: A multi-stakeholder perspective[END_REF]. As shown in chapters 2 and 3, achieving sustainable value creation implies two major issues, on the one hand, it is concerned with multiple dimensions of value creation (defined in chapter 2 as economic, environmental, social, relational, and functional); on the other hand, it faces the multiple perspectives of the set actors involved in the collaborative process [START_REF] Reypens | Leveraging value in multi-stakeholder innovation networks: A process framework for value co-creation and capture[END_REF]. The current business environment is characterised by actor's interdependences and conflicting objectives, leading to complex group decision making processes [START_REF] Baudry | Range-based multi-actor multi-criteria analysis: A combined method of multi-actor multi-criteria analysis and monte carlo simulation to support participatory decision making under uncertainty[END_REF]. This problem can be addressed from two levels of analysis, fi level and system level. The fi level is concerned with the set of value expectations each actor has with respect to the collaborative process. The system level refers to the interdependences (generated from the value exchanges) and conflicts between the actors in the collaborative process. The major issue at the fi level is the individual defi of the value expectations, while at the system level is the fair distribution of the value created among all the actors, in a way to achieve a consensus. To determine whether value has been created or not for a given actor, it is necessary to implement value assessment mechanisms [START_REF] Baldassarre | Bridging sustainable business model innovation and user-driven innovation: A process for sustainable value proposition design[END_REF]. Many authors have approached the problem of sustainable value creation as a multi-stakeholder and multi-criteria decision problem [START_REF] Ueda | Value creation and decision-making in sustainable society[END_REF][START_REF] Hajkowicz | Supporting multi-stakeholder environmental decisions[END_REF][START_REF] García-Melo ´n | Assessing mutual funds' corporate social responsibility: a multistakeholder-AHP based methodology[END_REF][START_REF] Schillo | Linking advanced biofuels policies with stakeholder interests: A method building on quality function deployment[END_REF][START_REF] Baudry | Range-based multi-actor multi-criteria analysis: A combined method of multi-actor multi-criteria analysis and monte carlo simulation to support participatory decision making under uncertainty[END_REF]. Moreover, a mandatory aspect dealing with complex decision problems is adopting a systemic vision, including all the relevant elements to the decision, and representing the best the complexity of the decision situation [START_REF] Roy | The outranking approach and the foundations of electre methods[END_REF][START_REF] Norese | ELECTRE III as a support for participatory decision-making on the localization of waste-treatment plants[END_REF][START_REF] Bruno | Applying supplier selection methodologies in a multi-stakeholder environment: A case study and a critical assessment[END_REF]. The objective of this chapter is to provide the conceptual basis to address the problem of sustainable value creation in the context of multiple value dimensions and multiple stakeholders. The research questions guiding this chapter are the following:

• RQ1.
What are the existing approaches addressing multi-stakeholder and multi-criteria decision situations in industry?

• RQ2. How to represent multi-stakeholder and multi-criteria decision situations in the context of sustainable value creation?

• RQ3. How to achieve a consensus between multi-stakeholder expectations in collaborative decisions?

To answer these questions, a literature review is conducted, seeking for multi-criteria and multi-stakeholders decision methods successfully implemented in industrial cases. Then, these methods are analysed according to the specific context of sustainable value creation. Figure 4.1 shows the principal elements to be explored in this chapter and the linkage with the previous chapters (i.e., chapters 2 and 3).

Mines Saint-E ´ tienne Martha Orellano Carrasquilla

Literature review methodology

Firstly, we performed a research using the key words "multi-criteria decision" AND "multi-stakeholder*" OR "multi-actor*". The research was performed for titles, abstract and keywords in Web of Sciences (WOS) between 2010 and 2019. We obtained a fi sample of 789. Then, we fi the contributions choosing only peer-reviewed journals in the fi of engineering, management, environmental sciences, and computer science, obtaining a sample of 128 research works. Starting with the base of the 128 articles, we performed a fi process by reading titles, keywords and abstracts. 17 papers were retained for further analysis. Three articles correspond to literature reviews [START_REF] Chai | Application of decision-making techniques in supplier selection: A systematic review of literature[END_REF][START_REF] Kumar | A review of multi criteria decision making (MCDM) towards sustainable renewable energy development[END_REF][START_REF] Santos | The analytic hierarchy process supporting decision making for sustainable development: An overview of applications[END_REF], and highlight the strengths, weaknesses and application areas of the most used MCDA methods in industry. 14 articles present the application of MCDA methods for multi-stakeholder decisions through specific case studies (Table 4.2). To address specifically MCDA in the context of multiple stakeholders, some insights were taken from a prominent literature review conducted in the fi of decision making [START_REF] Chai | Application of decision-making techniques in supplier selection: A systematic review of literature[END_REF]. The authors analysed 123 articles between 2008 and 2012 related to decision making techniques. This work has a great infl in the fi of supply chain management concerning strategic sourcing decisions. [START_REF] Chai | Application of decision-making techniques in supplier selection: A systematic review of literature[END_REF] classify existing methods for decision making into multi-criteria techniques, mathematical programming techniques, and artificial intelligence techniques. Our research is positioned Mines Saint-E ´ tienne Martha Orellano Carrasquilla 4 Decision making in multidimensional and multi-stakeholder value 48 creation in the fi group. In table 4.1, eight of the most infl tial methods in this category are listed from the most to the least used in real industrial cases (see for instance [START_REF] Kumar | A review of multi criteria decision making (MCDM) towards sustainable renewable energy development[END_REF]). Regarding the 14 papers selected for our literature review, only SMART method is not longer evoked in recent researches. Instead, another multi-criteria method well used in the context of sustainable value creation is the life cycle assessment (LCA) [START_REF] Ren | Prioritization of bioethanol production pathways in china based on life cycle sustainability assessment and multicriteria decision-making[END_REF][START_REF] Liu | Evaluation of social life-cycle performance of buildings: Theoretical framework and impact assessment approach[END_REF][START_REF] Santos | The analytic hierarchy process supporting decision making for sustainable development: An overview of applications[END_REF] (Table 4.2). Table 4.1: Most used multi-criteria decision making techniques according to [START_REF] Chai | Application of decision-making techniques in supplier selection: A systematic review of literature[END_REF] and [START_REF] Kumar | A review of multi criteria decision making (MCDM) towards sustainable renewable energy development[END_REF]. In the following the theoretical background of MCDA approaches is presented, pointing out on the key elements, multi-stakeholder related elements, MCDA process, and existing methods.

Multi-Criteria Decision Analysis (MCDA)

In general, multi-criteria decision approaches are concerned with the understanding, modelling and solution of complex decision problems, generally supported by a mathematical basis [START_REF] Saaty | How to make a decision: The analytic hierarchy process[END_REF][START_REF] Roy | The outranking approach and the foundations of electre methods[END_REF]. Nevertheless, diff t visions have been developed in parallel from the origin of multi-criteria decision theories, deriving in two main streams [START_REF] Roy | The outranking approach and the foundations of electre methods[END_REF]. The fi one oriented to the selection of "the best" solution for a given problem (multi-criteria decision making -MCDM), while the other one oriented to guide the decision process (multi-criteria decision aiding -MCDA). In line with [START_REF] Baudry | Range-based multi-actor multi-criteria analysis: A combined method of multi-actor multi-criteria analysis and monte carlo simulation to support participatory decision making under uncertainty[END_REF] and [START_REF] Macharis | Multi actor multi criteria analysis (mamca) as a tool to support sustainable decisions: State of use[END_REF], both approaches can be considered as complementary, resulting into comprehensive methodological frameworks for guiding the entire decision process (multi-criteria decision analysis). In this sense, MCDA approaches should satisfy both methodological and operational requirements, always considering the context of application [START_REF] Baudry | Range-based multi-actor multi-criteria analysis: A combined method of multi-actor multi-criteria analysis and monte carlo simulation to support participatory decision making under uncertainty[END_REF].

The fi requirement for implementing MCDA is problem structuring, which involves a systemic vision of relevant actors, their value systems and their interactions in the decision situation [START_REF] Roy | The outranking approach and the foundations of electre methods[END_REF][START_REF] Keeney | Value-focused thinking: Identifying decision opportunities and creating alternatives[END_REF]. From the literature review, it is possible to distinguish fi , the basic elements required to perform a MCDA; secondly, the characteristics of multi-stakeholder decision problem, thirdly, the general pathways to their implementation for solving a given decision problem; fi , the existing MCDA methods, their strengths and weaknesses.

Basic elements in MCDA

Three elements are fundamental to perform a MCDA approach: actors, criteria and alternatives.

Actor. Most of the reviewed papers defi an "actor", designated as "stakeholder" in the business context, according to the Stakeholder Theory of Freeman (1984) [START_REF] Norese | ELECTRE III as a support for participatory decision-making on the localization of waste-treatment plants[END_REF][START_REF] Macharis | Multi actor multi criteria analysis (mamca) as a tool to support sustainable decisions: State of use[END_REF][START_REF] Govindan | Evaluating the drivers of corporate social responsibility in the mining industry with multi-criteria approach: A multi-stakeholder perspective[END_REF][START_REF] Igoulalene | Novel fuzzy hybrid multi-criteria group decision making approaches for the strategic supplier selection problem[END_REF][START_REF] Bruno | Applying supplier selection methodologies in a multi-stakeholder environment: A case study and a critical assessment[END_REF][START_REF] Schillo | Linking advanced biofuels policies with stakeholder interests: A method building on quality function deployment[END_REF][START_REF] Liu | Evaluation of social life-cycle performance of buildings: Theoretical framework and impact assessment approach[END_REF]. The "actor" or "stakeholder" is defi as any group or individual, who can affect or be affected by the achievement of organizational goals. The stakeholder has inherent interests and goals expected to be achieved thought a given decision (cf. Chapter 3).

Criterion. It is a reference element through which an alternative can be judged. In MCDA a criterion can have either qualitative or quantitative nature. The characteristics of an adequate set of criteria to perform a MCDA approach are: completeness, non-redundancy, operationality, minimality and homogeneity [START_REF] Roy | The outranking approach and the foundations of electre methods[END_REF][START_REF] Macharis | Multi actor multi criteria analysis (mamca) as a tool to support sustainable decisions: State of use[END_REF]. Completeness implies that all the relevant points of view are taken into account during the decision process. Operationality refers to the meaningfulness of each criterion regarding the decision context, and the ability to measure it. The non-redundancy means that two or more criteria should not express the Mines Saint-E ´ tienne Martha Orellano Carrasquilla 4 Decision making in multidimensional and multi-stakeholder value 50 creation same idea, or one criterion should not be contained into another one. The minimality suggest that the problem should be kept simple enough to be understood and treatable, but representative of the real problem. Finally, the homogeneity means that a given set of criteria shares the same level of detail, enabling a specific level of analysis.

Alternative. It represents a possible solution to the decision problem. It is the element being judged by the actors according to the predefi criteria. According to [START_REF] Roy | The outranking approach and the foundations of electre methods[END_REF], alternatives can be partial (need to be combined with other partial alternatives to fulfi the entire decision problem) or complete (provides by itself a comprehensive solution to the decision problem).

Elements in multi-stakeholder MCDA

In the application of a MCDA approach, the following elements characterise a decision situation involving multiple stakeholders.

Value system. Values are highly abstract concepts that explain the interest of the actors participating in a decision. The value system represents the set of principles and global objectives of an actor, guiding its decisions. The value system can be observed in individuals, organizations or societies [START_REF] Keeney | Value-focused thinking: Identifying decision opportunities and creating alternatives[END_REF].

Preference. The preference is the result of a value judgement emitted by a stakeholder when comparing two or more elements. It depends on the stakeholder value system and indicates the relative importance of an element with respect to another under a common criterion [START_REF] Saaty | How to make a decision: The analytic hierarchy process[END_REF][START_REF] Keeney | Value-focused thinking: Identifying decision opportunities and creating alternatives[END_REF].

Conflict.

A common characteristic of multi-stakeholder decision making processes is the presence of conflicting objectives [START_REF] Macharis | Multi actor multi criteria analysis (mamca) as a tool to support sustainable decisions: State of use[END_REF][START_REF] Dowling | A framework for multistakeholder decision-making and conflict resolution[END_REF][START_REF] Baudry | Range-based multi-actor multi-criteria analysis: A combined method of multi-actor multi-criteria analysis and monte carlo simulation to support participatory decision making under uncertainty[END_REF]. Conflicts arise due to the existence of opposite objectives between two or more stakeholders. Mathematically, a conflict arises when no alternative reaches the Pareto efficiency, which means, there is no a single alternative that allows improving one objective without degrading another one. To solve conflicting situations, a trade-off between stakeholders' priorities is necessary, achieving a form of consensus.

Consensus. It represents a major issue in multi-stakeholder decision making [START_REF] Macharis | Multi actor multi criteria analysis (mamca) as a tool to support sustainable decisions: State of use[END_REF][START_REF] Dowling | A framework for multistakeholder decision-making and conflict resolution[END_REF]. It can be defi as the agreement between all the stakeholder with respect to a decision. Mathematically, a consensus means the aggregation of stakeholders' preference functions, looking for a global satisfaction [START_REF] Igoulalene | Novel fuzzy hybrid multi-criteria group decision making approaches for the strategic supplier selection problem[END_REF][START_REF] Li | Modeling multi-stakeholder multiobjective decisions during public participation in major infrastructure and construction projects: A decision rule approach[END_REF][START_REF] Schillo | Linking advanced biofuels policies with stakeholder interests: A method building on quality function deployment[END_REF][START_REF] Baudry | Range-based multi-actor multi-criteria analysis: A combined method of multi-actor multi-criteria analysis and monte carlo simulation to support participatory decision making under uncertainty[END_REF]. MCDA literature provides some valuable insights to achieve a consensus through mathematics modelling techniques. For instance, [START_REF] Schillo | Linking advanced biofuels policies with stakeholder interests: A method building on quality function deployment[END_REF] propose the use of Quality Function Deployment (QFD) in order to capture the "voice of the stakeholder", Mines Saint-E ´ tienne 51 leading to stakeholders' importance factors. Similarly, [START_REF] Macharis | Multi actor multi criteria analysis (mamca) as a tool to support sustainable decisions: State of use[END_REF] argue that each stakeholder should defi its own value structure and criteria independently, then, aggregating their preferences through a stakeholders' weighting procedure. AHP and ANP solve the question of consensus through two diff t methods, the aggregation of individual judgements (AIJ) and the aggregation of individual priorities (AIP) (see for instance [START_REF] Basak | Group decision making using the analytic hierarchy process[END_REF], more detailed in section 4.6).

Complexity. Refers to the degree of diffi y in analysing and solving a decision situation. Complexity is a inherent characteristic of multi-stakeholder decision processes, characterised by diverse and conflicting objectives [START_REF] Igoulalene | Novel fuzzy hybrid multi-criteria group decision making approaches for the strategic supplier selection problem[END_REF][START_REF] Macharis | Multi actor multi criteria analysis (mamca) as a tool to support sustainable decisions: State of use[END_REF][START_REF] Bruno | Applying supplier selection methodologies in a multi-stakeholder environment: A case study and a critical assessment[END_REF][START_REF] Schillo | Linking advanced biofuels policies with stakeholder interests: A method building on quality function deployment[END_REF][START_REF] Baudry | Range-based multi-actor multi-criteria analysis: A combined method of multi-actor multi-criteria analysis and monte carlo simulation to support participatory decision making under uncertainty[END_REF]. Depending on the decision problem nature, the complexity comes from various sources. It could be linked to a lack of clarity on the main decision objective, incompleteness or overwhelming amount of information, highly heterogeneity of actors (associated to competencies, power asymmetries, culture, etc.), among others (see for instance [START_REF] Keeney | Value-focused thinking: Identifying decision opportunities and creating alternatives[END_REF]).

MCDA process

MCDA is above all a global logic based on human rationality, aiming at facilitating decision making in complex situations, in which several criteria and actors are considered [START_REF] Roy | The outranking approach and the foundations of electre methods[END_REF]. As presented in table 4.2, many MCDA methods are available in literature [START_REF] Kumar | A review of multi criteria decision making (MCDM) towards sustainable renewable energy development[END_REF], all of them proposing their own implementation procedure. For instance, [START_REF] Saaty | How to make a decision: The analytic hierarchy process[END_REF] proposes the well known pathway of AHP method corresponding to three main steps: 1) structuring the decision problem into a hierarchy of objectives, criteria and alternatives, 2) performing pairwise comparison in each level, and 3) calculating alternatives priorities, leading to a decision. Besides, [START_REF] Macharis | Multi actor multi criteria analysis (mamca) as a tool to support sustainable decisions: State of use[END_REF] propose a comprehensive and methodological MCDA framework called MAMCA, which includes seven steps: 1) problem scope defi n, 2) alternatives and criteria identifi 3) criteria weights allocation, 4) alternatives performance assessment, 5) decision method application and consensus, 6) results analysis, and 7) decision recommendations. Those are diff t procedures, however, the underlying logic is very similar. The seminal works on decision making for complex problems (see for example [START_REF] Roy | The outranking approach and the foundations of electre methods[END_REF]; [START_REF] Keeney | Value-focused thinking: Identifying decision opportunities and creating alternatives[END_REF]; [START_REF] Friend | Planning under pressure: the strategic choice approach[END_REF]), and provide a systemic view of the MCDA process, in which actors (with their corresponding value systems), alternatives and criteria interact within a system. For these authors, in order to help individuals make good decisions in a complex environment, it is necessary to follow a generic framework, guiding the entire decision process. Particularly, [START_REF] Friend | Planning under pressure: the strategic choice approach[END_REF] propose an iterative process for strategic decision aid called the Strategic Choice Approach (SCA). This framework is composed by four generic steps necessary to perform any MCDA approach (figure 4.2):

Four modes of the decision process are explained in the SCA framework. 1) In the shaping mode, the stakeholders structure the decision situation, setting the main objective and identifying the key actors and values. represent the decision situation into a model, in which the elements, their relations and possible combinations are represented. At this stage, consequence analysis of the alternatives is performed.

3) The comparing mode refers to the modelling of actors preferences respect to the designed alternatives. Finally, 4) the choosing mode corresponds to the generation of actor's priorities, consensus process, and recommendation for the fi decision.

Holding consensus in multi-stakeholder decisions

Particularly, in the case of multi-stakeholder decision making processes, the satisfaction of the actors with the fi decision should be considered, which implies a search for consensus [START_REF] Li | Modeling multi-stakeholder multiobjective decisions during public participation in major infrastructure and construction projects: A decision rule approach[END_REF][START_REF] Dowling | A framework for multistakeholder decision-making and conflict resolution[END_REF]. [START_REF] Baudry | Range-based multi-actor multi-criteria analysis: A combined method of multi-actor multi-criteria analysis and monte carlo simulation to support participatory decision making under uncertainty[END_REF] identify two diff t ways to hold group decisions, one is a normative approach, in which a powerful actor (for instance, an authority entity) makes the fi decision. The second approach is the consensus one, seeking for a trade-off between all the actors points of view [START_REF] Li | Modeling multi-stakeholder multiobjective decisions during public participation in major infrastructure and construction projects: A decision rule approach[END_REF][START_REF] Dowling | A framework for multistakeholder decision-making and conflict resolution[END_REF]. As a partial answer to the question of consensus, mathematical aggregation techniques are available in the literature (for instance, [START_REF] Aczél | Procedures for synthesizing ratio judgements[END_REF]).

Multi-stakeholder decision processes are particularly complex for large and heterogeneous groups. Several authors have tried to overcome this problem combining both mathematics and social techniques [START_REF] Macharis | Multi actor multi criteria analysis (mamca) as a tool to support sustainable decisions: State of use[END_REF][START_REF] Li | Modeling multi-stakeholder multiobjective decisions during public participation in major infrastructure and construction projects: A decision rule approach[END_REF][START_REF] Igoulalene | Novel fuzzy hybrid multi-criteria group decision making approaches for the strategic supplier selection problem[END_REF][START_REF] Dowling | A framework for multistakeholder decision-making and conflict resolution[END_REF]. Moreover, achieving a consensus requires fi to identify the conflicting points [START_REF] Li | Modeling multi-stakeholder multiobjective decisions during public participation in major infrastructure and construction projects: A decision rule approach[END_REF]. Conflicts, instead of being a negative aspect, reflect the positioning of a determined actor or group of actors with respect to the decision problem. Thus, conflicts can be seen as an important source of Mines Saint-E ´ tienne Martha Orellano Carrasquilla 4.3 Multi-Criteria Decision Analysis (MCDA) 53 knowledge, necessary for succeeding any decision process. Regarding the literature, some authors approach the consensus process, or more precisely, the conflict identification process, through the implementation of clustering techniques [START_REF] Zahir | Clusters in a group: Decision making in the vector space formulation of the analytic hierarchy process[END_REF][START_REF] Giordano | Integrating conflict analysis and consensus reaching in a decision support system for water resource management[END_REF][START_REF] Srdjevic | A two-phase algorithm for consensus building in AHP-group decision making[END_REF]. In the context of decision making, these techniques provide the operational support for analysing actors' preferences.

MCDA methods

MCDA methods can be classified into three subcategories: i) Multi-attribute utility methods (also known as value measurement methods); ii) Outranking methods; and iii) Compromise-oriented methods [START_REF] Chai | Application of decision-making techniques in supplier selection: A systematic review of literature[END_REF]. The fi subcategory aims at assigning an utility value to each of the alternatives being evaluated. The utility value is the mathematical representation of the actors' preferences, leading to the choice of the best alternative within a set of alternatives. AHP and ANP are widely used multi-attribute utility methods [START_REF] Erdog ˘muş | Evaluation of alternative fuels for residential heating in turkey using analytic network process (ANP) with group decision-making[END_REF][START_REF] Lin | A novel hybrid MCDM approach for outsourcing vendor selection: A case study for a semiconductor company in taiwan[END_REF][START_REF] Macharis | Multi actor multi criteria analysis (mamca) as a tool to support sustainable decisions: State of use[END_REF][START_REF] Ren | Prioritization of bioethanol production pathways in china based on life cycle sustainability assessment and multicriteria decision-making[END_REF][START_REF] Bruno | Applying supplier selection methodologies in a multi-stakeholder environment: A case study and a critical assessment[END_REF][START_REF] Schillo | Linking advanced biofuels policies with stakeholder interests: A method building on quality function deployment[END_REF][START_REF] Baudry | Range-based multi-actor multi-criteria analysis: A combined method of multi-actor multi-criteria analysis and monte carlo simulation to support participatory decision making under uncertainty[END_REF][START_REF] Chen | Multi-attribute sustainability evaluation of alternative aviation fuels based on fuzzy anp and fuzzy grey relational analysis[END_REF].

Outranking methods as ELECTRE and PROMETHEE, assume that the stakeholders know in advance the weights of the evaluation criteria as well as the performance values of the alternatives being evaluated [START_REF] Chai | Application of decision-making techniques in supplier selection: A systematic review of literature[END_REF]. The aim of these methods is to rank alternatives establishing a binary outranking relation between them (i.e., alternative a is as good as alternative b with no enough evidence to affirm the opposite). The result of these methods is the ranking of the alternatives rather than the choice of the best one [START_REF] Norese | ELECTRE III as a support for participatory decision-making on the localization of waste-treatment plants[END_REF][START_REF] Macharis | Multi actor multi criteria analysis (mamca) as a tool to support sustainable decisions: State of use[END_REF][START_REF] Baudry | Range-based multi-actor multi-criteria analysis: A combined method of multi-actor multi-criteria analysis and monte carlo simulation to support participatory decision making under uncertainty[END_REF]. Compromise-oriented methods include TOPSIS and VIKOR [START_REF] Ren | Prioritization of bioethanol production pathways in china based on life cycle sustainability assessment and multicriteria decision-making[END_REF][START_REF] Igoulalene | Novel fuzzy hybrid multi-criteria group decision making approaches for the strategic supplier selection problem[END_REF]. In this case, the best solution is the one with the shortest distance to an ideal solution, which is an existing or imagined reference model, which can be modelled. Finally, there exist other MCDA techniques as DEMATEL and LCA, which are out of the above main categories. DEMATEL aims at the identification of cause-effect relations between complex evaluation criteria, establishing the interdependence relationships between them [START_REF] Govindan | Evaluating the drivers of corporate social responsibility in the mining industry with multi-criteria approach: A multi-stakeholder perspective[END_REF][START_REF] Mathivathanan | Sustainable supply chain management practices in indian automotive industry: A multi-stakeholder view[END_REF]Liu et al., 2019). LCA is a method broadly used in environmental evaluation. Despite it is implemented as a MCDA method in some research papers [START_REF] Thabrew | Environmental decision making in multistakeholder contexts: applicability of life cycle thinking in development planning and implementation[END_REF][START_REF] Liu | Evaluation of social life-cycle performance of buildings: Theoretical framework and impact assessment approach[END_REF], it is rather a methodological guideline for a very detailed evaluation of the environmental impacts.

Mines Saint-E ´ tienne Martha Orellano Carrasquilla 4 Decision making in multidimensional and multi-stakeholder value 54 creation

Problem structure modelling in multi-stakeholder MCDA

Most of the authors highlight the need for developing consistent models at the early stages of the MCDA process, more precisely in the case of unstructured or ill-defi decision problems [START_REF] Roy | The outranking approach and the foundations of electre methods[END_REF][START_REF] Norese | ELECTRE III as a support for participatory decision-making on the localization of waste-treatment plants[END_REF][START_REF] Bruno | Applying supplier selection methodologies in a multi-stakeholder environment: A case study and a critical assessment[END_REF][START_REF] Macharis | Multi actor multi criteria analysis (mamca) as a tool to support sustainable decisions: State of use[END_REF][START_REF] Igoulalene | Novel fuzzy hybrid multi-criteria group decision making approaches for the strategic supplier selection problem[END_REF][START_REF] Schillo | Linking advanced biofuels policies with stakeholder interests: A method building on quality function deployment[END_REF][START_REF] Baudry | Range-based multi-actor multi-criteria analysis: A combined method of multi-actor multi-criteria analysis and monte carlo simulation to support participatory decision making under uncertainty[END_REF].

In contrast, well-defined problems can be solved through mathematical modelling, implementing traditional Operational Research techniques [START_REF] Mingers | Problem structuring methods in action[END_REF][START_REF] Chai | Application of decision-making techniques in supplier selection: A systematic review of literature[END_REF]. A suitable model should represent the principal elements in the decision process: actors, criteria, and alternatives, and their interrelationships. In this aspect, [START_REF] Bruno | Applying supplier selection methodologies in a multi-stakeholder environment: A case study and a critical assessment[END_REF] use stakeholder map to represent the key actors and their value exchanges (i.e., money, knowledge, resources, among others). [START_REF] Lin | A novel hybrid MCDM approach for outsourcing vendor selection: A case study for a semiconductor company in taiwan[END_REF] propose a relational map performed thought the Interpretive Structural Modelling (ISM) technique, which allows representing the interrelationships between the elements of the decision problem and determining their correlation. [START_REF] Norese | ELECTRE III as a support for participatory decision-making on the localization of waste-treatment plants[END_REF] recommends the use of a cognitive map with the aim of delimiting the problem and representing actors points of view, identifying both shared and conflicting objectives.

The above modelling methodologies are framed into a literature stream known as Problem Structuring Modelling (PSM), which focuses on unstructured or ill-defi decision problems [START_REF] Mingers | Problem structuring methods in action[END_REF]. These types of problems are characterised by the multiple actors, conflicting objectives, incommensurable criteria and multiple sources of uncertainty [START_REF] Keeney | Value-focused thinking: Identifying decision opportunities and creating alternatives[END_REF][START_REF] Mingers | Problem structuring methods in action[END_REF]. These approaches seek for problem representation, based on actors as the central element [START_REF] Keeney | Value-focused thinking: Identifying decision opportunities and creating alternatives[END_REF][START_REF] Macharis | Multi actor multi criteria analysis (mamca) as a tool to support sustainable decisions: State of use[END_REF][START_REF] Govindan | Evaluating the drivers of corporate social responsibility in the mining industry with multi-criteria approach: A multi-stakeholder perspective[END_REF]. Furthermore, the importance of adopting an standard language is highlighted, since it allows the capitalisation and reproducibility of knowledge.

The main objective of PSM methodologies are mapping stakeholders, representing their values, and their shared and conflicting objectives in a systemic way [START_REF] Mingers | Problem structuring methods in action[END_REF]. Some frameworks from the fi of system engineering have addressed the problem of multi-stakeholder modelling. For instance, Goal Modelling (GM) is an approach of requirement engineering developed to capture the intentions of diff t actors interacting in a system.

A well-used GM framework is i * (i-star ), which models organisational collaboration based on actors' dependence relationships [START_REF] Yu | Social Modeling and i*[END_REF][START_REF] Yu | Social modeling for requirements engineering[END_REF]. This framework has been developed in the fi of system engineering to analyse and model stakeholders' requirements in early stages of system development, focusing on intentions and strategic goals.

Mines Saint-E ´ tienne Martha Orellano Carrasquilla 4.5 MCDA application in the context of sustainable value creation 55

MCDA application in the context of sustainable value creation

Choosing a MCDA method

The selection of a proper MCDA method to hold complex decisions is an important preoccupation for analysts, experts and stakeholders at the beginning of any decision process (Erdogmuş et al., 2006;[START_REF] Macharis | Multi actor multi criteria analysis (mamca) as a tool to support sustainable decisions: State of use[END_REF][START_REF] Bruno | Applying supplier selection methodologies in a multi-stakeholder environment: A case study and a critical assessment[END_REF][START_REF] Schillo | Linking advanced biofuels policies with stakeholder interests: A method building on quality function deployment[END_REF][START_REF] Baudry | Range-based multi-actor multi-criteria analysis: A combined method of multi-actor multi-criteria analysis and monte carlo simulation to support participatory decision making under uncertainty[END_REF]. Certainly, there is not a MCDA method that fi with any decision situation. The selection of a particular method should be in line with the context of application and the nature of the problem [START_REF] Baudry | Range-based multi-actor multi-criteria analysis: A combined method of multi-actor multi-criteria analysis and monte carlo simulation to support participatory decision making under uncertainty[END_REF]). An appropriate MCDA method has the ability to provide a structured and realistic representation of the problem being treated, capturing its complexity in a way to be understandable for all the actors [START_REF] Macharis | Multi actor multi criteria analysis (mamca) as a tool to support sustainable decisions: State of use[END_REF][START_REF] De Montis | Assessing the quality of different MCDA methods[END_REF] propose a list of criteria based on the common preoccupations in sustainability related problems (table 4.3). (2005).

N Criteria AHP ANP ELECTRE PROMETHEE TOPSIS VIKOR DEMATEL LCA Operational aspects 1 Weights X X transparency 2 Considers X X interdependencies 3 Combination with X X X X X other methods 4 Robustness X X X analysis 5 T rade-off oriented X X results Usability 6 Efficiency (cost X X X X and time) 7 Stakeholder X X X X participation 8 Problem X X X X structurin g 9 Mathematical X X X X simplicity Data characteristics 10 Scale X X X X X heterogeneit y 11 Qualitative and X X X X X X X quantitative data 12 Information X incompleteness 13 Consideration of X X uncertainties 14 High amount of X X X X X X data processing Mines Saint-E ´ tienne Martha Orellano Carrasquilla
4 Decision making in multidimensional and multi-stakeholder value 56 creation Three main categories of the criteria are proposed according to identified needs in sustainability related problems. Firstly, the operational aspects refer to the theoretical foundations of the method. It is concerned with the construction of the evaluation criteria, the weighting procedures, the mathematical robustness, among others. Secondly, the usability deals with the ease of use of the method regarding the specific context, and the simplicity of mathematics operations to be done. For example, whether the method enables participation of multiple actors in a collaborative way, or the possibility for non experts to use the method. Thirdly, the data characteristics, which is an important aspect in the context of sustainability, refer to data heterogeneity (i.e., quantitative and qualitative data, incomplete data, uncertainties, etc.), type of measurement scales, amount of data, among others.

MCDA domains of application

Decisions concerning sustainability can be approached as multi-criteria decision problems, and require the participation of several actors [START_REF] Macharis | Multi actor multi criteria analysis (mamca) as a tool to support sustainable decisions: State of use[END_REF][START_REF] Baudry | Range-based multi-actor multi-criteria analysis: A combined method of multi-actor multi-criteria analysis and monte carlo simulation to support participatory decision making under uncertainty[END_REF]. Literature review reveals that MCDA approaches have been largely implemented to solve diff t problems in relation with sustainability. For instance, supplier selection for sustainability [START_REF] Lin | A novel hybrid MCDM approach for outsourcing vendor selection: A case study for a semiconductor company in taiwan[END_REF][START_REF] Igoulalene | Novel fuzzy hybrid multi-criteria group decision making approaches for the strategic supplier selection problem[END_REF]; energy policy development [START_REF] Erdog ˘muş | Evaluation of alternative fuels for residential heating in turkey using analytic network process (ANP) with group decision-making[END_REF][START_REF] Schillo | Linking advanced biofuels policies with stakeholder interests: A method building on quality function deployment[END_REF]; energy production assessment [START_REF] Ren | Prioritization of bioethanol production pathways in china based on life cycle sustainability assessment and multicriteria decision-making[END_REF][START_REF] Baudry | Range-based multi-actor multi-criteria analysis: A combined method of multi-actor multi-criteria analysis and monte carlo simulation to support participatory decision making under uncertainty[END_REF][START_REF] Chen | Multi-attribute sustainability evaluation of alternative aviation fuels based on fuzzy anp and fuzzy grey relational analysis[END_REF]; urban transport project evaluation [START_REF] Macharis | Multi actor multi criteria analysis (mamca) as a tool to support sustainable decisions: State of use[END_REF][START_REF] Bruno | Applying supplier selection methodologies in a multi-stakeholder environment: A case study and a critical assessment[END_REF]; sustainable practices identification [START_REF] Govindan | Evaluating the drivers of corporate social responsibility in the mining industry with multi-criteria approach: A multi-stakeholder perspective[END_REF][START_REF] Mathivathanan | Sustainable supply chain management practices in indian automotive industry: A multi-stakeholder view[END_REF]; urban waste management [START_REF] Norese | ELECTRE III as a support for participatory decision-making on the localization of waste-treatment plants[END_REF]; product-service systems development [START_REF] Doualle | Selection method of sustainable product-service system scenarios to support decision-making during early design stages[END_REF]Liu et al., 2019); and project performance assessment [START_REF] Medini | Tailoring performance evaluation to specific industrial contextsapplication to sustainable mass customisation enterprises[END_REF][START_REF] Liu | Evaluation of social life-cycle performance of buildings: Theoretical framework and impact assessment approach[END_REF].

Authors agree that these problems comprehend several dimensions related to the interests of the actors involved (see for instance [START_REF] Norese | ELECTRE III as a support for participatory decision-making on the localization of waste-treatment plants[END_REF]; [START_REF] Macharis | Multi actor multi criteria analysis (mamca) as a tool to support sustainable decisions: State of use[END_REF]; [START_REF] Bruno | Applying supplier selection methodologies in a multi-stakeholder environment: A case study and a critical assessment[END_REF]). In the consulted articles, multiple dimensions of value (i.e., also called macro-categories) are included in the problem modelling phase. For instance, economic, environmental, social, relational, functional (defined in chapter 2), and others as legal and political (Erdogmuş et al., 2006;[START_REF] Norese | ELECTRE III as a support for participatory decision-making on the localization of waste-treatment plants[END_REF][START_REF] Macharis | Multi actor multi criteria analysis (mamca) as a tool to support sustainable decisions: State of use[END_REF][START_REF] Govindan | Evaluating the drivers of corporate social responsibility in the mining industry with multi-criteria approach: A multi-stakeholder perspective[END_REF]. Particularly, most of the cases involving critical environmental and social issues involve non-economic actors as governmental entities and local communities [START_REF] Norese | ELECTRE III as a support for participatory decision-making on the localization of waste-treatment plants[END_REF][START_REF] Govindan | Evaluating the drivers of corporate social responsibility in the mining industry with multi-criteria approach: A multi-stakeholder perspective[END_REF].

Implementing MCDA in industry

Using MCDA approaches goes beyond selecting a good alternative to solve a given problem. Instead, MCDA is considered as a powerful tool to structure complex problems and to facilitate the communication among a heterogeneous group of actors [START_REF] Erdog ˘muş | Evaluation of alternative fuels for residential heating in turkey using analytic network process (ANP) with group decision-making[END_REF][START_REF] Norese | ELECTRE III as a support for participatory decision-making on the localization of waste-treatment plants[END_REF][START_REF] Macharis | Multi actor multi criteria analysis (mamca) as a tool to support sustainable decisions: State of use[END_REF][START_REF] Igoulalene | Novel fuzzy hybrid multi-criteria group decision making approaches for the strategic supplier selection problem[END_REF][START_REF] Bruno | Applying supplier selection methodologies in a multi-stakeholder environment: A case study and a critical assessment[END_REF][START_REF] Schillo | Linking advanced biofuels policies with stakeholder interests: A method building on quality function deployment[END_REF][START_REF] Liu | Evaluation of social life-cycle performance of buildings: Theoretical framework and impact assessment approach[END_REF]. MCDA is useful to: structure a common vision with respect to a decision situation [START_REF] Norese | ELECTRE III as a support for participatory decision-making on the localization of waste-treatment plants[END_REF][START_REF] Igoulalene | Novel fuzzy hybrid multi-criteria group decision making approaches for the strategic supplier selection problem[END_REF]; increase Mines Saint-E ´ tienne Martha Orellano Carrasquilla 4.6 Retained elements for proposal development 57

collective knowledge and skills for future decisions [START_REF] Bruno | Applying supplier selection methodologies in a multi-stakeholder environment: A case study and a critical assessment[END_REF][START_REF] Schillo | Linking advanced biofuels policies with stakeholder interests: A method building on quality function deployment[END_REF]; enable transparency and mutual trust along the decision process [START_REF] Schillo | Linking advanced biofuels policies with stakeholder interests: A method building on quality function deployment[END_REF]; among others. Applying MCDA in real cases in industry have both operational and methodological requirements [START_REF] Medini | Tailoring performance evaluation to specific industrial contextsapplication to sustainable mass customisation enterprises[END_REF]. Operational requirements concern the identification of actors, criteria and alternatives, as well as technical requisites related to the selected MCDA method. From the methodological point of view, any MCDA method integrates two main phases, modelling and evaluation. Most of authors agree the modelling phase is fundamental to get realistic and useful results at the end of the decision process [START_REF] Norese | ELECTRE III as a support for participatory decision-making on the localization of waste-treatment plants[END_REF][START_REF] Lin | A novel hybrid MCDM approach for outsourcing vendor selection: A case study for a semiconductor company in taiwan[END_REF][START_REF] Macharis | Multi actor multi criteria analysis (mamca) as a tool to support sustainable decisions: State of use[END_REF][START_REF] Schillo | Linking advanced biofuels policies with stakeholder interests: A method building on quality function deployment[END_REF][START_REF] Baudry | Range-based multi-actor multi-criteria analysis: A combined method of multi-actor multi-criteria analysis and monte carlo simulation to support participatory decision making under uncertainty[END_REF][START_REF] Liu | Evaluation of social life-cycle performance of buildings: Theoretical framework and impact assessment approach[END_REF]. Firstly, during the problem modelling, actors, alternatives and criteria should be identified. Actors are selected according to the context of decision, regarding the resources and knowledge needs. For instance, in complex contexts involving sustainability-related problems, the actors correspond to the supply chain, governmental entities, communities, research institutions, etc. Alternatives and criteria can be obtained by combining literature review and actors knowledge, performing interviews, workshops and meetings [START_REF] Erdog ˘muş | Evaluation of alternative fuels for residential heating in turkey using analytic network process (ANP) with group decision-making[END_REF][START_REF] Norese | ELECTRE III as a support for participatory decision-making on the localization of waste-treatment plants[END_REF][START_REF] Macharis | Multi actor multi criteria analysis (mamca) as a tool to support sustainable decisions: State of use[END_REF][START_REF] Chen | Multi-attribute sustainability evaluation of alternative aviation fuels based on fuzzy anp and fuzzy grey relational analysis[END_REF][START_REF] Mathivathanan | Sustainable supply chain management practices in indian automotive industry: A multi-stakeholder view[END_REF]Liu et al., 2019). Moreover, the criteria can be designed following two diff t approaches, top-down and bottom-up [START_REF] Keeney | Value-focused thinking: Identifying decision opportunities and creating alternatives[END_REF][START_REF] Baudry | Range-based multi-actor multi-criteria analysis: A combined method of multi-actor multi-criteria analysis and monte carlo simulation to support participatory decision making under uncertainty[END_REF]. In the former, the criteria are obtained after a consequence analysis of real or hypothetical alternatives, allowing identifying needs from the diff t actors perspectives. In the latter, the global goal is decomposed into macro-categories, then into refined objectives, leading to a criteria set.

Secondly, for the evaluation phase, [START_REF] Macharis | Multi actor multi criteria analysis (mamca) as a tool to support sustainable decisions: State of use[END_REF] identify three diff t approaches that can be adopted: analyst approach, expert approach, and stakeholder approach.

Depending on the selected approach, the analyst, the experts or the stakeholders are responsible for performing the evaluation process. They should be able to provide value judgements about the relative importance of criteria and alternatives. Most of the authors agree that stakeholder approach is the most suitable for defi and prioritizing criteria, while expert approach is preferred for carrying out an accurate evaluation process of the alternatives [START_REF] Norese | ELECTRE III as a support for participatory decision-making on the localization of waste-treatment plants[END_REF][START_REF] Macharis | Multi actor multi criteria analysis (mamca) as a tool to support sustainable decisions: State of use[END_REF][START_REF] Govindan | Evaluating the drivers of corporate social responsibility in the mining industry with multi-criteria approach: A multi-stakeholder perspective[END_REF][START_REF] Schillo | Linking advanced biofuels policies with stakeholder interests: A method building on quality function deployment[END_REF][START_REF] Mathivathanan | Sustainable supply chain management practices in indian automotive industry: A multi-stakeholder view[END_REF]Liu et al., 2019).

Retained elements for proposal development 4.6.1 The Analytic Hierarchy Process (AHP)

Motivations to use AHP in the context of sustainable value creation. An evaluation of the eight consulted methods was performed using the criteria set proposed by De [START_REF] De Montis | Assessing the quality of different MCDA methods[END_REF], and the content analysis of the reviewed articles (Table 4.3). AHP and ANP are placed among the most suitable methods to be used in the context of sustainability related projects, followed by the outranking methods ELECTRE Mines Saint-E ´ tienne Martha Orellano Carrasquilla 4 Decision making in multidimensional and multi-stakeholder value 58 creation and PROMETHEE. The above affirmation is supported by the fi in the literature review, in which AHP and AND have been used alone or in combination with other methods in a plethora of domains [START_REF] Erdog ˘muş | Evaluation of alternative fuels for residential heating in turkey using analytic network process (ANP) with group decision-making[END_REF][START_REF] Lin | A novel hybrid MCDM approach for outsourcing vendor selection: A case study for a semiconductor company in taiwan[END_REF][START_REF] Macharis | Multi actor multi criteria analysis (mamca) as a tool to support sustainable decisions: State of use[END_REF][START_REF] Ren | Prioritization of bioethanol production pathways in china based on life cycle sustainability assessment and multicriteria decision-making[END_REF][START_REF] Bruno | Applying supplier selection methodologies in a multi-stakeholder environment: A case study and a critical assessment[END_REF][START_REF] Schillo | Linking advanced biofuels policies with stakeholder interests: A method building on quality function deployment[END_REF][START_REF] Baudry | Range-based multi-actor multi-criteria analysis: A combined method of multi-actor multi-criteria analysis and monte carlo simulation to support participatory decision making under uncertainty[END_REF][START_REF] Chen | Multi-attribute sustainability evaluation of alternative aviation fuels based on fuzzy anp and fuzzy grey relational analysis[END_REF]. The main aspects motivating the use of AHP and ANP in real contexts are: the simplicity of the evaluation process for non-experts, the consideration of subjectivity, the transparency of the weighting process and the detection of inconsistencies in actor's judgements [START_REF] Macharis | Multi actor multi criteria analysis (mamca) as a tool to support sustainable decisions: State of use[END_REF][START_REF] Bruno | Applying supplier selection methodologies in a multi-stakeholder environment: A case study and a critical assessment[END_REF][START_REF] Schillo | Linking advanced biofuels policies with stakeholder interests: A method building on quality function deployment[END_REF]. Additionally, as shown in a recent literature review by [START_REF] Santos | The analytic hierarchy process supporting decision making for sustainable development: An overview of applications[END_REF], AHP is one of the preferred MCDA methods in sustainability related problems. The authors found that between 2014 and 2018 this method have been largely implemented to guide decision in eco-design, product-life cycle management, sustainable supplier selection, assessment of manufacturing processes, among others, showing the fl y of the method. Similarly, [START_REF] Chai | Application of decision-making techniques in supplier selection: A systematic review of literature[END_REF] perform a literature review between 2008 and 2012, and found out the preference to use AHP in the context of supply chain management instead of another MCDA technique. The authors highlight that one important motivations for using AHP is the possibility to be combined with other MCDA techniques.

Theoretical background of AHP. The Analytic Hierarchy Process (AHP) is a MCDA method introduced by Prof. Thomas Saaty [START_REF] Saaty | How to make a decision: The analytic hierarchy process[END_REF]. The main base of AHP is psychological, seeking at integrating actors' judgement to the decision process. AHP aims at systematizing actors' subjectivity instead of eliminating it [START_REF] Saaty | How to make a decision: The analytic hierarchy process[END_REF]. It consists on two main phases: modelling and evaluation. The modelling phase aims at structuring the problem into a hierarchy, involving the levels of goals, criteria and alternatives (figure 4.3). The bottom level of the hierarchy is constituted by the alternatives; the top level corresponds to the main decisional goal; the middle comprehends n levels of criteria and sub-criteria, depending on the problem size, available information, and desired level of detail.

From the theoretical point of view, AHP is based on three main axioms:

1. Homogeneity : elements in the same category should be comparable.

2. Hierarchy : elements in each level of the hierarchy should be independent.

Reciprocity : expressed as

a ij = 1/a ji
The evaluation phase performs a pair comparison between the elements of each level of the hierarchy, by using an ordinal scale proposed by Saaty (Table 4.4). The process of pair comparison takes into account the following mathematics rules: for n elements, a matrix A ∈ R n×n of comparisons is obtained, which is positive and reciprocal. Only n × (n -1)/2 comparisons a ij are needed, taking into account that a ii = 1 and a ij = 1/a ji , ∀i ∈ {1, • • • , n}. This process results in a set of judgements matrix A for each category of comparison.

Mines Saint-E ´ tienne Martha Orellano Carrasquilla AHP deals with heterogeneous data, since it is based on an ordinal scale to express actors' value judgements 4.4. Furthermore, AHP allows integrating several actors in the decision process [START_REF] Saaty | How to make a decision: The analytic hierarchy process[END_REF]. Thus, this method appears to be suitable for complex problems facing uncertainties, multiple actors, and diverse types of data. Using this method for preliminary decision analysis provides two main benefits: i) illustrating actors priorities (i.e., weighting evaluation criteria) and their compatibility, and ii) verifying the adequacy of the problem structuring (i.e., hierarchical model constituted by value dimensions, criteria, and alternatives).

Searching a consensus

From the perspective of the Stakeholder Theory (evoked in chapter 3), the consensus between actors goes beyond mathematical aggregation. It entails a discussion about the Importance level of i over j a

Verbal scale 1 i and j are equally preferred 3

Weak preference of i over j 5

Net preference of i over j 7

Very strong preference of i over j 9

Absolute preference of i over j

Mines Saint-E ´ tienne Martha Orellano Carrasquilla 4 Decision making in multidimensional and multi-stakeholder value 60 creation power interrelationships between actors and their infl in the fi decision [START_REF] Li | Modeling multi-stakeholder multiobjective decisions during public participation in major infrastructure and construction projects: A decision rule approach[END_REF][START_REF] Macharis | Multi actor multi criteria analysis (mamca) as a tool to support sustainable decisions: State of use[END_REF][START_REF] Schillo | Linking advanced biofuels policies with stakeholder interests: A method building on quality function deployment[END_REF]. To address this issue, two solutions found in literature are developed in the following.

Priority aggregation with AHP. Given the fl y of AHP, it has been broadly implemented for guiding group or multi-stakeholder decision problems [START_REF] Basak | Group decision making using the analytic hierarchy process[END_REF][START_REF] Escobar | Aggregation of individual preference structures in AHP-group decision making[END_REF]. The central question in multi-stakeholder decisions is the achievement of a consensus [START_REF] Macharis | Multi actor multi criteria analysis (mamca) as a tool to support sustainable decisions: State of use[END_REF][START_REF] Dowling | A framework for multistakeholder decision-making and conflict resolution[END_REF][START_REF] Li | Modeling multi-stakeholder multiobjective decisions during public participation in major infrastructure and construction projects: A decision rule approach[END_REF]. Mathematically, it means the aggregation of stakeholders' preference functions [START_REF] Saaty | How to make a decision: The analytic hierarchy process[END_REF][START_REF] Igoulalene | Novel fuzzy hybrid multi-criteria group decision making approaches for the strategic supplier selection problem[END_REF][START_REF] Li | Modeling multi-stakeholder multiobjective decisions during public participation in major infrastructure and construction projects: A decision rule approach[END_REF][START_REF] Schillo | Linking advanced biofuels policies with stakeholder interests: A method building on quality function deployment[END_REF][START_REF] Baudry | Range-based multi-actor multi-criteria analysis: A combined method of multi-actor multi-criteria analysis and monte carlo simulation to support participatory decision making under uncertainty[END_REF]. In AHP, there are two techniques to aggregate individual results, aggregation of individual judgements (AIJ) and aggregation of individual priorities (AIP) [START_REF] Aczél | Procedures for synthesizing ratio judgements[END_REF]). On the one side, performing the AIJ implies to build a group pair comparison matrix by aggregating the individual judgements. Such an aggregation should be done using the geometric mean of the value judgements for each pair of elements of the hierarchy (i.e., the geometric mean, in contrast to the arithmetic mean, guarantee the respect of the reciprocity condition in the matrices) [START_REF] Aczél | Procedures for synthesizing ratio judgements[END_REF]. Then, the priority vector is calculated as in the normal procedure by using the group judgement matrix. On the other side, in the AIP approach, the individual priority vectors are aggregated by using two possibilities, the arithmetic mean or the geometric mean [START_REF] Aczél | Procedures for synthesizing ratio judgements[END_REF]. These methods are simple and work well for small and homogeneous decision groups. Otherwise, an effect of compensation between two values mathematically very diff t occurs. Two major issues can be observed in these aggregation methods. Firstly, the effect of compensation can provide unrealistic results that do not represent properly any actor preference. Secondly, both methods assume the same importance for all the actors, which is not always the case on real decision problems.

Similarity-based priority aggregation using clustering technique.

Several clustering techniques are available and there is not a single solution for a determined typology of problem [START_REF] Jain | Data clustering: 50 years beyond k-means[END_REF]. Instead, a clustering technique should be selected in function of the problem nature, the objective of the clustering process, and the a priori knowledge about the data [START_REF] Zahir | Clusters in a group: Decision making in the vector space formulation of the analytic hierarchy process[END_REF][START_REF] Jain | Data clustering: 50 years beyond k-means[END_REF][START_REF] Srdjevic | A two-phase algorithm for consensus building in AHP-group decision making[END_REF]. Two main techniques can be distinguished, partitioning and hierarchical clustering. In the fi category, the k -means algorithm is one of the most used given its efficiency [START_REF] Jain | Data clustering: 50 years beyond k-means[END_REF]. This technique requires the defi of the number of cluster to be formed, as well as a random value (cluster centroid) to initiate the partitioning process. Considering the randomness of the initial point, each iteration of the algorithm results in diff ent clustering results.

The hierarchical clustering technique does not require the specification of the number of clusters. Particularly, in the agglomerative hierarchical clustering, the process starts by considering each element of the data frame as a single cluster. Then the clusters are aggregated by calculating the shortest distance between them, and the process stops when all the elements are assigned to a cluster [START_REF] Jain | Data clustering: 50 years beyond k-means[END_REF].

At the end of the process, the hierarchical clustering technique provides a unique Mines Saint-E ´ tienne Martha Orellano Carrasquilla 4.6 Retained elements for proposal development 61 configuration of clusters for a given data set, represented in a dendrogram or tree-like graph. This technique is more appropriated for multi-stakeholder decision problems than the partitioning one, since does not require the defi a priori of the number of clusters, favouring the transparency of the decisional process. Moreover, since the result obtained is unique for a given context, it is more appropriated to analyse actors preferences.

Actors' prioritization. [START_REF] Li | Modeling multi-stakeholder multiobjective decisions during public participation in major infrastructure and construction projects: A decision rule approach[END_REF]; [START_REF] Macharis | Multi actor multi criteria analysis (mamca) as a tool to support sustainable decisions: State of use[END_REF]; [START_REF] Schillo | Linking advanced biofuels policies with stakeholder interests: A method building on quality function deployment[END_REF] highlight the need for ranking stakeholders in some complex situations, according to their degree of infl over the final decision. In collaborative decision process, the power interrelationships between actors can infl e the fi decision [START_REF] Li | Modeling multi-stakeholder multiobjective decisions during public participation in major infrastructure and construction projects: A decision rule approach[END_REF][START_REF] Macharis | Multi actor multi criteria analysis (mamca) as a tool to support sustainable decisions: State of use[END_REF][START_REF] Schillo | Linking advanced biofuels policies with stakeholder interests: A method building on quality function deployment[END_REF]. These authors highlight the need for ranking stakeholders in some complex situations, according to their degree of infl nce over the fi decision. For instance, [START_REF] Schillo | Linking advanced biofuels policies with stakeholder interests: A method building on quality function deployment[END_REF] claims that stakeholder weighting reflects the importance of a given stakeholder to achieve the strategic goals of the focal organisation. This author propose the use of a Liker scale to determine the weights, by directly asking to the focal company. [START_REF] Li | Modeling multi-stakeholder multiobjective decisions during public participation in major infrastructure and construction projects: A decision rule approach[END_REF] use the framework proposed by [START_REF] Mitchell | Toward a theory of stakeholder identification and salience: Defining the principle of who and what really counts[END_REF], in which a stakeholder importance is determined according to three criteria: power (P), legitimacy (L), and urgency (U). Similarly to [START_REF] Schillo | Linking advanced biofuels policies with stakeholder interests: A method building on quality function deployment[END_REF], [START_REF] Li | Modeling multi-stakeholder multiobjective decisions during public participation in major infrastructure and construction projects: A decision rule approach[END_REF] use a Liker scale to calculate the stakeholder weights. In mathematical terms, the stakeholder weighting should be included into the aggregation results obtained from the AHP, obtaining diff t results in function of the stakeholder importance. The interest of using the framework proposed by [START_REF] Mitchell | Toward a theory of stakeholder identification and salience: Defining the principle of who and what really counts[END_REF] is the standard base to judge the stakeholder importance. Table 4.5 describes the criteria of stakeholder importance according to [START_REF] Mitchell | Toward a theory of stakeholder identification and salience: Defining the principle of who and what really counts[END_REF]. Table 4.5: Criteria of stakeholder importance [START_REF] Mitchell | Toward a theory of stakeholder identification and salience: Defining the principle of who and what really counts[END_REF].

Criteria Definition

Power A relationship among actors, in which one of them can push another one to do something without a declared opposition.

Legitimacy

A general perception that actions or judgements issued by an actor are right and proper within a social system of norms and values. Urgency Degree to which an actor claims immediateness regarding a situation, based on its criticality and time-sensitivity.

i * Goal Modelling framework for problem structure modelling

There is a need for developing structured frameworks to model collaborative relationships among actors in early stages of the decision process. A system engineering Mines Saint-E ´ tienne Martha Orellano Carrasquilla 4 Decision making in multidimensional and multi-stakeholder value 62 creation based methodology as i * could be useful to develop consistent and reusable models. Moreover, since i * is a called social-modelling framework (based on actors and goals), it is possible to combine it with some insights from Stakeholder Theory in order to provide a organisational-oriented tool for multi-stakeholders decision making. Goal Modelling (GM) is an approach to requirement engineering developed to model socio-technical problems. It has been applied to business-related problems, precisely to support knowledge generation involved in organisational transformation [START_REF] Yu | Social modeling for requirements engineering[END_REF]. GM aims at capturing stakeholders' intentions and modelling strategic relationships (of dependence) between them. The central elements in this framework are the actors and their intentional elements (i.e., goals, soft-goals, tasks and resources). The interaction between actors and their intentional elements results in a set of dependence relationships. Such dependencies suppose reciprocal relationships of gains and losses, which needs making strategic decisions. Elements on i * framework. It is composed by two abstract elements: intentional element, and actor. The intentional element is the abstract representation of goals, criteria, tasks and resources of a set of actors. The element actor represents the strategic stakeholders involved in the system and their relationships. Each actor has a corresponding role according to its function in the system. In the following, the main objects contained in the goal model are explained based on [START_REF] Dalpiaz | istar 2.0 language guide[END_REF].

• Agent: an actor with a concrete identity (e.g., an organisation, an individual)

Mines Saint-E ´ tienne Martha Orellano Carrasquilla 4. 6 Retained elements for proposal development 63

• Role: the behaviour of an actor according to its specialized domain of competences.

• Goal: high-level intentions of strategic actors. What they want to achieve through the design of the system.

• Criterion: evaluates the level of accomplishment of a goal.

• Task: actions to be executed in order to achieve the determined goal.

• Resource: physical or informational elements required to perform a task.

Notation on i * framework. There are two diff t notation families, one related to the element actor, and the other one to the intentional element. Actors association links can be is-a or participates in, and link a single actor to another single actor (figure 4.5). There exist dependence links between actors (figure 4.6) according to the type of dependum (goal, soft-goal, task or resource) [START_REF] Dalpiaz | istar 2.0 language guide[END_REF]. Intentional element are represented as shown in fi 4.7, and can be linked to another intentional elements (table 4.6, fi 4.8).

Conclusions

The objective of this chapter is to provide the conceptual basis to address the problem of sustainable value creation in the context of multiple value dimensions and multiple stakeholders. Based on the research questions guiding this chapter, the following conclusions are drawn out:

• RQ1. What are the existing approaches addressing multi-stakeholder and multidimensional decision situations in industry?. Several approaches to guide a multi-stakeholder and multi-criteria decision situation are available in the literature. In general, the existing methods are classified into multi-attribute utility, outranking and compromise oriented techniques. The selection of a method depends on the nature of the problem (i.e., choice, outranking, classification, etc.); the type of available data (e.g., whether alternatives, criteria, and actors are known from the beginning of the process or not; qualitative or quantitative data, etc.); and the power relationships between the actors (i.e., whether all the actors have the same importance in the decision process or not). The preferred methods are those easy to use, and which facilitate actors' learning and participation. Based on those criteria, one of the most used methods in the context of sustainability-related projects an supply chain management is the Analytic Hierarchy Process (AHP) [START_REF] Saaty | How to make a decision: The analytic hierarchy process[END_REF][START_REF] Chai | Application of decision-making techniques in supplier selection: A systematic review of literature[END_REF]. This multiattribute utility method is particularly interesting for modelling unstructured decision situations.

• RQ2. How to model multi-stakeholder and multidimensional decision situations in

the context of sustainable value creation?. The literature reveals that most of the Mines Saint-E ´ tienne Martha Orellano Carrasquilla 4. 7 Conclusions 65 sustainability-related projects entails complex decision situations, including several actors and conflicting goals. This type of situations need to be modelled (i.e., visual representation) before applying a specific MCDA method, which allow the collective understanding, and reduce the probability to get incoherent decisions or results. It exists a literature stream known as Problem Structure Modelling (PSM), proposing techniques for modelling unstructured problems. Some of the PSM techniques are based on of system engineering, enabling knowledge capitalisation and transfer. For modelling unstructured problems, a system engineering-based framework called i * (i-star appears to be suitable [START_REF] Yu | Social modeling for requirements engineering[END_REF]). This framework allows capturing stakeholders' intentions and modelling their strategic relationships of dependence.

• RQ3. How to achieve a consensus between conflicting multi-stakeholder expectations in collaborative decisions?. Achieving a consensus is a major issue in multi-stakeholder MCDA, but also a big challenge. Mathematically, there exist several methods to aggregate individual priorities, obtaining almost satisfactory results. Nevertheless, the multi-stakeholder approach goes beyond arithmetic aggregation, and it is rather concerned with social agreement. To this end, the Stakeholder Theory provides some insights that enable the incorporation of stakeholder weighting into the selected MCDA method. Hence, the criteria of power, legitimacy, and urgency are adopted from [START_REF] Mitchell | Toward a theory of stakeholder identification and salience: Defining the principle of who and what really counts[END_REF], with the aim of capturing the voice of the stakeholder in the decision process.

Part III

Proposal development

Introduction

The preceding chapters presented the conceptual basis of this thesis work. This chapter aims at developing the methodological proposal for the analysis and decision-making around the creation of sustainable value in collaborative businesses. Following a stepby-step approach, the elements retained from the literature and adapted to the context of sustainable value creation are integrated into a holistic methodological framework presented in fi 5.1. Four main phases are included in the proposed framework: i) value creation analysis, ii) value alignment model, iii) preference modelling, and iv) consensus process. Each phase is refined into sub-stages, which are developed along the chapter.

The fi phase aims at performing an internal analysis of the focal company, considered as a system of value creation. Three levels of analysis are considered: external environment, strategical level, and operational level. Although, the value analysis is placed into the operational level of the company, it is infl by the strategic level and the external environment. Precisely, the notion of value is analysed following three elements: value proposition, value structure, and value creation. The output of this phase is the identification of relevant stakeholders, and the characterization of value creation in terms of needs of the focal company along the life cycle. The company needs are expressed as strategic objectives.

The second phase allows moving from the internal to a collaborative analysis. Here, the needs of the focal company are confronted with the external relevant actors. Then, a two-fold modelling methodology is performed to identify the convergence between customer needs (value expectations) and providers capabilities (value propositions). The output is a set of criteria supporting the measurement of strategic objectives of the focal company, and a set of feasible alternatives proposed by the providers.

The third phase uses as inputs the actors, the criteria, and the alternatives defi in the previous phases. With these elements, the Analytic Hierarchy Process (AHP) is implemented to model actors' priorities with respect to the criteria set and alternatives. The output of this phase corresponds to the declared priorities of the strategic actors regarding sustainable value creation model.

The fourth and last phase corresponds to a consensus process. Here a conflict analysis is approached through a clustering technique, and a process of actors' prioritization is proposed to guide the strategic decisions. Then, the degree of acceptance of the actors regarding the possible decisions is measured, and some recommendations are presented.

The proposal aims at contributing to the following research axes, introduced in detail at the beginning of this thesis work:

Research axe 1 -Exploring sustainable value creation opportunities within a company and the effects on its internal and external organizations.

Research axe 2 -Modelling the collaborative innovation process between multiple actors to enable sustainable value creation.

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Value creation analysis 71

Research axe 3 -Conducting value assessment in collaborative business models innovation.

Figure 5.1: Overview of the proposal.

Value creation analysis

This phase has a threefold aim. Firstly, identifying external pressures that trigger sustainable value creation into a company. Secondly, analysing the infl of decision-makers on pursuing sustainable value creation. Thirdly, drawing out a set of value propositions and actors' configurations, which enable sustainable value creation.

Stakeholder analysis

This step aims at defi the set of relevant stakeholders that should be integrated to the collaborative project. According to the Stakeholder Theory [START_REF] Freeman | Stakeholder Theory: The State of the Art[END_REF], stakeholders exist at three diff t levels, as follows:

• Focal-firm level: company's shareholders, managers and employees.

• Operating environment: suppliers, customers, competitors and fi intermediaries. In this stage of the methodology, the stakeholders should be identified for each stage of the life cycle, considering the context and the scope of the collaborative project. It should be noticed that the consideration of life cycle is a prerequisite for the development of sustainable innovative offerings, in contrast to traditional product-based ones [START_REF] Vezzoli | Product-Service System Design for Sustainability[END_REF].

Interest of the stakeholder analysis. Including all the relevant stakeholders to the process of sustainable value creation has two main objectives, from the relational and instrumental points of view. From the relational perspective, it allows mitigating the resistance that some stakeholders can impose to the project development. From the instrumental perspective, it facilitates the access to new resources and knowledge necessary for the project development. Concerning this thesis work, the stakeholder theory contributes with its supporting framework to analyse stakeholders relationships, which have been largely accepted and tested in diff t industrial contexts. Moreover, it is suitable to innovative and sustainability related projects, since it integrates a strategic vision of the stakeholder management, with the aim of equitably creating value [START_REF] Freeman | Stakeholder Theory: The State of the Art[END_REF].

Value characterisation

In this stage, the factors of value creation are analysed according to three elements: value proposition, value structure, and dimensions of value creation. The framework of Boons and Lu ¨deke-Freund (2013) has been enriched with literature on innovation and sustainability, resulting in a generalized framework for value analysis (figure 5.2). This conceptual framework allows analysing current and future value systems throughout the lens of value creation. There are three levels of analysis in the framework, external environment, strategic and operational levels.

External environment. Concerns the external pressures (market behaviour, legal context, etc.) the company is confronted with. It allows identifying the factors triggering the transformation of a given model of value creation. According to [START_REF] Freeman | Stakeholder Theory: The State of the Art[END_REF], external pressures can be legal, coercive, technological, or market-related.

• Legal pressures: come from the governmental stakeholders.

• Coercive pressures: are exerted by organisations and communities claiming specific rights in front of the business activity.

• Technological pressures: are induced by competitors or knowledge development in a specific industrial sector.

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2 Value creation analysis 73

Figure 5.2: Sustainable value creation model framework (Orellano et al., 2018b,a).

• Market pressures: emerge with a change on the consumer behaviour, provoking new market needs.

Identifying the nature of external pressures guides the development of the company's strategy.

Strategic level. The internal strategic objectives, drivers, and barriers conditioning the system of value creation are identified. Moreover, the governance structure (i.e., decision-makers) is defi This phase allows to defi the strategic objectives of the company to guide the operationalization of value creation. Particularly, it is necessary to include all the decision-makers, who are the promoters of the organizational transformation towards sustainability.

Operational level. It covers the value proposition, the value structure and the value creation, and their dynamics along the life cycle.

• Value proposition: is related to the offer developed to fulfil specific customer needs. We consider that at the beginning of life (BOL), the value proposition is likely to be a product-oriented offer, in which the product has an important role and it is surrounded by a set of services. At the middle of life (MOL) and at the end of life (EOL), the value proposition evolves, and services gain an important role. the required processes and the relationships between them. On the one side, the needs for intra-organisational collaboration (across the diff rent functions) should be identified.

On the other side, the dynamic perspective induced by life cycle vision, allows designing collaborative actors' configurations following a modular logic. It means that for each phase of the life cycle, it could exists diff t partnerships according to the needs in terms of resources, skills, and activities. This analysis allows identifying the degree of integration of each actor according to the life cycle phases. It is conditioned by the degree of trust, maturity, and power positioning of the actors.

• Value creation: concerns the performance of the business activity along the life cycle, in terms of the fi e value dimensions defi in chapter 2 (i.e., economic, environmental, social, relational and functional). These dimensions of value evolve through the life cycle phases and depend on the actors involved.

The output of this phase is a global overview of the value creation from the focal company perspective. It is summarized in terms of expected value propositions, needs for internal and external actors' configurations, and needs for value creation expressed as company's strategic objectives.

Interest of the value characterisation model

A dynamic vision of the value creation system contributes to frame the complexity, uncertainty and unpredictability of a given business sector. It helps to react to changes in the external environment (e.g., evolution of sustainability exigencies), in a faster and appropriate way. Furthermore, adopting the life cycle vision allows analysing the elements of the value creation model in each phase, and enabling iterative feedbacks between them.

Problem structure modelling

Value alignment framework

This phase aims at confronting customer needs with providers' innovation capabilities. We propose a generic two-fold approach illustrated in fi 5.3. The model establishes the link between actors' strategic objectives (expressed here as value expectations), and operational capabilities of the provider network (value propositions), seeking for a strategic value alignment. Since this thesis work aims at supporting early stages of innovative offers development, there is neither a set of well-defined value propositions (alternatives), nor a predefi set of criteria to evaluate them. The aim of this step is to represent and generate suitable alternatives for sustainable value creation, based on the customer needs. The elements of the model are explained in the following.

Mines Saint-E ´ tienne Martha Orellano Carrasquilla Collaborative process. The collaborative process between customer and providers takes place in three main stages corresponding to the innovation development: inception, ignition, and implementation (reported in chapter 3). Each actor has a boundary space and a shared space of interaction determined by the interdependence Mines Saint-E ´ tienne Martha Orellano Carrasquilla 5 Framew ork to support sustainable value creation in collaborative 76 innovation relationship. Our framework is positioned in the inception and ignition phases of the collaborative process, the early stages of innovation development from the strategic point of view. The operational development of the offer corresponds to the next stages, which are not covered in this thesis work.

The value alignment framework is operationalized throughout a formal system modelling language belonging to the Goal Modelling methodologies. A specific modelling framework called i * has been selected to visualize actors interdependence relationships (introduced in chapter 4). The i * modelling process is carried out with the aid of the software OpenOME. The resulting models allows to identify the set of criteria refining the strategic objectives of the customer, as well as the feasible alternatives matching those criteria. The following sections describe the process for building criteria and alternatives.

Interest of the value alignment model and the goal modelling framework.

The main idea behind the proposed two-fold logic of the value alignment model is to confront customer needs to provider capabilities, leading to feasible value propositions or alternatives. The modelling framework helped to visualize the information coming from the diff t actors in early steps of the offer development. This visualization enabled to have more informed decisions and facilitated a transparent communication between the actors.

Criteria definition

Based on the outputs from the value analysis and the value alignment model, the evaluation criteria can be defi According to the decision-aiding principles [START_REF] Keeney | Value-focused thinking: Identifying decision opportunities and creating alternatives[END_REF], and to recent empirical research (see for instance, [START_REF] Baudry | Range-based multi-actor multi-criteria analysis: A combined method of multi-actor multi-criteria analysis and monte carlo simulation to support participatory decision making under uncertainty[END_REF]), criteria can be defi following two main approaches:

• Bottom-up: consists on analysing the consequences of real or hypothetical alternatives, which elucidate the necessity to consider a determined set of criteria.

• Top-down: the process is carried out from prior defi strategic objectives, which are gradually refined into criteria.

We consider both approaches as complementary, and adopt a stakeholder-based approach for the criteria defi performed through focus group methodology [START_REF] Brown | Why do companies pursue collaborative circular oriented innovation?[END_REF]. Hence, the key internal stakeholders (customer view) should defi the criteria based on two inputs: i) a consequence analysis of the current model, from the company knowledge and supported by literature review, and ii) a refinement of the company's strategic objectives into evaluation criteria, sub-criteria... indicators (i.e., depending on the level of available information). Table 5.1 presents the methodological guide to be completed by the participants.

The participants in the focus group should design a set of criteria following the rules of completeness, non-redundancy, operationality, minimality and homogeneity (detailed Mines Saint-E ´ tienne Martha Orellano Carrasquilla 5. 3 Problem structure modelling 77 Table 5.1: Criteria building template.

in chapter 4). The fi e dimensions of value defi in chapter 2 constitute the starting basis for criteria defi

Alternative identification

In this step, a participatory approach is suitable to generate the alternatives or value propositions (allowing interaction between the customer and the provider). Based on insights from innovation literature (reported in chapter 3), this approach is pertinent in the context of offer innovation, taking as starting point the customer unmet needs, and collaboratively building possible solutions [START_REF] Calabrese | Fostering sustainability-oriented service innovation (SOSI) through business model renewal: The SOSI tool[END_REF]. The customer criteria, built in the previous step, are the input to start alternatives generation process, as follows:

• Each criterion is translated in terms of innovation type (i.e., offer-oriented, technological, or organisational).

• A brainstorming of value propositions is conducted, regarding customer criteria and innovation type.

• The potential value propositions are analysed in terms of maturity and barriers for further development, depending on their current state (i.e., idea, prototyping, or production).

• Finally, the feasible value propositions are selected through an agreement between the customer and the providers.

Value dimension

Consequence analysis

(E) Economic Strategic objectives SO -1 SO -i . . .

Criteria Sub-criteria Indicator

C -1 C -i . . . SC -1.1 SC -1.i . . . (N) Environmental (S) Social (R) Relational (F) Functional
List of negative impacts of current model . . .

I -1.1.1 I -1.1.i . . . SO -n . . . C -n . . . SC -1.n . . . I -

Preference modelling

This phase is deployed by using a multi-criteria decision analysis method (MCDA). The selected method to perform the preference modelling is the Analytic Hierarchy Process (AHP). This method is suitable for three main reasons: i) systematic calculation of criteria priorities, ii) consideration of subjective information in a systematic way, and iii) possibility to be coupled with other MCDA methods, enabling fl y (further detailed in chapter 4).

This phase seeks for the analysis and quantification of the actors' preferences with respect to the elements considered on the decision situation, namely, criteria and alternatives. The preferences about the criteria express the basis from which actors desire to evaluate the alternatives. The preferences about the alternatives express the global degree in which an alternative i satisfies the set of criteria.

To perform the preference modelling, it is necessary to determine a sub-set of actor named "evaluators", and the means to collect the information about their preferences (i.e., verbally expressed for pragmatic ease). These elements are detailed in the following sections.

Preparation

Actors selection. This stage aims at selecting key actors to perform the evaluation process, named "evaluators". At a prerequisite, the actors should belong to one of the stakeholder groups defi ed at in the fi phase: focal-firm, operating environment, or external environment (see chapter 5, subsection 5.2.1). Then, the selection of evaluators is performed based on two criteria: i) strategic positioning on the project development, Mines Saint-E ´ tienne Martha Orellano Carrasquilla

4 Preference modelling 79

and ii) expertise on the decisional domain (experimental or academic knowledge).

Questionnaire building. The questionnaire approach has been selected as a viable methodology to collect the information from the evaluators. An on-line questionnaire represents a suitable option, since it enables an easy diffusion, data capitalization, and data transfer (e.g., ability to use and to process the data with other informatics tools).

To successfully implement AHP in and industrial context, the questionnaire should: i) follow the hierarchical structure of AHP in the questions, and ii) use only the verbal scale for the pairwise comparison process.

Performing the evaluation process

Pairwise comparison matrices. Following the AHP theory, the evaluation phase consists on a pairwise comparison between the elements of each level of the AHP hierarchy. To this end, the ordinal scale proposed by Saaty [START_REF] Saaty | How to make a decision: The analytic hierarchy process[END_REF]) is implemented, resulting into a set of judgements a ij ∈ {1, 9} (reported in 4).

To remind, the pairwise comparison process takes into account the following mathematics rules:

• For n elements, a matrix A ∈ R n×n of comparisons is obtained, which is positive and reciprocal.

• Only n × (n -1)/2 comparisons are needed, taking into account that a ii = 1 and

a ij = 1/a ji , ∀i ∈ {1, • • • , n}.
Where a ij ∈ {1, 9} is the relative importance of the element i over the element j with respect to an element k in the next level up on the hierarchical model.

A = 1 a ij 1/a ij 1
This process results in a set of judgements matrices A ∈ R n×n for each level of the hierarchical model and for each individual actor.

Priority calculation. To calculate the priorities, it is necessary to normalize the values on the columns of each matrix A, then calculate the average of the rows, obtaining the called eigenvector or priority vector [START_REF] Saaty | How to make a decision: The analytic hierarchy process[END_REF]. The vectors are obtained from equation 5.1.

n aij ), n j=1 aij (5.1) w i = , ∀i ∈ {1, • • • , n}
Then, given an alternative j ∈ {1, • • • , m} with a priority vector v v j , its global priority P is calculated from the following equation 5.2:

P = \"' w i × v v j , ∀j ∈ {1, • • • , m} (5.2) i=1
At the end of this process, the individual priorities of criteria and alternatives are obtained for each actor j.

Verifying consistency ratio of comparison matrices. Once the priorities are calculated, the consistency of the matrices should be verified. To this end, AHP proposes the eigenvalue method [START_REF] Saaty | How to make a decision: The analytic hierarchy process[END_REF]. The consistency ratio (CR) is calculated from equation 5.3, and using the random consistency indexes established for reciprocal matrices (RI), presented in table 5.3.

CR = λmax n-1 , (5.

3) RI

where n is the number of compared elements, and λ max is the maximum value among the eigenvalues of the judgement matrix A ∈ R n×n , and can be obtained from equation 5.4.

n n λ max = \"' \"' a ij × w j (5.4) i=1 j=1
where a i j is the initial judgement value between the elements i and j, and w j is the priority of the element j. RI 0,58 0.9 1.12 1.24 1.32 1.41

A judgement matrix is consistent when CR ≤ 0.1 [START_REF] Saaty | How to make a decision: The analytic hierarchy process[END_REF]. In case of inconsistent matrices, the corresponding evaluations should be either repeated or rejected from the fi analysis. Typically, inconsistencies reflect unclear or poor modelling of the decision problem, a lack of knowledge from the evaluator, or a lack of accuracy during the evaluation process.

Given the exploratory nature of innovation problems related to sustainability, we consider important to keep inconsistency matrices as an input for further analysis of the decision situation. For instance, information provided by inconsistent matrices can be useful to discuss the limits of the decision model and improve it (e.g., criteria clarity, elimination or inclusion of new alternatives, among others), but also to develop training programs for industrial actors.

Mines Saint-E ´ tienne Martha Orellano Carrasquilla 5.5 Researching a consensus 81

Researching a consensus

This phase presents a guideline to facilitate the consensus process between industrial actors, considering the context of collaboration for sustainable value creation. As introduced in chapter 4, in multi-stakeholder MCDA problems, a fundamental aspect is achieving a consensus between divergent points of view. AHP proposes two simple methods, the aggregation of individual judgements (AIJ), and the aggregation of individual priorities (AIP). Nevertheless, the main disadvantage of these methods is the effect of compensation between two values mathematically very different. To deal with this issue, we propose on the one side an analytical approach based on a clustering technique to support further consensus building. Then, on the other side, a pragmatic approach based on actors' prioritization through weighted arithmetic mean.

Interest of adopting a stakeholder-approach in the consensus process.

Considering individual actor positioning during the consensus process evokes the perspective of the Stakeholder Theory of Freeman et al. ( 2010) (chapter 3). Here, the consensus between actors' priorities goes beyond a mathematical aggregation. It entails a discussion about power interrelationships between actors and the individual infl ce on the fi decision [START_REF] Li | Modeling multi-stakeholder multiobjective decisions during public participation in major infrastructure and construction projects: A decision rule approach[END_REF][START_REF] Macharis | Multi actor multi criteria analysis (mamca) as a tool to support sustainable decisions: State of use[END_REF][START_REF] Schillo | Linking advanced biofuels policies with stakeholder interests: A method building on quality function deployment[END_REF]. In the following, two ways to facilitate a form of consensus are described.

Clustering process

This step is related to the problem of conflict analysis stated in the literature about group decision-making [START_REF] Li | Modeling multi-stakeholder multiobjective decisions during public participation in major infrastructure and construction projects: A decision rule approach[END_REF][START_REF] Dowling | A framework for multistakeholder decision-making and conflict resolution[END_REF]. The aim of the clustering process is to reveal actors' positioning with respect to a determined set of sustainability-oriented strategies.

Building similarity matrices. Before performing the clustering process, it is necessary to build a set of similarity matrices, which are the input to perform the clustering procedure. Each similarity matrix is built from the pairwise comparison between the individual priority matrices of the actors. The process is applied to each level of the hierarchical model. The similarity is be calculated by applying the following equation [START_REF] Giordano | Integrating conflict analysis and consensus reaching in a decision support system for water resource management[END_REF]:

S ijk = 1 -|w ik -w jk |, (5.5)
where S ijk is the similarity degree between the priorities of actor i and actor j regarding the element k. And, w ik and w jk are the priorities of the element k judged by the actors i and j, respectively. Here, 0 ≤ S ijk ≤ 1, being 1 the maximum value of similarity between two actor's priorities, representing equal opinions. A set of symmetric matrices B ∈ R n×n are obtained, with n being the number of actors compared. Then, an aggregated similarity Mines Saint-E ´ tienne Martha Orellano Carrasquilla 5 Framew ork to support sustainable value creation in collaborative 82 innovation matrix is generated, calculating the arithmetic mean of the set of similarity matrices for the elements being judged (e.g., criteria and alternatives). The resulting matrix is:

S 11 • • • S 1n B = . . . . . . . . . , 0 ≤ S ij ≤ 1 S n1 • • • S nn
Applying clustering technique. The hierarchical clustering technique has been selected to perform this step. As reported in chapter 4, this technique is more appropriated for multi-stakeholder decision problems than the partitioning one, since does not require the defi a priori of the number of clusters, favouring the transparency of the decisional process. Moreover, since the result obtained is unique for a given context, it is more appropriated to analyse actors preferences.

Firstly, using the aggregated similarity matrix, a distance matrix should be calculated. This can be computed automatically using R Studio, throughout the following steps:

• Generating the distance matrix.

• Implementing agglomerative hierarchical clustering technique to generate the clusters.

• Calculating the distance in each clustering iteration using the ward's minimum variance method or any other desired method (see chapter 4).

• Finally, the clusters can be represented as a dendrogram (tree-like graph).

Using the dendrogram representation, one can identify the actors' sub-groups. The dendrogram is interpreted based on the yaxis, which represents the distance at which two points are assigned to a cluster [START_REF] Jain | Data clustering: 50 years beyond k-means[END_REF]. The shortest distance, the biggest similarity between the two points. The simplest rule to choose the number of clusters from the dendrogram consists on drawing an horizontal line at a height in which the maximum distance up and down is reached without intersecting any merging point [START_REF] Jain | Data clustering: 50 years beyond k-means[END_REF]. However, selecting the number of clusters depends also on the knowledge about the problem and the data.

Identifying decisional profiles based on sustainability. The resulting clusters can be compared and assigned to one of the three sustainability decisional profi supported by literature on sustainability [START_REF] Pope | Conceptualising sustainability assessment[END_REF][START_REF] Vezzoli | Product-Service System Design for Sustainability[END_REF], aforementioned in chapter 2: eco-efficiency, societal, and triple bottom line (TBL).

• DP1-Eco-efficiency: the vision of sustainable value creation is product-oriented, focusing on the functional dimension of value as a means to achieve environmental sustainability.

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5 Researching a consensus 83

• DP2-Societal: in this decisional profi environmental and social dimensions are the priority along the innovation process. Sustainable value creation corresponds to the global standards related to environmental protection and social well-being.

• DP3-Triple bottom line (TBL): in sustainability literature, this profi can be aligned to the weak sustainability approach. It allows the compensation between the diff t dimensions of value, which supposes achieving gains on one dimension by degrading another one.

Priority aggregation according to the sustainability decisional profile. All the priorities of the actors belonging to a specific decisional profi should be aggregated by using one of the two aggregation methods of AHP, namely AIJ or AIP. It corresponds to the geometric mean of the judgements or the arithmetic mean of the priorities, respectively. Then, a priority vector v v p is generated for each decisional profi p.

Interest of sustainability-oriented decisional profiles. The decisional profi provide a characterisation of actors' interests, which can be considered as a base for further discussion and negotiation. In any case, the decision-makers should take a specific positioning guiding the fi decision, seeking for the highest possible collective acceptance. It is possible to obtain some clusters out of the three decisional profi Such a case probably reflects a lack of engagement of a given actor or group of actors with respect to the sustainability goals. Thus, "isolated" actors profi can provide precious information about the weak points in the CSR (Corporate Social Responsibility) strategy of a given company. For instance, it can be useful to design communication strategies or training programs related to sustainability for the company employees.

Actors' prioritization

Calculating preferences based on heterogeneous actor prioritization. Considering the case of heterogeneous actor importance, we propose to use the (P, L, U ) framework proposed by [START_REF] Mitchell | Toward a theory of stakeholder identification and salience: Defining the principle of who and what really counts[END_REF] (introduced in chapter 4), derived from the stakeholder theory. This framework defi the stakeholder importance according to the level of power (P ), legitimacy (L), and urgency (U ) in relation to the decision problem.

For instance, according to the three decisional profi defi above, the actors can be prioritized diff tly. The importance of each actor can be calculated using a 1 to 5 licker scale (where 1 = very low and 5 = very high) as suggested and applied by [START_REF] Li | Modeling multi-stakeholder multiobjective decisions during public participation in major infrastructure and construction projects: A decision rule approach[END_REF]; [START_REF] Schillo | Linking advanced biofuels policies with stakeholder interests: A method building on quality function deployment[END_REF]. The importance coefficient µ i of the actor i is calculated from equation 5.6:

µ i = n P i + L i + U i , ∀i ∈ {1, • • • , n} (5.6) j=1 (P j + L j + U j ) Mines Saint-E ´ tienne Martha Orellano Carrasquilla
5 Framew ork to support sustainable value creation in collaborative 84 innovation Finally, the aggregated priority of a given element j, considering all the actors, is calculated through equation 5.7.

n P j = \"' µ i × p ji , ∀j ∈ {1, • • • , n}, (5.7) i=1
where, p ji is the individual priority of the element j judged by the actor i.

Conclusions

This chapter presented a methodological framework supporting sustainable value creation in collaborative business contexts. The proposal is described following a step-by-step approach, which favours the clear understanding and the reproducibility in diff t industrial contexts. Two main objectives guided the development of this chapter, on the one side, describing the diff t methods supporting the proposal, and on the other side, exhibiting the harmony between the diff t phases of the methodological framework. The proposal covers four main phases, which are divided into specific stages. Each phase is supported by diff ent frameworks issued from the literature review and an analytical effort to consolidate them into a holistic framework. First, a called value analysis phase helps to characterise the elements of value creation, namely value proposition, value structure and value dimensions. Moreover, it enables the identification of value creation opportunities from the point of view of the focal company. Then, the second phase named as Problem structure modelling introduces a two-fold modelling framework aiming at confronting customer needs with providers' capabilities, resulting in the selection of feasible value propositions. The third phase corresponding to the preference modelling is supported on the Analytic Hierarchy Process (AHP), and aims at capturing actors' subjective preferences with respect to a set of criteria and alternatives. Finally, the fourth phase consists on a consensus process, allowing to take into consideration individual opinions, favouring the negotiation process. Specially, in this phase, different decisional profi have been identified from literature review on sustainable value creation, crossed with the preference modelling results to get rigorous insights.

The result of this holistic proposal is a powerful tool facilitating knowledge generation and decision aiding in complex innovation projects, specifically oriented towards sustainability issues. The entire methodology helps to structure a decision situation from the very beginning of customer's needs expression. Furthermore, it provides a systematic set of coupled methods that help to reduce the problem complexity until the achievement of a satisfactory solution. The proposal is useful to support the early development stages of innovative offerings from a strategic perspective. The scope of the proposal does not address the operational development of the offers.

In the next chapter, the holistic framework is applied to a real case of innovation development, illustrating the framework applicability and usefulness for guiding strategic decisions.

Chapter 6

Framework application to the case of ICOVET project

Introduction

Chapter 5 presented the methodological development of the proposed framework. In this chapter, the framework is applied to the case of EDF (Electricité de France in French), a large-sized company in France, involved in a collaborative project of innovation for sustainability. EDF is the main producer and distributor of energy in France. In 2017, the company launched a two-years innovation project called ICOVET concerned with the transformation of its safety clothing system. The aim of the project is to move from a product-based offer towards a global solution. The problem faced in ICOVET project is a non-typical example of innovation development for three major reasons. Firstly, the innovation in this case is triggered by the customer (EDF) instead of the provider, corresponding to the demand-pull approach to innovation (see chapter 3). Secondly, since the desired offer is not available in the market, it pushes EDF to develop a radical 6 Framework applicatio n to the case of ICOVET project innovation in collaboration with current and potential providers. Thirdly, the expected offer seeks for the creation of sustainable value. Considering the above characteristics, the decision problem faced by EDF is a complex strategic problem that implies a global management of its safety clothing supply chain. Moreover, the collaborative dimension is essential to the project, integrating economic and non-economic actors.

ICOVET project description

EDF (Electricité de France, in French) is the main producer and distributor of energy in France, and a leading company on the world in the energy sector. Given the safety risks associated to the company's activity, one of the most important support processes of the company is the provision of safety clothing to the employees. About 44000 employees of EDF-France wear safety clothes and should be re-provisioned each year. It represents near six millions e of purchasing and almost 300 tons of material at the end of life per year (data obtained from EDF purchasing reports).

From a general perspective, the textile industry is one of the largest on the world in terms of production and contribution to the global employment [START_REF] Karthik | Environmental Analysis of Textile Value Chain: An Overview[END_REF]. The textile supply chain is categorised as a global supply chain, since it includes several actors geographically dispersed. According to ADEME (Agence de l'Environnement et de la Maîtrise de l'Energie, in French), at 2010, 60% of the textile consumption in the European Union (EU) has been imported from China, Turkey, India, Bangladesh, and Tunis 1 . This implies critical issues concerning sustainability and business ethics at the three stages of the life cycle. According to [START_REF] Karthik | Environmental Analysis of Textile Value Chain: An Overview[END_REF], the production of safety clothing, primarily in cotton, is characterised by the consumption of huge amounts of water, energy and a variety of chemical products that pollute air and water. Furthermore, the consumption in developed countries as France implies long-circuits transportation, translated into a high carbon footprint. Finally, the principal mechanisms at the end of life of safety clothing in France is the incineration, which involves sanitary risks for the surrounding communities. 1 To mitigate the inherent risks linked to the textile value chain, the Ministry of ecology, sustainable development and energy of France launched a decree on 2017 to improve the regulation of textile waste treatment 2 . Other requirements regard the beginning of life, in which the main determinants comprehend the use of sustainable fi best production practices, limited use of dangerous substances, and extension of the products lifespan. Certainly, these legal aspects impact the functioning of European companies engaged in Corporate Social Responsibility (CSR) policies.

Considering the above panorama, the purchasing direction of EDF launched a two-years project of innovation called ICOVET (Innovation Collaborative des Vêtements de Travail, 1 http://www.adem e.fr/ecolabel eu in French), over the period 2017-2019. The aim of the project is to transform the current system of safety clothing by considering its entire life cycle. Pragmatically, the company aims at moving from traditional product purchasing towards the acquisition of a global solution, which fi the best the CSR strategy of the company. The project involves several members of EDF group, some of them are Enedis, Electricité de Strasbourg, and EDF luminus, and the direction of purchasing is the project leader.

Research methodology

The research-intervention framework proposed by David (2000) has been adopted to guide the deployment of ICOVET project. In this approach the knowledge is generated from the iterative confrontation between theory and reality. The empirical research starts by setting the customer needs and corresponding objectives, then identifying key actors, and fi , drawing out a set of possible alternatives in collaboration with the providers.

Then, Problem Structure Modelling (PSM) and Analytic Hierarchy Process (AHP) are applied. Finally, several points of view of actors resulted on divergent results, which are analysed and conciliated following a consensus process, completing the holistic framework application.

Hence, the theoretical effort presented in Part II has been developed in parallel with an empirical work in EDF, structured in three main phases: i) context analysis, ii) defi of the future model, and iii) transformation of the purchasing strategy.

Development phases

Context analysis (Sept. 2017 -March 2018). the aim of this phase is the identification of key internal and external actors, the characterisation of the value creation and the understanding of the key actors' expectations. Firstly, a workshop with the employees from the departments of purchasing, prescription, sustainable development, human resources, and research & development (R&D) was conducted, with the aim of setting their objectives and expectations. Secondly, a workshop with key contractual and potential providers belonging to the fi of confection, transportation, washing and end of life treatment was deployed. The aim was to understand providers' expectations, interest to participate in the project, and capabilities to meet EDF needs throughout their value propositions.

Definition of the future model (April 2018 -March 2019)

. the aim of this phase is to identify possible models for the evolution of the current model of safety clothing towards a sustainable solution. Collaborative workshops between internal and external actors were carried out to identify alternatives responding to the EDF needs, to formalize and prioritize evaluation criteria, and to perform an evaluation process of the selected alternatives.

Mines Saint-E ´ tienne Martha Orellano Carrasquilla this phase aims at delivering some recommendations for the improvements the purchasing strategy throughout the inclusion of CSR criteria. A single workshop with internal actors was carried out to validate the results obtained from the previous phases. Moreover, it is expected to incentive new configuration of the supply chain in terms of actors and collaborative relationships in the horizon 2025. Furthermore, an internal mechanism of governance was implemented to coordinate the project development. The three phases were piloted by an internal steering committee, composed by the internal strategic actors of the project.

Managerial objectives

ICOVET project has been launched to satisfy the following managerial objectives defi by the direction of EDF purchasing department.

• Identifying the conditions to stimulate the development of radical innovation in both the offer and the organisation of the actors implied in the safety clothing value chain

• Enhancing the global performance of the purchasing function concerning the CSR strategy

• Improving the corporate image of the company throughout the inclusion of sustainability criteria on the purchasing strategy

• Encouraging long-term relationships with the providers along the offer life cycle.

Development of the proposed framework

Value creation analysis

Stakeholder analysis

Given the holistic nature of the problem, the project involves several internal and external actors, classified according to the following categories:

• Focal-firm level: two groups are identified, strategic actors and users. the former comprehends the departments of purchasing (project leader), prescription, sustainable development, human resources and research & development (R&D). The latter is composed by operational employees, who wear safety clothes to develop their daily activities.

• Operating environment: it comprehends the supply chain actors: confectioners, logistics providers, washing service providers, and end of life service providers. The actors belonging to the manufacturing processes are excluded from the project given Mines Saint-E ´ tienne

Martha Orellano Carrasquilla

Pr the geographical distance (principally India, China and North Africa), however their activities are considered thought the confectioners' information. Moreover, other buying companies are integrated into the project with the perspective of reaching large volumes of safety clothing at the end of life, but also to explore circular economy opportunities.

• External environment: it comprehend two categories, economic and noneconomic actors. The fi category Non-economic actors (e.g., research institutions, recycling entities and social organizations) are integrated to the project with the aim at identifying sustainable-oriented opportunities (e.g., innovative fi development, circular economy, short-circuits transport models, among others). The key stakeholders were analysed through an semi-structured interview approach. The analysed sample have diverse profi s, for instance, operative employees, managers and CEOs of the implied organizations. In the following the data collection and analysis techniques are described.

Data collection.

Primary and secondary data were exploited.

The former was collected throughout workshops and semi-structured interviews (see Annex A and B, Mines Saint-E ´ tienne Martha Orellano Carrasquilla V). The latter comprehends corporative documents of EDF. The interviews were addressed to the three main groups of actors in the diff t phases of the project (tables 6.1 and 6.2). The interviews were built based on literature review, starting by the identification of main topics, and then refined into questions. The interviews were structured into two major sections, one oriented to the study of the safety clothing market, and the other one considering the organizational impacts provoked by innovation development. and actors relationships. The interviews were recorded and transcribed ad verbatim.

Finally, a lexical analysis was performed by using the software ALCESTE.

Data analysis. ALCESTE is an statistics-based tool that allows performing qualitative data analysis. The software calculates n clusters that represent the major topics associated to a specifi group of interviewed actors, by the means of keywords analysis. Figure 6.3 shows an example of clustering extracted from the internal actors interviews. The main aim of this study was to confront actors' perspectives regarding the main issues treated in the project. Table 6.3 summarizes the obtained results.

Value characterisation

Since EDF is interested in reviewing the entire value chain associated to the safety clothing, the problem has been broken down into the three stages of the offer life cycle: T he economic component is not perceived as an important aspect.

High volumes and standard purchasing of safety clothes is essential for maintaining EDF purchasing performance.

Besides, the corporate image of EDF linked to the destine of the safety clothes at the end of life is a major preoccupation.

T here is a urgent need to develop analysis tools for the global monitoring of the processes.

Logistics related to washing and the end of life are the critical points of the project.

It is perceived as an environmental project of EDF group, but also as an opportunity to improve the employees satisfaction. A possible barrier can be created from the suppression of the monetary aid given by EDF to the employees for managing the middle and end of life of the clothing.

It is perceived as the way to guarantee the safety and comfort of employees. T he value of the safety clothing depends on the capability to fulfil users activities in complete comfort.

T here is not a preoccupation about the life cycle of the safety clothes, linked to a lack of knowledge in this aspect.

T he project represents high financial risks, however it could improve provider's corporate image. T he technical requirements of the future safety clothing system is a major issue, and could represent a strong constraint. Ecological and social aspects are within the providers interests.

T he safety clothes represent a physical way to provide services to EDF.

Focus on distribution and logistics processes, but also in the opportunity to develop collaborative partnership, especially related to the economic aspect (e.g. sharing prototyping costs).

beginning of life (BOL), middle of life (MOL) and end of life (EOL). The value characterisation comprehends the description of the value proposition, the value structure and the value creation of a given system or business model.

We implemented the sustainable value analysis framework with the aim of shaping current and future models of the safety clothing in EDF, from the internal point of view (figure 6.4 and 6.5, respectively).

Current model. The current model supporting the safety clothing system in EDF (figure 6.4) presents the following characteristics. At the strategic level the principal decision-maker is the prescription department, which defi the requirements, the quantity and the lead time for the safety clothing. Then, purchasing department is able to select the providers and to launch the command to the market. Besides, the department of human resources (HR) manages a premium assignment to the employees, which are responsible for the middle and end of life of the safety clothing.

Concerning the operational level, fi , the value proposition is defi as the annual endowment of the safety clothing, determined by the volume of purchased products at the beginning of life. The criteria to select a value proposition are the traditional triad price, quality and delivery time, with a special focus on the best possible price. Secondly, the value structure reveals an internal organisation by silos, in which each department work separately. Moreover, there are not specific procedures for managing the middle Organisation by "silos". Central role of the prescription and support role of purchaser.

Washing and maintenance is the user responsibility.

The end of life is the user responsibility.

Value structure

Transactional relationships.

Risk of oligopoly.

Partially collaborative relationships. N/A Value creation

High costs. High resource consumption and pollution.

Non control of externalities created.

Non control of the waste. Risk of image degradation. and end of life of the clothing, which are entirely managed by the users. The external value structure shows a pure transactional relationship between EDF and their providers at the beginning of life, while a partial collaboration with the logistics providers thought the deployment of productivity partnerships (i.e., aiming at developing logistics service portfolios). At the end of life there is not any formal relationship with any provider, however, in some dependencies of EDF group (e.g., Enedis), a small percentage of the clothing is sent to social organisations for recycling, destined to charity. Thirdly, through the interviews, it has been found that value is being destroyed with the current system. It is evidenced through the high purchasing costs and the non control of environmental and social externalities.

Expected model. Concerning the expected model, the study reveals interesting points of evolution (figure 6.5). Firstly, external pressures trigger the evolution of the current model. It is concerned with the rising exigencies of the French legislation regarding waste management, precisely in relation with non-dangerous waste as textile.

Besides the legal aspects, the actors highlight existent opportunities to develop new markets in France by the means of circular economy, using wasted safety clothing as a resource. The expected model conveys the transformation of both strategic and operational levels of the system. At the strategic level, new actors are expected to integrate the decision-making processes: besides prescription, purchasing, and human

External Internal

Mines Saint-E ´ tienne Martha Orellano Carrasquilla 94 6 Framework applicatio n to the case of ICOVET project Figure 6.5: Expected business model of the safety clothing between EDF and its providers.

resources; the departments of sustainable development and R&D were found relevant for the construction of the new model. The main internal driver for the construction of the new model is the integration of sustainability exigencies contained into the Corporate Social Responsibility (CSR) strategy of EDF group. At the operational level, the value proposition should be transformed from a product purchasing to a global solution corresponding to the needs of each stage of the life cycle. The expected offer should focus on the availability of the safety clothing "as needed", and the reduction of environmental and social impacts. The value structure is impacted in the following ways. The role of the purchaser becomes strategically important, since it is the integrative actor between the internal and external value chains. Moreover, there is a need for a cross-functional collaboration to redesign the offer, and the reinforcement of the prescription department regarding waste management aspects. Concerning the external value chain, horizontal and vertical partnerships should be formed to meet CSR criteria for the new offer. Vertical collaboration (i.e., between confectioners, research entities, service providers, socio-environmental organisations and EDF) is needed for innovation prototyping, reducing the risk of failure and sharing economic expenses. Horizontal collaboration between EDF and other buyer companies favours the achievement of important purchasing volumes, enabling the minimum production quantity required for the providers. Concerning value creation, table 6.4 details the actors vision in terms of value destroyed and opportunities along the life cycle. -Education of employees about the accurate use of safety clothes -Information sharing.

-Information sharing.

-Reinforcement of the waste prescription service.

-Horizontal and vertical collaboration (long-term relationships) -Sharing responsibility and costs -New market development -High customization.

Value creation

-Economic savings linked to the reduction of purchasing -Economic risk sharing -Reduction of water and energy consumption.

-Reduction of water and energy consumption linked to the control of the washing process -Guarantee of employees security and comfort.

-Remanufacturing, reusing and recycling -Social value, working with local companies and social organisations.

External pressures:

Waste Standard washing procedure. Traceability system. On-site washing process. Additional services contained in the offer (e.g., sewing, repair).

Turning clothes at the end of life into a resource (circular economy). Creating new markets in France. Developing solidarity economics (social organisations).

Problem structure modelling

In the precedent sections, current and expected models of EDF's safety clothing system have been analysed throughout the lens of value creation from the EDF perspective. In this section, the situation is analysed from the collective vision between EDF and the external actors, implementing Goal Modelling framework to represent actors interdependencies and value expectations. The application of the goal modelling technique through the i * framework, helps to structure EDF problem, and to illustrate the collaborative process for the development of the offer. From the goal modelling between customer and the different providers along the supply chain, the evaluation criteria and alternatives (i.e., value propositions) have been defi ed. Both elements represent the main input to start the MCDA process, and are detailed in the following.

Criteria definition

During the development of EDF's goal model, fi e strategic objectives where identified, corresponding to each dimension of value creation. Then, the strategic objectives were refined into criteria. To defi the criteria a combination between top-down and bottomup approaches was implemented. Firstly, the consequence analysis of the current scenario allowed to identify the factors of value destruction, but also opportunities of value creation (see table 6.4). Secondly, the fi e dimensions of value were used to ask the internal actors their expected benefits throughout the project. The results of both analysis, enabled the defi n of EDF strategic objectives linked to each value dimension. Then, those objectives were refined into criteria (see fi 6.6). This constituted an iterative and extensive process carried out with the key internal actors. Each group identified a set of criteria for each value dimension, establishing the link with EDF's CSR strategy. The criteria were analysed and synthesized by the research group, and then validated with the participants.

The strategic objectives were defined regarding the stages of the life cycle, defi as follows:

(E) Economics: reducing the purchasing costs, suppressing the users' premium, and developing circular economy in France throughout the transforming of the wasted clothing into resource. The above suggests the consideration of risks, uncertainties and return on investments in long-term horizons.

(N) Environmental: EDF aims at implementing an environmental management plan over the entire system, pointing outs on providers management and waste treatment.

(S) Social : the social value for EDF is defi in terms of respect for the human rights in the manufacturing countries, dignifi conditions of employment, and development of the French economy.

(R) Relational: establishing long-term relationships with providers, sharing responsibilities and promoting innovation development.

(F) Functional: improving the lifespan of the safety clothes, establishing a system based on the availability "as needed" rather than the annual re-provisioning.

Value dimension Criterion Sense Description

It includes a multiple criteria evaluation taking into account: the country of production, the feasibility of Environmental quality of the fibre + production, the possibility to recycle the fibre, the emissions to the air du to the transport of raw materials, water consumption, the use of chemical products, energy consumption and the price per kg of fibre.

Environmental(5)

Environmental performance of providers + Provider performance category accordin g to the auditory score.

Corresponds to the quantity of CO2 equivalent emitted to Carbon footprint the air in the activities of transportation (from producer to the customer) and washing.

Economic(2)

Chemical use -Quantity of chemical used during the washing process, generating water pollution and possible health damages.

Recycling capability + Capability of the system to enable recycling expressed as the percentage of recycled material at the end of life.

Alternative identification

In the workshop taking place on December 2018, during the second phase of ICOVET project, internal and external actors worked collaboratively to generate ideas alternatives meeting EDF's criteria. Individual interviews were carried out with 11 Mines Saint-E ´ tienne Martha Orellano Carrasquilla 6. 4 Development of the proposed framework 99 providers (reported in table 6.2) to detail the offers. It was possible to draw out the decision focus for each stage of the life cycle.

(BOL) Beginning of life: the main decision concerns the type of fi used to manufacture the safety clothes. A critical aspect for the providers in terms of sustainability is the country of production, hence, a mix between Asian, North-African, and European production was considered. After a brainstorming integrating providers capabilities and EDF criteria for the future model, three fi options were retained.

• Tencel: it is a biodegradable artificial fi obtained from eucalyptus, mostly present in South Africa, but also found in European forests (e.g., Lenzing, Austria). Some of its properties include high resistance, breathability, and high absorption capacity. Concerning maintenance, high washing temperatures (up to 40 • C ) can produce a shrinkage of the fabric. This fi is very convenient from the environmental point of view since eucalyptus cultivation has a lower consumption water with respect to cotton, and a profi ratio between production volume an soil occupation. • Poly-cotton: the main strength of using a mix with polyester is its availability on the market. Polyester is the most widely produced synthetic textile fi around the world (about 70% of synthetic fi used in the clothing industry). Poly-cotton combines the benefits of natural fi re with those of synthetic fi being cheaper than pure cotton. In terms of maintenance, this fi is fast-drying, shrinkable, almost wrinkle-less, resistant to high washing temperatures, and has a good conservation of colours after washing.

• Organic cotton: contrary to conventional cotton production, it is grown with natural compost that replaces chemical fertilizers and pesticides. The water consumption required for its cultivation is very less compared to conventional cotton. In terms of process, organic farming ensures the maintenance or improvement of soil fertility, dying process is done without carcinogenic substances, the fi has same structural characteristics of conventional cotton (i.e., soft, breathable, resistant, dye absorbent, and can stand up against high washing temperatures.).

(MOL) Middle of life: decisions in this stage focus on the washing system (localised or centralised) and on the type of technology used for ensuring clothes traceability (RFID tag or bar code).

• Localised washing: distribution model comprehending several local nodes, favouring proximity with the customer in small, well-defined areas. Some of the advantages this system offers are a good level of service in terms of order processing time and customization, and the possibility of adjusting the functioning to local needs. The above can result in cost and time savings in Mines Saint-E ´ tienne Martha Orellano Carrasquilla 100 6 Framework applicatio n to the case of ICOVET project terms of decision-making. Nevertheless, shipping to multiple distribution sites can negatively affect the global efficiency of the system.

• Centralised washing: in this model, the orders are assigned to a central base, or very few bases geographically dispersed. Fewer points of service make possible a higher level of standardization and, therefore, more efficient and easy to manage. Nevertheless, the ownership costs of large storage holds can be very high, and order processing time can be very long.

• RFID tag: it is an object-identification system based on non-optical proximity communication, and enables two-way communication (connected clothing). This system can be applied to inventory management, logistics, transportation, manufacturing, and product tracking.

However, until nowadays the system entails some risks related to information privacy. Moreover, it presents some diffi related to the preservation of the RFID tag due to the special conditions of washing (high temperatures for the technical clothes).

• Bar code: this system is commonly used for product information management to perform inventory control. It requires an optical scanner for getting the product-related information. The amount of information stored in a bar code is lower compared to RFID, nevertheless, this system does not face the security risks. Concerning EDF, this system has been already tested successfully in pilot projects in some EDF divisions.

(EOL) End of life: decisions concern the system for waste upgrading and the opportunities to develop new markets in France by using the wasted textile. Three general options are drawn out from the providers interviews.

• New product: this category involves some alternatives as children overalls, tennis rackets, hand towels, and car seat covers, manufactured from the recycled fi of the wasted safety clothing. The most versatile fi in this case is the poly-cotton, since the polyester component can be recovered in the form of plastic granules.

• New clothing: second-life clothing is the most desirable alternative in terms of environmental sustainability, since the transformation process is less energy consumer than the manufacturing of a diff t product. Nevertheless, it can produce negative impacts on employees security, since the mechanic properties of the fi could be degraded. This alternative is suitable for safety clothes destined to low-risks activities. An important advantage of this option is the existent know-how, the available logistics and productive infrastructures, and the consolidated network of actors working on it (e.g., ADEME (Agence de l'Environnement et de la Maîtrise de l'Energie, in French), CETI (Centre Européen des Textiles Innovants, in French), French confectioners, among others).

Mines Saint-E ´ tienne Martha Orellano Carrasquilla 6. 4 Development of the proposed framework 101

• Energy recovery: it represents one of the most used practices in France for the re-valuation of non-dangerous waste. Some of the advantages of this alternative are the low cost and the possibility to treat high volumes with a high recovery rate. The disadvantages of this option are linked to air pollution and, subsequently, the increase of health risk for the surrounding communities.

Preference modelling Preparation

Given the complexity of the problem treated in ICOVET project, it has been divided into three sub-problems corresponding to each stage of the life cycle, treated independently.

Once the criteria and alternatives are defi the hierarchical models can be built. The fi level of the hierarchy is determined by the life cycle stage general decision. The second level is determined by the dimensions of value creation, designated as E (economic), N (environmental), S (social), R (relational), and F (functional). The third level comprehends the criteria designed for each value dimension. The last level is composed by the alternatives, introduced in the above section (see fi 6.7, 6.8 and 6.9).

Analytic hierarchy process (AHP) has been used to support purchasing decisions in several contexts [START_REF] Santos | The analytic hierarchy process supporting decision making for sustainable development: An overview of applications[END_REF]. In the particular case of ICOVET project, AHP facilitated the task of experts in manifesting their preferences, and enabled a structure collaborative approach internally to EDF, and between the company and its external stakeholders. In this case, a common hierarchical model for each stage of the life cycle has been used to perform the evaluation. The respondent actors were selected considering two criteria: fi , a strategic positioning on the company and with respect to the project; and secondly, a high level of technical knowledge about the decisions treated in each stage of the offer life cycle. 16 respondents were retained for the evaluation (i.e., EDF internal actors belonging to the departments of purchasing, prescription, sustainable development, human resources, and R&D). The evaluation was performed by the means of an on-line questionnaire using the software Sphinx, which allows coding the collected information in Excel format for further analysis. The questionnaires were built and tested within an iterative improvement process in collaboration with the purchasing department, with the aim of ensuring the conceptual clarity and usability before launching it to the respondents. Moreover, the questionnaires were answered with the guidance of the research team involved in the project and supported by the corresponding documentation about the criteria and alternatives.

Mines Saint-E ´ tienne Martha Orellano Carrasquilla

Performing the evaluation process

As described in chapter 5, the evaluation process consists on the pairwise comparison between elements in each level of the hierarchical model, using the Saaty scale [START_REF] Saaty | How to make a decision: The analytic hierarchy process[END_REF]. Following the recommendations of the original AHP methodology proposed by Prof. Saaty, the evaluation was carried out from the bottom to the top of the hierarchy. Hence, the respondents started by comparing the alternatives between them with respect to each criteria. Then, the criteria were compared to each other with respect to their respective value dimension. Finally the value dimensions were compared between them

Mines Saint-E ´ tienne Martha Orellano Carrasquilla with respect to the main objective at the top of the hierarchical model. According to [START_REF] Saaty | How to make a decision: The analytic hierarchy process[END_REF], performing the evaluation from the bottom to the top facilitates the cognitive process on the respondents, since it consists on moving from the most concrete to the most abstract level of the hierarchy.

Once the evaluation was fi by all the participants, the consistency of the judgement matrices was verified throughout the calculation of the consistency ratio CR. After verification process, some of the evaluations were discarded as did not respect the threshold of acceptance in at least one of the comparison matrices. Among the 16 evaluations, 9, 12, and 8 were retained for the BOL, MOL, and EOL, respectively, since they were fully consistent (CR < 0.1) (see Annex D, V). The retained evaluations per stage of the life cycle represent at least one member of each key department (a fi condition to perform the collective analysis).

The weights were calculated for each stage of the life cycle. Tables 6.6, 6.8, and 6.10 show the results of the actors priorities with respect to value dimensions and criteria. Besides, tables 6.7, 6.9, and 6.11 present the global priorities of the alternatives defi ed for each stage of the life cycle. Since the evaluations were based on a common set of criteria, the aggregation of individual priorities method (AIP) (see chapter 4 for further explanation) was used to obtain the group results for value dimensions, criteria, and alternatives.

From the individual evaluations, the following insights were obtained. At the beginning of life, seven out of nine actors agree that environmental and social dimensions are a priority for the purchasing strategy regarding safety clothes (tables 6.6 and 6.7). The two remaining actors adopted a functional positioning, arguing that security should be the priority. In general economic and relational dimensions are the less important for the actors when regarding decision related to the fi Moreover, the alternative "Tencel" appears to be the most suitable regarding all the criteria and all the actors, while organic cotton is the less preferred. Nevertheless, for the two actors taking a functional positioning, the poly-cotton is the preferred alternative since it is the most available fi on the market. At the middle of life, results vary considerable from one actor to another (tables 6.8 and 6.9). A fi group of actors considers environmental and social dimensions as the priority; a second group prefers economic, functional and environmental dimensions; and the third group is rather neutral, considering that all the dimensions have a similar importance. Here, actors' opinions are very conflicting regarding the prioritization of value dimensions, however, all the actors consider that the alternative "localised washing system " is the most suitable to respond the decision problem at the middle of life. Finally, at the end of life, the environmental, social, and economic dimensions are the most important to take into account to evaluate the offer (tables 6.10 and 6.11). The economic dimension gained in importance with respect to the beginning and middle of life. This change reflects the actors' expectations to create new markets from circular economy strategies, but also the interest to pay as less as possible for services at the end of life, to avoid an important increase on the current purchasing costs. Concerning the alternatives, all the actors reject the energetic transformation of the safety clothes. Besides, transforming waste on a new product or on second-life safety clothing are both judged as good options by the actors, with a slightly preference by the latter.

Researching a consensus

Clustering process

Firstly, the similarity matrices based on actors preferences were calculated (see Annex E, V), then, the corresponding clustering algorithm reported in 5 was executed by using R Studio. The procedure was applied to each stage of the life cycle, aiming at identifying actor's decisional profi if they exist. A dendrogram (tree-like graph) corresponding to each stage of the life cycle was obtained from the clustering method (see fi 6.10, 6.11, 6.12). We implemented the procedure to the criteria priority matrices, since they show conflicting preferences between the actors, while the alternatives priority matrices are rather consensual.

After applying the dendrogram rule for clustering selection, two or three clusters can be identified for each stage of the life cycle, detailed in the following.

At the beginning of life, two main clusters were identified. C1 BOL formed by actors A2, A3 and A4; and C2 BOL constituted by actors A1, A5, A6, A7, A8 and A9. The fi cluster comprehends actors whose priority is the functional dimension of the safety clothes, seen as a means to achieve environmental sustainability. The second cluster is formed by actors who consider environmental and social dimensions as the priority to select the type of fi The common characteristic observed among all the actors is the weak importance allocated to the economic dimension.

At the middle of life, four well defi clusters can be identified. The fi C1 MOL composed by actors A1, A3, A6, and A7; C2 MOL by actors A2, A5, and A8; C3 MOL integrates A9, and A10; and C4 MOL formed by actors A4, A11, and A12. Actors in Mines Saint-E ´ tienne Martha Orellano Carrasquilla C1 MOL prioritize environmental and social dimensions. Actors in C2 MOL allocate a similar importance to all the value dimensions, suggesting a trade-off between them. The actors in C3 MOL consider the functional dimension as the main priority and as a means to favour environmental sustainability. Finally, C4 MOL integrates actors with a particular and isolated positioning about the priorities, A11 mostly oriented to the socio-economical development; while A4 is an outlier element with respect to all the formed clusters.

At the end of life, two main clusters were identified, C1 EOL formed by actors A1, A2, A4, and A6, characterised by a strong environmental positioning. C2 EOL formed by actors A3, A5, A7 and A8, reveals an increased importance of the economic dimension in comparison with the results obtained at the beginning and middle of life.

Decisional profiles in sustainable value creation

In the case of ICOVET, the resulting clusters can be assimilated to three decisional profi eco-efficiency, societal, and triple bottom line (TBL).

• Eco-efficiency: the identified clusters for this profi in the diff t phases of the life cycle are C1 BOL , C3 MOL , and C2 EOL .

When adopting this profi

EDF is willing to reduce environmental impacts only if the economic expenses are kept stable (i.e., in relation to the current model of safety clothing). Internally, this decisional profi is translated into the combined efforts of the purchasing and prescription departments, with the support of sustainable development. Concerning the relationship with the providers, EDF This profi suppose strong internal transformation to EDF. For instance, the roles of sustainable development and human resources departments gain in importance in the defi of the purchasing strategy. Besides, the purchasing department should be able to cooperate with the providers of the entire supply chain in order to accomplish sustainability goals from a normative perspective. Such a collaboration should be a common effort to transform the supply chain practices and co-create sustainable offer portfolios covering the entire life cycle.

• Triple bottom line (TBL): here, only the cluster C2 MOL is identified.

In this case, EDF is willing to pay higher prices for the safety clothing washing services (i.e., degradation of economic dimension), while reducing the environmental and social impacts, and guaranteeing the traceability and the quality of the product (i.e., improvement of environmental, social, and functional dimensions).

In the case of EDF, these profi represent an input for the transformation of the purchasing strategy.

Actors' prioritization

According to the three decisional profi the actors have been prioritized diff tly. In the societal profi sustainable development and human resources departments were allocated with the highest values in the three criteria Power (P), Legitimacy (L), and Urgency (U). Regarding the eco-efficiency profi prescription and purchasing departments were prioritized with the highest scores. As for the TBL profi all actors have the same priority, the aggregation results are the same as AIP (i.e., resulting from the arithmetic mean of all the actors' priorities).

The results are presented in tables 6.12, 6.13, and 6.14, corresponding to each stage of the life cycle. The results show a slight variability on the criteria priorities, corresponding to the defi of each profi For instance, the eco-efficiency profi reveals an increase on the priority of the functional dimension of value. In the societal profi the priorities of the environmental and social dimensions are improved. In contrast, the results regarding the alternatives on the diff t stages of the life cycle remains stable. The above is explained by the general agreement between the actors concerning the alternatives for all the stages of the life cycle.

Regarding the results, EDF is able to select between the more convenient profi and adopt accordingly its purchasing strategy. Nevertheless, it is recommended to evaluate the collective acceptance of the fi decision.

Mines

Conclusions

The main inte of lifnt of this chapter was to illustrate the applicability of the proposed framework, resulting from this thesis work. Hence, ICOVET project was analysed, an initiative of innovation triggered by EDF (Electricité de France, in French), seeking for the transformation of its safety clothing system by considering sustainability goals. The project involves the participation of current and potential providers of EDF belonging to the safety clothing supply chain. This project represents a non-typical case of sustainable innovation development, in which the initiative is triggered by the customer, without any previous knowledge about the possible solutions. Moreover, from EDF's perspective, ICOVET project represents a strategic sourcing problem, centred on innovation development from the initiative of purchasing department. The project is also a way to reinforce the relationships between EDF and its providers.

The case has been analysed following the four steps of the proposed methodological framework: i) value analysis, ii) problem structure modelling, iii) preference modelling, and iv) consensus process. Several methods were implemented in each step of the framework, and the main results were discussed and confronted with the company reality, deriving into some managerial recommendations. Firstly, the framework allowed representing hidden customer needs and encouraging the industrial transformation towards sustainable and innovative businesses. Secondly, from the cognitive point of view, the approach enabled an iterative process of knowledge generation and capitalisation between the internal and external actors. Thirdly, the approach helped to elucidate the priorities of the key actors in terms of value creation, analysing their compatibility, and proposing a process to reach a form of consensus. Finally, some conclusions can be highlighted regarding the managerial implications to EDF. Particularly, the analysis of decisional profi represent a base for the transformation of EDF's purchasing strategy.

Part IV

General conclusion

Chapter 7

Conclusions and research perspectives

Further discussion

This thesis work contributes to the literature on sustainability, innovation, and value creation. Precisely, the proposed framework contributes to the conceptualization, modelling and assessment of sustainable value creation in the contexts of collaborative innovation between industrial actors. The framework has been built from solid conceptual basis obtained from literature review in the domains of value creation, innovation management, system modelling, and decision-making. Our proposal is, thus, the result of the convergence between several disciplines, demonstrating the complexity that sustainable value creation conveys.

The framework is structured in four main phases: 1) value analysis, 2) problem structure modelling, 3) preference modelling, and 4) researching a consensus. Several methods were implemented in each phase, and the framework has been tested in a real case related to sustainability improvement through collaborative innovation. The adopted approach helped to structure the expectations of the key actors in terms of value creation, analyse actors' compatibilities, and propose a decision aid for consensus building. In the following, the main contributions derived from literature review, the proposed framework, and the case study are described according to the research axes reported on chapter 1.

Mines Saint-E ´ tienne Martha Orellano Carrasquilla 116

7 Conclusions and research perspectives

Scientific contributions and implications

Research axe 1 -Conceptualization of sustainable value creation. This was addressed through the phase 1 of the proposal. Indeed, we propose a framework to characterise sustainable value into fi e dimensions namely, economics, environmental, social, relational, and functional. The fi e dimensions resulted from a deep analysis of the literature on the notion of value. This framework is useful to understand and to represent the value created in sustainability-oriented businesses (e.g., circular economy, product-service systems, industrial symbiosis, among others). The value framework was implemented in the ICOVET project, allowing representing hidden customer needs. This multidimensional characterisation of value allows overcoming the barriers of economic interests, enabling the representation of new benefits emerging from the collaboration (e.g., relational value creation throughout knowledge sharing). Furthermore, the value characterisation framework represents a tool to encourage the industrial transformation towards sustainable and innovative businesses.

Research axe 2 -Modelling collaborative innovation processes. This was addressed through the phase 2 of the proposal. Supported by Problem Structure Modelling (PSM) tools, a collaborative innovation approach was proposed. This approach, named in this work "value alignment generic model" aims at aligning customer value expectations with providers' value propositions. The generic model is implemented through goal modelling techniques. This approach allows to structure complex situations, which involve several dimensions of value creation and actors. Based on the value alignment modelling, it is possible to refine the value creation dimensions into criteria from the perspective of each actor. Then, from the criteria, feasible value propositions can be identified. This step of the framework allowed reducing the problem complexity, moving from a highly unstructured representation of actors expectations towards a structured set of criteria and alternatives. This step provided the required inputs for modelling actor's preferences, supported by a multicriteria decision analysis method.

Research axe 3-Value assessment in early phases of collaborative innovation.

This was addressed through the phases 3 and 4 of the proposal. Sustainable value creation in the context of collaborative innovation has been approached as a multi-stakeholder and multi-criteria decision problem in this thesis work. Then, the Analytic Hierarchy Process was selected to structure the complex decision situation, and to perform preference modelling. AHP was selected since it appears suitable for unstructured and very complex problems. Moreover, it allows capturing actor's subjectivity and knowledge lacking, which are typical characteristic of radical innovation problems. From the cognitive point of view, AHP helped to perform an iterative process of knowledge generation and capitalisation between the actors. From the practical point of view, the approach was supported by the development of an on-line questionnaire, reproducible over other decision situations beyond the safety clothing system.

Mines Saint-E ´ tienne Martha Orellano Carrasquilla

Managerial contributions and implications 117

Furthermore, we proposed to enrich AHP with actors' importance issued from the Stakeholder Theory, and to couple it with a clustering technique. The clustering technique allows to identify actors' positioning, that can be crossed with a set of named "sustainability profi decisional profi were proposed, based on the literature in sustainability. The output of this process provides a base for discussion and negotiation between several stakeholders, enabling a form of consensus.

Managerial contributions and implications

Considering the managerial objective described in 6.3.2, subsection 6.3.2, the main implications derived from the proposed framework are the following:

Identifying the conditions to stimulate the development of radical innovation in both the offer and the organisation of the actors implied in the safety clothing supply chain. During the fi phase of the ICOVET project, several seminars were developed with internal and external actors. The main results allowed identifying the internal and external conditions to develop a radical innovative offering. For instance, internal conditions can be summarized into the following points: inter-department collaboration; transforming of the internal culture towards sustainability (i.e., eliminating the resistance to change of the employees); re-orienting the purchasing strategy overcoming the value for money mindset; improving internal skills with respect to sustainability practices; moving from the purchasing focus towards supply management focus. Besides, external conditions mainly evokes the following aspects: creating a market for innovative offer development; sharing costs of innovation (e.g., prototyping, technology upgrading, logistics configuration, among others); deploying vertical and horizontal collaboration schemes (i.e., integrating economic and non-economic actors); guaranteeing long-term relationships between the customer and the providers; and ensuring the willingness to pay for innovation.

Enhancing the global performance of the purchasing function concerning the CSR company strategy. the collective effort carried out along the ICOVET project resulted on a fi st step towards the transformation of EDF's purchasing strategy. The results obtained after the two years of the project revealed an increase of the maturity on the purchasing function.

The above is reflected on a declared willingness to pay a higher price in exchange of a better offer in terms of environmental, social, and functional performance. Although, EDF is still constrained by the public procurement policies in France (i.e., any no provider can be privileged by arbitrary selection criteria). Nevertheless, the results of the ICOVET project provides a base for discussion and co-creation with the provider panel, encouraging the development of sustainable and innovative solutions. Moreover, the results represent a fi step towards the consolidation of new customer needs regarding the sourcing of safety clothing, which can be reproduced within other purchasing companies.

Mines Saint-E ´ tienne Martha Orellano Carrasquilla 118

7 Conclusions and research perspectives

Improving the corporate image of the company throughout the integration of sustainability criteria in the purchasing decisions. With the development of ICOVET project, EDF acquired new skills and knowledge about radical innovation development, sustainability, and collaboration with external actors. Thus, the results of the project represent a collective learning process, in which internal and external actors discovered new ways to work together for improving collective progress. Although the results can not be incorporated immediately neither on the purchasing strategy nor in the textile supply chain, they constitute a powerful communication instrument that pushes the internal and external transformation towards sustainability. In concrete terms, the project triggered the acceleration of providers' innovation processes, and promoted the consolidation of sustainability-oriented requirements regarding the safety clothing fi

Encouraging long-term relationships with the providers along the life cycle. One of the identified conditions stated by the providers to develop innovative solutions, is the guarantee of long-term relationships. After the project, new links were created between EDF and some economic and non-economic actors. Moreover the conditions to establish collaborative partnerships were discussed, concerning the contract duration, investments conditions, and knowledge sharing. However, nowadays there is no a concrete proposal from the providers to respond the emerging needs of EDF regarding the safety clothing. This fact reveals a lack of maturity of the textile industry to integrate sustainability-oriented requirements. Nevertheless, the providers consider this panorama as an opportunity to progress rather than a constraint. Certainly, further work is still needed in collaboration with the actors on the supply chain to reach concrete sustainable value propositions and collaborative agreements.

Limits of the study

The limits can be classified into two main categories, the fi one concerning to the methodological approach, and the second one regarding the implemented methods along the framework phases.

The methodological approach. Firstly, considering the empirical methodology, one major limit is about the analysis of an unique case study, making the results very context-dependant. As a perspective, the proposed framework should be implemented in diff t cases and industrial sectors, for further validation. Secondly, the decision situation was addressed separately at each stage the life cycle of the offer development. Although this allowed holding complexity, the interdependencies between solutions at each stage of the life cycle have not been considered. Hence, as a research perspective, a combinatorial phase of analysis could enrich the decision process, providing comprehensive and more realis tic results.

Thirdly, although many actors on the textile supply chain were included in the problem structuring phase, the decisional phase of the proposal was focused on EDF perspective.

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Limits of the study 119

For future research, the framework should be applied with a broader set of stakeholders, verifying its applicability in more complex situations.

The implemented methods. The main limits found in the proposed framework are related to the multi-stakeholder and multi-criteria decision analysis part. The fi major issue concerns the subjective evaluation, given the use of the Analytic Hierarchy Process (AHP). The subjectivity character of this method becomes a weakness when the evaluators are not experts in the concerned domain. Moreover, in the presence of incomplete information, the results are subject to high uncertainty, which makes it risky for strategic decisions. Moreover, the application of AHP can be very time-consuming for a high number of compared elements. Some research perspectives are derived from these limits. For instance, combining AHP with quantitative methods helps to reduce the uncertainty of the fi decision. Moreover, when quantitative data is available, domain experts are not mandatory to perform the evaluation process.

The second point concerns the consensus process. Here, the major diffi y consists on meeting all actor's preferences. In realistic situations, only partial consensus can be reached. A research perspective in this direction is the integration of a satisfaction measure to evaluate the appropriateness of a given solution with respect to each actor.

Scientifi productions

International conference articles

• Towards an integration of life cycle thinking into PSS business models. [START_REF] Orellano | Towards an integration of lifecycle thinking into pss business models[END_REF] • The demand-pull approach to business model innovation through product-service systems: a case study. (Orellano et al., 2018a) • A system modelling approach to collaborative PSS design. (Orellano et al., 2019a) • A Multi-criteria Approach to Collaborative Product-Service Systems Design. (Orellano et al., 2019b) Poster presentations -Comment qualifiez-vous la qualité de la collaborati on avec les acteurs internes au groupe qui interviennent sur le vêtement de travail ? Avez-vous l'occasion de travailler avec les usagers ? -Avez-vous l'occasion de rencontrer les acteurs impliqués dans la fourniture des produits ou les prestations de service ? Quelle est votre perception sur ces prestataires ? -Avez-vous l'occasion de rencontrer d'autres acteurs qui ne sont pas titulaires de ces marchés mais qui pourraient l'être à l'avenir ? -Ces offres peuvent-elles être de nature à changer la représentation du besoin ?

-Comment appréciez-vous la qualité de la relation avec les prestataires avec lesquels vous êtes en contact ?

-Qui sont les autres PP extérieures au groupe et aux prestataires avec qui vous collaborez sur ce thème ?

-Quels sont leurs rôles ? Quelle relation ?

Avez-vous d'autres éléments que nous n'avons pas abordés et qui vous viennent à l'esprit, vous paraissent importants de nous mentionner.

Merci de votre participation

Annex B: Interview guidelines External actors

Interlocuteur (Nom, fonction):

Première phase : Diagnostic Marché des Vêtements de travail

IV.ALT E R N A T I V E S PRI O R I T I Z A T I O N

1 1 1 1 1 0,2 0,2 0,2 0,2 0,2 Environmental 1 1 1 1 1 0,2 0,2 0,2 0,2 0,2 Social 1 1 1 1 1 0,2 0,2 0,2 0,2 0,2 Relational 1 1 1 1 1 0,2 0,2 0,2 0,2 0,2 Functional 1 1 1 1 1 0,2 0,2 0,2 0,2 0,2 5

Abstract:

The increasing environmental and social needs require the adoption of more sustainable practices in the industry. This pushes companies to integrate new criteria related to the creation of sustainable value in their innovation process, i.e. economic, but also environmental and social.

The main objective of this thesis work is to provide a methodological support to companies for the integration of sustainable development criteria into their innovation processes. The contribution of this thesis is threefold. Firstly, a framework for conceptualizing sustainable value creation is proposed. This framework is based on fi e dimensions of value: the three dimensions of sustainable development, economic, environmental, social, to which are added two dimensions, relational and functional. Secondly, a system modelling approach is adopted to analyse the process of aligning customer value expectations with feasible alternatives in terms of suppliers' value propositions. Finally, given the diversity of stakeholders and the multidimensionality of sustainable value, a multi-criteria and multi-stakeholder decision support approach is adopted to evaluate feasible alternatives to value creation. The proposed framework is then applied to a project aiming at revisiting the provision process of safety clothing to employees of a large French company (EDF).

E ´ cole

2 .

 2 Content analysis of the selected articles on value creation. ..................................16 2. Evolution of the research on value creation............................................................22 3.1 Content analysis of the selected articles. ................................................................32 4. Most used multi-criteria decision making techniques according to Chai et al. (2013) and Kumar et al. (2017). ...................................................................48 4. MCDA methods and applications of the reviewed articles. ..................................48 4. Comparative analysis of multi-criteria decision techniques based on the quality criteria proposed by De Montis et al. (2005). ...........................................55 4. Scale of preferences of AHP (Saaty, 1990). ...........................................................59 4. Criteria of stakeholder importance (Mitchell et al., 1997). ..................................61 4. Associations between intentional elements. ............................................................64 5. Criteria building template. .......................................................................................77 5. Alternative generation template. .............................................................................78 5. Random indexes of reciprocal matrices. .................................................................80 6. Interviews conducted during 2017 with internal and external actors in ICOVET project........................................................................................................90 6. Interviews with users and external actors in ICOVET project (2018). . . 91 6. Actors' perceptions of major topics in ICOVET project. .....................................92 6. Consequence analysis along the life cycle of the current system of safety clothing in EDF (internal workshop 2017). ...........................................................95 6. Criteria for the evaluation of sustainable safety clothing offers. ..........................98 6. Relative importance of the value dimensions and criteria at the beginning of life of the safety clothing system. ......................................................................104 6. Relative importance of the alternatives at the beginning of life. .......................104 6. Relative importance of the value dimensions and criteria at the middle of life of the safety clothing system. ..........................................................................105 6. Relative importance of the alternatives at the middle of life. ............................105 6. Relative importance of the value dimensions and criteria at the end of life of the safety clothing system. .................................................................................105 6. Relative importance of the alternatives at the end of life. ..................................

  II: Theoretical Background ........................................ 6 1.4.2 Part III: Proposal Development ........................................ 7 1.4.3 Part IV: General conclusion .............................................. 8

Chapter 3 :

 3 Figure 1.1: Structure of the manuscript.

Figure 2 .

 2 Figure 2.1: Systematic literature review methodology.

Figure 2 . 2 :

 22 Figure 2.2: Number of publications over time using the keywords "value creation" (2000-2018).

Figure 2 . 3 :

 23 Figure 2.3: Distribution of articles on value creation according to the research domains.

Figure 2 . 4 :

 24 Figure 2.4: Value co-creation process according to Service-Dominant Logic (SDL)[START_REF] Vargo | Service-dominant logic: continuing the evolution[END_REF]

Figure 2 . 5 :

 25 Figure 2.5: Value creation configuration: supplier network (left) and demand network (right).

Figure 2 . 6 :

 26 Figure 2.6: Value creation configuration: business ecosystem.

Figure 3 .

 3 Figure 3.1: Research design framework.

Figure 3 . 2 :

 32 Figure 3.2: Cluster analysis of the scientific research in collaboration, innovation and sustainability (between 1975 and 2019).

CentralityFigure 3 . 3 :

 33 Figure 3.3: Thematic map of the selected articles.

4. 2 Figure 4 . 1 :

 241 Figure 4.1: Research framework.

2 )Figure 4 . 2 :

 242 Figure 4.2: Generic decision process according to Friend (1987).

4. 6 Figure 4 . 3 :

 643 Figure 4.3: Hierarchical structure of AHP.

Figure 4 .

 4 4 illustrates the i * meta-model.

Figure 4 . 4 :

 44 Figure 4.4: i * meta-model (Yu et al., 2011).

Figure 4 . 5 :

 45 Figure 4.5: Actor notation and associations.

Figure 4 . 6 :

 46 Figure 4.6: actors' dependence notation.

Figure 4 .

 4 Figure 4.7: Intentional element notation.

  , social, economic, functional and relational Strategic level: Drivers and barriers Governance structure: decision-making actors External pressures / opportunities: Market, technology, public sector, society. Innovation trigger: demand-pull / technology-push Mines Saint-E ´ tienne Martha Orellano Carrasquilla 5 Framew ork to support sustainable value creation in collaborative 74 innovation • Value structure: refers to the set of internal and external actors involved in

5. 3 Figure 5 . 3 :

 353 Figure 5.3: Generic framework for collaborative offer development(Orellano et al., 2019a).

  to support sustainable value creation in collaborative 80 innovation n

Contents 6 .

 6 1 Introduction ......................................................................... 85 6.2 ICOVET project description ............................................. 86 6.3 Research methodology ...................................................... 87 6.3.1 Development phases ....................................................... 87 6.3.2 Managerial objectives...................................................... 88 6.4 Development of the proposed framework .................... 88 6.4.1 Value creation analysis ................................................... 88 6.4.2 Problem structure modelling .......................................... 96 6.4.3 Preference modelling .................................................... 101 6.4.4 Researching a consensus ............................................... 106 6.5 Conclusions .......................................................................... 112

88 6 Framework

 6 applicatio n to the case of ICOVET project Transformation of the purchasing strategy (April 2019 -Dec. 2019).

  P e r s e cr s i c p r t i i p o t n ion Pu P r u ch rc a h si a n s g ing Clo C t l h o e t s hes coc no fe ncfteic ot nion En E d n o d f o li f fe life dis dp is op sa olsal E D F (France) Tra T n r s a p n o s r p t ort Us U e s a e nd and mm ain at ie nn te an nc ae nce Fra Fn rc ae nce 6. 4 Development of the proposed framework 89

Figure 6 .

 6 Figure 6.1 illustrates the current supply chain of safety clothing in EDF, while fi 6.2 represents the key stakeholders considered within the scope of ICOVET project.

Figure 6 . 1 :

 61 Figure 6.1: Current stakeholders in the supply chain of safety clothing of EDF.

90 6 Framework

 6 Figure 6.2: Key stakeholders included in ICOVET project.

Figure 6 . 3 :

 63 Figure 6.3: Clustering of internal actors interviews obtained from ALCESTE.

  offer: Annual dotation of safety clothes for the employees, which incorporates high security standards at the best price.

Figure 6 . 4 :

 64 Figure 6.4: Current business model of the safety clothing between EDF and its providers.

Figure 6 . 6 :

 66 Figure 6.6: Extract of the Goal Modelling between EDF and the supply chain actors.

102 6 Framework

 6 Figure 6.7: Hierarchical model of the Beginning of life (BOL).

Figure 6 . 8 :

 68 Figure 6.8: Hierarchical model of the middle of life (MOL).

6. 4

 4 Figure 6.9: Hierarchical model of the End of life (EOL).

Figure 6 .Figure 6 .

 66 Figure 6.10: Cluster dendrogram of actors' priorities at the beginning of life.

  positioning rather than collaborative, in which the purchasing function ask for eco-innovative products to the providers.• Societal: in this profi clusters C2 BOL , C1 MO L , and C1 EOL are positioned.

4

 4 discussion ............................................................. 115 7.2 Scientific contributions and implications..................Limits of the study ............................................................118

Theoretical background Chapter 2 Characterisation of sustainable value creation Contents 2

.1 Introduction .......................................................................... 11 2.2 Literature review methodology ....................................... 13 2.2.1 Identification of sources .................................................. 13 2.2.2 Selection filtering............................................................. 14 2.2.3 Descriptive analysis......................................................... 15 2.2.4 Content analysis .............................................................. 15 2.3 The notion of value throughout the time...................... 17 2.3.1 Economic value ............................................................... 17

2.3.2 Customer value ............................................................... 18 2.3.3 Sustainable value............................................................. 19 2.3.4 Multi-stakeholder value ..................................................

20 2.4 Sustainable value creation in B2B markets

..................

22 2.5 Proposed framework for the characterisation of sustainable value creation

.................................................25 2.6 Conclusion............................................................................. 26

Table 2 .

 2 1: Content analysis of the selected articles on value creation.

	N	Author	Journal
	1	Best et al. (2018)	IJOP
	2	Kähkönen and Lintukangas (2018)	IJOP
	3	Kaihara et al. (2018)	CIRP
	4	Aquilani et al. (2018)	JCP
	5	Hankammer and Kleer (2018)	JCP
	6	Arnold (2017)	JCP
	7	Baldassarre et al. (2017)	JCP
	8	Ha ¨nninen and Karjaluoto (2017)	JCP
	9	Yan and Wagner (2017)	IJPE
	10 Matinheikki et al. (2017)	JCP
	11 Yan et al. (2017)	JPSM
	12 Volschenk et al. (2016)	IMM
	13 Wang et al. (2016)	LRP
	14 Lacoste (2016)	IMM
	15 Lages (2016)	JBR
	16 Zacharias et al. (2016)	JBR
	17 Joyce and Paquin (2016)	JCP
	18 Manda et al. (2016)	JCP
	19 Ekman et al. (2016)	IMM
	20 Reypens et al. (2016)	IMM
	21 Patala et al. (2016)	IMM
	22 Sc henkel et al. (2015)	JPSM
	23

Table 2 .

 2 2 summarizes the results obtained from the literature review, highlighting the evolution of the value concept in relation to the context, the value drivers, the mobilised theories, and the kinds of relationships between the involved actors.

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Table 2 .

 2 2: Evolution of the research on value creation.

		Economic value Customer value	Sustainable	Multi-stakeholder
					value	value
	Representative	Bowman	and	Vargo and Lusch		Reypens et al.
	research Industrial context	Ambrosini (2000) Mass production	(2008) Service development	Hart et al. (2003) Circular economy	(2016) Open innovation
	Value driver	Utility margin		Customer satisfaction	Resource efficiency	Knowledge
	Actors'			Dyadic	Networked	Networked
	Relationships	Economic theory T ransactional	co-creation	co-creation	co-creation
	Mobilised Theories	of value Resource-based		Service-Dominant Logic (SDL)	Strong and weak sustainability	Stakeholder theory
		view (RBV)

4 Triggers of collaborative innovation (why

3.1 Introduction ......................................................................... 28 3.2 Literature review methodology ...................................... 28 3.2.1 Sources identification ...................................................... 29 3.2.2 Conceptual structure ....................................................... 29 3.2.3 Thematic analysis............................................................ 30 3.3 Collaborative innovation: key concepts .........................34 3.?) ..................35 3.4.1 Technology-push approach ............................................. 35 3.4.2 Demand-pull approach ................................................... 35 3.5 Types of innovation (what?) ............................................ 36 3.5.1 According to the innovation object................................. 36 3.5.2 According to the innovation strategy ............................. 37 3.5.3 According to the degree of collaboration ....................... 37 3.6 Collaborative innovation in today's business to business relationships (how?)......................................... 39 3.6.1 The requisites for successful collaborative innovation . 39 3.6.2 The process of collaborative innovation ......................... 41 3.6.3 Collaborative innovation and sustainable value creation in the supply chain 42 3.7 Conclusions ............................................................................43

Table 3 .

 3 1: Content analysis of the selected articles.

				Trigger
	N	Theme / Author	Journal	Approach

Contents 4.1 Introduction

  .........................................................................

46 4.2 Literature review methodology

  .......................................

47 4.3 Multi-Criteria Decision Analysis (MCDA)

  .................... 49

	4.3.1 Basic elements in MCDA ................................................ 49
	4.3.2 Elements in multi-stakeholder MCDA............................ 50
	4.3.3 MCDA process ................................................................ 51
	4.3.4 Holding consensus in multi-stakeholder decisions . . . 52
	4.3.5 MCDA methods	53

4.4 Problem structure modelling in multi-stakeholder MCDA.......................................................................................54 4.5 MCDA application in the context of sustainable value creation........................................................................55

  Goal Modelling framework for problem structure modelling.........................................................................

	4.5.1 Choosing a MCDA method ............................................ 55
	4.5.2 MCDA domains of application....................................... 56
	4.5.3 Implementing MCDA in industry .................................. 56
	4.6 Retained elements for proposal development ..............57
	4.6.1 The Analytic Hierarchy Process (AHP) .......................... 57
	4.6.2 Searching a consensus..................................................... 59
	4.6.3 i

*

61 4.7 Conclusions

  ........................................................................... 64

		4 Decision making in multidimensional and multi-stakeholder value
	46	creation

N Multi-criteria decision making techniques Abbreviation

	1 Analytic hierarchy process	AHP
	2 Technique for order performance by similarity to ideal solution	TOPSIS
	3 Analytic network process	ANP
	4 Elimination and choice expressing reality	ELECTRE
	5 Multi-criteria optimization and compromise solution	VIKOR
	6 Decision making trial and evaluation laboratory	DEMATEL
	7 Preference ranking organization method for enrichment	PROMETHEE
	evaluation
	8 Simple multi-attribute rating technique	SMART

Table 4 .

 4 2: MCDA methods and applications of the reviewed articles.

	N	Reference	Journal	Method	Application context
	1	Erdogmuş et al. (2006)	Renew Sust Energ Rev ANP	Energy policy development
	2	Norese (2006)	Land Use Policy	ELECT RE III	Incinerator location
	3	Lin et al. (2010)	Expert Syst Appl	ANP -ISM	Industrial vendor selection
	4	Macharis et al. (2012)	Decis Support Syst	AHP -PROMET HEE	T ransport project evaluation
	5	Go vindan et al. (2014)	J Clean Prod	Fuzzy DEMAT EL	Policy identification in mining
					industry
	6	Ren et al. (2015)	Int J Life Cycle Assess	LCA-AHP-VI KOR	Bio-ethanol production
				Fuzzy theory
	7	Igoulalene et al. (2015) Expert Syst Appl	Fuzzy T OPSIS	Supplier selection problem
	8	Bruno et al. (2016)	Expert Syst Appl	Fuzzy AHP	Supplier selection problem
	9	Schillo et al. (2017)	Energy policy	QFD -AHP	Energy policy development
	10 Baudry et al. (2018)	Eur J Oper Res	Range-based	Biofuel selection
				AHP-PROMET HEE
	11 Chen and Ren (2018)	J Air T rans Manag	Fuzzy ANP -Fuzzy	Aviation fuel evaluation
				grey relational analysis
	12 Mathivathanan et al.	Resour Conserv Recy	DEMAT EL	Identification of sustainable supply
		(2018)			management practices
	13 Liu et al. (2019)	J Clean Prod	Fuzzy DEMAT EL	Innovation design
	14 Liu and Qian (2019)	J Clean Prod	Social-LCA	Construction project evaluation

Table 4 .

 4

3: Comparative analysis of multi-criteria decision techniques based on the quality criteria proposed by De Montis et al.

Table 4 .

 4

4: Scale of preferences of AHP

[START_REF] Saaty | How to make a decision: The analytic hierarchy process[END_REF]

). a with

2,4,6, and 8 as intermediary values.

Table 4 .

 4 6: Associations between intentional elements.

	From/to	Goal	Soft-goal	Task	Resource
	Goal	Refinement	Contribution	Refinement	n/a
	Soft-goal	Qualification	Contribution	Qualification	Qualification
	Task	Refinement	Contribution	Refinement	n/a
	Resource	n/a	Contribution	NeededBy	n/a
	Figure 4.

Mines Saint-E ´ tienne Martha Orellano Carrasquilla 4 Decision making in multidimensional and multi-stakeholder value 64 creation 8: Representation of intentional element associations.

  External environment: sociocultural forces (e.g., local communities, activist groups), political/legal forces (e.g., governmental entities), and technological change (e.g., innovation entities).

	5 Framew ork to support sustainable value creation in collaborative
	72	innovation
	•
	Value analysis
	Problem structure
	modelling
	Preference
	modelling
		Consensus
		process
	Mines Saint-E ´ tienne	Martha Orellano Carrasquilla

Table 5 .

 5 2: Alternative generation template.

	1.1.n
	. . .

a

VD = Value dimensions; E=Economics; N=Environmental; S=Social; R=Relational; F=Functional

Table 5 . 3 :

 53 Random indexes of reciprocal matrices.

	n	3	4	5	6	7	8

Table 6 .

 6 1: Interviews conducted during 2017 with internal and external actors in ICOVET project.

	Internal actors	Date	Function	Time (hh/mm/ss)
	1	31/10/2017	Purchasing department (group interview)	01:34:23
	2	31/10/2017	Purchasing	00:47:39
	3	31/10/2017	Purchasing -distribution	00:48:19
	4	31/10/2017	Purchasing -Nuclear safety clothing	00:49:01
	5	14/11/2017	Sustainable development direction	00:56:25
	6	14/11/2017	R&D engineering	00:40:10
	7	14/11/2017	Sustainable development direction	00:47:44
	8	14/11/2017	Prescription (Industrial security)	00:51:39
	9	14/11/2017	Human Resources	01:38:48
	10	14/11/2017	Prescription	00:45:52
	11	14/11/2017	Prescription-Waste management	01:41:46
	12	27/11/2017	Social dialogue direction -CSR	00:39:53
	13	04/12/2017	Human resources -Normative expert	00:30:28
	External actors
	14	05/12/2017	Confectioner	00:44:55
	15	05/12/2017	Logistics provider	00:40:17
	16	05/12/2017	Washing service provider	00:45:18
	17	05/12/2017	Logistics, washing and location service provider	00:46:55
	18	05/12/2017	Waste management -energy recovery	00:18:30
	19	19/12/2017	Recycling organisation	01:42:21
	20	17/12/2017	Security service provider	00:46:00

Table 6 .

 6 The specific topics treated on the interviews were value creation factors, textile supply chain, 2: Interviews with users and external actors in ICOVET project (2018).

	Mines Saint-E ´ tienne

Table 6 .

 6 3: Actors' perceptions of major topics in ICOVET project.

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Table 6 .

 6 4: Consequence analysis along the life cycle of the current system of safety clothing in EDF (internal workshop 2017).

	treatment policies in France, water scarcity and poor	working conditions in cotton-producing countries.	opportunities to develop local market in France.	Demand-pull innovation	External Internal

Table 6 .

 6 5 details the criteria defi in collaboration with internal actors in EDF.

	Mines Saint-E ´ tienne

Table 6 .

 6 5: Criteria for the evaluation of sustainable safety clothing offers.

Table 6 .

 6 6: Relative importance of the value dimensions and criteria at the beginning of life of the safety clothing system.

	Mines Saint-E ´ tienne

a A= Actor; AIP= Aggregation of Individual Priorities; SAP = Solidarity purchasing

Table 6 .

 6 7: Relative importance of the alternatives at the beginning of life.

	Alternative	A1 a A2	A3	A4 A5	A6 A7	A8 A9 AIP
	Tencel	56% 48% 35% 35% 45% 43% 55% 36% 43% 44,1%
	Poly-cotton	21% 36% 38% 37% 27% 29% 14% 20% 25% 27,5%
	Cotton BIO	23% 16% 27% 28% 27% 28% 31% 44% 32% 28,5%

a

A= Actor; AIP= Aggregation of Individual Priorities

Table 6 .

 6 8: Relative importance of the value dimensions and criteria at the middle of life of the safety clothing system.

	Mines Saint-E ´ tienne

a A= Actor; AIP= Aggregation of Individual Priorities; SAP = Solidarity purchasing Table 6.9: Relative importance of the alternatives at the middle of life. a A= Actor; AIP= Aggregation of Individual Priorities

Table 6 .

 6 10: Relative importance of the value dimensions and criteria at the end of life of the safety clothing system.

	Criterion	A1 a	A2	A3	A4	A5	A6	A7	A8	AIP
	Economic	10% 5% 21%

8% 20% 20% 19% 22% 15,7% Environmental 46% 53% 21% 41% 20% 49% 17% 16% 32,7%

	106	6 Framework applicatio n to the case of ICOVET project
	Carbon footprint	17% 17% 17% 17% 17% 17% 17% 17% 16,7%
	Recycling		83% 83% 83% 83% 83% 83% 83% 83% 83,3%
	Social		20% 13% 12% 38% 20% 7% 54% 40% 25,5%
	Local job		63% 66% 41% 72% 7% 45% 18% 41% 44,1%
	User resistance		11% 16% 11% 8%	7%	9% 70% 11% 18,0%
	SAP purchasing		26% 19% 48% 19% 7% 45% 11% 48% 27,9%
	Relational		20% 13% 5%	6% 20% 7%	5% 10% 10,7%
	Brand image		25% 50% 83% 17% 50% 50% 83% 50% 51,0%
	Innovation		75% 50% 17% 83% 50% 50% 17% 50% 49,0%
	Functional		4% 15% 41% 6% 20% 18% 5% 12% 15,3%
					Martha Orellano Carrasquilla

a A= Actor; AIP= Aggregation of Individual Priorities; SAP = Solidarity purchasing Mines Saint-E ´ tienne

Table 6 .

 6 11: Relative importance of the alternatives at the end of life.

	Alternative	A1 a A2	A3	A4 A5	A6 A7	A8	AIP
	Other product	65% 37% 60% 27% 39% 39% 39% 37% 43,0%
	New clothing	18% 49% 12% 61% 51% 29% 39% 46% 38,2%
	Energy	17% 14% 28% 11% 10% 32% 22% 16% 18,9%

a A= Actor; AIP= Aggregation of Individual Priorities

Table 6 .

 6 12: Results aggregation at the beginning of life according to decisional profi

	Martha Orellano Carrasquilla

Saint-E

´ tienne

Table 6 .

 6 13: Results aggregation at the middle of life according to decisional profi s.

	Criterion	TBL Eco-efficiency Societal
	Economic	14%	12%	12%
	Environmental	31%	28%	40%
	Carbon footprint	59%	53%	64%
	Chemical use	41%	47%	36%
	Social	28%	23%	24%
	Local job	33%	43%	37%
	User resistance	20%	17%	12%
	Solidarity purchasing	43%	40%	51%
	Relational	12%	12%	13%
	Brand image	52%	63%	39%
	Innovation	48%	37%	61%
	Functional	16%	24%	11%
	Lifespan	31%	32%	30%
	Comfort	46%	47%	51%
	Traceability	22%	22%	19%
	Alternatives
	Centralised washing	32%	34%	31%
	Localised washing	67%	65%	69%

Table 6 .

 6 14: Results aggregation at the end of life according to decisional profi

	Criterion	TBL Eco-efficiency Societal
	Economic	16%	18%	11%
	Environmental	33%	29%	41%
	Carbon footprint	17%	17%	17%
	Recycling	83%	83%	83%
	Social	25%	22%	27%
	Local job	44%	44%	63%
	User resistance	18%	19%	12%
	Solidarity purchasing	28%	37%	25%
	Relational	11%	8%	12%
	Brand image	51%	63%	31%
	Innovation	49%	37%	69%
	Functional	15%	23%	9%
	Alternatives
	Other product	43%	48%	46%
	New clothing	38%	29%	38%
	Energy	19%	23%	16%

Conclusion de la première partie : Synthèse du diagnostic sur stratégie achat. II. Deuxième phase : Diagnostic et identification des processus internes et de l'organisation 2.1. Description du Processus (internes et externes) et acteurs concernés

	1.2. Politique Produit -vêtements de travail Question d'ouverture : En ce qui concerne les vêtements de travail, quel regard portez-vous ? Quels sont 139
	les éléments clés de la politique produit ?
	1.3. Politique Fournisseur
	Sous-thèmes	Informati ons à recueillir		Questions
	Parmi les points évoqués ce matin sur les questions d'impact et les opportunités d'amélioration au niveau 1. Vous choisissez vos prestataires sur une stratégie de
	de la valeur à chaque étape du cycle de vie, est-ce que vous avez des remarques, interrogations…. ? mieux disance. Mais au final, est-ce que vous
	Voulez-vous revenir sur un élément ?		choisissez le moins cher ?
	Connaissance de l'Interlocuteur (Nom, fonction, anciennté…): I. Première phase : Diagnostic Marché des Vêtements de travail 1.1. Généralités du Marché / Développement de Filière innovante  Ethique, qualité, 2. De quelle manière réalisez-vous un benchmark des Elaboration de politiques pratiques des donneurs d'ordres ? la stratégie produits et 3. Quelles sont les ressources extérieures (les parties achats chez fournisseurs prenantes) que vous mobilisez pour vous aider à EDF  Gouvernance déterminer votre stratégie achats ?
	Question d'ouverture : Comment caractérisez-vous, décrivez-vous le marché du vêtement de travail ? 4. Quel poids est accordé au critère monétaire ? et aux
	(Stable, diversifié, hostile, coopératif ?)		critères non monétaires (DD, innovation.) ? Avez-vous
				apporté des modifications sur ces critères ? lesquelles ?
	Sous-thèmes Prix	Informati ons à recueillir  Coût  Marge	Part V 1. Comment vous assurez-vous que les prix garantissent la Questions pérennité économique des fournisseurs ?
	Acteurs en présence Aspects contractuels Contexte et entrants / nouveaux Marché Evolution du Nature des relations	Appendices Annex A: Interview guidelines  Nombre, poids et caractéristiques, Intermédiaires  Caractéristiques  Consultation 1. Quelles sont les étapes clés du déroulement de la 1. Quelle est votre perception sur le marché ? Peut-on  Négociation négociation ? parler de marché dominé par quelques fournisseurs ? 2. Veillez-vous à ce que les acteurs impliqués sur les 2. Quelles sont les améliorations qui ont pu être apportées  Contractualisation dans le cadre des partenariats productivité ? différentes étapes du processus de fabrication se offre/demande connaissent ?  Plan Ethique 1. Comment percevez-vous les relations entre EDF et ses  Relations entre les acteurs -Entretiennent-ils des relations collaboratives ?  Partage d'information, fournisseurs (hors Bétrancourt)? 2. Quels sont les éléments déterminants dans la nature de Internal actors -Quels sont les obstacles à leur résolution ?  Enjeux -Quelles sont les principales difficultés rencontrées ? technologiques répondent à ces besoins ?  Evolutions -Y-a-t-il dans le marché actuel des offres qui contexte légal) des priorités chez EDF ?  Tendances du marché : passés, 1. A votre avis, quelles sont et seront les tendances du marché ? (Les acteurs, les prix, les évolutions des  Transparence ses relations ?  Interdépendance 3. Y-a-t-il des difficultés chez les fournisseurs qui nuisent  Index PCI au processus achat? actuelles, futures fibres, ennoblissement, l'ergonomie, la sécurité, (justice,, courage, 4. Percevez-vous des opportunités de  Réglementation l'usage, customisation.) tempérance, collaboration complémentaires avec les fournisseurs en (évolution des normes et 2. Quels sont les besoins d'innovation produit en fonction patience) place?
	3. Y-a-t-il des nouveaux entrants au marché ? Sont-ils innovants ? quelles sont ses forces ? 1. Qui sont les parties prenantes avec lesquelles vous êtes amenées à collaborer sur la question des SWOT  Opportunités
	 Contraintes vêtements de travails (internes, externes, …) ?
	 Menaces 2. Comment qualifiez-vous les relations entretenues avec la prescription ? En phase de définition du
	1. La direction parle de filière lin-chanvre et d'autres, besoin ? dans la phase de négociation ? Dans le suivi du marché ?
	qu'en pensez-vous ? 3. Pensez-vous à des acteurs externes qui seraient ou pourraient être impliqués dans la requalification du
	Développement besoin ou sur la réalisation du marché ?  Opportunités	2. A votre avis quelle serait la plus-value de cette filière ?
	de nouvelles	 Contraintes		3. A quelle condition pourrait-elle représenter une plus-
	filières (Lin-	 Menaces		value ?
	chanvre, ortie)	 Enjeux		4. Quels seraient les freins à la prise en compte de cette
				filière lin-chanvre dans vos achats? les leviers pour les
				lever ?
	Mines Saint-E ´ tienne		Martha Orellano Carrasquilla

• Sustainable Business Models design for Product Service Systems: a collaborative innovation approach. Journée de la recherche ED-SIS 2019, Saint-E ´tienne, France.

De façon globale, quelles difficultés majeures trouvez-vous dans les processus internes liés au vêtements de travail ? Quelles perspecti ves ? Conclusion de la deuxième partie : Synthèse du diagnostic processus. Cartographie à demander. III. Troisième phase : Diagnostic du marché et Développement d'une offre collaborati ve / innovante

	Sous-thèmes	Informati ons à recueillir	Questions
			1. Pourriez-vous reformuler votre besoin sous forme d'une
			unité fonctionnelle ? (Besoin d'usage, performance.)
			2. Avez-vous déjà eu l'occasion d'expérimenter d'autres
			formes de mises à disposition des vêtements de travail
			(location, location-entretien ?...) Si oui, quelles ont été vos
			retours d'expériences par rapport à ces formes de
			prestations ?
		 Motivations	-Quelles seraient vos motivations à (re)développer ce
	Innovation de l'offre de VT (basé service)	 Freins et leviers  Besoins de transformations organisationnelles	type de pratique VT chez EDF ? 3. Le numérique est-il de nature à améliorer les offres proposées ? Avez-vous déjà des propositions sur le sujet ? 4. Quelles seraient les transformations induites par une dotation à l'usure dans votre organisation ?
			5. La mise en place d'un système produits-service pourrait-
			elle remettre en question les prestataires actuels ?
			6. Quelle valeur ajoutée en attendre ?
			7. Quels risques ?
			8. Avez-vous déjà recensé des prestataires susceptibles de vous
			aider ?
			Comment appréciez -
		 Collaboration
		interne et externe
	Pratiques	actuel
	collaboratives	 Besoins de
		collaboration pour
		le futur
		 Impact du
		changement du
		modèle dans le
	Impact sur le	processus achats
	service Achat	 Impact sur la valeur
		de l'offre
		 Impact sur votre
		métier d'acheteur

vous la qualité et le niveau de la collaborati on en interne

?

-Comment les faire évoluer ? -Sur quels points il sera difficile de les faire évoluer ?

Et en externe -Qui sont les autres PP extérieures

au groupe et aux prestataires avec qui vous collaborez sur ce thème ?

-Quels sont leurs rôles ? Quelle relation ? 1

. Si vous deviez aujourd'hui repasser un marché, quelles seraient les améliorati ons ?

  L'objet spécifique de cet entretien est de connaitre la contribution du service DD chez EDF au marché et à la mise à disposition des vêtements de travail et de connaitre le positionnement du service DD face aux opportunités d'innovation visées.

	Parmi les points évoqués ce matin sur les questions d'impact et les opportunités d'amélioration au
	niveau de la valeur à chaque étape du cycle de vie, est-ce que vous avez des remarques,
	interrogations…? Voulez-vous revenir sur un élément ?
	Connaissance de l'Interlocuteur (Nom, fonction, ancienneté…):
	Première phase : Généralités politique de Développent Durable / Développement de
	Filière innovante
	Du point de vue du DD quel regard portez-vous sur le sujet des VT en lien avec la fonction
	achats du groupe ?
		-Quelle est votre contribution au marché du vêtement de
		travail ? Avec quelle organisation ?
		o Depuis combien de temps travaillez-vous sur ce
	Comprendre le rôle actuel de l'acteur	sujet ? o Avec qui travaillez-vous ? Externe ? interne ? o A quelles étapes ?
		-Comment envisagez-vous les innovati ons en matière de
		textile ?
		Avez-vous des attentes particulières ?
	Contribution au marché	-Une des opportuni tés d'améliorati on réside dans le développement de nouvelles filières lin-chanvre, ortie, …
	Vêtements	Quel est votre regard à ce sujet ?
		o Avez-vous pensé à d'autres alternatives ?
	Perception de la transformation de l'offre et rôle dans	-Quelle pourrait être votre contributi on ? -Comment à votre avis peut être modifiée la valeur? Sur quels aspects du DD peut travailler ? Quelle valeur ajoutée ?
	la transformation
		-Vous proposeriez quel type de stratégie ?
		-Quels bénéfices pour EDF, vous, les usagers… ? quelles
		difficultés ?
		2. Comment voyez-vous évoluer votre métier d'acheteur ?
		Quelles sont ou quelles seraient les compétences à
	Stratégie de	développer pour intégrer une offre SPS ? les changements de
	Développement	processus ?
	Durable et les
	achats

Avez-vous d'autres éléments que nous n'avons pas abordés et qui vous viennent à l'esprit, vous paraissent importants de nous mentionner .

Conclusion globale finale.

Merci de votre participation GUIDE D'ENTRETIEN (Autre service interne) -Pour vous, la

transformati on de l'offre s'accompag ne t'elle d'un changement au

  niveau de votre service ? lequel ? -Quels bénéfices percevez-vous pour votre service, entreprise, usagers ? Quels freins au développement identifiez-vous?

	-Sinon, comment évaluez-vous la performance
	environnementale et sociale en matière de vêtements de
	travail ?
	-A votre avis, quels sont les points critiques du
	parcours des VT qui pourraient être améliorés en
	regardant la politique RSE-DD de EDF ?
	Matières premières, tissage, distribution, usage, fin de vie...?
	-Quels pourraient être les freins à l'amélioration de ces
	pratiques ?
	-Comment communiquez-vous en interne les
	changements au niveau des axes du DD ?
	Sous-thèmes	Questions
	-Quels risques ?
	-EDF est engagé sur Six objectifs de DD (changement
	climatique, développement humain, précarité
	énergétique, efficacité énergétique, Dialogue et
	concertation, biodiversité) ....
	-Quelle est la contribution des achats à ces objectifs ?
	-Quels sont les critères que vous avez prescrits en matière
	d'achats de vêtements de travail ?
	-Y-a-t'il des indicateurs de performance qui vous sont
	remontés sur ce marché ?

Conclusion de la première partie : Synthèse du diagnostic sur stratégie RSE-DD en lien avec les achats. Deuxième phase : Développement d'une offre collaborative / innovante

	Innovation de
	l'offre de VT
	(basé service)
		Condition de
		collaboration intra-
		organisationnelles
	Condition de	Condition de
	collaboration	collaboration avec
		les prestataires ?
		Conditions de
		collaboration avec
		les autres PP

-Pourriez-vous reformuler votre besoin sous forme d'une unité fonctionnelle? J'ai besoin d'un vêtement conçu pour X …. Et Y utilisations ? et comportementale ? qui va servir à quoi ? pourquoi ? -Avez-vous déjà eu l'occasion d'expérimenter d'autres formes de mises à disposition des vêtements de travail (location, location-entretien ?...) Si oui, quels ont été vos retours d'expériences par rapport à ces formes de prestations ?

  1.1. Généralités du Marché / Développement de Filière innovante

	II.SUB-CRITERIA COMPARISON Actor A2 II.SUB-C R I T E R I A COM P A RI S O N
	I. ALTERNATIVES COMPARISON CRITERION 1 : Economic
	Question d'ouverture : Comment caractérisez-vous, décrivez-vous le marché du vêtement de travail ? (Stable, diversifié, hostile, coopératif ?) Acteurs en présence  Nombre, poids et caractéristiques, Intermédiaires  Caractéristiques offre/demande  Relations entre les acteurs 1. Quelle est votre perception sur le marché ? Peut-on parler de marché dominé par quelques fournisseurs ? 2. Comment vous positionnez-vous ? 3. Avez-vous des contacts avec l'ensemble des acteurs de la filière (culture, tissage, ennoblissement, confection, logistique, mise à disposition, fin de vie ?) -Qui ? Où ils se trouvent ? 4. Comment qualifiez vous : -la qualité de la relation ? (Rythme, fréquence, projets collaboratifs, …) Contexte et Evolution du Marché / nouveaux entrants  Tendances du marché : passés, actuelles, futures  Réglementation (évolution des normes et contexte légal)  Evolutions technologiques  Enjeux SWOT  Opportunités  Contraintes  Menaces 1. A votre avis, quelles sont et seront les tendances du marché ? (Les acteurs, les prix, les évolutions des fibres, ennoblissement, l'ergonomie, la sécurité, l'usage, customisation, la réglementation) 2. Quels sont les nouveaux besoins que vous ressentez de la part de vos clients ? 3. Où vous positionnez vous par rapport à ces nouvelles tendances ? Avez-vous déjà fait des expériences d'innovation ? lesquelles ? Dans quel contexte ? 4. Y-a-t-il des nouveaux entrants au marché ? Sont-ils innovants ? quelles sont ses forces ? Sous-thèmes Informations à recueillir Questions 1.2. Politique Fournisseur Elaboration de la stratégie achats chez EDF Prix Aspects contractuels  Ethique, qualité, politiques produits et fournisseurs  Gouvernance  Coût  Marge  Consultation  Négociation  Contractualisation  Collaboration interne et externe actuel 1. Quelle place occupe EDF dans votre portefeuille de clients ? 2. Est-ce que EDF a des exigences, des modes de travail spécifiques par rapport aux autres grands comptes ? Comment percevez-vous la politique achats EDF en termes de CDC et critères de sélection ? 3. Quelles sont les difficultés que vous rencontrez à leur égard (relationnelles, contractuelles, techniques, tarifaires…) 1. Est-ce que les prix vous permettent d'assurer votre pérennité économique en tant que fournisseurs ? 1. Etes vous soumis à des partenariats de productivité ? 2. Si oui, quels sont les bénéfices que vous tirez d'un tel dispositif ? Quelles améliorations souhaiteriez voir appliquées à ce partenariat ? 1. Depuis combien de temps travaillez-vous avec EDF ? 2. Avec quels acteurs internes êtes-vous en contact ? 3. Avec quels services de chez EDF êtes-vous amené à collaborer ? Nature des relations  Plan Ethique  Partage d'information,  Transparence  Interdépendance  Index PCI (justice, courage, tempérance, patience) Comment appréciez-vous la qualité et le niveau de la collaboration avec EDF ? 5. Observez vous des différences de comportement significatives entre les différents publics auxquels vous de la chaîne de valeur, …). 6. Quelles sont les difficultés auxquelles vous pouvez être confrontés ? 7. Quels sont les éléments déterminants dans la nature de ses relations ? 8. Percevez-vous des opportunités de création de valeur supplémentaires avec EDF? Impact sur les processus actuels changement du modèle dans les processus actuels de Tencel Poly Coton Coton BIO Normalized Priority vector lmax  Impact sur la valeur CR SUBCRITERION 2 : availability 0% l'entreprise les avantages de votre offre? Que pourriez vous mettre en avant ? -Quels bénéfices pour EDF, vous, les usagers… d'autres acteurs ? quelles difficultés ? Tencel Poly Coton Coton BIO Normalized Priority vector lmax Tencel 1 3 3 0,6 0,6 0,6 0,6 Poly Coton 1/3 1 1 0,2 0,2 0,2 0,2 Coton BIO 1/3 1 1 0,2 0,2 0,2 0,2 Total 1 2/3 5 5 lmax Priority vector 0,6 0,2 0,2 CI 0,00% RC 0,58 Priority 0,833333333 CR 0,063642421 0,166666667 RC 0,58 3 Coton BIO 0,2 0,26 0,210082993 Priority vector 0,570575318 0,363065437 0,066359245 CI 0,036912604 0,6 Poly Coton 0,2 0,63 0,272224287 Total 1 2/3 3 1/7 15 lmax 3,073825209 0,6 Tencel 0,6 0,11 0,517692721 Coton BIO 1/7 1/7 1 0,086956522 0,045454545 0,066666667 0,066359245 0,199736495 1,8 fiber quality av ailability Functional Tencel 1 2 7 0,608695652 0,636363636 0,466666667 0,570575318 1,761220905 Poly Coton 1/2 1 7 0,304347826 0,318181818 0,466666667 0,363065437 1,112867809 Conclusion de la première partie : Synthèse du diagnostic sur stratégie achat. Innovation collaborative  Besoins de collaboration pour le futur tangibles et non tangibles ? 3. Chez vous, quelles conditions seront nécessaires pour créer une telle valeur ajoutée ? 1. Avez-vous le besoin de collaborer différemment avec EDF pour répondre aux enjeux d'innovation attendus ? 2. Ressentez-vous le besoin de développer des collaborations avec d'autres acteurs de la chaîne de valeur ? lesquels ?  Impact du 1. Si vous deviez aujourd'hui répondre à un marché, quelles seraient CR CRITERION 5 : Functional SUBCRITERION 1 : fiber quality SUBCRITERION 2 : Tencel Poly Coton Coton BIO Normalized Priority vector Tencel 1 3 3 3/5 0,6 0,6 0,6 Poly Coton 1/3 1 1 0,2 0,2 0,2 0,2 Coton BIO 1/3 1 1 0,2 0,2 0,2 0,2 Total 1 2/3 5 5 lmax Priority vector 0,6 0,2 0,2 CI 0,00% RC 0,58 CR 0,00% Tencel 0,643388869 0,6 Poly Coton 0,073772106 0,2 Coton BIO 0,282839025 0,2 Priority 0,5 Tencel Poly Coton Coton BIO Normalized Priority vector lmax 0,5 SUBCRITERION 1 : fiber quality 0,241419512 CRITERION 5 : Functional 0,136886053 CR 0,061082427 0,621694435 RC 0,58 3 Brand image Innov ation Relational Priority vector 0,555926916 0,353721034 0,09035205 CI 0,035427807 0,6 Total 1 2/3 3 1/5 11 lmax 3,070855615 0,6 Priority 0,875 0,125 Coton BIO 1/5 1/5 1 0,117647059 0,0625 0,090909091 0,09035205 0,27228164 1,8 Coton BIO 0,229871176 0,643388869 Poly Coton 1/2 1 5 0,294117647 0,3125 0,454545455 0,353721034 1,083444742 0,281560887 lmax Poly Coton 0,122181965 0,073772106 Tencel 1 2 5 0,588235294 0,625 0,454545455 0,555926916 1,715129234 0,116130732 Innovation Social performance User resistance Social Tencel 0,64794686 0,282839025 Tencel Poly Coton Coton BIO Normalized Priority vector lmax 0,602308381 SUBCRITERION 2 : Innovation 0,083384313 leviers Priority vector 0,643388869 0,073772106 0,282839025 CI 0,048362902 RC 0,58 Priority 0,5 CR 0,019287408 0,5 RC 0,58 Risques et Tencel Poly Coton Coton BIO Normalized Priority vector Tencel 1 7 3 0,677419355 0,538461538 0,714285714 0,643388869 Poly Coton 1/7 1 1/5 0,096774194 0,076923077 0,047619048 0,073772106 Coton BIO 1/3 5 1 0,225806452 0,384615385 0,238095238 0,282839025 Total 1 1/2 13 4 1/5 lmax 3,096725804 Coton BIO 0,260497956 0,114959115 0,187728536 Priority vector 0,745581448 0,134301475 0,120117078 CI 0,011186697 0,866162511 Poly Coton 0,106156324 0,47955748 0,292856902 Total 1 1/3 7 9 lmax 3,022373394 0,222252607 Tencel 0,63334572 0,405483405 0,519414563 1/7 1 1 0,106382979 0,142857143 0,111111111 0,120117078 0,360930188 Coton BIO 2,008310686 Fiber quality Provider performance Poly Coton 1/5 1 1 0,14893617 0,142857143 0,111111111 0,134301475 0,403534842 Env ironmental lmax Tencel 1 5 7 0,744680851 0,714285714 0,777777778 0,745581448 2,257908364 êtes confrontés (prescripteurs, acheteurs, autres acteurs Co-création de valeur d'une offre innovante ? 2. Quels sont les bénéfices et sacrifices que vous percevez en relation au développement d'une telle offre par rapport à l'offre ancienne ? -Pouvez-vous préciser par rapport aux bénéfices et sacrifices Les réponses du fournisseur CRITERION 4 : Relational SUBCRITERION 1 : Brand image Tencel 1 5 1/3 0,238095238 0,384615385 0,225806452 0,282839025 Poly Coton 1/5 1 1/7 0,047619048 0,076923077 0,096774194 0,073772106 0,222252607 Coton BIO 3 7 1 0,714285714 0,538461538 0,677419355 0,643388869 Total 4 1/5 13 1 1/2 lmax 3,096725804 Priority vector 0,282839025 0,073772106 0,643388869 CI 0,048362902 RC 0,58 CR 0,083384313 LCC PC Tencel 0,63334572 0,186749482 Poly Coton 0,106156324 0,655486542 Coton BIO 0,260497956 0,157763975 Priority 0,833333333 Tencel Poly Coton Coton BIO Normalized Priority vector lmax 0,166666667 SUBCRITERION 1 : Brand image 0,243375626 CRITERION 4 : Relational 0,19771136 CR 0 0,558913014 RC 0,58 Economic Priority vector 0,333333333 0,333333333 0,333333333 CI 0 2,008310686 Priority vector 0,097533806 0,447205109 0,277299737 0,13548537 Total 3 3 3 lmax 3 0,042475977 Coton BIO 1 1 1 0,333333333 0,333333333 0,333333333 0,333333333 1 0,866162511 Total 1 1 1 1 1 1 Poly Coton 1 1 1 0,333333333 0,333333333 0,333333333 0,333333333 1 1. A votre avis, quelle est la valeur ajoutée lors du développement Tencel Poly Coton Coton BIO Normalized Priority vector lmax Coton BIO 0,243375626 0,187728536 0,281560887 0,241419512 0,21 Tencel 1 1 1 0,333333333 0,333333333 0,333333333 0,333333333 1 0,227399564 4. Comment percevez-vous les relations avec EDF ? Sous-thèmes Informations à recueillir Questions Innovation de l'offre de VT (basé service)  Motivations  Freins et leviers  Besoins de transformations organisationnelles 1. EDF s'intéresse à de nouvelles filières (filière lin-chanvre) et d'autres, qu'en pensez-vous ? -Pourriez-vous prendre en compte ces nouvelles attentes dans I. Deuxième phase : Développement d'une offre collaborative / innovante Sous-thèmes Informations à recueillir Questions Annex C: Template for alternative generation SUBCRITERION 1 : LCC Tencel Poly Coton Coton BIO Normalized Priority vector lmax Tencel 1 5 3 2/3 0,555555556 0,692307692 0,63334572 1,945621206 Poly Coton 1/5 1 1/3 0,130434783 0,111111111 0,076923077 0,106156324 0,31965812 Coton BIO 1/3 3 1 0,217391304 0,333333333 0,230769231 0,260497956 0,790082167 Total 1 1/2 9 4 1/3 lmax 3,055361493 Priority vector 0,63334572 0,106156324 0,260497956 CI 0,027680747 RC 0,58 CR 0,047725425 CRITERION 2 : Env ironmental CRITERION 1 : Economic LCC Purchasing cost Priority vector Global priority LCC 1 5 0,833333333 0,081278172 Purchasing cost 1/5 1 0,166666667 0,016255634 Total 1 1/5 CRITERION 1 : LCC Purchasing cost Priority vector Global priority Economic SUBCRITERION 1 : LCC 1 7 0,875 0,042537312 LCC Tencel Poly Coton Coton BIO Normalized Priority vector Purchasing cost 1/7 1 0,125 0,006076759 lmax Tencel 1 2 5 0,588235294 0,625 0,454545455 0,555926916 Total 1 1/7 8 1,715129234 6 Fiber quality Provider performance Priority vector Global priority Fiber quality 1 3 0,75 0,335403832 Provider performance 1/3 1 0,25 Poly Coton 1/2 1 5 0,294117647 0,3125 0,454545455 0,353721034 1,083444742 Coton BIO 1/5 1/5 1 0,117647059 0,0625 0,090909091 0,09035205 CRITERION 2 : Environmental 0,27228164 Total 1 2/3 3 1/5 11 lmax Fiber quality Provider perform an ce Priority vector Global priority 3,070855615 Priority vector 0,555926916 0,353721034 0,09035205 CI Fiber quality 1 1 0,5 0,077252432 0,035427807 RC Provider perform an ce 1 1 0,5 0,077252432 0,58 CR 0,061082427 Total 2 2 0,111801277 Total 1 1/3 SUBCRITERION 2 : Purchasing cost 4 Tencel Poly Coton Coton BIO Normalized Priority vector lmax CRITERION 3 : Social votre processus et répondre aux attentes EDF? 2. Aviez-vous déjà entendu parler de l'économie de fonctionnalité ? 3. Aviez-vous déjà entendu parler des systèmes produits-services ? 4. Avez-vous déjà eu l'occasion d'expérimenter d'autres formes de mises à disposition des vêtements de travail (location, location-entretien ?...) Si oui, quelles ont été vos retours d'expériences par rapport à ces formes de prestations ? -Quelles seraient vos motivations à (re)développer ce type de pratique VT chez EDF ? GRILLE ANALYSE PROCESSUS INNOVATION COLLABORATIVE -Entretiens fournisseurs du 11 décembre 2018 NOM DU FOURNISSEUR -NOM ET FONCTION DE L'INTERLOCUTEUR : ……………………………………………………………………………………………………………………………………. SOLUTIONS POTENTIELLES CONDITIONS DE COLLABORATION TOUT AU LES OPPORTUNITES DE CRITERION 2 : Environmental SUBCRITERION 1 : Fiber quality Tencel Poly Coton Coton BIO Normalized Priority vector lmax Tencel 1 5 3 0,652173913 0,555555556 0,692307692 0,63334572 1,945621206 Poly Coton 1/5 1 1/3 0,130434783 0,111111111 0,076923077 0,106156324 0,31965812 Coton BIO 1/3 3 1 0,217391304 0,333333333 0,230769231 0,260497956 0,790082167 Total 1 1/2 9 4 1/3 lmax 3,055361493 Priority vector 0,63334572 0,106156324 0,260497956 CI 0,027680747 RC Tencel Poly Coton Coton BIO Normalized Priority vector lmax Tencel 1 1/3 1 0,2 0,217391304 0,142857143 0,186749482 0,563008972 Poly Coton 3 1 5 0,6 0,652173913 0,714285714 0,655486542 2,004554865 Coton BIO 1 1/5 1 0,2 0,130434783 0,142857143 0,157763975 0,475610766 Total 5 1 1/2 7 lmax 3,043174603 Priority vector 0,186749482 0,655486542 0,157763975 CI CRITERION 3 : Tencel 1 2 5 0,588235294 0,625 0,454545455 0,555926916 1,715129234 Social perform an ce User resistance Priority vector Global priority Social Social performance User resistance Priority vector Poly Coton 1/2 1 5 0,294117647 0,3125 0,454545455 0,353721034 1,083444742 Social perform an ce 1 3 0,75 0,157760639 Global priority Social performance 1 7 0,875 Coton BIO 1/5 1/5 1 0,117647059 0,0625 0,090909091 0,09035205 0,27228164 User resistance 1/3 1 0,25 0,05258688 0,24263727 User resistance 1/7 1 0,125 0,034662467 Total 1 1/7 Total 1 2/3 3 1/5 11 lmax 3,070855615 Priority vector 0,555926916 0,353721034 0,09035205 CI Total 1 1/3 4 0,035427807 8 RC 0,58 CRITERION 4 : Relational 0,021587302 RC 0,58 CR 0,037219485 CRITERION 4 : Relational CRITERION 5 : Brand image Innovation Priority vector Global priority Brand image 1 1 0,5 0,067742685 Innovation 1 1 0,5 CRITERION 2 : CR 0,061082427 Brand image Innovation Priority vector Global priority Environmental SUBCRITERION 1 : Brand image 1 5 0,833333333 0,209278557 Fiber quality Tencel Poly Coton Coton BIO Normalized Priority vector Innovation 1/5 1 0,166666667 0,041855711 lmax Tencel 1 2 5 0,588235294 0,625 0,454545455 0,555926916 Total 1 1/5 6 1,715129234 0,067742685 Total 2 2 Poly Coton 1/2 1 5 0,294117647 0,3125 0,454545455 0,353721034 1,083444742 Coton BIO 1/5 1/5 1 0,117647059 0,0625 0,090909091 0,09035205 CRITERION 5 : Functional 0,27228164 Total 1 2/3 3 1/5 11 lmax fiber quality availability Priority vector Global priority 3,070855615 Functional fiber quality availability Priority vector Priority vector 0,555926916 0,353721034 0,09035205 CI fiber quality 1 1 0,5 0,167699639 0,035427807 Global priority fiber quality 1 5 0,833333333 RC availability 1 1 0,5 0,167699639 0,58 0,035396648 CR 0,061082427 Total 2 2 0,58 CR 0,047725425 availability 1/5 1 0,166666667 SUBCRITERION 2 : Provider performance 0,00707933 Total 1 1/5 6 Tencel Poly Coton Coton BIO Normalized Priority vector lmax III.CRI T E RI A COM P A R I S O N -Percevez vous les transformations à mener dans votre organisation pour y parvenir ? -Quelles sont les difficultés que vous pourriez rencontrer dans la transformation de votre modèle économique ? -Sentez vous un risque ou une opportunité à développer cette offre avec EDF ? 5. Le numérique est-il de nature à améliorer les offres proposées ? Avez-vous déjà des propositions sur le sujet ? 6. Avez-vous déjà recensé des prestataires susceptibles de vous aider ? PROPOSEES PAR LE FOURNISSEUR LONG DE LA CHAINE DE VALEUR Tencel Poly Coton Coton BIO Normalized Priority vector lmax Tencel 1 1 1 0,333333333 0,333333333 0,333333333 0,333333333 1 CREATION DE VALEUR Les attendus -Temporalité (capacité à répondre dans le délais imparti) -Capacité à répondre sur les différents sites géographiques et en termes de volume -Opportunité de répondre dans le cadre normatif et réglementaire d'un marché public la gestion de projet Priority vector 0,64794686 0,122181965 0,229871176 CI 0,002697262 RC 0,58 CR Poly Coton 0,19771136 0,292856902 0,116130732 0,136886053 0,27 0,212562716 Tencel Poly Coton Coton BIO Normalized Priority vector lmax 0,004650453 Economic Env ironmental Social Relational Functional Tencel 0,558913014 0,519414563 0,602308381 0,621694435 0,52 SUBCRITERION 2 : User resistance 0,56003772 CR 0 Ranking RC 0,58 -Accompagnement de EDF dans -Connaissances des acteurs impliqués dans la chaîne de valeur amont et aval -Capacité à évaluer les risques et les impacts dans un logique cycle de vie -Capacité à garantir une traçabilité tout au long de la chaîne de valeur -Compétences pour engager une collaboration dans une perspective d'économie circulaire -Conditions de financement du dispositif d'innovation -Mesure de la création de valeur sur les thématiques de la grille multicritères environnementale) Tencel 1 5 3 0,652173913 0,625 0,666666667 0,64794686 1,948470209 Poly Coton 1/5 1 1/2 0,130434783 0,125 0,111111111 0,122181965 Coton BIO 1/3 2 1 0,217391304 0,25 0,222222222 0,229871176 0,690217391 Total 1 1/2 8 4 1/2 lmax 3,005394525 Priority vector 0,333333333 0,333333333 0,333333333 CI 0 IV.ALTERNATIVES PRIORITIZATION Total 3 3 3 lmax 3 0,366706924 priority vector 0,097533806 0,447205109 0,277299737 0,13548537 Coton BIO 1 1 1 0,333333333 0,333333333 0,333333333 0,333333333 1 0,042475977 Poly Coton 1 1 1 0,333333333 0,333333333 0,333333333 0,333333333 1 sociale, économique, Tencel Poly Coton Coton BIO Normalized Priority vector lmax Total 12 1/3 2 4 3/4 8 1/5 21 1 1 1 0,333333333 0,333333333 0,333333333 0,333333333 1 Tencel (fonctionnelle, relationnelle, CRITERION 3 : Social SUBCRITERION 1 : Provider performance Tencel 1 1 3 0,428571429 0,454545455 0,333333333 0,405483405 1,22991823 Poly Coton 1 1 5 0,428571429 0,454545455 0,555555556 0,47955748 1,45983646 Coton BIO 1/3 1/5 1 0,142857143 0,090909091 0,111111111 0,114959115 0,346031746 Total 2 1/3 2 1/5 9 lmax 3,035786436 Priority vector 0,405483405 0,47955748 0,114959115 CI 0,017893218 RC 0,58 CR 0,030850376 Poly Coton 1 1 1 0,333333333 0,333333333 0,333333333 0,333333333 1 Economic Environmental Social Relational Functional Normalized III.CRITERIA COMPARISON Economic Env ironmental Social Relational Functional Normalized Economic 1 1/5 1/5 1 3 0,081081081 0,09953 0,04225 0,122 0,1429 Env ironmental 5 1 3 3 7 0,405405405 0,49763 0,6338 0,3659 0,3333 Social 5 1/3 1 3 5 0,405405405 0,16588 0,21127 0,3659 0,2381 Relational 1 1/3 1/3 1 5 0,081081081 0,16588 0,07042 0,122 0,2381 Functional 1/3 1/7 1/5 1/5 1 0,027027027 0,07109 0,04225 0,0244 0,0476 CRITERION 3 : Coton BIO 1 1 1 0,333333333 0,333333333 0,333333333 0,333333333 1 Total 3 3 3 lmax Economic 1 1/5 1/3 1/5 1/7 0,04761905 0,0217 0,07692 0,05405405 0,04273504 3 Priority vector 0,333333333 0,333333333 0,333333333 CI Environmental 5 1 1 1/2 1/5 0,23809524 0,1087 0,23077 0,13513514 0,05982906 0 RC Social 3 1 1 1 1 0,14285714 0,1087 0,23077 0,27027027 0,2991453 0,58 CR Relational 5 2 1 1 1 0,23809524 0,2174 0,23077 0,27027027 0,2991453 0 Functional 7 5 1 1 1 0,33333333 0,5435 0,23077 0,27027027 0,2991453 Social SUBCRITERION 1 : Total 21 9 1/5 4 1/3 3 5/7 3 1/3 Provider performance Tencel Poly Coton Coton BIO Normalized Priority vector lmax priority vector 0,04861407 0,154504863 0,210347519 0,251134269 0,335399279
	Tencel Tencel Poly Coton Poly Coton Coton BIO Coton BIO Total Total Priority vector Priority vector	Tencel 1  Impact sur votre Poly Coton 1/3 de l'offre 1 1/5 3 1 5 1 1/3 1/7 3 1/3 4 1/3 1 1/2 9 1 1/2 0,243100985 0,668696895 métier 0,106156324 0,63334572	Coton BIO 3 1/3 7 3 1 1 11 4 1/3 0,08820212 0,260497956	0,230769231 0,111111111 0,692307692 0,555555556 0,076923077 0,333333333	Normalized 0,225806452 0,272727273 0,130434783 0,076923077 0,677419355 0,636363636 0,652173913 0,692307692 0,096774194 0,090909091 0,217391304 0,230769231	Priority vector 0,243100985 0,106156324 0,668696895 0,63334572 0,08820212 0,260497956 lmax lmax CI CI RC RC CR	lmax 0,730606311 2,015414693 0,31965812 0,26476391 1,945621206 3,010784914 0,790082167 3,055361493 0,005392457 0,58 0,027680747 0,58 0,00929734
						CR	0,047725425

2. Comment voyez-vous évoluer votre métier? Quelles sont ou quelles seraient les compétences à développer pour intégrer une offre SPS ? quels changements dans le processus ? paraissent importants de nous mentionner. Conclusion globale finale. Avez-vous d'autres éléments que nous n'avons pas abordés et qui vous viennent à l'esprit, vous

Fiber quality Provider perform an ce

	Economic 0,555926916 0,353721034 0,09035205 1 0,04861407 0,555926916 0,353721034 0,09035205 0,875 0,555926916 0,353721034 0,09035205 0,5 Social performance 0,333333333 0,333333333 0,333333333 0,75 Brand image 0,745581448 0,134301475 0,120117078 0,833333333 fiber quality 0,570575318 0,363065437 0,066359245 0,5 Tencel 1 1 1 3 0,333333333 Tencel Poly Coton Coton BIO Total Priority vector SUBCRITERION 2 : Tencel Poly Coton Coton BIO Total Priority vector Tencel Poly Coton Coton BIO Priority Tencel Poly Coton Coton BIO Priority Tencel Poly Coton Coton BIO Priority Tencel Poly Coton Coton BIO Priority Tencel Poly Coton Coton BIO Priority Tencel Poly Coton Coton BIO Total Priority vector 0,142857143 Environmental 0,444630125 0,343527184 0,211842692 1 0,154504863 0,555926916 0,353721034 0,09035205 0,125 0,333333333 0,333333333 0,333333333 0,5 User resistance 0,333333333 0,333333333 0,333333333 Innovation 0,555926916 0,353721034 0,09035205 0,166666667 availability 0,24 0,67 0,09 0,5 Poly Coton 1 1 1 3 0,333333333 Tencel Poly Coton 1 1/5 5 1 1 1/5 7 1 2/5 0,714285714 SUBCRITERION 2 : Tencel Poly Coton Tencel 1 1/5 Poly Coton 5 1 Coton BIO 2 1 Total 8 2 1/5 Priority vector 0,138636364 0,493181818 SUBCRITERION 2 : Tencel Poly Coton Tencel 1 1 Poly Coton 1 1 Coton BIO 1 1 Total 3 3 Priority vector 0,333333333 0,333333333 Priority vector 0,111111111 0,777777778 0,111111111 Social 0,333333333 0,333333333 0,333333333 1 0,210347519 Economic 0,555926916 0,353721034 0,09035205 Environmental 0,444630125 0,343527184 0,211842692 Social 0,333333333 0,333333333 0,333333333 Relational 0,713972359 0,170871401 0,11515624 Functional 0,406838152 0,515881166 0,077280683 Coton BIO 1 1 1 3 0,333333333 Coton BIO 1 5 1 7 0,142857143 Coton BIO 1/2 1 1 2 1/2 0,368181818 Coton BIO 1 1 1 3 0,333333333 Total 9 1 2/7 9 Coton BIO 1 1/7 1 0,111111111 0,714285714 0,333333333 Relational 0,713972359 0,170871401 0,11515624 1 0,251134269 Normalized 0,335399279 Functional 0,41 0,52 0,08 1 0,333333333 0,333333333 Ranking 0,48159538 0,35632611 0,16207851 1 Priority vector 0,333333333 0,333333333 0,333333333 0,333333333 0,333333333 0,333333333 0,333333333 0,333333333 0,333333333 lmax CI RC CR Normalized Priority vector 1/7 1/7 0,142857143 0,142857143 0,714285714 0,714285714 0,714285714 0,142857143 0,142857143 0,142857143 0,142857143 lmax CI RC CR Normalized Priority vector 0,125 0,090909091 0,2 0,138636364 0,421363636 lmax 1 1 1 3 0 0,58 0 lmax 0,428571429 2,142857143 0,428571429 3 0% 0,58 0% lmax 0,625 0,454545455 0,4 0,493181818 1,554545455 0,25 0,454545455 0,4 0,368181818 1,138636364 lmax 3,114545455 CI 0,057272727 RC 0,58 CR 0,098746082 Normalized Priority vector 0,333333333 0,333333333 0,333333333 0,333333333 0,333333333 0,333333333 0,333333333 0,333333333 0,333333333 0,333333333 0,333333333 0,333333333 lmax CI RC CR 0 CR 0 0,58 RC 0,58 0 CI 0 3 lmax 3 1 0,111111111 0,111111111 0,111111111 0,333333333 1 Poly Coton 7 1 7 0,777777778 0,777777778 0,777777778 0,777777778 2,333333333 1 Tencel 1 1/7 1 0,111111111 0,111111111 0,111111111 0,111111111 0,333333333 lmax Tencel Poly Coton Coton BIO Normalized Priority vector lmax availability SUBCRITERION 2 : availability availability availability CRITERION 5 : Functional SUBCRITERION 1 : fiber quality Tencel Poly Coton Coton BIO Normalized Priority vector lmax Tencel 1 1/7 1 0,111111111 0,111111111 0,111111111 0,111111111 0,333333333 Poly Coton 7 1 7 0,777777778 0,777777778 0,777777778 0,777777778 2,333333333 Coton BIO 1 1/7 1 0,111111111 0,111111111 0,111111111 0,111111111 0,333333333 Total 9 1 2/7 9 lmax 3 Priority vector 0,111111111 0,777777778 0,111111111 CI 0 RC 0,58 CR 0 SUBCRITERION 2 : Innovation Tencel Poly Coton Coton BIO Normalized Priority vector lmax Tencel 1 5 1 0,454545455 0,625 0,4 0,493181818 1,554545455 Poly Coton 1/5 1 1/2 0,090909091 0,125 0,2 0,138636364 0,421363636 Coton BIO 1 2 1 0,454545455 0,25 0,4 0,368181818 1,138636364 Total 2 1/5 8 2 1/2 lmax 3,114545455 Priority vector 0,493181818 0,138636364 0,368181818 CI 0,057272727 RC 0,58 CR 0,098746082 Poly Coton 0,138636364 0,777777778 0,458207071 Coton BIO 0,368181818 0,111111111 0,239646465 Priority 0,5 0,5 Brand image Innov ation Relational Tencel 0,510533911 0,493181818 0,501857864 Poly Coton 0,1001443 0,138636364 0,119390332 Coton BIO 0,389321789 0,368181818 0,378751804 Priority 0,5 0,5 fiber quality av ailability Functional Tencel 0,111111111 0,33 0,148148148 Poly Coton 0,777777778 0,33 0,703703704 Coton BIO 0,111111111 0,33 0,148148148 Priority 0,833333333 0,166666667 SUBCRITERION 2 : availability CRITERION 5 : Functional SUBCRITERION 1 : fiber quality Tencel Poly Coton Coton BIO Normalized Priority vector lmax Tencel 1 1/5 1/3 0,111111111 0,130434783 0,076923077 0,106156324 0,31965812 Poly Coton 5 1 3 0,555555556 0,652173913 0,692307692 0,63334572 1,945621206 Coton BIO 3 1/3 1 0,333333333 0,217391304 0,230769231 0,260497956 0,790082167 Total 9 1 1/2 4 1/3 lmax 3,055361493 Priority vector 0,106156324 0,63334572 0,260497956 CI 0,027680747 RC 0,58 CR 0,047725425 Tencel Poly Coton Coton BIO Normalized Priority vector lmax Tencel 1 5 5 0,714285714 0,625 0,769230769 0,702838828 2,188644689 Poly Coton 1/5 1 1/2 0,142857143 0,125 0,076923077 0,11492674 0,346611722 Coton BIO 1/5 2 1 0,142857143 0,25 0,153846154 0,182234432 0,552655678 Total 1 2/5 8 6 1/2 lmax 3,087912088 Priority vector 0,702838828 0,11492674 0,182234432 CI 0,043956044 RC 0,58 CR 0,075786283 Poly Coton 0,142857143 0,186749482 0,179434092 Coton BIO 0,428571429 0,655486542 0,617667357 Priority 0,166666667 0,833333333 Brand image Innov ation Relational Tencel 0,63334572 0,702838828 0,642032359 Poly Coton 0,106156324 0,11492674 0,107252626 Coton BIO 0,260497956 0,182234432 0,250715016 Priority 0,875 0,125 fiber quality av ailability Functional Tencel 0,106156324 0,14 0,110743926 Poly Coton 0,63334572 0,71 0,64346322 Coton BIO 0,260497956 0,14 0,245792854 Priority 0,875 0,125 CRITERION 5 : Functional SUBCRITERION 1 : Tencel Poly Coton Coton BIO Normalized Priority vector lmax Tencel 1 1/5 1 0,142857143 0,130434783 0,2 0,157763975 0,475610766 Poly Coton 5 1 3 0,714285714 0,652173913 0,6 0,655486542 2,004554865 Coton BIO 1 1/3 1 0,142857143 0,217391304 0,2 0,186749482 0,563008972 Total 7 1 1/2 5 lmax 3,043174603 Priority vector 0,157763975 0,655486542 0,186749482 CI 0,021587302 RC 0,58 CR CR 0 CR 0 0,037219485 fiber quality av ailability Functional Tencel 0,157763975 0,14 0,152982072 Poly Coton 0,655486542 0,49 0,614910361 Coton BIO 0,186749482 0,37 0,232107566 Priority 0,75 0,25 SUBCRITERION 1 : fiber quality Tencel Poly Coton Coton BIO Normalized Priority vector Tencel 1 7 7 0,777777778 0,777777778 0,777777778 0,777777778 Poly Coton 1/7 1 1 0,111111111 0,111111111 0,111111111 0,111111111 Coton BIO 1/7 1 1 0,111111111 0,111111111 0,111111111 0,111111111 Total 1 2/7 9 9 lmax Priority vector 0,777777778 0,111111111 0,111111111 CI RC 0,58 RC 0,58 0 Priority vector 0,333333333 0,333333333 0,333333333 CI 0 3 Priority 0,25 0,75 Total 3 3 3 lmax 3 0,333333333 Coton BIO 0,111111111 0,33 0,277777778 Coton BIO 1 1 1 0,333333333 0,333333333 0,333333333 0,333333333 1 0,333333333 Poly Coton 0,111111111 0,33 0,277777778 1 1 1 0,333333333 0,333333333 0,333333333 0,333333333 1 Poly Coton 2,333333333 Tencel 0,777777778 0,33 0,444444444 Tencel 1 1 1 0,333333333 0,333333333 0,333333333 0,333333333 1 lmax fiber quality av ailability Tencel Poly Coton Coton BIO Normalized Priority vector lmax Functional SUBCRITERION 1 : fiber quality fiber quality SUBCRITERION 2 : Innovation Tencel Poly Coton Coton BIO Normalized Priority vector lmax Tencel 1 7 5 0,744680851 0,636363636 0,789473684 0,723506057 2,272591537 Poly Coton 1/7 1 1/3 0,106382979 0,090909091 0,052631579 0,083307883 0,251061244 Coton BIO 1/5 3 1 0,14893617 0,272727273 0,157894737 0,19318606 Total 1 1/3 11 6 1/3 lmax Priority vector 0,723506057 0,083307883 0,19318606 CI 0,055731851 RC 0,58 CR 0,096089398 Tencel 0,723506057 0,723506057 0,723506057 Poly Coton 0,083307883 0,083307883 0,083307883 Coton BIO 0,19318606 0,19318606 0,19318606 Priority 0,5 0,5 CRITERION 5 : Functional Total 1 1/3 6 1/3 11 lmax Priority vector 0,723506057 0,19318606 0,083307883 CI 0,055731851 RC 0,58 CR 0,096089398 Poly Coton 0,19318606 0,19318606 Coton BIO 0,083307883 0,083307883 Priority 0,5 CRITERION 5 : Functional 0,5 CR 0 0,083307883 RC 0,58 0,19318606 Priority vector 0,466666667 0,066666667 0,466666667 CI 0 3,111463701 Tencel 0,723506057 0,723506057 0,723506057 Total 2 1/7 15 2 1/7 lmax 3 3,111463701 Brand image Innov ation Relational Coton BIO 1/7 1/3 1 0,106382979 0,052631579 0,090909091 0,083307883 0,251061244 Brand image Innov ation Relational Coton BIO 1 7 1 0,466666667 0,466666667 0,466666667 0,466666667 1,4 0,58781092 Poly Coton 0,333333333 0,333333333 0,333333333 Coton BIO 0,333333333 0,333333333 0,333333333 Priority 0,833333333 0,166666667 SUBCRITERION 2 : Tencel Poly Coton Coton BIO Normalized Priority vector Tencel Poly Coton 1/5 1 3 0,14893617 0,157894737 0,272727273 0,19318606 0,58781092 Poly Coton 1/7 1 1/7 0,066666667 0,066666667 0,066666667 0,066666667 0,2 1 5 7 0,744680851 0,789473684 0,636363636 0,723506057 2,272591537 Priority 0,833333333 Tencel 1 7 1 0,466666667 0,466666667 0,466666667 0,466666667 1,4 0,166666667 lmax Coton BIO 0,333333333 0,486557887 Tencel Poly Coton Coton BIO Normalized Priority vector lmax 0,358870759 Innovation Poly Coton 0,333333333 0,435275835 0,35032375 SUBCRITERION 2 : Innovation 0,25 SUBCRITERION 2 : Purchasing cost SUBCRITERION 2 : Provider performance SUBCRITERION 2 : User resistance Actor A3 I. ALTERNATIVES COMPARISON CRITERION 1 : Economic SUBCRITERION 1 : LCC Tencel Poly Coton Coton BIO Normalized Priority vector lmax Tencel 1 1/5 1 0,142857143 0,142857143 0,142857143 0,142857143 0,428571429 Poly Coton 5 1 5 0,714285714 0,714285714 0,714285714 0,714285714 2,142857143 Coton BIO 1 1/5 1 0,142857143 0,142857143 0,142857143 0,142857143 0,428571429 Total 7 1 2/5 7 lmax 3 Priority vector 0,142857143 0,714285714 0,142857143 CI 0% RC 0,58 CR 0% CRITERION 2 : Environmental SUBCRITERION 1 : Fiber quality Tencel Poly Coton Coton BIO Normalized Priority vector lmax Tencel 1 5 1 0,454545455 0,625 0,4 0,493181818 1,554545455 Poly Coton 1/5 1 1/2 0,090909091 0,125 0,2 0,138636364 0,421363636 Coton BIO 1 2 1 0,454545455 0,25 0,4 0,368181818 1,138636364 Total 2 1/5 8 2 1/2 lmax 3,114545455 Priority vector 0,493181818 0,138636364 0,368181818 CI 0,057272727 RC 0,58 CR 0,098746082 CRITERION 3 : Social SUBCRITERION 1 : Provider performance Tencel Poly Coton Coton BIO Normalized Priority vector lmax Tencel 1 5 1 0,454545455 0,625 0,4 0,493181818 1,554545455 Poly Coton 1/5 1 1/2 0,090909091 0,125 0,2 0,138636364 0,421363636 Coton BIO 1 2 1 0,454545455 0,25 0,4 0,368181818 1,138636364 Total 2 1/5 8 2 1/2 lmax 3,114545455 Priority vector 0,493181818 0,138636364 0,368181818 CI 0,057272727 RC 0,58 CR 0,098746082 CRITERION 4 : Relational SUBCRITERION 1 : Brand image Tencel Poly Coton Coton BIO Normalized Priority vector lmax Tencel 1 7 1 0,466666667 0,636363636 0,428571429 0,510533911 1,600865801 Poly Coton 1/7 1 1/3 0,066666667 0,090909091 0,142857143 0,1001443 0,302851646 Coton BIO 1 3 1 0,466666667 0,272727273 0,428571429 0,389321789 1,2002886 Total 2 1/7 11 2 1/3 lmax 3,104006047 Priority vector 0,510533911 0,1001443 0,389321789 CI 0,052003023 RC 0,58 CR 0,089660385 Tencel Poly Coton Coton BIO Normalized Priority vector lmax Tencel 1 1/5 1 0,142857143 0,142857143 0,142857143 0,142857143 0,428571429 Poly Coton 5 1 5 0,714285714 0,714285714 0,714285714 0,714285714 2,142857143 Coton BIO 1 1/5 1 0,142857143 0,142857143 0,142857143 0,142857143 0,428571429 Total 7 1 2/5 7 lmax 3 Priority vector 0,142857143 0,714285714 0,142857143 CI 0% RC 0,58 CR 0% Tencel Poly Coton Coton BIO Normalized Priority vector lmax Tencel 1 5 1 0,454545455 0,625 0,4 0,493181818 1,554545455 Poly Coton 1/5 1 1/2 0,090909091 0,125 0,2 0,138636364 0,421363636 Coton BIO 1 2 1 0,454545455 0,25 0,4 0,368181818 1,138636364 Total 2 1/5 8 2 1/2 lmax 3,114545455 Priority vector 0,493181818 0,138636364 0,368181818 CI 0,057272727 RC 0,58 CR 0,098746082 Tencel Poly Coton Coton BIO Normalized Priority vector lmax Tencel 1 1/7 1 0,111111111 0,111111111 0,111111111 0,111111111 0,333333333 Poly Coton 7 1 7 0,777777778 0,777777778 0,777777778 0,777777778 2,333333333 Coton BIO 1 1/7 1 0,111111111 0,111111111 0,111111111 0,111111111 0,333333333 Total 9 1 2/7 9 lmax 3 Priority vector 0,111111111 0,777777778 0,111111111 CI 0 RC 0,58 CR 0 CRITERION 2 : Env ironmental CRITERION 3 : Social CRITERION 4 : Relational CRITERION 5 : Functional II.SUB-CRITERIA COMPARISON CRITERION 1 : Economic LCC Purchasing cost Priority vector Global priority LCC 1 1 0,5 0,038855443 Purchasing cost 1 1 0,5 0,038855443 Total 2 2 Fiber quality Provider performance Priority vector Global priority Fiber quality 1 1 0,5 0,211769126 Provider performance 1 1 0,5 0,211769126 Total 2 2 Social performance User resistance Priority vector Global priority Social performance 1 1 0,5 0,074451727 User resistance 1 1 0,5 0,074451727 Total 2 2 Brand image Innovation Priority vector Global priority Brand image 1 1 0,5 0,040885294 Innovation 1 1 0,5 0,040885294 Total 2 2 fiber quality availability Priority vector Global priority fiber quality 1 5 0,833333333 0,223397349 availability 1/5 1 0,166666667 0,04467947 Total 1 1/5 6 III.CRITERIA COMPARISON Economic Env ironmental Social Relational Functional Normalized Economic 1 1/3 1/3 1 1/5 0,07692308 0,1493 0,04 Env ironmental 3 1 5 5 2 0,23076923 0,4478 0,6 Social 3 1/5 1 1 1 0,23076923 0,0896 0,12 Relational 1 1/5 1 1 1/5 0,07692308 0,0896 0,12 Functional 5 1/2 1 5 1 0,38461538 0,2239 0,12 Total 13 2 1/4 8 1/3 13 4 2/5 priority vector 0,077710886 0,423538253 0,148903455 0,081770588 0,268076819 IV.ALTERNATIVES PRIORITIZATION Economic Env ironmental Social Relational Functional Ranking Tencel 0,142857143 0,493181818 0,302146465 0,501857864 0,15 0,34572587 Poly Coton 0,714285714 0,138636364 0,458207071 0,119390332 0,70 0,38086346 Coton BIO 0,142857143 0,368181818 0,239646465 0,378751804 0,15 0,27341067 Total 1 1 1 1 1 1 Priority vector 0,077710886 0,423538253 0,148903455 0,081770588 0,268076819 LCC PC Economic Tencel 0,142857143 0,142857143 0,142857143 Poly Coton 0,714285714 0,714285714 0,714285714 Coton BIO 0,142857143 0,142857143 0,142857143 Priority 0,5 0,5 Fiber quality Provider performance Env ironmental Tencel 0,493181818 0,493181818 0,493181818 Poly Coton 0,138636364 0,138636364 0,138636364 Coton BIO 0,368181818 0,368181818 0,368181818 Priority 0,5 0,5 Social performance User resistance Social Tencel 0,493181818 0,111111111 0,302146465 SUBCRITERION 2 : Purchasing cost SUBCRITERION 2 : Provider performance SUBCRITERION 2 : User resistance Actor A4 I. ALTERNATIVES COMPARISON CRITERION 1 : Economic SUBCRITERION 1 : LCC Tencel Poly Coton Coton BIO Normalized Priority vector lmax Tencel 1 1/7 1/2 0,1 0,111111111 0,058823529 0,089978214 0,271023965 Poly Coton 7 1 7 0,7 0,777777778 0,823529412 0,767102397 2,397385621 Coton BIO 2 1/7 1 0,2 0,111111111 0,117647059 0,14291939 0,432461874 Total 10 1 2/7 8 1/2 lmax 3,10087146 Priority vector 0,089978214 0,767102397 0,14291939 Consistency Index (CI) 0,05043573 Ra ndom Consistency (RC) 0,58 Consistency Ra tio (CR) 0,086958155 CRITERION 2 : Environmental SUBCRITERION 1 : Fiber quality Tencel Poly Coton Coton BIO Normalized Priority vector lmax Tencel 1 7 7 0,777777778 0,7 0,823529412 0,767102397 2,397385621 Poly Coton 1/7 1 1/2 0,111111111 0,1 0,058823529 0,089978214 0,271023965 Coton BIO 1/7 2 1 0,111111111 0,2 0,117647059 0,14291939 0,432461874 Total 1 2/7 10 8 1/2 lmax 3,10087146 Priority vector 0,767102397 0,089978214 0,14291939 CI 0,05043573 RC 0,58 CR 0,086958155 CRITERION 3 : Social SUBCRITERION 1 : Provider performance Tencel Poly Coton Coton BIO Normalized Priority vector lmax Tencel 1 3 1 0,428571429 0,428571429 0,428571429 0,428571429 1,285714286 Poly Coton 1/3 1 1/3 0,142857143 0,142857143 0,142857143 0,142857143 0,428571429 Coton BIO 1 3 1 0,428571429 0,428571429 0,428571429 0,428571429 1,285714286 Total 2 1/3 7 2 1/3 lmax 3 Priority vector 0,428571429 0,142857143 0,428571429 CI 0 RC 0,58 CR 0 CRITERION 4 : Relational SUBCRITERION 1 : Brand image Tencel Poly Coton Coton BIO Normalized Priority vector lmax Tencel 1 5 3 0,652173913 0,555555556 0,692307692 0,63334572 1,945621206 Poly Coton 1/5 1 1/3 0,130434783 0,111111111 0,076923077 0,106156324 0,31965812 Coton BIO 1/3 3 1 0,217391304 0,333333333 0,230769231 0,260497956 0,790082167 Total 1 1/2 9 4 1/3 lmax 3,055361493 Priority vector 0,63334572 0,106156324 0,260497956 CI 0,027680747 RC 0,58 CR 0,047725425 SUBCRITERION 2 : Innovation Tencel Poly Coton Coton BIO Normalized Priority vector lmax Tencel 1 1/4 1/3 0,125 0,157894737 0,076923077 0,119939271 0,36262933 Poly Coton 4 1 3 0,5 0,631578947 0,692307692 0,607962213 1,904014845 Coton BIO 3 1/3 1 0,375 0,210526316 0,230769231 0,272098516 0,8345704 Total 8 1 4/7 4 1/3 lmax 3,101214575 Priority vector 0,119939271 0,607962213 0,272098516 CI 0,050607287 RC 0,58 CR 0,087253944 Tencel Poly Coton Coton BIO Normalized Priority vector lmax Tencel 1 7 5 0,744680851 0,636363636 0,789473684 0,723506057 2,272591537 Poly Coton 1/7 1 1/3 0,106382979 0,090909091 0,052631579 0,083307883 0,251061244 Coton BIO 1/5 3 1 0,14893617 0,272727273 0,157894737 0,19318606 0,58781092 Total 1 1/3 11 6 1/3 lmax 3,111463701 Priority vector 0,723506057 0,083307883 0,19318606 CI 0,055731851 RC 0,58 CR 0,096089398 Tencel Poly Coton Coton BIO Normalized Priority vector lmax Tencel 1 1 1/5 0,142857143 0,2 0,130434783 0,157763975 0,475610766 Poly Coton 1 1 1/3 0,142857143 0,2 0,217391304 0,186749482 0,563008972 Coton BIO 5 3 1 0,714285714 0,6 0,652173913 0,655486542 2,004554865 Total 7 5 1 1/2 lmax 3,043174603 Priority vector 0,157763975 0,186749482 0,655486542 CI 0,021587302 RC 0,58 CR 0,037219485 CRITERION 2 : Env ironmental CRITERION 3 : Social CRITERION 4 : Relational CRITERION 5 : Functional II.SUB-CRITERIA COMPARISON CRITERION 1 : Economic LCC Purchasing cost Priority vector Global priority LCC 1 7 0,875 0,103319933 Purchasing cost 1/7 1 0,125 0,01475999 Total 1 1/7 8 Fiber quality Provider performance Priority vector Global priority Fiber quality 1 3 0,75 0,233127185 Provider performance 1/3 1 0,25 0,077709062 Total 1 1/3 4 Social performance User resistance Priority vector Global priority Social performance 1 1/5 0,166666667 0,031449967 User resistance 5 1 0,833333333 0,157249835 Total 6 1 1/5 Brand image Innovation Priority vector Global priority Brand image 1 7 0,875 0,043854308 Innovation 1/7 1 0,125 0,006264901 Total 1 1/7 8 fiber quality availability Priority vector Global priority fiber quality 1 7 0,875 0,290731716 availability 1/7 1 0,125 0,041533102 Total 1 1/7 8 III.CRITERIA COMPARISON Economic Env ironmental Social Relational Functional Normalized Economic 1 1/2 1/3 3 1/3 0,107142857 0,164835165 0,0442478 0,15789474 0,11627907 0,077 0,045455 0,385 0,454545 0,077 0,227273 0,077 0,045455 0,385 0,227273 Env ironmental 2 1 3 5 1 0,214285714 0,32967033 0,3982301 0,26315789 0,34883721 Social 3 1/3 1 5 1/3 0,321428571 0,10989011 0,1327434 0,26315789 0,11627907 Relational 1/3 1/5 1/5 1 1/5 0,035714286 0,065934066 0,0265487 0,05263158 0,06976744 Functional 3 1 3 5 1 0,321428571 0,32967033 0,3982301 0,26315789 0,34883721 Total 9 1/3 3 7 1/2 19 2 6/7 priority vector 0,118079923 0,310836247 0,188699802 0,050119209 0,332264819 IV.ALTERNATIVES PRIORITIZATION Economic Env ironmental Social Relational Functional Ranking Tencel 0,093723346 0,745304227 0,202898551 0,642032359 0,11 0,349995795 Poly Coton 0,747209874 0,086643048 0,179434092 0,107252626 0,64 0,368197069 Coton BIO 0,159066781 0,168052725 0,617667357 0,250715016 0,25 0,281807136 Total 1 1 1 1 1 1 Priority vector 0,118079923 0,310836247 0,188699802 0,050119209 0,332264819 LCC PC Economic Tencel 0,089978214 0,119939271 0,093723346 Poly Coton 0,767102397 0,607962213 0,747209874 Coton BIO 0,14291939 0,272098516 0,159066781 Priority 0,875 0,125 Fiber quality Provider performance Env ironmental Tencel 0,767102397 0,723506057 0,745304227 Poly Coton 0,089978214 0,083307883 0,086643048 Coton BIO 0,14291939 0,19318606 0,168052725 Priority 0,5 0,5 Social performance User resistance Social Tencel 0,428571429 0,157763975 0,202898551 SUBCRITERION 2 : Actor A5 II.SUB-CRITERIA COMPARISON CRITERION 1 : Economic Actor A6 I. ALTERNATIVES COMPARISON II.SUB-CRITERIA COMPARISON CRITERION 1 : Actor A7 Economic I. ALTERNATIVES COMPARISON CRITERION 1 : Economic SUBCRITERION 1 : LCC Tencel Poly Coton Coton BIO Normalized Priority vector lmax Tencel 1 1/3 1/5 0,111111111 0,076923077 0,130434783 0,106156324 LCC Purchasing cost Priority vector Global priority LCC 1 1 0,5 0,046889751 Purchasing cost 1 1 0,5 0,046889751 Total 2 2 CRITERION 1 : LCC Priority vector Global priority I. ALTERNATIVES COMPARISON Purchasing cost Economic SUBCRITERION 1 : LCC Tencel Poly Coton Coton BIO Normalized Priority vector lmax Tencel 1 5 7 0,744680851 0,789473684 0,636363636 0,723506057 2,272591537 LCC 1 7 0,875 0,078389875 Purchasing cost 1/7 1 0,125 CRITERION 1 : Economic 0,011198554 Total 1 1/7 SUBCRITERION 1 : LCC 8 Tencel Poly Coton Coton BIO Normalized Priority vector lmax 0,31965812 Poly Coton 3 1 1/3 0,333333333 0,230769231 0,217391304 0,260497956 0,790082167 Coton BIO 5 3 1 0,555555556 0,692307692 0,652173913 0,63334572 1,945621206 Total 9 4 1/3 1 1/2 lmax 3,055361493 Priority vector 0,106156324 0,260497956 0,63334572 CI CRITERION 2 : Env ironmental Fiber quality Provider performance Priority vector Global priority Fiber quality 1 5 0,833333333 0,333130587 Poly Coton 1/5 1 3 0,14893617 0,157894737 0,272727273 0,19318606 0,58781092 Coton BIO 1/7 1/3 1 0,106382979 0,052631579 0,090909091 0,083307883 0,251061244 Total 1 1/3 6 1/3 11 lmax 3,111463701 Priority vector 0,723506057 0,19318606 0,083307883 CI 0,055731851 CRITERION 2 : Tencel 1 7 3 0,677419355 0,538461538 0,714285714 0,643388869 2,008310686 Env ironmental Fiber quality Provider performance Priority vector Poly Coton 1/7 1 1/5 0,096774194 0,076923077 0,047619048 0,073772106 0,222252607 Global priority Fiber quality 1 5 0,833333333 Coton BIO 1/3 5 1 0,225806452 0,384615385 0,238095238 0,282839025 0,866162511 0,223960752 Total 1 1/2 13 4 1/5 lmax 3,096725804 0,027680747 RC Provider performance 1/5 1 0,166666667 0,066626117 RC 0,58 Provider performance 1/5 1 0,166666667 0,04479215 Priority vector 0,643388869 0,073772106 0,282839025 CI 0,048362902 0,58 CR Total 1 1/5 6 CR 0,096089398 Total 1 1/5 6 RC 0,58 0,047725425 SUBCRITERION 2 : Purchasing cost CR 0,083384313 Purchasing cost SUBCRITERION 2 : Provider performance SUBCRITERION 2 : User resistance CRITERION 2 : Tencel Poly Coton Coton BIO Normalized Priority vector CRITERION 3 : Social Tencel Poly Coton Coton BIO Normalized Priority vector lmax CRITERION 3 : Social SUBCRITERION 2 : Purchasing cost lmax Tencel 1 1 1 0,333333333 0,333333333 0,333333333 0,333333333 1 Poly Coton 1 1 1 0,333333333 0,333333333 0,333333333 0,333333333 1 Coton BIO 1 1 1 0,333333333 0,333333333 0,333333333 0,333333333 1 Total 3 3 3 lmax 3 Priority vector 0,333333333 0,333333333 0,333333333 CI 0 RC 0,58 CR 0 CRITERION 4 : Relational Social performance User resistance Priority vector Global priority Social performance 1 5 0,833333333 0,176199422 User resistance 1/5 1 0,166666667 0,035239884 Total 1 1/5 6 Brand image Innovation Priority vector Global priority CRITERION 2 : Environmental Tencel 1 1/7 1/5 0,076923077 0,096774194 0,047619048 0,073772106 0,222252607 Poly Coton 7 1 3 0,538461538 0,677419355 0,714285714 0,643388869 2,008310686 Coton BIO 5 1/3 1 0,384615385 0,225806452 0,238095238 0,282839025 0,866162511 Total 13 1 1/2 4 1/5 lmax 3,096725804 Priority vector 0,073772106 0,643388869 0,282839025 CI Social performance User resistance Priority vector Tencel Poly Coton Coton BIO Normalized Priority vector lmax Global priority Social performance 1 5 0,833333333 Tencel 1 1/5 3 0,157894737 0,14893617 0,272727273 0,19318606 0,58781092 0,40495882 User resistance 1/5 1 0,166666667 Poly Coton 5 1 7 0,789473684 0,744680851 0,636363636 0,723506057 2,272591537 0,080991764 Total 1 1/5 Coton BIO 1/3 1/7 1 0,052631579 0,106382979 0,090909091 0,083307883 0,251061244 6 Total 6 1/3 1 1/3 11 lmax 3,111463701 0,048362902 RC Priority vector 0,19318606 0,723506057 0,083307883 CI 0,055731851 0,58 CR CRITERION 4 : Relational RC 0,58 0,083384313 Brand image Innovation Priority vector Global priority CR 0,096089398 Environmental SUBCRITERION 1 : Brand image 1 1 0,5 0,090130391 SUBCRITERION 1 : Fiber quality Brand image 1 1 0,5 0,029745728 CRITERION 2 : Environmental Fiber quality Tencel Poly Coton Coton BIO Normalized Priority vector lmax Tencel 1 7 5 0,744680851 0,777777778 0,714285714 0,745581448 2,257908364 Poly Coton 1/7 1 1 0,106382979 0,111111111 0,142857143 0,120117078 0,360930188 Coton BIO 1/5 1 1 0,14893617 0,111111111 0,142857143 0,134301475 0,403534842 Total 1 1/3 9 7 lmax 3,022373394 Priority vector 0,745581448 0,120117078 0,134301475 CI 0,011186697 RC 0,58 CR 0,019287408 CRITERION 3 : Social SUBCRITERION 1 : Tencel Poly Coton Coton BIO Normalized Priority vector lmax Tencel 1 1 1 0,333333333 0,333333333 0,333333333 0,333333333 1 Poly Coton 1 1 1 0,333333333 0,333333333 0,333333333 0,333333333 1 Coton BIO 1 1 1 0,333333333 0,333333333 0,333333333 0,333333333 1 Total 3 3 3 lmax 3 Priority vector 0,333333333 0,333333333 0,333333333 CI 0 RC 0,58 CR 0 CRITERION 5 : Functional Innovation 1 1 0,5 0,090130391 Total 2 2 fiber quality availability Priority vector Global priority fiber quality 1 3 0,75 0,086072779 availability 1/3 1 0,25 0,028690926 Total 1 1/3 4 III.CRITERIA COMPARISON Economic Env ironmental Social Relational Functional Normalized Economic 1 1/5 1/5 1 1 0,07692308 0,08451 0,0384615 0,1579 0,11111 Env ironmental 5 1 2 3 3 0,38461538 0,42254 0,3846154 0,4737 0,33333 Social 5 1/2 1 1 1 0,38461538 0,21127 0,1923077 0,1579 0,11111 Relational 1 1/3 1 1 3 0,07692308 0,14085 0,1923077 0,1579 0,33333 Functional 1 1/3 1 1/3 1 0,07692308 0,14085 0,1923077 0,0526 0,11111 SUBCRITERION 2 : Tencel Poly Coton Coton BIO Normalized Priority vector lmax Tencel 1 7 7 0,777777778 0,777777778 0,777777778 0,777777778 2,333333333 Poly Coton 1/7 1 1 0,111111111 0,111111111 0,111111111 0,111111111 Innovation 1 1 0,5 SUBCRITERION 1 : Fiber quality 0,029745728 Total 2 Tencel Poly Coton Coton BIO Normalized Priority vector lmax 2 Tencel 1 9 6 0,782608696 0,692307692 0,818181818 0,764366069 2,387503801 0,333333333 Coton BIO 1/7 1 1 0,111111111 0,111111111 0,111111111 0,111111111 0,333333333 Total 1 2/7 9 9 lmax 3 Priority vector 0,777777778 0,111111111 0,111111111 CI 0 RC 0,58 CR CRITERION 5 : Poly Coton 1/9 1 1/3 0,086956522 0,076923077 0,045454545 0,069778048 0,209992906 Functional fiber quality availability Priority vector Coton BIO 1/6 3 1 0,130434783 0,230769231 0,136363636 0,165855883 0,502584372 Global priority fiber quality 1 1/3 0,25 Total 1 2/7 13 7 1/3 lmax 3,100081078 0,024054157 availability 3 1 0,75 Priority vector 0,764366069 0,069778048 0,165855883 CI 0,050040539 0,072162472 RC 0,58 0 Total 4 1 1/3 CR 0,086276792 Provider performance CRITERION 3 : Social Tencel Poly Coton Coton BIO Normalized Priority vector SUBCRITERION 2 : Provider performance lmax Tencel 1 1 1 0,333333333 0,333333333 0,333333333 0,333333333 III.CRITERIA COMPARISON Tencel Poly Coton Coton BIO Normalized Priority vector lmax 1 Poly Coton 1 1 1 0,333333333 0,333333333 0,333333333 0,333333333 Tencel 1 9 6 0,782608696 0,692307692 0,818181818 0,764366069 2,387503801 1 Coton BIO 1 1 1 0,333333333 0,333333333 0,333333333 0,333333333 1 Total 3 3 3 lmax 3 Priority vector 0,333333333 0,333333333 0,333333333 CI 0 RC 0,58 CR 0 Economic Env ironmental Social Relational Functional Poly Coton 1/9 1 1/3 0,086956522 0,076923077 0,045454545 0,069778048 0,209992906 Normalized Economic 1 1/5 1/5 3 1/2 0,075 Coton BIO 1/6 3 1 0,130434783 0,230769231 0,136363636 0,165855883 0,502584372 0,0423 0,1066 0,17647 0,04762 Env ironmental 5 1 1/3 5 3 0,375 Total 1 2/7 13 7 1/3 lmax 3,100081078 0,2113 0,17766 0,29412 0,28571 Social 5 3 1 7 5 0,375 Priority vector 0,764366069 0,069778048 0,165855883 CI 0,050040539 0,6338 0,53299 0,41176 0,47619 Relational 1/3 1/5 1/7 1 1 0,025 RC 0,58 0,0423 0,07614 0,05882 0,09524 Functional 2 1/3 1/5 1 1 0,15 0,0704 0,1066 0,05882 0,09524 CRITERION 3 : CR 0,086276792 1 1/5 1/5 1/5 3 0,06122449 0,09952607 0,0408163 0,03125 0,14286 Social Provider performance Tencel Poly Coton Coton BIO Normalized Priority vector Total 13 2 3/8 5 1/5 6 1/3 9 SUBCRITERION 1 : Provider performance Total 13 1/3 4 3/4 1 7/8 17 10 1/2 SUBCRITERION 1 : Provider performance Env ironmental 5 1 3 3 7 0,30612245 0,49763033 0,6122449 0,46875 0,33333 lmax Tencel 1 1 1 0,333333333 0,333333333 0,333333333 0,333333333 1 Poly Coton 1 1 1 0,333333333 0,333333333 0,333333333 0,333333333 1 Coton BIO 1 1 1 0,333333333 0,333333333 0,333333333 0,333333333 1 Total 3 3 3 lmax 3 Priority vector 0,333333333 0,333333333 0,333333333 CI 0 RC 0,58 CR 0 CRITERION 4 : Relational SUBCRITERION 1 : Tencel Poly Coton Coton BIO Normalized Priority vector priority vector 0,093779501 0,399756705 0,211439306 0,180260782 0,114763706 IV.ALTERNATIVES PRIORITIZATION Economic Env ironmental Social Relational Functional Ranking Tencel 0,219744828 0,539457391 0,333333333 0,723506057 0,15 0,4547156 Poly Coton 0,296915645 0,226725205 0,333333333 0,083307883 0,61 0,27454583 Coton BIO 0,483339527 0,233817404 0,333333333 0,19318606 0,23 0,27073858 SUBCRITERION 2 : User resistance Tencel Poly Coton Coton BIO Normalized Priority vector lmax Tencel 1 1 1 0,333333333 0,333333333 0,333333333 0,333333333 priority vector 0,089588428 0,268752903 0,485950585 0,059491456 0,096216629 Tencel Poly Coton Coton BIO Normalized Priority vector lmax Social 5 1/3 1 2 5 0,30612245 0,16587678 0,2040816 0,3125 0,2381 1 Poly Coton 1 1 1 0,333333333 0,333333333 0,333333333 0,333333333 1 Coton BIO 1 1 1 0,333333333 0,333333333 0,333333333 0,333333333 1 Total 3 3 3 lmax 3 Priority vector 0,333333333 0,333333333 0,333333333 CI 0 RC 0,58 CR 0 IV.ALTERNATIVES PRIORITIZATION Economic Env ironmental Social Relational Functional Tencel 1 1 7 0,466666667 0,428571429 0,636363636 0,510533911 1,600865801 Poly Coton 1 1 3 0,466666667 0,428571429 0,272727273 0,389321789 Relational 5 1/3 1/2 1 5 0,30612245 0,16587678 0,1020408 0,15625 0,2381 1,2002886 Coton BIO 1/7 1/3 1 0,066666667 0,142857143 0,090909091 0,1001443 Functional 1/3 1/7 1/5 1/5 1 0,02040816 0,07109005 0,0408163 0,03125 0,04762 0,302851646 Total 2 1/7 2 1/3 11 lmax 3,104006047 Total 16 1/3 2 5 6 2/5 21 Ranking Tencel 0,642289313 0,555555556 0,290805491 0,723506057 0,44 Priority vector 0,510533911 0,389321789 0,1001443 CI 0,052003023 priority vector 0,075134805 0,443616202 0,245335219 0,193677056 0,042236717 0,4339713 Poly Coton 0,249461411 0,222222222 0,35032375 0,19318606 0,28 RC 0,58 0,2905315 Coton BIO 0,108249276 0,222222222 0,358870759 0,083307883 0,28 0,2754972 SUBCRITERION 2 : CR 0,089660385 IV. ALTERNATIVES PRIORITIZATION User resistance lmax Tencel 1 1 1 0,333333333 0,333333333 0,333333333 0,333333333 Total 1 1 1 1 1 1 Tencel Poly Coton Coton BIO Normalized Priority vector lmax Total 1 1 1 1 1 1 Tencel Poly Coton Coton BIO Normalized Priority vector lmax 1 Poly Coton 1 1 1 0,333333333 0,333333333 0,333333333 0,333333333 1 Coton BIO 1 1 1 0,333333333 0,333333333 0,333333333 0,333333333 1 Total 3 3 3 lmax 3 Priority vector 0,333333333 0,333333333 0,333333333 CI 0 RC 0,58 CR 0 Priority vector 0,093779501 0,399756705 0,211439306 0,180260782 0,114763706 LCC PC Economic Tencel 0,106156324 0,333333333 0,219744828 Poly Coton 0,260497956 0,333333333 0,296915645 Coton BIO 0,63334572 0,333333333 0,483339527 Priority 0,5 0,5 CRITERION 4 : Relational Tencel 1 1/5 1/7 0,076923077 0,090909091 0,066666667 0,078166278 0,234729715 Poly Coton 5 1 1 0,384615385 0,454545455 0,466666667 0,435275835 Priority vector 0,089588428 0,268752903 0,485950585 0,059491456 0,096216629 Tencel 1 1 1/3 0,2 0,25 0,181818182 0,210606061 Economic Env ironmental Social Relational Functional Ranking 0,634343434 1,312665113 Coton BIO 7 1 1 0,538461538 0,454545455 0,466666667 0,486557887 Poly Coton 1 1 1/2 0,2 0,25 0,272727273 0,240909091 0,725757576 Tencel 0,587113518 0,764366069 0,260594036 0,487014104 0,31 0,55435985 1,468997669 Total 13 2 1/5 2 1/7 lmax 3,016392496 Priority vector 0,078166278 0,435275835 0,486557887 CI 0,008196248 RC 0,58 CR 0,014131462 LCC PC Economic Tencel 0,723506057 0,073772106 0,642289313 Poly Coton 0,19318606 0,643388869 0,249461411 Coton BIO 0,083307883 0,282839025 Coton BIO 3 2 1 0,6 0,5 0,545454545 0,548484848 1,662121212 Total 5 4 1 5/6 lmax Poly Coton 0,15498885 0,069778048 0,265644541 0,060285518 0,39 0,135873 3,022222222 Priority vector 0,210606061 0,240909091 0,548484848 CI Coton BIO 0,257897632 0,165855883 0,473761424 0,452700378 0,31 0,30976715 0,011111111 RC 0,58 Total 1 1 1 1 1 1 0,108249276 Priority 0,875 CR 0,019157088 Priority vector 0,075134805 0,443616202 0,245335219 0,193677056 0,042236717 0,125 CRITERION 4 : Relational Brand image Tencel Poly Coton Coton BIO Normalized Priority vector lmax Tencel 1 7 5 0,744680851 0,636363636 0,789473684 0,723506057 2,272591537 Poly Coton 1/7 1 1/3 0,106382979 0,090909091 0,052631579 0,083307883 0,251061244 Coton BIO 1/5 3 1 0,14893617 0,272727273 0,157894737 0,19318606 Fiber quality Provider performance Env ironmental Tencel 0,745581448 0,333333333 0,539457391 Poly Coton 0,120117078 0,333333333 0,226725205 SUBCRITERION 1 : Brand image Tencel Poly Coton Coton BIO Normalized Priority vector lmax Tencel 1 5 7 0,744680851 0,789473684 0,636363636 0,723506057 2,272591537 Poly Coton 1/5 1 3 0,14893617 0,157894737 0,272727273 0,19318606 0,58781092 Fiber quality Provider performance Env ironmental Tencel 0,777777778 0,333333333 0,555555556 Poly Coton 0,111111111 0,333333333 0,222222222 SUBCRITERION 1 : Brand image Tencel Poly Coton Coton BIO Normalized Priority vector Economic lmax Tencel 1 9 1 0,473684211 0,529411765 0,466666667 0,489920881 Tencel 0,643388869 0,19318606 0,587113518 1,4749914 Poly Coton 1/9 1 1/7 0,052631579 0,058823529 0,066666667 0,059373925 0,178196035 Poly Coton 0,073772106 0,723506057 0,15498885 0,58781092 Total 1 1/3 11 6 1/3 lmax Coton BIO 0,134301475 0,333333333 0,233817404 Coton BIO 1/7 1/3 1 0,106382979 0,052631579 0,090909091 0,083307883 0,251061244 Coton BIO 0,111111111 0,333333333 0,222222222 Coton BIO 1 7 1 0,473684211 0,411764706 0,466666667 0,450705194 1,35624355 Coton BIO 0,282839025 0,083307883 0,257897632 3,111463701 Priority vector 0,723506057 0,083307883 0,19318606 CI 0,055731851 RC CR 0,096089398 Social performance User resistance Social Tencel 0,333333333 0,333333333 0,333333333 RC 0,58 CR 0,096089398 Social performance User resistance Tencel 0,333333333 0,078166278 0,290805491 CR 0,008130159 Social RC 0,58 0,58 Priority 0,5 0,5 Total 1 1/3 6 1/3 11 lmax 3,111463701 Priority vector 0,723506057 0,19318606 0,083307883 CI 0,055731851 Priority 0,5 0,5 Total 2 1/9 17 2 1/7 lmax 3,009430985 Priority vector 0,489920881 0,059373925 0,450705194 CI 0,004715492 Priority 0,875 0,

LCC

PC

LCC

PC

125 Fiber quality Provider performance Env ironmental

	Actor A8 II. SUB-CRITERIA COMPARISON Actor A9
	I. ALTERNATIVES COMPARISON CRITERION 1 : I. ALTERNATIVES COMPARISON Economic LCC		Purchasing cost		Priority vector	Global priority
	CRITERION 1 : LCC CRITERION 1 :		Economic 1 Economic				7				0,875	0,063661639
	SUBCRITERION 1 : Purchasing cost SUBCRITERION 1 : Tencel Total Poly Coton Tencel Coton BIO Total Priority vector CRITERION 2 : Poly Coton Coton BIO Fiber quality Total Provider performance Priority vector Total		LCC Tencel LCC 1/7 1 1 1/7 Tencel 5 1 3 9 0,106156324 1/5 Env ironmental Fiber quality 1/3 1 1 1/2 1 0,63334572 2	Poly Coton 1/5 Poly Coton 1 5 1/3 1 1/2 0,63334572 1 Provider performance 1 8 0,260497956 Coton BIO 1/3 Coton BIO 0,125 3 3 1 4 1/3 1/3 Priority vector 3 1 1 0,5 9 4 1/3 1 0,5 0,106156324 0,260497956 2	Normalized 0,00909452 0,111111111 0,130434783 0,076923077 Normalized 0,555555556 0,652173913 0,692307692 0,652173913 0,555555556 2/3 0,333333333 0,217391304 0,230769231 0,130434783 0,111111111 0,07692308 Priority vector 0,106156324 Priority vector 0,63334572 0,63334572 1,945621206 lmax lmax 0,31965812 1,945621206 0,260497956 0,790082167 lmax 3,055361493 CI 0,027680747 RC 0,58 CR 0,106156324 0,31965812 0,217391304 0,333333333 0,23076923 0,260497956 0,790082167 Global priority lmax 3,055361493 0,168428356 CI 0,027680747 0,168428356 RC 0,58 0,047725425 CR 0,047725425
	CRITERION 2 : Tencel CRITERION 3 : Poly Coton Coton BIO Total Priority vector Tencel Social performance Poly Coton User resistance Coton BIO Total Total Priority vector CRITERION 4 :		Environmental Tencel 1 Social Tencel 7 3 11 0,08820212 Social performance 1 1 1/5 1/7 1/3 1 1/7 1 1/2 0,63334572 Relational	Poly Coton 1/7 Poly Coton 1 1/3 1 1/2 0,668696895 User resistance 5 7 1 1 3 9 8 0,106156324	Coton BIO 1/3 Coton BIO 3 1 4 1/3 0,243100985 Priority vector 3 0,875 1/3 0,125 1 4 1/3 0,260497956	Normalized 0,096774194 0,076923077 Normalized 0,677419355 0,692307692 0,225806452 0,230769231 0,652173913 0,090909091 0,636363636 0,272727273 0,555555556 0,69230769 Priority vector 0,08820212 Priority vector 0,668696895 0,243100985 lmax CI RC 0,63334572 Global priority 0,130434783 0,111111111 0,07692308 0,106156324 0,26476391 lmax lmax 2,015414693 0,730606311 3,010784914 0,005392457 1,945621206 0,31965812 0,194096028 0,217391304 0,333333333 0,23076923 0,260497956 0,790082167 0,027728004 lmax 3,055361493 CI 0,027680747 0,58 CR RC 0,58 0,00929734 CR 0,047725425
	SUBCRITERION 1 : CRITERION 2 :		Fiber quality Brand image Environmental			Innovation		Priority vector	Global priority
	Brand image SUBCRITERION 1 :		Tencel 1 Fibre quality	Poly Coton		5		Coton BIO	0,833333333	Normalized 0,181890397	Priority vector	lmax
	Tencel Poly Coton Coton BIO Innovation Total Tencel Poly Coton		1 1/5 1/3 Tencel 1/5 1 1/5 1 1/5	5 1 3	Poly Coton 5 1	1 6		3 1/3 1 Coton BIO 0,166666667 2 1/5	0,652173913 0,130434783 0,217391304 0,036378079 0,555555556 0,692307692 0,111111111 0,076923077 0,333333333 0,230769231 Normalized 0,588235294 0,454545455 0,625 0,117647059 0,090909091 0,0625	0,63334572 0,106156324 0,260497956 Priority vector 0,555926916 1,945621206 0,31965812 0,790082167 lmax 1,715129234 0,09035205 0,27228164
	Total Coton BIO		1 1/2 1/2	9	5				4 1/3	1	0,294117647	0,454545455	0,3125	lmax 0,353721034 3,055361493 1,083444742
	Priority vector CRITERION 5 : Total		0,63334572 Functional 1 2/3	0,106156324 11			0,260497956 3 1/5	CI	lmax	0,027680747 3,070855615
	Priority vector		fiber quality 0,555926916		availability 0,09035205	Priority vector 0,353721034	Global priority	RC	CI	0,58 0,035427807
	fiber quality		1				3				0,75	0,112720965	CR	RC	0,047725425 0,58
	SUBCRITERION 2 : Tencel availability Total SUBCRITERION 2 :	Provider performance Tencel 1 1/3 1 1/3 Provider performance Tencel	Poly Coton 3 Poly Coton	1 4		Coton BIO 1 Coton BIO 0,25	Normalized 0,272727273 0,466666667 0,037573655 0,428571429 Normalized	Priority vector 0,389321789 CR Priority vector	lmax 1,2002886 0,061082427 lmax
	SUBCRITERION 2 : Poly Coton Coton BIO Tencel III. CRITERIA COMPARISON User resistance 1/3 1 1 Poly Coton 1 Total 2 1/3 Priority vector 0,389321789 Coton BIO 1 Economic Total 3 Economic 1 Priority vector 0,333333333 1 CRITERION 3 : Social SUBCRITERION 1 : Provider performance Tencel Tencel 1 Poly Coton 1/5 Env ironmental 3 Social 3 Relational 3 Functional 3 Total 13 priority vector 0,072756159 CRITERION 3 : Env ironmental 3 Social 3 Social SUBCRITERION 1 : Relational 1/3 Provider performance Tencel Functional 1/3 1 Total 7 2/3 Tencel Poly Coton 1 priority vector 0,174749763 Poly Coton 1 7 1 1 11 0,1001443 1 Env ironmental 3 1/3 0,333333333 5 1 1 1/3 1 1/3 3 0,336856712 1 1/3 0,510533911 1/7 1 1 1 2 1/7 1 3 0,333333333 Social 1/3 Coton BIO 1 1/7 3 1 1 1/3 5 2/3 0,221824032 1 1/3 Poly Coton Coton BIO 1/3 1 1 3 1 1 0,315812565 0,315812565 0,142857143 0,428571429 0,333333333 0,090909091 0,066666667 0,636363636 0,466666667 0,333333333 0,33333333 0,510533911 0,1001443 0,333333333 0,302851646 1,600865801 0,333333333 0,333333333 0,33333333 0,333333333 lmax 3,104006047 CI 0,333333333 0,333333333 0,33333333 0,333333333 0,052003023 RC Relational Functional Normalized lmax 0,58 CR 1/3 1/3 0,07692308 0,11111 0,059 0,076923 1 1 1 3 CI 0 1/3 3 3 0,13 0,11 0,11 0,29 0,23 0,04 0,089660385 Normalized Priority vector lmax 0,454545455 0,384615385 0,466666667 0,435275835 1,312665113 0,090909091 0,076923077 0,066666667 0,078166278 1 3 0,23076923 0,33333 0,529 0,230769 0,36 1 3 0,23076923 0,11111 0,176 0,230769 0,36 1 1 0,23076923 0,33333 0,176 0,230769 0,12 1 1 0,23076923 0,11111 0,059 0,230769 0,12 4 1/3 8 1/3 0,218268477 0,15029462 RC 0,58 CR 1 3 3 0,39 0,33 0,33 0,29 0,23 0 1 3 3 0,39 0,33 0,33 0,29 0,23 1/3 1 3 0,04 0,11 0,11 0,10 0,23 Normalized Priority vector 1/3 1/3 1 0,04 0,11 0,11 0,03 0,08 lmax 0,333333333 0,333333333 0,33333333 0,333333333 1 3 10 1/3 13 0,333333333 0,333333333 0,33333333 0,333333333 1 0,118648781 0,074976325 0,234729715 Coton BIO 1 7 1 0,454545455 0,538461538 0,466666667 0,486557887 Coton BIO 1 1 1 0,333333333 0,333333333 0,33333333 0,333333333 1 1,468997669 Total 2 1/5 13 2 1/7 lmax IV. ALTERNATIVES PRIORITIZA TION Total 3 3 3 lmax 3 3,016392496 Priority vector 0,435275835 0,078166278 0,486557887 CI 0,008196248 RC 0,58 CR 0,014131462 Tencel Poly Coton Coton BIO Normalized Priority vector lmax Tencel 1 1/3 0,2 0,142857143 0,217391304 0,186749482 0,563008972 Economic Env ironmental Social Relational Functional Priority vector 0,333333333 0,333333333 0,333333333 CI 0 RC IV.ALTERNATIVES PRIORITIZATION 0,58 Ranking Tencel 0,103912048 0,511333755 0,404210041 0,257566573 0,21 0,3568328 Poly Coton 0,637764617 0,103150312 0,08811599 0,071823245 0,57 0,20199403 Coton BIO 0,258323335 0,385515933 0,507673969 0,670610182 0,22 0,44117317 SUBCRITERION 2 : CR 0 Economic Env ironmental Social Relational Functional Ranking User resistance Tencel Poly Coton Coton BIO Normalized Priority vector Tencel 0,63334572 0,444630125 0,333333333 0,417027417 0,29 0,4275269 lmax Tencel 1 1 1 0,333333333 0,333333333 0,33333333 0,333333333 1 Poly Coton 0,106156324 0,211842692 0,333333333 0,128908129 0,60 0,2513521 1 Poly Coton 1 1 1/5 0,2 0,142857143 0,130434783 0,157763975 0,475610766 Total 1 1 1 1 1 1 Poly Coton 1 1 1 0,333333333 0,333333333 0,33333333 0,333333333 1 Coton BIO 0,260497956 0,343527184 0,333333333 0,454064454 0,11 0,321121
	CRITERION 4 : SUBCRITERION 1 : Coton BIO Total Priority vector Priority vector Coton BIO Total Total Priority vector Priority vector Tencel Poly Coton Coton BIO CRITERION 4 : Tencel SUBCRITERION 1 : Poly Coton	Relational Brand image 3 5 0,186749482 0,072756159 LCC 1 3 0,333333333 0,174749763 0,157763975 5 7 0,336856712 PC 1 3 1 0,333333333 0,315812565 1 1 1/2 0,655486542 0,221824032 1 3 1 0,333333333 0,315812565 0,6 0,218268477 0,714285714 0,652173913 0,15029462 0,333333333 0,333333333 0,33333333 0,655486542 lmax CI RC CR 0,333333333 2,004554865 3,043174603 0,021587302 0,58 0,037219485 lmax 1 1 1 1 CI 0,118648781 0,074976325 Economic 0,106156324 0,08820212 0,103912048 0,63334572 0,668696895 0,637764617 0,260497956 0,243100985 0,258323335 RC 0,58 1 3 0 CR Economic 0 0,63334572 0,63334572 0,63334572 Relational Brand image 0,106156324 0,106156324 0,106156324
	Priority Coton BIO		Tencel 0,875 Tencel 0,260497956 Poly Coton Poly Coton 0,125	Coton BIO Coton BIO 0,260497956	0,260497956	Normalized Normalized	Priority vector Priority vector	lmax	lmax
	Tencel Tencel Coton BIO Total Priority vector Tencel Poly Coton Coton BIO Priority Priority vector Total Coton BIO Poly Coton Poly Coton Tencel Priority		0,764366069 1 1/3 5 6 1/3 0,180402113 0,63334572 0,106156324 0,260497956 0,5 0,405483405 2 1/3 1 Fiber quality 1/3 1 0,75	0,764366069 0,071433473 3 1 9 13 0,389321789 0,1001443 0,510533911 0,5 0,114959115 9 5 Provider performance 0,748164414 0,764366069 1/5 1/9 1 1 1/3 0,385515933 0,47955748 0,103150312 2 1/5 0,511333755 1 Env ironmental 1 1/5 3 1 0,	0,157894737 0,052631579 0,789473684 0,428571429 0,230769231 0,152542373 0,076923077 0,084745763 0,692307692 0,762711864 0,555555556 0,45454545 0,180402113 0,071433473 0,748164414 lmax CI RC CR CR RC CI lmax 0,47955748 0,544335415 0,21469689 3,052108542 0,026054271 0,58 0,044921157 0,030850376 0,58 0,017893218 3,035786436 1,45983646 2,293076237 0,142857143 0,111111111 0,09090909 0,114959115 0,346031746 0,428571429 0,333333333 0,45454545 0,405483405 1,22991823
	Poly Coton Coton BIO SUBCRITERION 2 : SUBCRITERION 2 : Priority Tencel Poly Coton Coton BIO CRITERION 5 : Tencel Tencel Poly Coton Poly Coton Tencel Coton BIO Total Priority vector Coton BIO Poly Coton Priority Coton BIO Total Priority vector Tencel		0,069778048 0,165855883 Innovation Tencel Soci a l perfo r m a n c e Innovation 0,5 Social performance 0,510533911 0,389321789 0,1001443 Functional 1 0,435275835 Tencel 1/7 0,078166278 1 1/3 1 1/2 0,643388869 0,486557887 1/3 0,875 1 2 1/3 0,428571429 Brand image 0,180402113	0,069778048 0,165855883 Poly Coton User resistance 0,5 User resistance 0,210606061 0,240909091 0,548484848 7 0,186749482 Poly Coton 1 0,157763975 3 5 13 0,073772106 0,655486542 1 3 0,125 7 0,142857143 Innov ation 0,643388869	0,069778048 Coton BIO Social 0,165855883 Social 0,260594036 0,265644541 0,473761424 3 0,404210041 Coton BIO 1/5 0,08811599 1 1 4 1/5 0,282839025 1/3 0,507673969 1 2 1/3 0,428571429 Relational 0,257566573	Normalized 0,538461538 0,714285714 Normalized 0,076923077 0,047619048 0,428571429 0,677419355 0,096774194 0,428571429 0,42857143 Priority vector 0,643388869 Priority vector 0,073772106 0,428571429 2,008310686 lmax lmax 1,285714286 0,222252607 0,225806452 0,384615385 0,238095238 0,282839025 0,866162511 lmax 3,096725804 CI 0,142857143 0,142857143 0,14285714 0,142857143 0,428571429 0,428571429 0,428571429 0,42857143 0,428571429 1,285714286 lmax 3 0,048362902 RC CI 0 0,58 CR RC 0,58 0,083384313 CR 0
	Priority SUBCRITERION 1 : Poly Coton CRITERION 5 :		0,166666667 fiber quality 0,071433473 Functional		0,833333333 0,073772106			0,071823245
	Coton BIO SUBCRITERION 1 :		Tencel 0,748164414 Fibre quality	Poly Coton 0,282839025	Coton BIO	0,670610182	Normalized	Priority vector	lmax
	Tencel Tencel Poly Coton Priority Tencel Poly Coton Coton BIO Coton BIO Total Poly Coton Coton BIO Priority vector Tencel Total Priority Poly Coton Priority vector Coton BIO		Brand image 0,489920881 1 2 0,833333333 Tencel 1 0,059373925 0,450705194 1 4 fiber quality 1 1 0,240909091 0,240909091 3 0,875 0,548484848 0,333333333 0,210606061	Innov ation 0,466666667 1/2 1 Poly Coton 0,166666667 1 0,066666667 0,466666667 1/3 1 5/6 av ailability 1 1 0,548484848 0,11 3 0,63 0,333333333 0,125 0,26	Relational 1 3 Coton BIO 1 0,487014104 0,060285518 1 5 1 Functional 1 0,210606061 0,207220899 3 0,452700378 0,569700066 0,333333333 0,223079034	0,25 0,5 0,333333333 0,272727273 0,545454545 Normalized 0,333333333 0,33333333 0,2 0,240909091 0,6 0,548484848 Priority vector 0,333333333 0,725757576 1,662121212 lmax 1 0,25 0,181818182 0,2 0,210606061 0,634343434 lmax 0,333333333 0,333333333 0,33333333 0,333333333 1 0,333333333 0,333333333 0,33333333 0,333333333 1 3,022222222 CI 0,011111111 lmax 3 RC 0,58 CI 0 CR 0,019157088 RC 0,58
	SUBCRITERION 2 : Priority		fiber quality availability Tencel 0,75	av ailability Poly Coton 0,25		Functional Coton BIO	Normalized	Priority vector CR	lmax	0
	Tencel Tencel SUBCRITERION 2 :		0,333333333 1 availability	1/5	0,11		0,305555556 1/3	0,111111111	0,130434783 0,076923077	0,106156324	0,31965812
	Poly Coton Poly Coton Coton BIO Priority Coton BIO Total Tencel Poly Coton Priority vector Coton BIO		0,333333333 5 Tencel 0,333333333 0,875 3 9 1 3 0,106156324 1/5	0,78 Poly Coton 0,11 1/3 1 1 1/2 1/3 1 0,125 0,63334572 1/7		3 0,388888889 Coton BIO 0,305555556 1 4 1/3 5 7 0,260497956 1	0,555555556 0,333333333 0,238095238 0,652173913 0,692307692 Normalized 0,217391304 0,230769231 0,225806452 0,38461538 0,63334572 Priority vector 0,260497956 lmax 0,282839025 1,945621206 lmax 0,790082167 0,866162511 3,055361493 0,714285714 0,677419355 0,53846154 0,643388869 2,008310686 CI 0,027680747 0,047619048 0,096774194 0,07692308 0,073772106 0,222252607
	Total		4 1/5		1 1/2				13	RC	lmax	0,58 3,096725804
	Priority vector		0,282839025	0,643388869		0,073772106	CI	0,048362902
											RC	0,58
											CR	0,083384313

LCC

PC

25 Fibre quality Provider performance Env ironmental

	II.SUB-CRITERIA COMPARISON II.SUB-CRITERIA COMPARISON Actor A1 I. ALTERNATIVES COMPARISON CRITERION 1 : Economic Carbon footprint Chemical use Carbon footprint 1 1 CRITERION 2 : Environmental I. ALTERNATIVES COMPARISON Carbon footprint Chemical use Chemical use 1 1 Carbon footprint 1 1 Total 2 CRITERION 1 : Economic Chemical use 1 1 2 SUBCRITERION 1 : Purchasing cost Total 2 2	Priority vector 0,5 Priority vector 0,5 0,5 0,5	Global priority Global priority 0,243417326 0,10318934 0,243417326 0,10318934
	Tencel Poly Coton Coton BIO Priority Tencel Poly Coton Coton BIO Priority Tencel Poly Coton Coton BIO Priority Tencel Poly Coton Coton BIO Priority SUBCRITERION 2 : SUBCRITERION 2 : SUBCRITERION 3 : SUBCRITERION 2 : SUBCRITERION 2 : SUBCRITERION 3 : SUBCRITERION 1 : LC LL Total CRITERION 2 : SUBCRITERION 1 : LC LL Total LC LL Total CRITERION 3 : SUBCRITERION 1 : LC LL Total LC LL Total LC LL Total CRITERION 4 : SUBCRITERION 1 : LC LL Total LC LL Total CRITERION 5 : SUBCRITERION 1 : LC LL Total LC LL Total LC LL Total Social Soci a l perfo r m a n c e 0,555926916 0,09035205 0,353721034 0,5 0,333333333 0,333333333 0,333333333 0,166666667 Brand image 0,405483405 0,114959115 0,47955748 0,5 Fibre quality 0,333333333 0,333333333 0,333333333 0,125 Chemical use User resistance SAP purchasing Innovation Confort Traceability Purchasing cost LC 1 1/5 1 1/5 Environmental Carbon footprint LC 1 5 6 LC 1 3 4 Social Local job LC 1 7 8 LC 1 5 6 LC 1 5 6 Relational Brand image LC 1 5 6 LC 1 1/5 1 1/5 Functional Lifespan LC 1 1 2 LC 1 1 2 LC 1 1/3 CRITERION 4 : Relational CRITERION 5 : Functional Local job User resistance Local job 1 5 User resistance 1/5 1 SAP purchasing 1 5 Total 2 1/5 11 Priority vector 4/9 0 Brand image Innovation Brand image 1 1/3 Innovation 3 1 Total 4 1 1/3 Lifespan Confort Lifespan 1 1/3 Confort 3 1 Traceability 1/3 1/5 Total 4 1/3 1 1/2 Priority vector 1/4 5/8 III.CRITERIA COMPARISON Economic Environmental Economic 1 1/5 Environmental 5 1 Social 3 1/3 Relational 1 1/5 Functional 1/5 1/7 Total 10 1/5 1 7/8 priority vector 0,117712374 0,486834653 IV.ALTERNATIVES PRIORITIZATION Economic Environmental LC 0,833333333 0,208333333 LL 0,166666667 0,791666667 Total 1 1 Priority vector 0,117712374 0,486834653 Carbon footprint Chemical use Local job User resistance LC 0,125 0,166666667 LL 0,875 0,833333333 Priority 0,454545455 0,090909091 Brand image Innovation LC 0,166666667 0,833333333 LL 0,833333333 0,166666667 Priority 0,25 0,75 Lifespan Confort LC 0,5 0,50 LL 0,5 0,50 Priority 0,260497956 0,63334572 SUBCRITERION 2 : Chemical use SUBCRITERION 2 : User resistance SUBCRITERION 2 : Innovation SUBCRITERION 2 : Confort SUBCRITERION 3 : Traceability LC LC 1 LL 5 Total 6 CRITERION 2 : Environmental SUBCRITERION 1 : Carbon footprint LC LC 1 LL 3 Total 4 LC LC 1 LL 3 Total 4 CRITERION 3 : Social SUBCRITERION 1 : Local job LC LC 1 LL 5 Total 6 LC LC 1 LL 5 Total 6 LC 1 LL 3 Total 4 CRITERION 4 : Relational SUBCRITERION 1 : Brand image LC LC 1 LL 3 Total 4 LC LC 1 LL 5 Total 6 CRITERION 5 : Functional SUBCRITERION 1 : Lifespan LC LC 1 LL 5 Total 6 LC LC 1 LL 5 Total 6 LC LC 1 LL 5 CRITERION 3 : Social CRITERION 4 : Relational CRITERION 5 : Functional Local job User resistance Local job 1 1/3 User resistance 3 1 SA P purchasing 1 5 Total 5 6 1/3 Priority vector 1/4 2/7 Brand image Innovation Brand image 1 1 Innovation 1 1 Total 2 2 Lifespan Confort Lifespan 1 1/3 Confort 3 1 Traceability 3 2 Total 7 3 1/3 Priority vector 1/7 1/3 III.CRITERIA COMPARISON Economic Environmental Economic 1 1/7 Environmental 7 1 Social 7 3 Relational 3 1 Functional 5 1 Total 23 6 1/7 priority vector 0,046474418 0,206378681 IV.ALTERNATIVES PRIORITIZATION Economic Environmental LC 0,166666667 0,25 1 1/3 CRITERION 3 : LC 0,166666667 0,25 LL 0,833333333 0,75 Priority 0,5 SUBCRITERION 3 : LL 0,833333333 0,75 SAP purchasing Total 1 1 0,5 LC Priority vector 0,046474418 0,206378681	0,333333333 0,333333333 0,333333333 0,5 User resistance 0,333333333 0,333333333 0,333333333 0,833333333 Innov ation 0,428571429 0,142857143 0,428571429 0,5 av ailability 0,28 0,64 0,07 0,875 SAP purchasing 1 1/5 1 2 1/5 4/9 Priority vector 0,25 0,75 Traceability 3 5 1 9 1/9 Social 1/3 3 1 1/3 1/5 4 7/8 0,237754205 Social 0,147727273 0,852272727 1 0,237754205 Environmental SAP purchasing 0,166666667 0,833333333 0,454545455 Relational 0,666666667 0,333333333 Traceability 0,75 0,25 0,106156324 SA P purchasing LL 5 1 6 LL 1/5 1 1 1/5 LL 1/3 1 1 1/3 LL 1/7 1 1 1/7 LL 1/5 1 1 1/5 LL 1/5 1 1 1/5 LL 1/5 1 1 1/5 LL 5 1 6 LL 1 1 2 LL 1 1 2 LL 3 1 0,454545455 0,444630125 0,211842692 0,343527184 Social 0,333333333 0,333333333 0,333333333 Relational 0,417027417 0,128908129 0,454064454 Functional 0,289150813 0,604631927 0,106217259 Priority vector 0,833333333 0,166666667 Priority vector 0,166666667 0,833333333 Priority vector 0,25 0,75 Priority vector 0,125 0,875 Priority vector 0,166666667 0,833333333 Priority vector 0,166666667 0,833333333 Priority vector 0,166666667 0,833333333 Priority vector 0,833333333 0,166666667 Priority vector 0,5 0,5 Priority vector 0,5 0,5 Priority vector 0,75 0,25 Normalized 0,454545455 0,454545455 0,090909091 0,090909091 0,090909091 0,454545455 0,454545455 0,454545455 Global priority 0,029428094 0,088284281 Normalized 0,230769231 0,217391304 0,333333333 0,692307692 0,652173913 0,555555556 0,076923077 0,130434783 0,111111111 Relational Functional 1 5 0,098039216 5 7 0,490196078 3 5 0,294117647 1 5 0,098039216 1/5 1 0,019607843 10 1/5 23 0,117712374 0,039986394 Relational Functional Ranking 0,666666667 0,53 0,334169627 0,333333333 0,47 0,665830373 1 1 1 0,117712374 0,039986394 Social 0,147727273 0,852272727 Functional 0,526539081 0,473460919 LL Priority vector 1/5 0,166666667 1 0,833333333 1 1/5 LL Priority vector 1/3 0,25 1 0,75 1 1/3 LL Priority vector 1/3 0,25 1 0,75 1 1/3 LL Priority vector 1/5 0,166666667 1 0,833333333 1 1/5 LL Priority vector 1/5 0,166666667 1 0,833333333 1 1/5 1/3 0,25 1 0,75 1 1/3 LL Priority vector 1/3 0,25 1 0,75 1 1/3 LL Priority vector 1/5 0,166666667 1 0,833333333 1 1/5 LL Priority vector 1/5 0,166666667 1 0,833333333 1 1/5 LL Priority vector 1/5 0,166666667 1 0,833333333 1 1/5 LL Priority vector 1/5 0,166666667 1 0,833333333 Normalized 1 0,2 0,052631579 0,454545455 1/5 0,6 0,157894737 0,090909091 1 0,2 0,789473684 0,454545455 2 1/5 1/2 Priority vector Global priority 0,5 0,104976118 0,5 0,104976118 Traceability Normalized 1/3 0,142857143 0,1 0,181818182 1/2 0,428571429 0,3 0,272727273 1 0,428571429 0,6 0,545454545 1 5/6 1/2 Social Relational Functional 1/7 1/3 1/5 0,043478261 1/3 1 1 0,304347826 1 1 1 0,304347826 1 1 1 0,130434783 1 1 1 0,217391304 3 1/2 4 1/3 4 1/5 0,309851124 0,209952236 0,227343541 Social Relational Functional Ranking 0,206778309 0,208333333 0,17 0,205041538 0,208333333 0,791666667 0,793221691 0,791666667 0,83 0,794958462 1 1 1 1 LL Priority vector 0,309851124 0,209952236 0	Priority vector 0,454545455 0,090909091 0,454545455 Priority vector 0,260497956 0,63334572 0,106156324 0,106598985 0,532994924 0,177664975 0,106598985 0,076142132 Priority vector 0,235725678 Normalized Global priority 0,108070093 0,021614019 0,108070093 lmax CI RC CR Global priority 0,010416374 0,025325211 0,004244809 lmax CI RC CR 0,068493151 0,616438356 0,205479452 0,068493151 0,04109589 Global priority 1,36363636 lmax 0,27272727 1,36363636 3 0 0,58 0 lmax 0,79008217 1,94562121 0,31965812 3,05536149 0,02768075 0,58 0,04772543 0,09803922 0,2173913 0,49019608 0,3043478 0,29411765 0,2173913 0,09803922 0,2173913 0,01960784 0,0434783 lmax 0,073039866 0,811376927 0,282934609 0,087667607 1,086379585 0,481339713 0,149143651 2,131738437 lmax 4,029494949 CI 0,514747475 RC 0,58 CR 0,887495646 Priority vector Global priority lmax 0,141558442 0,032182397 0,427705628 0,333766234 0,075879597 1,020779221 0,524675325 0,119281546 1,616883117 lmax 3,065367965 CI 0,032683983 RC 0,58 CR 0,056351694 Normalized 0,023255814 0,04109589 0,076923077 0,047619 0,162790698 0,095890411 0,230769231 0,2380952 0,488372093 0,287671233 0,230769231 0,2380952 0,162790698 0,287671233 0,230769231 0,2380952 0,162790698 0,287671233 0,230769231 0,2380952
	Total	6	1 1/5

,227343541 Carbon footprint Chemical use

	Environmental 0,25 0,75 SAP purchasing 0,25 0,75 0,481339713 Relational 0,208333333 0,791666667 Traceability 0,17 0,83 0,524675325 Priority vector 0,5 0,5 SAP purchasing 1/2 1 1 2 1/2 3/8 Priority vector 0,875 0,125 Traceability 5 5 1 11 0 Social 1/5 1 1 1/3 1/3 2 7/8 0,31888587 Social 0,448011364 0,551988636 1 0,31888587 Environmental 0,3125 0,6875 SAP purchasing 0,5 0,5 0,368181818 Relational 0,208333333 0,791666667 Traceability 0,88 0,13 0,090909091 1/3 1 1 2 1/7 0,206778309 Social 0,793221691 Functional 0,166666667 0,833333333 LL LL 1 1 1/7 LL 1 1 2 LL 1/7 1 1 1/7 LL 1 1 2 LL 1 1 2 LL 1/5 1 1 1/5 LL 1 1 2 LL 7 1 8 LL 7 1 8 LL 7 1 Global priority 0,206962857 0,206962857 0,125 0,625 0,25 Global priority 0,067553279 0,009650468 Normalized 0,454545455 0,454545455 0,090909091 Relational 3 5 3 1 1 13 0,077203747 Relational 0,208333333 0,791666667 1 0,077203747 Social 0,448011364 0,551988636 Functional 0,875 0,125 LL 1 1 1/3 LL 1/5 1 1 1/5 LL 1/3 1 1 1/3 LL 1/5 1 1 1/5 LL 1 1 2 LL 1 1 2 LL 1/5 1 1 1/5 LL 1/5 1 1 1/5 LL 1/7 1 1 1/7 LL 1/7 1 1 1/7 LL 1/7 1 1 1/7 Priority vector Global priority Normalized Priority vector 0,5 0,5 Priority vector 0,125 0,875 Priority vector 0,5 0,5 Priority vector 0,125 0,875 Priority vector 0,5 0,5 Priority vector 0,5 0,5 Priority vector 0,166666667 0,833333333 Priority vector 0,5 0,5 Priority vector 0,875 0,125 Priority vector 0,875 0,125 Priority vector 0,875 0,125 0,090909091 0,2 0,454545455 0,4 0,454545455 0,4 0,454545455 0,454545455 0,454545455 0,454545455 0,090909091 0,090909091 Functional 1 0,069767442 5 0,488372093 3 0,348837209 1 0,023255814 1 0,069767442 11 0,086506073 Functional Ranking 0,88 0,415732505 0,13 0,584267495 1 1 0,086506073 Priority vector 0,25 0,75 Priority vector 0,166666667 0,833333333 Priority vector 0,25 0,75 Priority vector 0,166666667 0,833333333 Priority vector 0,5 0,5 Priority vector 0,5 0,5 Priority vector 0,166666667 0,833333333 Priority vector 0,166666667 0,833333333 Priority vector 0,125 0,875 Priority vector 0,125 0,875 Priority vector 0,125 0,875 0,833333333 0,131450241 0,166666667 0,026290048 SAP purchasing Normalized 1 0,428571429 0,428571429 0,428571429 1/3 0,142857143 0,142857143 0,142857143 1 0,428571429 0,428571429 0,428571429 2 1/3 3/7 Priority vector Global priority 0,833333333 0,033158996 0,166666667 0,006631799 Traceability Normalized 1 0,142857143 0,14893617 0,111111111 0,134301475 0,056491235 Priority vector Global priority 0,138636364 0,044209177 0,493181818 0,157268713 0,368181818 0,117407979 lmax CI RC CR Priority vector Global priority 0,454545455 0,039320942 0,454545455 0,039320942 0,090909091 0,007864188 lmax CI RC CR Normalized 0,056179775 0,069767442 0,393258427 0,348837209 0,393258427 0,348837209 0,078651685 0,11627907 0,078651685 0,11627907 Priority vector Global priority 0,428571429 0,052720348 0,142857143 0,017573449 0,428571429 0,052720348 lmax CI RC CR Priority vector Global priority 7 0,714285714 0,744680851 0,777777778 0,745581448 0,313613953 1 0,142857143 0,106382979 0,111111111 0,120117078 0,050524851 9 lmax 1/8 CI RC CR Social Relational Functional Normalized 3 5 1/3 0,205479452 0,38961039 0,326086957 2 5 1/3 0,068493151 0,12987013 0,217391304 1 5 1/3 0,068493151 0,064935065 0,108695652 1/5 1 1/7 0,04109589 0,025974026 0,02173913 3 7 1 0,616438356 0,38961039 0,326086957 9 1/5 23 2 1/7 0,123014146 0,039790795 0,420630039 Social Relational Functional Ranking 0,357142857 0,166666667 0,13 0,200712921 0,642857143 0,833333333 0,88 0,799287079 1 1 1 1 0,123014146 0,039790795 0,420630039 Environmental 0,208333333 0,791666667 SAP purchasing Social 0,5 0,357142857 0,5 0,642857143 0,428571429 Relational 0,166666667 0,833333333 Traceability Functional 0,13 0,125 0,88 0,875 0,120117078 LL Priority vector 1 0,5 1 0,5 2 LL Priority vector 3 0,75 1 0,25 4 LL Priority vector 1 0,5 1 0,5 2 LL Priority vector 1/3 0,25 1 0,75 1 1/3 LL Priority vector 1 0,5 1 0,5 2 LL Priority vector 1 0,5 1 0,5 2 LL Priority vector 1/5 0,166666667 1 0,833333333 1 1/5 LL Priority vector 1/3 0,25 1 0,75 1 1/3 LL Priority vector 1/3 0,25 1 0,75 1 1/3 LL Priority vector 1/3 0,25 1 0,75 1 1/3 LL Priority vector 1 0,5 1 0,5 2 Priority vector Global priority 0,166666667 0,042262086 0,833333333 0,211310429 SAP purchasing Normalized Priority vector Global priority 5 0,454545455 0,4 0,625 0,493181818 0,120573883 2 0,454545455 0,4 0,25 0,368181818 0,090013682 1 0,090909091 0,2 0,125 0,138636364 0,033894041 8 lmax 1/7 CI RC CR Priority vector Global priority 0,5 0,113149894 0,5 0,113149894 Traceability Normalized Priority vector Global priority 1 0,333333333 0,333333333 0,333333333 0,333333333 0,0564812 1 0,333333333 0,333333333 0,333333333 0,333333333 0,0564812 1 0,333333333 0,333333333 0,333333333 0,333333333 0,0564812 3 lmax 1/3 CI RC CR Social Relational Functional Normalized 1 1/3 1/3 0,090909091 0,086956522 0,230769231 1 1 2 0,272727273 0,260869565 0,230769231 1 1 3 0,090909091 0,260869565 0,230769231 1 1 1 0,272727273 0,260869565 0,230769231 1/3 1 1 0,272727273 0,130434783 0,076923077 4 1/3 4 1/3 7 1/3 0,244481605 0,226299787 0,1694436 Social Relational Functional Ranking 0,376704545 0,208333333 0,33 0,407308389 0,623295455 0,791666667 0,67 0,592691611 1 1 1 1 0,244481605 0,226299787 0,1694436 Environmental 0,625 0,375 SAP purchasing Social 0,5 0,376704545 0,5 0,623295455 0,138636364 Relational 0,208333333 0,791666667 Traceability Functional 0,50 0,333333333 0,50 0,666666667 0,333333333 LL Priority vector 5 0,833333333 1 0,166666667 6 LL Priority vector 1 0,5 1 0,5 2 LL Priority vector 1 0,5 1 0,5 2 LL Priority vector 1/7 0,125 1 0,875 1 1/7 LL Priority vector 1/7 0,125 1 0,875 1 1/7 LL Priority vector 1/7 0,125 1 0,875 1 1/7 LL Priority vector 1/5 0,166666667 1 0,833333333 1 1/5 LL Priority vector 3 0,75 1 0,25 4 LL Priority vector 5 0,833333333 1 0,166666667 6 LL Priority vector 1 0,5 1 0,5 2 LL Priority vector 7 0,875 1 0,125 Priority vector Global priority 0,833333333 0,409002162 0,166666667 0,081800432 SAP purchasing Normalized Priority vector Global priority 1 0,454545455 0,454545455 0,454545455 0,454545455 0,128858555 1/5 0,090909091 0,090909091 0,090909091 0,090909091 0,025771711 1 0,454545455 0,454545455 0,454545455 0,454545455 0,128858555 2 1/5 lmax 4/9 CI RC CR Priority vector Global priority 0,125 0,006705769 0,875 0,046940386 Traceability Normalized Priority vector Global priority 5 0,652173913 0,6 0,714285714 0,655486542 0,035164333 1 0,217391304 0,2 0,142857143 0,186749482 0,010018392 1 0,130434783 0,2 0,142857143 0,157763975 0,008463431 7 lmax 1/6 CI RC CR Social Relational Functional Normalized 1/5 3 3 0,085714286 0,109947644 0,043478261 3 7 7 0,428571429 0,54973822 0,652173913 1 5 5 0,428571429 0,183246073 0,217391304 1/5 1 1 0,028571429 0,078534031 0,043478261 1/5 1 1 0,028571429 0,078534031 0,043478261 4 3/5 17 17 0,28348882 0,053646156 0,053646156 Social Relational Functional Ranking 0,125 0,677083333 0,78 0,457558855 0,875 0,322916667 0,22 0,542441145 1 1 1 1 0,28348882 0,053646156 0,053646156 Environmental 0,5 0,5 SAP purchasing Social 0,125 0,125 0,875 0,875 0,454545455 Relational 0,677083333 0,322916667 Traceability Functional 0,88 0,777657005 0,13 0,222342995 0,157763975 LL Priority vector 1/7 0,125 1 0,875 1 1/7 LL Priority vector 1/7 0,125 1 0,875 1 1/7 LL Priority vector 1 0,5 1 0,5 2 LL Priority vector 1/7 0,125 1 0,875 1 1/7 LL Priority vector 3 0,75 1 0,25 4 LL Priority vector 1/7 0,125 1 0,875 1 1/7 LL Priority vector 1/7 0,125 1 0,875 1 1/7 LL Priority vector 1 0,5 1 0,5 2 LL Priority vector 1 0,5 1 0,5 2 LL Priority vector 1 0,5 1 0,5 2 LL Priority vector 3 0,75 1 0,25 Priority vector Global priority 0,875 0,466278348 0,125 0,066611193 SAP purchasing Normalized Priority vector Global priority 1/3 0,24 0,375 0,230769231 0,281923077 0,050625857 1/9 0,04 0,0625 0,076923077 0,059807692 0,010739865 1 0,72 0,5625 0,692307692 0,658269231 0,118207578 1 4/9 lmax 2/3 CI RC CR Priority vector Global priority 0,875 0,12325567 0,125 0,017607953 Traceability Normalized Priority vector Global priority 1 0,2 0,181818182 0,25 0,210606061 0,008962688 2 0,6 0,545454545 0,5 0,548484848 0,023341677 1 0,2 0,272727273 0,25 0,240909091 0,010252283 4 lmax 1/4 CI RC CR Social Relational Functional Normalized 1/3 1 3 0,096774194 0,114754098 0,044247788 5 5 7 0,483870968 0,573770492 0,663716814 1 1 5 0,290322581 0,114754098 0,132743363 1 1 5 0,096774194 0,114754098 0,132743363 1/5 1/5 1 0,032258065 0,081967213 0,026548673 7 1/2 8 1/5 21 0,1795733 0,140863622 0,042556648 Social Relational Functional Ranking 0,162379808 0,171875 0,56 0,256754001 0,837620192 0,828125 0,44 0,743245999 1 1 1 1 0,1795733 0,140863622 0,042556648 Environmental 0,3125 0,6875 SAP purchasing Social 0,125 0,162379808 0,875 0,837620192 0,658269231 Relational 0,171875 0,828125 Traceability Functional 0,75 0,560227273 0,25 0,439772727 0,240909091 LL Priority vector 1/3 0,25 1 0,75 1 1/3 LL Priority vector 1/7 0,125 1 0,875 1 1/7 LL Priority vector 1 0,5 1 0,5 2 LL Priority vector 1/7 0,125 1 0,875 1 1/7 LL Priority vector 1 0,5 1 0,5 2 LL Priority vector 1/7 0,125 1 0,875 1 1/7 LL Priority vector 1/9 0,1 1 0,9 1 1/9 LL Priority vector 1/9 0,1 1 0,9 1 1/9 LL Priority vector 1 0,5 1 0,5 2 LL Priority vector 1 0,5 1 0,5 2 LL Priority vector 1 0,5 1 0,5 2 Priority vector Global priority 0,125 0,024340659 0,875 0,170384615 SAP purchasing Normalized Priority vector Global priority 1/2 0,25 0,2 0,272727273 0,240909091 0,060677323 1/3 0,25 0,2 0,181818182 0,210606061 0,053044955 1 0,5 0,6 0,545454545 0,548484848 0,138145854 1 5/6 lmax 5/9 CI RC CR Priority vector Global priority 0,166666667 0,032454212 0,833333333 0,162271062 Traceability Normalized Priority vector Global priority 5 0,454545455 0,4 0,625 0,493181818 0,096034965 2 0,454545455 0,4 0,25 0,368181818 0,071694306 1 0,090909091 0,2 0,125 0,138636364 0,026996004 8 lmax 1/7 CI RC CR Social Relational Functional Normalized 1/3 1 1 0,142857143 0,2 0,076923077 1 1 1 0,142857143 0,2 0,230769231 1 1 1 0,428571429 0,2 0,230769231 1 1 1 0,142857143 0,2 0,230769231 1 1 1 0,142857143 0,2 0,230769231 4 1/3 5 5 0,251868132 0,194725275 0,194725275 Social Relational Functional Ranking 0,203977273 0,1 0,50 0,270051199 0,796022727 0,9 0,50 0,729948801 1 1 1 1 0,251868132 0,194725275 0,194725275 Environmental 0,3125 0,6875 SAP purchasing Carbon footprint 0,25 0,75 0,5 User resistance 0,166666667 0,833333333 0,282934609 Innovation 0,166666667 0,833333333 0,5 Confort 0,17 0,83 0,333766234 Chemical use User resistance SAP purchasing Innovation Confort Traceability I.ALTERNATIVES COMPARISON 0,25 0,75 0,5 Local job 0,166666667 0,833333333 0,235725678 Brand image 0,25 0,75 0,5 Lifespan 0,166666667 0,833333333 0,141558442 SUBCRITERION 2 : SUBCRITERION 2 : SUBCRITERION 3 : SUBCRITERION 2 : SUBCRITERION 2 : SUBCRITERION 3 : Actor A3 CRITERION 1 : Economic SUBCRITERION 1 : Purchasing cost LC LC 1 LL 1 Total 2 CRITERION 2 : Environmental SUBCRITERION 1 : LC LC 1 LL 7 Total 8 LC LC 1 LL 1 Total 2 CRITERION 3 : Social SUBCRITERION 1 : Local job LC LC 1 LL 7 Total 8 LC LC 1 LL 1 Total 2 LC LC 1 LL 1 Total 2 CRITERION 4 : Relational SUBCRITERION 1 : Brand image LC LC 1 LL 5 Total 6 LC LC 1 LL 1 Total 2 CRITERION 5 : Functional SUBCRITERION 1 : Lifespan LC LC 1 LL 1/7 Total 1 1/7 LC LC 1 LL 1/7 Total 1 1/7 LC LC 1 LL 1/7 Total 1 1/7 CRITERION 3 : LC LL Priority LC LL Priority LC LL Priority LC LL Priority Social CRITERION 4 : Relational CRITERION 5 : Functional II. SUB-CRITERIA COMPARISON Carbon footprint Chemical use Carbon footprint 1 1 Chemical use 1 1 Total 2 2 Local job User resistance Local job 1 1/5 User resistance 5 1 SAP purchasing 2 1 Total 8 2 1/5 Priority vector 1/7 1/2 Brand image Innovation Brand image 1 7 Innovation 1/7 1 Total 1 1/7 8 Lifespan Confort Lifespan 1 1 Confort 1 1 Traceability 1/5 1/5 Total 2 1/5 2 1/5 Priority vector 4/9 4/9 III. CRITERIA COMPARISON Economic Environmental Economic 1 1/7 Environmental 7 1 Social 5 1 Relational 1/3 1/5 Functional 1 1/5 Total 14 1/3 2 1/2 priority vector 0,103478596 0,413925714 IV. ALTERNATIVES PRIORITIZATION Economic Environmental LC 0,5 0,3125 LL 0,5 0,6875 Total 1 1 Priority vector 0,103478596 0,413925714 Carbon footprint Chemical use LC 0,125 0,5 LL 0,875 0,5 Priority 0,5 0,5 Local job User resistance LC 0,125 0,5 LL 0,875 0,5 Priority 0,138636364 0,493181818 Brand image Innovation LC 0,166666667 0,5 LL 0,833333333 0,5 Priority 0,875 0,125 Lifespan Confort LC 0,875 0,88 LL 0,125 0,13 Priority 0,454545455 0,454545455 SUBCRITERION 2 : Chemical use SUBCRITERION 2 : User resistance SUBCRITERION 3 : SAP purchasing SUBCRITERION 2 : Innovation SUBCRITERION 2 : Confort SUBCRITERION 3 : Traceability Actor A4 I. ALTERNATIVES COMPARISON CRITERION 1 : Economic SUBCRITERION 1 : Purchasing cost LC LC 1 LL 3 Total 4 CRITERION 2 : Environmental SUBCRITERION 1 : Carbon footprint LC LC 1 LL 5 Total 6 LC LC 1 LL 3 Total 4 CRITERION 3 : Social SUBCRITERION 1 : Local job LC LC 1 LL 5 Total 6 LC LC 1 LL 1 Total 2 LC LC 1 LL 1 Total 2 CRITERION 4 : Relational SUBCRITERION 1 : Brand image LC LC 1 LL 5 Total 6 LC LC 1 LL 5 Total 6 CRITERION 5 : Functional SUBCRITERION 1 : Lifespan LC LC 1 LL 7 Total 8 LC LC 1 LL 7 Total 8 LC LC 1 LL 7 Total 8 CRITERION 2 : Environmental CRITERION 3 : Social CRITERION 4 : Relational CRITERION 5 : Functional II.SUB-CRITERIA COMPARISON Carbon footprint Chemical use Carbon footprint 1 5 Chemical use 1/5 1 Total 1 1/5 6 Local job User resistance Local job 1 3 User resistance 1/3 1 SAP purchasing 1 3 Total 2 1/3 7 Priority vector 3/7 1/7 Brand image Innovation Brand image 1 5 Innovation 1/5 1 Total 1 1/5 6 Lifespan Confort Lifespan 1 1/5 Confort 5 1 Traceability 1 1/7 Total 7 1 1/3 Priority vector 1/7 3/4 III.CRITERIA COMPARISON Economic Environmental Economic 1 3 Environmental 1/3 1 Social 1/3 1/2 Relational 1/5 1/5 Functional 3 3 Total 4 6/7 7 5/7 priority vector 0,258824732 0,157740289 IV.ALTERNATIVES PRIORITIZATION Economic Environmental LC 0,25 0,208333333 LL 0,75 0,791666667 Total 1 1 Priority vector 0,258824732 0,157740289 Carbon footprint Chemical use LC 0,166666667 0,25 LL 0,833333333 0,75 Priority 0,5 0,5 Local job User resistance LC 0,166666667 0,5 LL 0,833333333 0,5 Priority 0,428571429 0,142857143 Brand image Innovation LC 0,166666667 0,166666667 LL 0,833333333 0,833333333 Priority 0,833333333 0,166666667 Lifespan Confort LC 0,125 0,13 LL 0,875 0,88 Priority 0,134301475 0,745581448 SUBCRITERION 2 : Chemical use SUBCRITERION 2 : User resistance SUBCRITERION 3 : SAP purchasing SUBCRITERION 2 : Innovation SUBCRITERION 2 : Confort SUBCRITERION 3 : Traceability Actor A5 I. ALTERNATIVES COMPARISON CRITERION 1 : Economic SUBCRITERION 1 : Purchasing cost LC LC 1 LL 1 Total 2 CRITERION 2 : Environmental SUBCRITERION 1 : Carbon footprint LC LC 1 LL 1/3 Total 1 1/3 LC LC 1 LL 1 Total 2 CRITERION 3 : Social SUBCRITERION 1 : Local job LC LC 1 LL 3 Total 4 LC LC 1 LL 1 Total 2 LC LC 1 LL 1 Total 2 CRITERION 4 : Relational SUBCRITERION 1 : Brand image LC LC 1 LL 5 Total 6 LC LC 1 LL 3 Total 4 CRITERION 5 : Functional SUBCRITERION 1 : Lifespan LC LC 1 LL 3 Total 4 LC LC 1 LL 3 Total 4 LC LC 1 LL 1 Total 2 CRITERION 2 : Environmental CRITERION 3 : Social CRITERION 4 : Relational CRITERION 5 : Functional II.SUB-CRITERIA COMPARISON Carbon footprint Chemical use Carbon footprint 1 1/5 Chemical use 5 1 Total 6 1 1/5 Local job User resistance Local job 1 1 User resistance 1 1 SAP purchasing 1/5 1/2 Total 2 1/5 2 1/2 Priority vector 1/2 3/8 Brand image Innovation Brand image 1 1 Innovation 1 1 Total 2 2 Lifespan Confort Lifespan 1 1 Confort 1 1 Traceability 1 1 Total 3 3 Priority vector 1/3 1/3 III.CRITERIA COMPARISON Economic Environmental Economic 1 1/3 Environmental 3 1 Social 1 1 Relational 3 1 Functional 3 1/2 Total 11 3 5/6 priority vector 0,106202493 0,253572514 IV.ALTERNATIVES PRIORITIZATION Economic Environmental LC 0,5 0,625 LL 0,5 0,375 Total 1 1 Priority vector 0,106202493 0,253572514 Carbon footprint Chemical use LC 0,75 0,5 LL 0,25 0,5 Priority 0,5 0,5 Local job User resistance LC 0,25 0,5 LL 0,75 0,5 Priority 0,493181818 0,368181818 Brand image Innovation LC 0,166666667 0,25 LL 0,833333333 0,75 Priority 0,5 0,5 Lifespan Confort LC 0,25 0,25 LL 0,75 0,75 Priority 0,333333333 0,333333333 SUBCRITERION 2 : Chemical use SUBCRITERION 2 : User resistance SUBCRITERION 3 : SAP purchasing SUBCRITERION 2 : Innovation SUBCRITERION 2 : Confort SUBCRITERION 3 : Traceability Actor A6 I. ALTERNATIVES COMPARISON CRITERION 1 : Economic SUBCRITERION 1 : Purchasing cost LC LC 1 LL 1/5 Total 1 1/5 CRITERION 2 : Environmental SUBCRITERION 1 : Carbon footprint LC LC 1 LL 1 Total 2 LC LC 1 LL 1 Total 2 CRITERION 3 : Social SUBCRITERION 1 : Local job LC LC 1 LL 7 Total 8 LC LC 1 LL 7 Total 8 LC LC 1 LL 7 Total 8 CRITERION 4 : Relational SUBCRITERION 1 : Brand image LC LC 1 LL 5 Total 6 LC LC 1 LL 1/3 Total 1 1/3 CRITERION 5 : Functional SUBCRITERION 1 : Lifespan LC LC 1 LL 1/5 Total 1 1/5 LC LC 1 LL 1 Total 2 LC LC 1 LL 1/7 Total 1 1/7 CRITERION 3 : Social CRITERION 4 : Relational CRITERION 5 : Functional II.SUB-CRITERIA COMPARISON Carbon footprint Chemical use Carbon footprint 1 5 Chemical use 1/5 1 Total 1 1/5 6 Local job User resistance Local job 1 5 User resistance 1/5 1 SAP purchasing 1 5 Total 2 1/5 11 Priority vector 4/9 0 Brand image Innovation Brand image 1 1/7 Innovation 7 1 Total 8 1 1/7 Lifespan Confort Lifespan 1 3 Confort 1/3 1 Traceability 1/5 1 Total 1 1/2 5 Priority vector 2/3 1/5 III.CRITERIA COMPARISON Economic Environmental Economic 1 1/5 Environmental 5 1 Social 5 1/3 Relational 1/3 1/7 Functional 1/3 1/7 Total 11 2/3 1 5/6 priority vector 0,118416273 0,490802595 IV.ALTERNATIVES PRIORITIZATION Economic Environmental LC 0,833333333 0,5 LL 0,166666667 0,5 Total 1 1 Priority vector 0,118416273 0,490802595 Carbon footprint Chemical use LC 0,5 0,5 LL 0,5 0,5 Priority 0,5 0,5 Local job User resistance LC 0,125 0,125 LL 0,875 0,875 Priority 0,454545455 0,090909091 Brand image Innovation LC 0,166666667 0,75 LL 0,833333333 0,25 Priority 0,125 0,875 Lifespan Confort LC 0,833333333 0,50 LL 0,166666667 0,50 Priority 0,655486542 0,186749482 SUBCRITERION 2 : Chemical use SUBCRITERION 2 : User resistance SUBCRITERION 3 : SAP purchasing SUBCRITERION 2 : Innovation SUBCRITERION 2 : Confort SUBCRITERION 3 : Traceability Actor A7 I.ALTERNATIVES COMPARISON CRITERION 1 : Economic SUBCRITERION 1 : Purchasing cost LC LC 1 LL 7 Total 8 CRITERION 2 : Environmental SUBCRITERION 1 : Carbon footprint LC LC 1 LL 7 Total 8 LC LC 1 LL 1 Total 2 CRITERION 3 : Social SUBCRITERION 1 : Local job LC LC 1 LL 7 Total 8 LC LC 1 LL 1/3 Total 1 1/3 LC LC 1 LL 7 Total 8 CRITERION 4 : Relational SUBCRITERION 1 : Brand image LC LC 1 LL 7 Total 8 LC LC 1 LL 1 Total 2 CRITERION 5 : Functional SUBCRITERION 1 : Lifespan LC LC 1 LL 1 Total 2 LC LC 1 LL 1 Total 2 LC LC 1 LL 1/3 Total 1 1/3 CRITERION 3 : Social CRITERION 4 : Relational CRITERION 5 : Functional II.SUB-CRITERIA COMPARISON Carbon footprint Chemical use Carbon footprint 1 7 Chemical use 1/7 1 Total 1 1/7 8 Local job User resistance Local job 1 6 User resistance 1/6 1 SAP purchasing 3 9 Total 4 1/6 16 Priority vector 2/7 0 Brand image Innovation Brand image 1 7 Innovation 1/7 1 Total 1 1/7 8 Lifespan Confort Lifespan 1 1/3 Confort 3 1 Traceability 1 1/2 Total 5 1 5/6 Priority vector 1/5 5/9 III.CRITERIA COMPARISON Economic Environmental Economic 1 1/5 Environmental 5 1 Social 3 1/5 Relational 1 1/5 Functional 1/3 1/7 Total 10 1/3 1 3/4 priority vector 0,104116888 0,532889541 IV. ALTERNATIVES PRIORITIZATION Economic Environmental LC 0,125 0,3125 LL 0,875 0,6875 Total 1 1 Priority vector 0,104116888 0,532889541 Carbon footprint Chemical use LC 0,125 0,5 LL 0,875 0,5 Priority 0,5 0,5 Local job User resistance LC 0,125 0,75 LL 0,875 0,25 Priority 0,281923077 0,059807692 Brand image Innovation LC 0,125 0,5 LL 0,875 0,5 Priority 0,875 0,125 Lifespan Confort LC 0,5 0,50 LL 0,5 0,50 Priority 0,210606061 0,548484848 SUBCRITERION 2 : Chemical use SUBCRITERION 2 : User resistance SUBCRITERION 3 : SAP purchasing SUBCRITERION 2 : Innovation SUBCRITERION 2 : Confort SUBCRITERION 3 : Traceability Actor A8 I. ALTERNATIVES COMPARISON CRITERION 1 : Economic SUBCRITERION 1 : Purchasing cost LC LC 1 LL 3 Total 4 CRITERION 2 : Environmental SUBCRITERION 1 : Carbon footprint LC LC 1 LL 7 Total 8 LC LC 1 LL 1 Total 2 CRITERION 3 : Social SUBCRITERION 1 : Local job LC LC 1 LL 7 Total 8 LC LC 1 LL 1 Total 2 LC LC 1 LL 7 Total 8 CRITERION 4 : Relational SUBCRITERION 1 : Brand image LC LC 1 LL 9 Total 10 LC LC 1 LL 9 Total 10 CRITERION 5 : Functional SUBCRITERION 1 : Lifespan LC LC 1 LL 1 Total 2 LC LC 1 LL 1 Total 2 LC LC 1 LL 1 Total 2 CRITERION 2 : Environmental CRITERION 3 : Social CRITERION 4 : Relational CRITERION 5 : Functional II. SUB-CRITERIA COMPARISON Carbon footprint Chemical use Carbon footprint 1 1/7 Chemical use 7 1 Total 8 1 1/7 Local job User resistance Local job 1 1 User resistance 1 1 SAP purchasing 2 3 Total 4 5 Priority vector 1/4 1/5 Brand image Innovation Brand image 1 1/5 Innovation 5 1 Total 6 1 1/5 Lifespan Confort Lifespan 1 1 Confort 1 1 Traceability 1/5 1/2 Total 2 1/5 2 1/2 Priority vector 1/2 3/8 III.CRITERIA COMPARISON Economic Environmental Economic 1 1 Environmental 1 1 Social 3 1 Relational 1 1 Functional 1 1 Total 7 5 priority vector 0,163956044 0,194725275 IV.ALTERNATIVES PRIORITIZATION Economic Environmental LC 0,25 0,3125 LL 0,75 0,6875 Total 1 1 Priority vector 0,163956044 0,194725275 Carbon footprint Chemical use LC 0,125 0,5 LL 0,875 0,5 Priority 0,5 0,5 Local job User resistance Social LC 0,125 0,5 0,125 0,203977273 LL 0,875 0,5 0,875 0,796022727 Priority 0,240909091 0,210606061 0,548484848 Brand image Innovation Relational LC 0,1 0,1 0,1 LL 0,9 0,9 0,9 Priority 0,166666667 0,833333333 Lifespan Confort Traceability Functional LC 0,5 0,50 0,50 0,5 LL 0,5 0,50 0,50 0,5 Priority 0,493181818 0,368181818 0,138636364 SUBCRITERION 2 : Chemical use SUBCRITERION 2 : User resistance SUBCRITERION 3 : SAP purchasing SUBCRITERION 2 : Innovation SUBCRITERION 2 : Confort SUBCRITERION 3 : Traceability Actor A9 I. ALTERNATIVES COMPARISON CRITERION 1 : Economic SUBCRITERION 1 : Purchasing cost LC LL Priority vector LC 1 1/5 0,166666667 LL 5 1 0,833333333 Total 6 1 1/5 CRITERION 2 : Environmental SUBCRITERION 1 : Carbon footprint LC LL Priority vector LC 1 1/9 0,1 LL 9 1 0,9 Total 10 1 1/9 LC LL Priority vector LC 1 1/7 0,125 LL 7 1 0,875 Total 8 1 1/7 CRITERION 3 : Social SUBCRITERION 1 : Local job LC LL Priority vector LC 1 1/7 0,125 LL 7 1 0,875 Total 8 1 1/7 LC LL Priority vector LC 1 1/7 0,125 LL 7 1 0,875 Total 8 1 1/7 LC LL Priority vector LC 1 1/9 0,1 LL 9 1 0,9 Total 10 1 1/9 CRITERION 4 : Relational SUBCRITERION 1 : Brand image LC LL Priority vector LC 1 1/9 0,1 LL 9 1 0,9 Total 10 1 1/9 LC LL Priority vector LC 1 1/9 0,1 LL 9 1 0,9 Total 10 1 1/9 CRITERION 5 : Functional SUBCRITERION 1 : Lifespan LC LL Priority vector LC 1 1/7 0,125 LL 7 1 0,875 Total 8 1 1/7 LC LL Priority vector LC 1 1/7 0,125 LL 7 1 0,875 Total 8 1 1/7 LC LL Priority vector LC 1 1/7 0,125 LL 7 1 0,875 Total 8 1 1/7 CRITERION 2 : Environmental CRITERION 3 : Social CRITERION 4 : Relational CRITERION 5 : Functional II.SUB-CRITERIA COMPARISON Carbon footprint Chemical use Priority vector Global priority Carbon footprint 1 9 0,9 0,337978056 Chemical use 1/9 1 0,1 0,037553117 Total 1 1/9 10 Local job User resistance SAP purchasing Normalized Priority vector Global priority Local job 1 1 1/7 0,111111111 0,111111111 0,111111111 0,111111111 0,010819885 0,33333333 lmax 0,421363636 1,554545455 1,138636364 3,114545455 0,057272727 0,58 0,098746082 lmax 1,363636364 1,363636364 0,272727273 3 0 0,58 0 0,230769231 0,090909091 0,384615385 0,454545455 0,230769231 0,272727273 0,076923077 0,090909091 0,076923077 0,090909091 lmax 1,285714286 0,428571429 1,285714286 3 0 0,58 0 lmax 0,403534842 2,257908364 0,360930188 3,022373394 0,011186697 0,58 0,019287408 0,217391304 0,1555556 0,217391304 0,1555556 0,217391304 0,1555556 0,043478261 0,0666667 0,304347826 0,4666667 lmax 1,554545455 1,138636364 0,421363636 3,114545455 0,057272727 0,58 0,098746082 lmax 1 1 1 3 0 0,58 0 0,076923077 0,0454545 0,230769231 0,2727273 0,230769231 0,4090909 0,230769231 0,1363636 0,230769231 0,1363636 lmax 1,363636364 0,272727273 1,363636364 3 0 0,58 0 lmax 2,004554865 0,563008972 0,475610766 3,043174603 0,021587302 0,58 0,037219485 0,176470588 0,1764706 0,411764706 0,4117647 0,294117647 0,2941176 0,058823529 0,0588235 0,058823529 0,0588235 lmax 0,860192308 0,179935897 2,042307692 3,082435897 0,041217949 0,58 0,071065429 lmax 0,634343434 1,662121212 0,725757576 3,022222222 0,011111111 0,58 0,019157088 0,12195122 0,1428571 0,609756098 0,3333333 0,12195122 0,2380952 0,12195122 0,2380952 0,024390244 0,047619 lmax 0,725757576 0,634343434 1,662121212 3,022222222 0,011111111 0,58 0,019157088 lmax 1,554545455 1,138636364 0,421363636 3,114545455 0,057272727 0,58 0,098746082 0,2 0,2 0,2 0,2 0,2 0,2 0,2 0,2 0,2 0,2 lmax User resistance 1 1 1/7 0,111111111 0,111111111 0,111111111 0,111111111 0,010819885 0,33333333 SAP purchasing 7 7 1 0,777777778 0,777777778 0,777777778 0,777777778 0,075739193 2,33333333 Total 9 9 1 2/7 lmax 3 Priority vector 1/9 1/9 7/9 CI 0% RC 0,58 CR 0% Brand image Innovation Priority vector Global priority Brand image 1 1/7 0,125 0,014758577 Innovation 7 1 0,875 0,10331004 Total 8 1 1/7 Lifespan Confort Traceability Normalized Priority vector Global priority lmax Lifespan 1 1/3 1 0,2 0,2 0,2 0,2 0,05505573 0,6 Confort 3 1 3 0,6 0,6 0,6 0,6 0,165167189 1,8 Traceability 1 1/3 1 0,2 0,2 0,2 0,2 0,05505573 0,6 Total 5 1 2/3 5 lmax 3 Priority vector 1/5 3/5 1/5 CI 0% RC 0,58 CR 0% III.CRITERIA COMPARISON Economic Environmental Social Relational Functional Normalized Economic 1 1/5 1 1 1 0,111111111 0,068965517 0,090909091 0,125 0,2727273 Environmental 5 1 5 2 1 0,555555556 0,344827586 0,454545455 0,25 0,2727273 Social 1 1/5 1 1 1/3 0,111111111 0,068965517 0,090909091 0,125 0,0909091 Relational 1 1/2 1 1 1/3 0,111111111 0,172413793 0,090909091 0,125 0,0909091 Functional 1 1 3 3 1 0,111111111 0,344827586 0,272727273 0,375 0,2727273 Total 9 2 8/9 11 8 3 2/3 priority vector 0,133742598 0,375531174 0,097378962 0,118068617 0,275278649 IV. ALTERNATIVES PRIORITIZATION Economic Environmental Social Relational Functional Ranking LC 0,166666667 0,1125 0,105555556 0,1 0,13 0,121033273 LL 0,833333333 0,8875 0,894444444 0,9 0,88 0,878966727 Total 1 1 1 1 1 1 Priority vector 0,133742598 0,375531174 0,097378962 0,118068617 0,275278649 Carbon footprint Chemical use Environmental LC 0,1 0,125 0,1125 LL 0,9 0,875 0,8875 Priority 0,5 0,5 Local job User resistance SAP purchasing Social LC 0,125 0,125 0,1 0,105555556 LL 0,875 0,875 0,9 0,894444444 Priority 0,111111111 0,111111111 0,777777778 Brand image Innovation Relational LC 0,1 0,1 0,1 LL 0,9 0,9 0,9 Priority 0,125 0,875 Lifespan Confort Traceability Functional LC 0,125 0,13 0,13 0,125 LL 0,875 0,88 0,88 0,875 Priority 0,2 0,6 0,2 SUBCRITERION 2 : Chemical use SUBCRITERION 2 : User resistance SUBCRITERION 3 : SAP purchasing SUBCRITERION 2 : Innovation SUBCRITERION 2 : Confort SUBCRITERION 3 : Traceability Actor A10 I. ALTERNATIVES COMPARISON CRITERION 1 : Economic SUBCRITERION 1 : Purchasing cost LC LL Priority vector LC 1 1 0,5 LL 1 1 0,5 Total 2 2 CRITERION 2 : Environmental SUBCRITERION 1 : Carbon footprint LC LL Priority vector LC 1 1/5 0,166666667 LL 5 1 0,833333333 Total 6 1 1/5 LC LL Priority vector LC 1 1 0,5 LL 1 1 0,5 Total 2 2 CRITERION 3 : Social SUBCRITERION 1 : Local job LC LL Priority vector LC 1 1/7 0,125 LL 7 1 0,875 Total 8 1 1/7 LC LL Priority vector LC 1 1/5 0,166666667 LL 5 1 0,833333333 Total 6 1 1/5 LC LL Priority vector LC 1 1 0,5 LL 1 1 0,5 Total 2 2 CRITERION 4 : Relational SUBCRITERION 1 : Brand image LC LL Priority vector LC 1 1/9 0,1 LL 9 1 0,9 Total 10 1 1/9 LC LL Priority vector LC 1 1 0,5 LL 1 1 0,5 Total 2 2 CRITERION 5 : Functional SUBCRITERION 1 : Lifespan LC LL Priority vector LC 1 1 0,5 LL 1 1 0,5 Total 2 2 LC LL Priority vector LC 1 1 0,5 LL 1 1 0,5 Total 2 2 LC LL Priority vector LC 1 1 0,5 LL 1 1 0,5 Total 2 2 CRITERION 2 : Environmental CRITERION 3 : Social CRITERION 4 : Relational CRITERION 5 : Functional II. SUB-CRITERIA COMPARISON Carbon footprint Chemical use Priority vector Global priority Carbon footprint 1 1 0,5 0,148581607 Chemical use 1 1 0,5 0,148581607 Total 2 2 Local job User resistance SAP purchasing Normalized Priority vector Global priority lmax Local job 1 5 1 0,454545455 0,45454545 0,45454545 0,454545455 0,121088174 1,363636364 User resistance 1/5 1 1/5 0,090909091 0,09090909 0,09090909 0,090909091 0,024217635 0,272727273 SAP purchasing 1 5 1 0,454545455 0,45454545 0,45454545 0,454545455 0,121088174 1,363636364 Total 2 1/5 11 2 1/5 lmax 3 Priority vector 4/9 0 4/9 CI 0 RC 0,58 CR 0 Brand image Innovation Priority vector Global priority Brand image 1 3 0,75 0,066598496 Innovation 1/3 1 0,25 0,022199499 Total 1 1/3 4 Lifespan Confort Traceability Normalized Priority vector Global priority lmax Lifespan 1 1 3 0,428571429 0,4 0,5 0,442857143 0,117974478 1,33968254 Confort 1 1 2 0,428571429 0,4 0,33333333 0,387301587 0,103174813 1,16984127 Traceability 1/3 1/2 1 0,142857143 0,2 0,16666667 0,16984127 0,045244692 0,511111111 Total 2 1/3 2 1/2 6 lmax 3,020634921 Priority vector 4/9 2/5 1/6 CI 0,01031746 RC 0,58 CR 0,017788725 III. CRITERIA COMPARISON Economic Environmental Social Relational Functional Normalized Economic 1 1/5 1/3 1 1/3 0,07692308 0,056603774 0,090909091 0,090909091 0,0909091 Environmental 5 1 1 3 1 0,38461538 0,283018868 0,272727273 0,272727273 0,2727273 Social 3 1 1 3 1 0,23076923 0,283018868 0,272727273 0,272727273 0,2727273 Relational 1 1/3 1/3 1 1/3 0,07692308 0,094339623 0,090909091 0,090909091 0,0909091 Functional 3 1 1 3 1 0,23076923 0,283018868 0,272727273 0,272727273 0,2727273 Total 13 3 1/2 3 2/3 11 3 2/3 priority vector 0,081250825 0,297163214 0,266393983 0,088797994 0,26639398 IV.ALTERNATIVES PRIORITIZATION Economic Environmental Social Relational Functional Ranking LC 0,5 0,333333333 0,299242424 0,2 0,50 0,37035279 LL 0,5 0,666666667 0,700757576 0,8 0,50 0,54166667 Total 1 1 1 1 1 0,91201946 Priority vector 0,081250825 0,297163214 0,266393983 0,088797994 0,26639398 Carbon footprint Chemical use Environmental LC 0,166666667 0,5 0,333333333 LL 0,833333333 0,5 0,666666667 Priority 0,5 0,5 Local job User resistance SAP purchasing Social LC 0,125 0,166666667 0,5 0,299242424 LL 0,875 0,833333333 0,5 0,700757576 Priority 0,454545455 0,090909091 0,454545455 Brand image Innovation Relational LC 0,1 0,5 0,2 LL 0,9 0,5 0,8 Priority 0,75 0,25 Lifespan Confort Traceability Functional LC 0,5 0,50 0,50 0,5 LL 0,5 0,50 0,50 0,5 Priority 0,442857143 0,387301587 0,16984127 SUBCRITERION 2 : Chemical use SUBCRITERION 2 : User resistance SUBCRITERION 3 : SAP purchasing SUBCRITERION 2 : Innovation SUBCRITERION 2 : Confort SUBCRITERION 3 : Traceability Actor A11 I. ALTERNATIVES COMPARISON CRITERION 1 : CRITERION 2 : Environmental II.SUB-CRITERIA COMPARISON Carbon footprint Chemical use Priority vector Global priority Carbon footprint 1 5 0,833333333 0,184620606 Chemical use 1/5 1 0,166666667 0,036924121 Total 1 1/5 6 Actor A12 I.ALTERNATIVES COMPARISON Actor A1 I.ALT E R N A T I V E S COM P A R I S O N CRITERION 1 : Economic SUBCRITERION 2 : Purchasing cost CRITERION 2 : Environmental II.SUB-C R I T E R I A COM P A RI S O N Carbon footprint Recycling Priority vector Global priority Carbon footprint 1 1/5 0,166666667 0,076538386 Recycling 5 1 0,833333333 0,382691929 Total 6 1 1/5 CRITERION 2 : Environmental II. SUB-CRITERIA COMPARISON Actor A3 CRITERION 2 : Environmental II.SUB-C R I T E R I A COM P A RI S O N Actor A4 CRITERION 2 : Environmental II.SUB-C R I T E R I A COM P A RI S O N II.SUB-C R I T E R I A COM P A RI S O N Actor A5 CRITERION 2 : Environmental Actor A2 I. ALTERNATIVES COMPARISON CRITERION 1 : Economic SUBCRITERION 2 : Purchasing cost Carbon footprint Recycling Priority vector Global priority Carbon footprint 1 1/5 0,166666667 I.ALT E R N A T I V E S COM P A R I S O N Carbon footprint Recycling Priority vector Global priority I.ALT E R N A T I V E S COM P A R I S O N Carbon footprint Recycling Priority vector Global priority I.ALT E R N A T I V E S COM P A R I S O N Carbon footprint Recycling Priority vector Global priority 0,088647643 Recycling 5 1 0,833333333 Carbon footprint 1 1/5 0,166666667 0,034839127 Carbon footprint 1 1/5 0,166666667 0,06873973 Carbon footprint 1 1/5 0,166666667 0,033333333 0,443238217 Total 6 1 1/5 CRITERION 1 : Recycling 5 1 0,833333333 0,174195637 CRITERION 1 : Economic Recycling 5 1 0,833333333 0,34369865 CRITERION 1 : Economic Recycling 5 1 0,833333333 0,166666667 Economic SUBCRITERION 2 : Purchasing cost Total 6 1 1/5 SUBCRITERION 2 : Purchasing cost Total 6 1 1/5 SUBCRITERION 2 : Purchasing cost Total 6 1 1/5 Economic SUBCRITERION 1 : Purchasing cost LC LL Priority vector LC 1 1/3 0,25 LL 3 1 0,75 Total 4 1 1/3 CRITERION 2 : Environmental SUBCRITERION 1 : Carbon footprint LC LL Priority vector LC 1 1/7 0,125 LL 7 1 0,875 Total 8 1 1/7 LC LL Priority vector LC 1 1 0,5 LL 1 1 0,5 Total 2 2 CRITERION 3 : Social SUBCRITERION 1 : Local job LC LL Priority vector LC 1 1/7 0,125 LL 7 1 0,875 Total 8 1 1/7 LC LL Priority vector LC 1 1/3 0,25 LL 3 1 0,75 Total 4 1 1/3 LC LL Priority vector LC 1 1/7 0,125 LL 7 1 0,875 Total 8 1 1/7 CRITERION 4 : Relational SUBCRITERION 1 : Brand image LC LL Priority vector LC 1 1/5 0,166666667 LL 5 1 0,833333333 Total 6 1 1/5 LC LL Priority vector LC 1 1/3 0,25 LL 3 1 0,75 Total 4 1 1/3 CRITERION 5 : Functional SUBCRITERION 1 : Lifespan LC LL Priority vector LC 1 1 0,5 LL 1 1 0,5 Total 2 2 LC LL Priority vector LC 1 1 0,5 LL 1 1 0,5 Total 2 2 LC LL Priority vector LC 1 1 0,5 LL 1 1 0,5 Total 2 2 CRITERION 3 : Social CRITERION 4 : Relational CRITERION 5 : Functional Local job User resistance SA P purchasing Normalized Priority vector Global priority lmax Local job 1 5 5 0,714285714 0,769230769 0,625 0,702838828 0,346837806 2,188644689 User resistance 1/5 1 2 0,142857143 0,153846154 0,25 0,182234432 0,089929281 0,552655678 SA P purchasing 1/5 1/2 1 0,142857143 0,076923077 0,125 0,11492674 0,056714195 0,346611722 Total 1 2/5 6 1/2 8 lmax 3,087912088 Priority vector 5/7 1/5 1/9 CI 0,043956044 RC 0,58 CR 0,075786283 Brand image Innovation Priority vector Global priority Brand image 1 3 0,75 0,039471317 Innovation 1/3 1 0,25 0,013157106 Total 1 1/3 4 Lifespan Confort Traceability Normalized Priority vector Global priority lmax Lifespan 1 1/7 1/5 0,076923077 0,096774194 0,04761905 0,073772106 0,006865233 0,222252607 Confort 7 1 3 0,538461538 0,677419355 0,71428571 0,643388869 0,059873778 2,008310686 Traceability 5 1/3 1 0,384615385 0,225806452 0,23809524 0,282839025 0,026321004 0,866162511 Total 13 1 1/2 4 1/5 lmax 3,096725804 Priority vector 0 2/3 2/7 CI 0,048362902 RC 0,58 CR 0,083384313 III.CRITERIA COMPARISON Economic Environmental Social Relational Functional Normalized Economic 1 1/3 1/5 3 3 0,10344828 0,066666667 0,106598985 0,176470588 0,2432432 Environmental 3 1 1/3 3 3 0,31034483 0,2 0,177664975 0,176470588 0,2432432 Social 5 3 1 7 5 0,51724138 0,6 0,532994924 0,411764706 0,4054054 Relational 1/3 1/3 1/7 1 1/3 0,03448276 0,066666667 0,076142132 0,058823529 0,027027 Functional 1/3 1/3 1/5 3 1 0,03448276 0,066666667 0,106598985 0,176470588 0,0810811 Total 9 2/3 5 1 7/8 17 12 1/3 priority vector 0,139285552 0,221544727 0,493481283 0,052628423 0,093060016 IV.ALTERNATIVES PRIORITIZATION Economic Environmental Social Relational Functional Ranking LC 0,25 0,3125 0,147779304 0,1875 0,50 0,23337827 LL 0,75 0,6875 0,852220696 0,8125 0,50 0,734375 Total 1 1 1 1 1 0,96775327 Priority vector 0,139285552 0,221544727 0,493481283 0,052628423 0,093060016 Carbon footprint Chemical use Environmental LC 0,125 0,5 0,3125 LL 0,875 0,5 0,6875 Priority 0,5 0,5 Local job User resistance SAP purchasing Social LC 0,125 0,25 0,125 0,147779304 LL 0,875 0,75 0,875 0,852220696 Priority 0,702838828 0,182234432 0,11492674 Brand image Innovation Relational LC 0,166666667 0,25 0,1875 LL 0,833333333 0,75 0,8125 Priority 0,75 0,25 Lifespan Confort Traceability Functional LC 0,5 0,50 0,50 0,5 LL 0,5 0,50 0,50 0,5 Priority 0,073772106 0,643388869 0,282839025 SUBCRITERION 2 : Chemical use SUBCRITERION 2 : User resistance SUBCRITERION 3 : SAP purchasing SUBCRITERION 2 : Innovation SUBCRITERION 2 : Confort SUBCRITERION 3 : Traceability CRITERION 1 : Economic SUBCRITERION 1 : Purchasing cost LC LL Priority vector LC 1 1 0,5 LL 1 1 0,5 Total 2 2 CRITERION 2 : Environmental SUBCRITERION 1 : Carbon footprint LC LL Priority vector LC 1 1/5 0,166666667 LL 5 1 0,833333333 Total 6 1 1/5 LC LL Priority vector LC 1 1/5 0,166666667 LL 5 1 0,833333333 Total 6 1 1/5 CRITERION 3 : Social SUBCRITERION 1 : Local job LC LL Priority vector LC 1 5 0,833333333 LL 1/5 1 0,166666667 Total 1 1/5 6 LC LL Priority vector LC 1 1/5 0,166666667 LL 5 1 0,833333333 Total 6 1 1/5 LC LL Priority vector LC 1 5 0,833333333 LL 1/5 1 0,166666667 Total 1 1/5 6 CRITERION 4 : Relational SUBCRITERION 1 : Brand image LC LL Priority vector LC 1 1 0,5 LL 1 1 0,5 Total 2 2 LC LL Priority vector LC 1 1 0,5 LL 1 1 0,5 Total 2 2 CRITERION 5 : Functional SUBCRITERION 1 : Lifespan LC LL Priority vector LC 1 1/5 0,166666667 LL 5 1 0,833333333 Total 6 1 1/5 LC LL Priority vector LC 1 1/5 0,166666667 LL 5 1 0,833333333 Total 6 1 1/5 LC LL Priority vector LC 1 1 0,5 LL 1 1 0,5 Total 2 2 1 5 1/5 5 5 0,151515152 0,333333333 0,122807018 0,3333333 0,333333 Environmental 1/5 1 1/7 1 1 0,03030303 0,066666667 0,087719298 0,0666667 0,066667 Social 5 7 1 7 7 0,757575758 0,466666667 0,614035088 0,4666667 0,466667 Relational 1/5 1 1/7 1 1 0,03030303 0,066666667 0,087719298 0,0666667 0,066667 Functional 1/5 1 1/7 1 1 0,03030303 0,066666667 0,087719298 0,0666667 0,066667 Total 6 3/5 15 1 5/8 15 15 priority vector 0,254864434 0,063604466 0,554322169 0,063604466 0,06360447 IV.ALTERNATIVES PRIORITIZATION Economic Environmental Social Relational Functional Ranking LC 0,5 0,166666667 0,611111111 0,5 0,28 0,526255538 LL 0,5 0,833333333 0,388888889 0,5 0,72 0,473744462 Total 1 1 1 1 1 1 Priority vector 0,254864434 0,063604466 0,554322169 0,063604466 0,06360447 Carbon footprint Chemical use Environmental LC 0,166666667 0,166666667 0,166666667 LL 0,833333333 0,833333333 0,833333333 Priority 0,5 0,5 Local job User resistance SAP purchasing Social LC 0,833333333 0,166666667 0,833333333 0,611111111 LL 0,166666667 0,833333333 0,166666667 0,388888889 Priority 0,333333333 0,333333333 0,333333333 Brand image Innovation Relational LC 0,5 0,5 0,5 LL 0,5 0,5 0,5 Priority 0,5 0,5 Lifespan Confort Traceability Functional LC 0,166666667 0,17 0,50 0,277777778 LL 0,833333333 0,83 0,50 0,722222222 Priority 0,333333333 0,333333333 0,333333333 SUBCRITERION 2 : Recycling SUBCRITERION 2 : User resistance SUBCRITERION 2 : SAP purchasing SUBCRITERION 2 : Innovation Other product New clothing Energy Normalized Priority vector lmax Other product 1 3 1/5 0,15789473 7 0,27272727 3 0,14893617 0,19318606 0,58781092 New clothing 1/3 1 1/7 0,05263157 9 0,09090909 1 0,10638297 9 0,083307883 0,251061244 Energy 5 7 1 0,78947368 4 0,63636363 6 0,74468085 1 0,723506057 2,272591537 Total 6 1/3 11 1 1/3 lmax 3,111463701 Priority vector 0,19318606 0,083307883 0,723506057 lmax 0,055731851 CI 0,58 RC 0,096089398 CRITERION 3 : Social Local job User resistance SAP purchasing Normalized Priority vector Global priority lmax Local job 1 5 3 0,652173913 0,555555556 2/3 0,63334572 0,125480418 1,94562 User resistance 1/5 1 1/3 0,130434783 0,111111111 0,076923077 0,106156324 0,02103202 0,31966 SAP purchasing 1/3 3 1 0,217391304 0,333333333 0,230769231 0,260497956 0,051610663 0,79008 Total 1 1/2 9 4 1/3 lmax 3,05536 Priority vector 0,63334572 0,106156324 0,260497956 CI 0,02768 RC 0,58 Other product New clothing Energy Normalized Priority vector lmax Other product 1 1 2 0,4 0,454545455 0,25 0,368181818 1,138636364 New clothing 1 1 5 0,4 0,454545455 0,625 0,493181818 1,554545455 Energy 1/2 1/5 1 0,2 0,090909091 0,125 0,138636364 0,421363636 Total 2 1/2 2 1/5 8 lmax 3,114545455 Priority vector 0,368181818 0,493181818 0,138636364 CI 0,057272727 RC 0,58 CR 0,098746082 CRITERION 3 : Social Local job User resistance SA P purchasing Normalized Priority vector Global priority lmax Local job 1 5 3 0,652173913 0,714285714 3/5 0,655486542 0,085152017 2,0045549 User resistance 1/5 1 1 0,130434783 0,142857143 0,2 0,157763975 0,020494579 0,4756108 SA P purchasing 1/3 1 1 0,217391304 0,142857143 0,2 0,186749482 0,024259987 0,563009 Total 1 1/2 7 5 lmax 3,0431746 Priority vector 2/3 1/6 1/5 CI 0,0215873 RC 0,58 CR 0,0372195 Other product New clothing Energy Normalized Priority vector Other product New clothing Energy Normalized Priority vector lmax Other product New clothing Energy Normalized Priority vector lmax lmax Other product 1 3 3 3/5 0,5 0,66666666 0,588888889 1,822222222 New clothing 1/3 1 1/2 0,2 0,16666666 7 0,11111111 0,159259259 0,481481481 Energy 1/3 2 1 0,2 0,33333333 3 0,22222222 0,251851852 0,766666667 Total 1 2/3 6 4 1/2 lmax 3,07037037 Priority vector 0,588888889 0,159259259 0,251851852 CI 0,035185185 RC 0,58 CR 0,060664112 CRITERION 3 : Social Local job User resistance SAP purchasing Normalized Priority vector Global priority lmax Local job 1 3 1 0,428571429 0,333333333 4/9 0,405483405 0,049317449 1,22991823 User resistance 1/3 1 1/5 0,142857143 0,111111111 0,090909091 0,114959115 0,013982053 0,34603175 SAP purchasing 1 5 1 0,428571429 0,555555556 0,454545455 0,47955748 0,058326805 1,45983646 Total 2 1/3 9 2 1/5 lmax 3,0357864 4 Priority vector 2/5 1/9 1/2 CI 0,0178932 2 RC 0,58 Other product 1 1/7 1/5 0,076923077 0,09677419 4 0,04761904 0,073772106 0,222252607 New clothing 7 1 3 0,538461538 0,67741935 5 0,71428571 0,643388869 2,008310686 Energy 5 1/3 1 0,384615385 0,22580645 2 0,23809523 0,282839025 0,866162511 Total 13 1 1/2 4 1/5 lmax 3,096725804 Priority vector 0,073772106 0,643388869 0,282839025 CI 0,048362902 RC 0,58 CR 0,083384313 CRITERION 3 : Social Local job User resistance SAP purchasing Normalized Priority vector Global priority lmax Local job 1 7 5 0,744680851 0,636363636 4/5 0,723506057 0,272092355 2,27259153 User resistance 1/7 1 1/3 0,106382979 0,090909091 0,052631579 0,083307883 0,031329991 0,25106124 SAP purchasing 1/5 3 1 0,14893617 0,272727273 0,157894737 0,19318606 0,072652398 0,58781092 Total 1 1/3 11 6 1/3 lmax 3,1114637 Priority vector 5/7 0 1/5 CI 0,055731851 RC 0,58 Other product 1 1 3 0,42857142 9 0,46666666 7 0,27272727 0,389321789 CRITERION 3 : Social 1,2002886 New clothing 1 1 7 0,42857142 9 0,46666666 7 0,63636363 0,510533911 Local job User resistance SAP purchasing Normalized Priority vector Global priority lmax 1,600865801 Energy 1/3 1/7 1 0,14285714 3 0,06666666 7 0,09090909 0,1001443 Local job 1 1 1 0,333333333 0,333333333 1/3 0,333333333 0,066666667 1 0,302851646 Total 2 1/3 2 1/7 11 lmax User resistance 1 1 1 0,333333333 0,333333333 0,333333333 0,333333333 0,066666667 1 3,104006047 Priority vector 0,389321789 0,510533911 0,1001443 CI SAP purchasing 1 1 1 0,333333333 0,333333333 0,333333333 0,333333333 0,066666667 1 0,052003023 RC Total 3 3 3 lmax 3 0,58 CR Priority vector 1/3 1/3 1/3 CI 0 0,089660385 RC 0,58 CR Other product New clothing Energy Normalized Priority vector lmax Other product 1 5 7 0,744680851 0,789473684 0,636363636 0,723506057 2,272591537 New clothing 1/5 1 3 0,14893617 0,157894737 0,272727273 0,19318606 0,58781092 Energy 1/7 1/3 1 0,106382979 0,052631579 0,090909091 0,083307883 0,251061244 Total 1 1/3 6 1/3 11 lmax 3,111463701 Priority vector 0,723506057 0,19318606 0,083307883 CI 0,055731851 RC 0,58 CR 0,096089398 CRITERION 3 : Social SUBCRITERION 1 : Local job Other product New clothing Energy Normalized Priority vector lmax Other product 1 5 5 0,71428571 4 0,71428571 4 0,71428571 4 0,714285714 2,142857143 New clothing 1/5 1 1 0,14285714 3 0,14285714 3 0,14285714 3 0,142857143 0,428571429 Energy 1/5 1 1 0,14285714 3 0,14285714 3 0,14285714 3 0,142857143 0,428571429 Total 1 2/5 7 7 lmax 3 Priority vector 0,71428571 4 0,14285714 3 0,14285714 3 CI 0,00 RC 0,58 CR 0,00 Other product New clothing Energy Normalized Priority vector lmax Other product 1 1 1 0,33333333 3 0,33333333 3 0,33333333 3 0,333333333 1 New clothing 1 1 1 0,33333333 3 0,33333333 3 0,33333333 3 0,333333333 1 Energy 1 1 1 0,33333333 3 0,33333333 3 0,33333333 3 0,333333333 1 Total 3 3 3 lmax 3 Priority vector 0,333333333 0,333333333 0,333333333 CI 0 RC 0,58 CR 0 Other product New clothing Energy Normalized Priority vector lmax Other product 1 5 7 0,74468085 1 0,78947368 4 0,63636363 6 0,723506057 2,272591537 New clothing 1/5 1 3 0,14893617 0,15789473 7 0,27272727 3 0,19318606 0,58781092 Energy 1/7 1/3 1 0,10638297 9 0,05263157 9 0,09090909 1 0,083307883 0,251061244 Total 1 1/3 6 1/3 11 lmax 3,111463701 Priority vector 0,723506057 0,19318606 0,083307883 CI 0,055731851 RC 0,58 CRITERION 4 : SUBCRITERION 1 : Brand image Other product New clothing Energy Normalized Priority vector lmax Other product 1 7 5 0,74468085 1 0,77777777 8 0,71428571 4 0,745581448 2,257908364 New clothing 1/7 1 1 0,10638297 9 0,11111111 1 0,14285714 3 0,120117078 0,360930188 Energy 1/5 1 1 0,14893617 0,11111111 1 0,14285714 3 0,134301475 0,403534842 Total 1 1/3 9 7 lmax 3,022373394 Priority vector 0,745581448 0,120117078 0,134301475 CI 0,011186697 RC 0,58 CR 0,019287408 CRITERION 5 : Functional SUBCRITERION 1 : fiber quality Other product New clothing Energy Normalized Priority vector lmax Other product 1 3 7 0,67741935 5 0,71428571 4 0,53846153 8 0,643388869 2,008310686 New clothing 1/3 1 5 0,22580645 2 0,23809523 8 0,38461538 5 0,282839025 0,866162511 Energy 1/7 1/5 1 0,09677419 4 0,04761904 8 0,07692307 7 0,073772106 0,222252607 Total 1 1/2 4 1/5 13 lmax 3,096725804 Priority vector 0,643388869 0,282839025 0,073772106 CI 0,048362902 RC 0,58 CR 0,083384313 Other product New clothing Energy Normalized Priority vector lmax Other product 1 5 7 0,74468085 1 0,78947368 4 0,63636363 6 0,723506057 2,272591537 New clothing 1/5 1 3 0,14893617 0,15789473 7 0,27272727 3 0,19318606 0,58781092 Energy 1/7 1/3 1 0,10638297 9 0,05263157 9 0,09090909 1 0,083307883 0,251061244 Total 1 1/3 6 1/3 11 lmax 3,111463701 Priority vector 0,723506057 0,19318606 0,083307883 CI 0,055731851 RC 0,58 CR Other product 1 1 2 0,4 0,454545455 0,25 0,368181818 1,138636364 New clothing 1 1 5 0,4 0,454545455 0,625 0,493181818 1,554545455 Energy 1/2 1/5 1 0,2 0,090909091 0,125 0,138636364 0,421363636 Total 2 1/2 2 1/5 8 lmax 3,114545455 Priority vector 0,368181818 0,493181818 0,138636364 CI 0,057272727 RC 0,58 CR 0,098746082 CRITERION 5 : SUBCRITERION 1 : Other product New clothing Energy Normalized Priority vector Other product 1 5 3 0,65217391 3 0,55555555 6 0,69230769 0,63334572 1,945621206 New clothing 1/5 1 1/3 0,13043478 3 0,11111111 1 0,07692307 0,106156324 0,31965812 Energy 1/3 3 1 0,21739130 4 0,33333333 3 0,23076923 0,260497956 0,790082167 Total 1 1/2 9 4 1/3 lmax 3,055361493 Priority vector 0,63334572 0,106156324 0,260497956 CI 0,027680747 RC 0,58 CR 0,047725425 Other product 1 1/3 5 0,238095238 0,22580645 2 0,38461538 0,282839025 New clothing 3 1 7 0,714285714 0,67741935 5 0,53846153 0,643388869 Energy 1/5 1/7 1 0,047619048 0,09677419 4 0,07692307 0,073772106 Total 4 1/5 1 1/2 13 lmax Priority vector 0,282839025 0,643388869 0,073772106 CI RC CR CR 0,089660385 0,083384313 RC 0,58 0,58 Priority vector 0,389321789 0,510533911 0,1001443 CI 0,052003023 0,048362902 Total 2 1/3 2 1/7 11 lmax 3,104006047 3,096725804 Energy 1/3 1/7 1 0,14285714 3 0,06666666 7 0,09090909 0,1001443 0,302851646 0,222252607 New clothing 1 1 7 0,42857142 9 0,46666666 7 0,63636363 0,510533911 1,600865801 2,008310686 Other product 1 1 3 0,42857142 9 0,46666666 7 0,27272727 0,389321789 1,2002886 0,866162511 lmax Other product New clothing Energy Normalized Priority vector Other product New clothing Energy Normalized Priority vector lmax lmax fiber quality SUBCRITERION 1 : SUBCRITERION 1 : fiber quality recycling capability Functional CR 0,019157088 CRITERION 5 : CRITERION 5 : Functional Functional CR CR 0,089660385 0,086958155 0,096089398 SUBCRITERION 2 : Innovation Other product 1 1 2 0,4 0,454545455 0,25 0,368181818 1,138636364 New clothing 1 1 5 0,4 0,454545455 0,625 0,493181818 1,554545455 Energy 1/2 1/5 1 0,2 0,090909091 0,125 0,138636364 0,421363636 Total 2 1/2 2 1/5 8 lmax 3,114545455 Priority vector 0,368181818 0,493181818 0,138636364 CI 0,057272727 RC 0,58 CR 0,098746082 CRITERION 5 : Functional SUBCRITERION 1 : Revaluation capability Other product New clothing Energy Normalized Priority vector lmax Other product New clothing Energy Normalized Priority vector lmax Other product 1 1 2 0,4 0,454545455 0,25 0,368181818 New clothing 1 1 5 0,4 0,454545455 0,625 0,493181818 1,554545455 Energy 1/2 1/5 1 0,2 0,090909091 0,125 0,138636364 Total 2 1/2 2 1/5 8 lmax Priority vector 0,368181818 0,493181818 0,138636364 CI 0,057272727 RC 0,58 CR 0,098746082 Other product 1 3 2 5/9 0,6 0,5 0,548484848 New clothing 1/3 1 1 0,18181818 2 0,2 0,25 0,210606061 0,634343434 Energy 1/2 1 1 0,27272727 3 0,2 0,25 0,240909091 Total 1 5/6 5 4 lmax 3,022222222 Priority vector 0,548484848 0,210606061 0,240909091 CI 0,011111111 RC 0,58 Total 8 1/2 1 2/7 10 lmax Priority vector 0,14291939 0,767102397 0,089978214 CI RC RC 0,58 0,58 Priority vector 0,389321789 0,510533911 0,1001443 CI 0,052003023 0,05043573 Total 2 1/3 2 1/7 11 lmax 3,104006047 3,10087146 0,725757576 New clothing 7 1 7 0,823529412 0,77777777 8 0,7 0,767102397 1/2 1/7 1 0,058823529 0,11111111 1 0,1 0,089978214 0,271023965 Energy 1/3 1/7 1 0,14285714 3 0,06666666 7 0,09090909 0,1001443 0,302851646 Energy New clothing 1 1 7 0,42857142 9 0,46666666 7 0,63636363 0,510533911 1,600865801 2,397385621 1,662121212 Other product 1 1/7 2 0,117647059 0,11111111 1 0,2 0,14291939 Other product 1 1 3 0,42857142 9 0,46666666 7 0,27272727 0,389321789 1,2002886 0,432461874 3,114545455 Other product New clothing Energy Normalized Priority vector lmax Other product New clothing Energy Normalized Priority vector lmax Other product New clothing Energy Normalized Priority vector lmax 0,421363636 SUBCRITERION 2 : Innovation CR SUBCRITERION 2 : Innovation SUBCRITERION 2 : Innovation 0 1,138636364 CRITERION 4 : SUBCRITERION 1 : Brand image Other product New clothing Energy Normalized Priority vector lmax Other product 1 1 1 0,33333333 3 0,33333333 3 0,33333333 0,333333333 1 New clothing 1 1 1 0,33333333 3 0,33333333 3 0,33333333 0,333333333 1 Energy 1 1 1 0,33333333 3 0,33333333 3 0,33333333 0,333333333 1 Total 3 3 3 lmax 3 Priority vector 0,333333333 0,333333333 0,333333333 CI 0 RC 0,58 Other product New clothing Energy Normalized Priority vector Other product 1 1/5 3 0,157894737 0,14893617 0,272727273 0,19318606 New clothing 5 1 7 0,789473684 0,744680851 0,636363636 0,723506057 Energy 1/3 1/7 1 0,052631579 0,106382979 0,090909091 0,083307883 Total 6 1/3 1 1/3 11 lmax Priority vector 0,19318606 0,723506057 0,083307883 CI RC CR CR 0,089660385 0,096089398 RC 0,58 0,58 Priority vector 0,389321789 0,510533911 0,1001443 CI 0,052003023 0,055731851 Total 2 1/3 2 1/7 11 lmax 3,104006047 3,111463701 Energy 1/3 1/7 1 0,14285714 3 0,06666666 7 0,09090909 0,1001443 0,302851646 0,251061244 New clothing 1 1 7 0,42857142 9 0,46666666 7 0,63636363 0,510533911 1,600865801 2,272591537 Other product 1 1 3 0,42857142 9 0,46666666 7 0,27272727 0,389321789 1,2002886 0,58781092 Other product New clothing Energy Normalized Priority vector lmax lmax Relational SUBCRITERION 1 : SUBCRITERION 1 : Brand image Brand image Relational CRITERION 2 : Environmental SUBCRITERION 1 : Carbon footprint Other product New clothing Energy Normalized Priority vector lmax Other product 1 5 3 0,65217391 3 0,71428571 4 0,6 0,655486542 2,004554865 New clothing 1/5 1 1 0,13043478 3 0,14285714 3 0,2 0,157763975 0,475610766 Energy 1/3 1 1 0,21739130 4 0,14285714 3 0,2 0,186749482 0,563008972 Total 1 1/2 7 5 lmax 3,043174603 Priority vector 0,655486542 0,157763975 0,186749482 CI 0,021587302 RC 0,58 CR 0,037219485 CRITERION 4 : Relational CR 0,04773 Brand image Innovation Priority vector Global priority Brand image 1 1/3 0,25 0,049530775 Innovation 3 1 0,75 0,148592326 Total 4 1 1/3 III.CRI T E RI A COM P A R I S O N Economic Environmental Social Relational Functional Normalized Economic 1 1/5 1/3 1/3 5 0,081967213 0 0,060240964 0,06024 0,217391 Environmental 5 1 3 3 7 0,409836066 0,497630332 0,542168675 0,54217 0,304348 Social 3 1/3 1 1 5 0,245901639 0,165876777 0,180722892 0,18072 0,217391 Relational 3 1/3 1 1 5 0,245901639 0,165876777 0,180722892 0,18072 0,217391 Functional 1/5 1/7 1/5 1/5 1 0,016393443 0,071090047 0,036144578 0,03614 0,043478 12 1/5 2 5 1/2 5 1/2 23 priority vector 0,103873302 0,459230315 0,198123101 0,198123101 0,040650182 IV.ALT E R N A T I V E S PRI O R I T I Z A T I O N Economic Environmental Social Relational Functional Ranking Other product 0,19318606 0,712169471 0,676247091 0,729024905 0,64 0,651687404 New clothing 0,083307883 0,187282379 0,176187975 0,174918814 0,28 0,175719034 Energy 0,723506057 0,100548149 0,147564934 0,096056281 0,07 0,172593562 Total 1 1 1 1 1,00 1 Priority vector 0,103873302 0,459230315 0,198123101 0,198123101 0,040650182 Carbon footprint Recycling Environmental Other product 0,655486542 0,723506057 0,712169471 New clothing 0,157763975 0,19318606 0,187282379 Energy 0,186749482 0,083307883 0,100548149 Priority 0,166666667 0,833333333 Local job User resistance SAP purchasing Social Other product 0,714285714 0,333333333 0,723506057 0,676247091 New clothing 0,142857143 0,333333333 0,19318606 0,176187975 Energy 0,142857143 0,333333333 0,083307883 0,147564934 Priority 0,63334572 0,106156324 0,260497956 Brand image Innovation Relational Other product 0,745581448 0,723506057 0,729024905 New clothing 0,120117078 0,19318606 0,174918814 Energy 0,134301475 0,083307883 0,096056281 Priority 0,25 0,75 SUBCRITERION 2 : Recycling SUBCRITERION 2 : User resistance CRITERION 2 : Environmental SUBCRITERION 1 : Carbon footprint Other product New clothing Energy Normalized Priority vector lmax Other product 1 1 2 0,4 0,454545455 0,25 0,368181818 1,138636364 New clothing 1 1 5 0,4 0,454545455 0,625 0,493181818 1,554545455 Energy 1/2 1/5 1 0,2 0,090909091 0,125 0,138636364 0,421363636 Total 2 1/2 2 1/5 8 lmax 3,114545455 Priority vector 0,368181818 0,493181818 0,138636364 CI 0,057272727 RC 0,58 CR 0,098746082 Other product New clothing Energy Normalized Priority vector lmax Other product 1 1 2 0,4 0,454545455 0,25 0,368181818 1,138636364 New clothing 1 1 5 0,4 0,454545455 0,625 0,493181818 1,554545455 Energy 1/2 1/5 1 0,2 0,090909091 0,125 0,138636364 0,421363636 Total 2 1/2 2 1/5 8 lmax 3,114545455 Priority vector 0,368181818 0,493181818 0,138636364 CI 0,057272727 RC 0,58 CR 0,098746082 CRITERION 3 : Social SUBCRITERION 1 : Local job Other product New clothing Energy Normalized Priority vector lmax Other product 1 1 2 0,4 0,454545455 0,25 0,368181818 1,138636364 New clothing 1 1 5 0,4 0,454545455 0,625 0,493181818 1,554545455 Energy 1/2 1/5 1 0,2 0,090909091 0,125 0,138636364 0,421363636 Total 2 1/2 2 1/5 8 lmax 3,114545455 Priority vector 0,368181818 0,493181818 0,138636364 CI 0,057272727 RC 0,58 CR 0,098746082 Other product New clothing Energy Normalized Priority vector lmax Other product 1 1 2 0,4 4/9 0,25 0,368181818 1,138636364 New clothing 1 1 5 0,4 0,454545455 0,625 0,493181818 1,554545455 Energy 1/2 1/5 1 0,2 0,090909091 0,125 0,138636364 0,421363636 Total 2 1/2 2 1/5 8 lmax 3,114545455 Priority vector 0,368181818 0,493181818 0,138636364 CI 0,057272727 RC 0,58 CR 0,098746082 CRITERION 4 : Relational SUBCRITERION 1 : Brand image Other product New clothing Energy Normalized Priority vector lmax SUBCRITERION 2 : SAP purchasing Other product New clothing Energy Normalized Priority vector lmax Other product 1 1 2 0,4 0,454545455 0,25 0,368181818 1,138636364 New clothing 1 1 5 0,4 0,454545455 0,625 0,493181818 1,554545455 Energy 1/2 1/5 1 0,2 0,090909091 0,125 0,138636364 0,421363636 Total 2 1/2 2 1/5 8 lmax 3,114545455 Priority vector 0,368181818 0,493181818 0,138636364 CI 0,057272727 RC 0,58 CR 0,098746082 CRITERION 4 : Relational Brand image Innovation Priority vector Global priority Brand image 1 1 0,5 0,064953292 Innovation 1 1 0,5 0,064953292 Total 2 2 III. CRITERIA COMPARISON Economic Environmental Social Relational Functional Normalized Economic 1 1/5 1/3 1/3 1/5 0,05882353 0,111111111 0,04 0,04 0,02439 Environmental 5 1 5 5 5 0,29411765 0,555555556 0,6 0,6 CRITERION 2 : CR 0,03085038 CRITERION 2 : Environmental CR 0,09608939 CRITERION 2 : Environmental CR 0 Environmental SUBCRITERION 1 : Carbon footprint Other product New clothing Energy Normalized Priority vector lmax Other product 1 5 5 0,71428571 4 0,625 0,76923076 0,702838828 2,188644689 New clothing 1/5 1 1/2 0,14285714 3 0,125 0,07692307 0,11492674 0,346611722 Energy 1/5 2 1 0,14285714 3 0,25 0,15384615 0,182234432 0,552655678 Total 1 2/5 8 6 1/2 lmax 3,087912088 Priority vector 0,702838828 0,11492674 0,182234432 CI 0,043956044 RC 0,58 CR 0,075786283 CRITERION 4 : Relational Brand image Innovation Priority vector Global priority Brand image 1 5 0,833333333 0,03840419 Innovation 1/5 1 0,166666667 0,007680838 Total 1 1/5 6 III.CRI T E RI A COM P A R I S O N Economic Environmental Social Relational Functional Normalized SUBCRITERION 1 : Carbon footprint Other product New clothing Energy Normalized Priority vector lmax Other product 1 1/5 3 0,157894737 0,14893617 0,27272727 0,19318606 0,58781092 New clothing 5 1 7 0,789473684 0,74468085 1 0,63636363 0,723506057 2,272591537 Energy 1/3 1/7 1 0,052631579 0,10638297 9 0,09090909 0,083307883 0,251061244 Total 6 1/3 1 1/3 11 lmax 3,111463701 Priority vector 0,19318606 0,723506057 0,083307883 CI 0,055731851 RC 0,58 CR 0,096089398 CRITERION 4 : Relational Brand image Innovation Priority vector SUBCRITERION 1 : Carbon footprint CRITERION 4 : Relational Global priority Brand image 1 1/5 0,166666667 0,010685762 Innovation 5 1 0,833333333 0,053428811 Total 6 1 1/5 III.CRI T E RI A Other product New clothing Energy Normalized Priority vector lmax Other product 1 1 3 0,42857142 9 0,46666666 7 0,27272727 0,389321789 Brand image Innovation Priority vector Global priority 1,2002886 New clothing 1 1 7 0,42857142 9 0,46666666 7 0,63636363 0,510533911 Brand image 1 1 0,5 0,1 1,600865801 Energy 1/3 1/7 1 0,14285714 3 0,06666666 7 0,09090909 0,1001443 Innovation 1 1 0,5 0,1 0,302851646 Total 2 1/3 2 1/7 11 lmax Total 2 2 3,104006047 COM P A R I S O N Economic Environmental Social Relational Functional Priority vector 0,389321789 0,510533911 0,1001443 CI 0,052003023 RC III.CRI T E RI A COM P A R I S O N 0,58 Normalized Economic 1 1/5 1/3 1 1 0,090909091 0,08045977 0,127272727 0,058823529 0,058823529 CR 0,089660385 Economic Environmental Social Relational Functional Normalized 0,609756 Social 3 1/5 1 1 1 0,17647059 0,111111111 0,12 0,12 0,121951 Relational 3 1/5 1 1 1 0,17647059 0,111111111 0,12 0,12 0,121951 Functional 5 1/5 1 1 1 0,29411765 0,111111111 0,12 0,12 0,121951 17 1 4/5 8 1/3 8 1/3 8 1/5 priority vector 0,054864977 0,53188586 0,129906584 0,129906584 0,153435996 IV. ALTERNATIVES PRIORITIZATION Economic Environmental Social Relational Functional Ranking Other product 0,368181818 0,368181818 0,368181818 0,368181818 0,37 0,36818182 New clothing 0,493181818 0,493181818 0,493181818 0,493181818 0,49 Energy 0,138636364 0,138636364 0,138636364 0,138636364 0,14 0,13863636 Total 1 1 1 1 1,00 1 Priority vector 0,054864977 0,53188586 0,129906584 0,129906584 0,153435996 Carbon footprint Recycling Environmental Other product 0,368181818 0,368181818 0,368181818 New clothing 0,493181818 0,493181818 0,493181818 Energy 0,138636364 0,138636364 0,138636364 Priority 0,166666667 0,833333333 Local job User resistance SAP purchasing Social Other product 0,368181818 0,368181818 0,368181818 0,368181818 New clothing 0,493181818 0,493181818 0,493181818 0,493181818 Energy 0,138636364 0,138636364 0,138636364 0,138636364 Priority 0,655486542 0,157763975 0,186749482 Brand image Innovation Relational Other product 0,368181818 0,368181818 0,368181818 New clothing 0,493181818 0,493181818 0,493181818 Energy 0,138636364 0,138636364 0,138636364 Priority 0,5 SUBCRITERION 2 : Other product New clothing Energy Normalized Priority vector lmax Other product 1 5 5 0,71428571 4 0,71428571 4 0,71428571 0,714285714 2,142857143 New clothing 1/5 1 1 0,14285714 3 0,14285714 3 0,14285714 0,142857143 0,428571429 Energy 1/5 1 1 0,14285714 3 0,14285714 3 0,14285714 0,142857143 Total 1 2/5 7 7 lmax Priority vector 0,714285714 0,142857143 0,142857143 CI RC CR CRITERION 4 : CRITERION 4 : Relational Relational -7,65671E-16 CR 0,086958155 0,58 RC CR 0,089660385 0,58 -4,44089E-16 Priority vector 0,14291939 0,767102397 0,089978214 CI RC 0,58 0,05043573 3 8 1/2 1 2/7 10 lmax 3,10087146 Priority vector 0,389321789 0,510533911 0,1001443 CI 0,052003023 Total 0,428571429 New clothing 0,333333333 0,210606061 0,312878788 Energy 0,333333333 0,240909091 0,317929293 Priority 0,833333333 0,166666667 Other product New clothing Energy Normalized Priority vector lmax Other product 1 1/7 2 0,117647059 0,111111111 0,2 0,14291939 0,432461874 New clothing 7 1 7 0,823529412 0,777777778 0,7 0,767102397 2,397385621 Energy 1/2 1/7 1 0,058823529 0,111111111 0,1 0,089978214 0,271023965 Other product 0,19318606 0,14291939 New clothing 0,723506057 0,767102397 Energy 0,083307883 0,089978214 Priority 0,166666667 Total 2 1/3 2 1/7 11 lmax 3,104006047 0,833333333 Energy 1/3 1/7 1 0,14285714 3 0,06666666 7 0,09090909 0,1001443 0,302851646 0,088866492 New clothing 1 1 7 0,42857142 9 0,46666666 7 0,63636363 0,510533911 1,600865801 0,75983634 Other product 1 1 3 0,42857142 9 0,46666666 7 0,27272727 0,389321789 1,2002886 0,151297168 SAP purchasing Other product 0,333333333 0,548484848 0,369191919 SUBCRITERION 2 : SAP purchasing Brand image Innovation Relational Other product New clothing Energy Normalized Priority vector lmax 0,5 SUBCRITERION 2 : Other product New clothing Energy Normalized Priority vector lmax Other product 1 5 5 0,71428571 4 0,71428571 4 0,71428571 0,714285714 2,142857143 New clothing 1/5 1 1 0,14285714 3 0,14285714 3 0,14285714 0,142857143 0,428571429 Energy 1/5 1 1 0,14285714 3 0,14285714 3 0,14285714 0,142857143 0,428571429 Total 1 2/5 7 7 lmax 3 Priority vector 0,714285714 0,142857143 0,142857143 CI -4,44089E-16 RC 0,58 CR Brand image Innovation Relational SUBCRITERION 2 : SAP purchasing -7,65671E-16 Priority 0,166666667 0,833333333 Local job User resistance SAP purchasing Social Other product 0,405483405 0,714285714 0,714285714 0,589071502 New clothing 0,114959115 0,142857143 0,142857143 0,131544955 Energy 0,47955748 0,142857143 0,142857143 0,279383542 Priority 0,405483405 0,114959115 0,47955748 Other product New clothing Energy Normalized Priority vector lmax Other product 1 3 3 3/5 0,6 0,6 0,6 1,8 New clothing 1/3 1 1 0,2 0,2 0,2 0,2 Energy 1/3 1 1 0,2 0,2 0,2 0,2 0,6 Total 1 2/3 5 5 lmax 3 Priority vector 0,6 0,2 0,2 CI 0% RC 0,58 CR 0% Local job User resistance SAP purchasing Other product 0,47955748 0,6 0,14291939 New clothing 0,405483405 0,2 0,767102397 Energy 0,114959115 0,2 0,089978214 Priority 0,723506057 0,083307883 0,19318606 CR 0,089660385 0,117217729 RC 0,58 0,458224766 Priority vector 0,389321789 0,510533911 0,1001443 CI 0,052003023 0,424557505 Total 2 1/3 2 1/7 11 lmax 3,104006047 Social Energy 1/3 1/7 1 0,14285714 3 0,06666666 7 0,09090909 0,1001443 0,302851646 0,6 Energy 0,083307883 0,083307883 Priority 0,166666667 New clothing 1 1 7 0,42857142 9 0,46666666 7 0,63636363 0,510533911 1,600865801 0,833333333 Other product 1 1 3 0,42857142 9 0,46666666 7 0,27272727 0,389321789 1,2002886 0,083307883 User resistance CRITERION 3 : SUBCRITERION 1 : Other product New clothing Energy Normalized Priority vector lmax Other product 1 3 1 0,42857142 9 0,33333333 3 0,45454545 0,405483405 1,22991823 New clothing 1/3 1 1/5 0,14285714 3 0,11111111 1 0,09090909 0,114959115 0,346031746 Energy 1 5 1 0,42857142 9 0,55555555 6 0,45454545 0,47955748 1,45983646 Total 2 1/3 9 2 1/5 lmax 3,035786436 Priority vector 0,40548340 5 0,11495911 5 0,47955748 CI 0,017893218 RC 0,58 CR Energy 0,182234432 0,363065437 0,332926936 New clothing 0,723506057 0,723506057 Other product New clothing Energy Normalized Priority vector lmax 0,723506057 0,030850376 New clothing 0,159259259 0,074453827 0,131544955 0,312878788 0,11 0,123244495 Energy 0,251851852 0,332926936 0,279383542 0,317929293 0,26 0,278774503 Total 1 1 1 1 1,00 1 Priority vector 0,209034764 0,209034764 0,121626307 0,046085028 0,414219138 Carbon footprint Recycling Other product 0,702838828 0,570575318 0,592619237 New clothing 0,11492674 0,066359245 0,074453827 RC 0,58 CR 0,030850376 Carbon footprint Recycling Other product 0,19318606 0,19318606 SUBCRITERION 2 : User resistance 0,19318606 CR 0,089660385 Environmental RC 0,58 Environmental Other product 1 1 5 0,454545455 0,42857142 9 0,55555555 0,47955748 1,45983646 New clothing 1 1 3 0,454545455 0,42857142 9 0,33333333 0,405483405 1,22991823 Energy 1/5 1/3 1 0,090909091 0,14285714 3 0,11111111 0,114959115 0,346031746 Total 2 1/5 2 1/3 9 lmax 3,035786436 Priority vector 0,47955748 0,40548340 5 0,114959115 CI 0,017893218 Other product 0,073772106 0,19318606 0,424557505 0,151297168 0,28 New clothing 0,643388869 0,723506057 0,458224766 0,75983634 0,64 Energy 0,282839025 0,083307883 0,117217729 0,088866492 0,07 Total 1 1 1 1 1,00 Priority vector 0,083257729 0,41243838 0,376074743 0,064114574 Priority vector 0,38932178 9 0,51053391 1 0,1001443 CI 0,052003023 0,064114574 Total 2 1/3 2 1/7 11 lmax 3,104006047 1 Energy 1/3 1/7 1 0,14285714 3 0,06666666 7 0,09090909 0,1001443 0,302851646 0,112418035 New clothing 1 1 7 0,42857142 9 0,46666666 7 0,63636363 0,510533911 1,600865801 0,61426271 Other product 1 1 3 0,42857142 9 0,46666666 7 0,27272727 0,389321789 1,2002886 0,273319255 Local job Other product 0,588888889 0,592619237 0,589071502 0,369191919 0,63 0,597981001 Other product New clothing Energy Normalized Priority vector lmax Economic Environmental Social Relational Functional Other product New clothing Energy Normalized Priority vector lmax Ranking Social Economic Environmental Social Relational Functional Ranking SUBCRITERION 1 : Local job SUBCRITERION 1 : Local job 0,49318182 SUBCRITERION 2 : Recycling Other product New clothing Energy Normalized Priority vector lmax Other product 1 7 2 0,608695652 0,466666667 0,636363636 0,570575318 1,761220905 New clothing 1/7 1 1/7 0,086956522 0,066666667 0,045454545 0,066359245 0,199736495 Energy 1/2 7 1 0,304347826 0,466666667 0,318181818 0,363065437 1,112867809 Total 1 2/3 15 3 1/7 lmax 3,073825209 Priority vector 0,570575318 0,066359245 0,363065437 CI 0,036912604 RC 0,58 CR 0,063642421 Economic 1 1 3 5 1/3 0,180722892 0,180722892 0,294117647 0,23809524 0,151515 Environmental 1 1 3 5 0,333333333 0,180722892 0,180722892 0,294117647 0,23809524 0,151515 Social 1/3 1/3 1 5 1/3 0,060240964 0,060240964 0,098039216 0,23809524 0,151515 Relational 1/5 1/5 1/5 1 1/5 0,036144578 0,036144578 0,019607843 0,04761905 0,090909 Functional 3 3 3 5 1 0,542168675 0,542168675 0,294117647 0,23809524 0,454545 5 1/2 5 1/2 10 1/5 21 2 1/5 priority vector 0,209034764 0,209034764 0,121626307 0,046085028 0,414219138 IV.ALT E R N A T I V E S PRI O R I T I Z A T I O N CRITERION 3 : Social SUBCRITERION 2 : Recycling Other product New clothing Energy Normalized Priority vector lmax Other product 1 1/5 3 0,157894737 0,14893617 0,272727273 0,19318606 0,58781092 New clothing 5 1 7 0,789473684 0,744680851 0,636363636 0,723506057 2,272591537 Energy 1/3 1/7 1 0,052631579 0,106382979 0,090909091 0,083307883 0,251061244 Total 6 1/3 1 1/3 11 lmax 3,111463701 Priority vector 0,19318606 0,723506057 0,083307883 CI RC CR IV.ALT E R N A T I V E S CRITERION 3 : Social PRI O R I T I Z A T I O N CR 0,089660385 0,096089398 RC 0,58 0,58 Priority vector 0,389321789 0,510533911 0,1001443 CI 0,052003023 0,055731851 Environmental 5 1 1 7 7 0,454545455 0,402298851 0,381818182 0,411764706 0,411764706 Social 3 1 1 7 7 0,272727273 0,402298851 0,381818182 0,411764706 Relational 1 1/7 1/7 1 1 0,090909091 0,057471264 0,054545455 0,058823529 Functional 1 1/7 1/7 1 1 0,090909091 0,057471264 0,054545455 0,058823529 11 2 1/2 2 5/8 17 priority vector 0,083257729 0,41243838 0,376074743 0,064114574 Total 2 1/3 2 1/7 11 lmax 3,104006047 0,064114574 Energy 1/3 1/7 1 0,142857143 0,066666667 0,090909091 0,1001443 0,302851646 17 New clothing 1 1 7 0,428571429 0,466666667 0,636363636 0,510533911 1,600865801 0,058823529 Other product 1 1 3 0,428571429 0,466666667 0,272727273 0,389321789 1,2002886 0,058823529 Other product New clothing Energy Normalized Priority vector lmax 0,411764706 SUBCRITERION 2 : Recycling Economic

CRITERION 4 : Relational SUBCRITERION 1 : Brand image Other product New clothing Energy Normalized Priority vector lmax Other product

	5 0,2 Environmental 0,389321789 0,510533911 0,1001443 1 0,2 Recycling 0,389321789 0,510533911 0,1001443 0,833333333 User resistance 0,389321789 0,510533911 0,1001443 0,333333333 Innovation 0,389321789 0,510533911 0,1001443 0,5 Recycling Recycling Recycling New clothing 2 1 7 10 0,089978214 New clothing 2 1 1/5 3 1/5 0,353721034 New clothing 2 1 1 4 0,261111111 New clothing 1 1 1/5 2 1/5 0,45454545 5 New clothing 5 1 1/3 6 1/3 0,19318606 New clothing 2 1 1/9 3 1/9 0,36848587 0,387301587 1 5 New clothing 0,739577046 0,45454545 5 0,2 PRI O R I T I Z A T I O N Economic 0,389321789 0,510533911 0,1001443 1 0,2 Carbon footprint 0,389321789 0,510533911 0,1001443 0,166666667 Local job 0,389321789 0,510533911 0,1001443 0,333333333 Brand image 0,389321789 0,510533911 0,1001443 0,5 Recycling User resistance Actor A6 priority vector IV.ALT E R N A T I V E S Other product New clothing Energy Total Priority vector Other product New clothing Energy Priority Other product New clothing Energy Priority Other product New clothing Energy Priority SUBCRITERION 2 : SUBCRITERION 2 : I.ALT E R N A T I V E S CRITERION 2 : Environmental II.SUB-C R I T E R I A COM P A RI S O N Carbon footprint CRITERION 2 : Environmental II.SUB-C R I T E R I A COM P A RI S O N II.SUB-C R I T E R I A COM P A RI S O N Actor A8 CRITERION 2 : Environmental Actor A7 Carbon footprint I.ALT E R N A T I V E S COM P A R I S O N Carbon footprint COM P A R I S O N CRITERION 1 : Economic SUBCRITERION 2 : Purchasing cost Other product Other product 1 New clothing 1/2 Energy 7 Total 8 1/2 Priority vector 0,14291939 CRITERION 2 : Environmental SUBCRITERION 1 : Carbon footprint Other product Other product 1 New clothing 1/2 Energy 1/5 Total 1 2/3 Priority vector 0,555926916 Other product Other product 1 New clothing 1/2 Energy 1 Total 2 1/2 Priority vector 0,411111111 CRITERION 3 : Social SUBCRITERION 1 : Local job Other product Other product 1 New clothing 1 Energy 1/5 Total 2 1/5 Priority vector Other product Other product 1 New clothing 1/5 Energy 1/7 Total 1 1/3 Priority vector 0,723506057 CRITERION 4 : Relational SUBCRITERION 1 : Brand image Other product Other product 1 New clothing 1/2 Energy 1/9 Total 1 3/5 Priority vector 0,579077003 Priority vector 0,442857143 New clothing 1/5 Other product 1 Other product A9 0,967499653 0,806899506 SAP purchasing 5 0,2 Social 0,389321789 0,510533911 0,1001443 1 0,2 Environmental 0,389321789 0,510533911 0,1001443 0,389321789 0,510533911 0,1001443 0,333333333 Relational 0,389321789 0,510533911 0,1001443 Priority vector Global priority Priority vector Global priority 5 0,2 Relational 0,389321789 0,510533911 0,1001443 1 0,2 Social 0,389321789 0,510533911 0,1001443 Priority vector Global priority Energy Normalized 1/7 0,11764705 9 0,2 0,11111111 5 0,2 Functional 0,39 0,51 0,10 1,00 0,2 1/7 0,05882352 9 0,1 0,11111111 1 0,82352941 2 0,7 0,77777777 1 2/7 0,767102397 Energy Normalized 5 0,58823529 4 0,625 0,45454545 5 0,29411764 7 0,3125 0,45454545 1 0,11764705 9 0,0625 0,09090909 11 0,09035205 Energy Normalized 1 0,4 0,5 0,333333333 1 0,2 0,25 0,333333333 1 0,4 0,25 0,333333333 3 0,327777778 Energy Normalized 5 0,45454545 5 0,45454545 5 0,45454545 5 0,45454545 5 0,45454545 5 0,45454545 1 0,09090909 1 0,09090909 1 0,09090909 11 0,09090909 1 Energy Normalized 7 0,74468085 1 0,78947368 4 0,63636363 3 0,14893617 1/6 0,27272727 1 0,10638297 9 0,05263157 9 0,09090909 11 0,083307883 Energy Normalized 9 0,62068965 5 0,64285714 3 0,47368421 9 0,31034482 8 0,32142857 1 0,47368421 1 0,06896551 7 0,03571428 6 0,05263157 19 0,052437127 0,16984127 3 0,14893617 0,15789473 7 7 0,74468085 1 0,78947368 4 Energy Normalized 0,742711506 0,960212619 SUBCRITERION 2 : SAP purchasing Other product New clothing Energy Normalized Other product 1 1 3 0,42857142 9 0,42857142 9 0,42857142 New clothing 1 1 3 0,42857142 9 0,42857142 9 0,42857142 Energy 1/3 1/3 1 0,14285714 3 0,14285714 3 0,14285714 Total 2 1/3 2 1/3 7 Priority vector 0,428571429 0,428571429 0,142857143 CRITERION 4 : Relational SUBCRITERION 1 : Brand image Other product New clothing Energy Normalized Other product 1 1 3 0,42857142 9 0,4 New clothing 1 1 2 0,42857142 9 0,4 0,33333333 Ranking 0,389321789 0,510533911 0,1001443 1 Priority vector 0,14291939 0,089978214 0,767102397 lmax CI RC CR Priority vector 0,555926916 0,353721034 0,09035205 lmax CI RC CR Priority vector 0,411111111 0,261111111 0,327777778 lmax CI RC CR Priority vector 0,454545455 0,454545455 0,090909091 lmax CI RC CR Priority vector 0,723506057 0,19318606 0,083307883 lmax CI RC CR Priority vector 0,579077003 0,36848587 0,052437127 lmax CI RC CR 0,27272727 3 0,19318606 0,432461874 lmax 0,271023965 2,397385621 3,10087146 0,05043573 0,58 0,086958155 lmax 1,715129234 1,083444742 0,27228164 3,070855615 0,035427807 0,58 0,061082427 lmax 1,261111111 0,794444444 1 3,055555556 0,027777778 0,58 0,04789272 lmax 1,363636364 1,363636364 0,272727273 3 0 0,58 0 lmax 2,272591537 0,58781092 0,251061244 3,111463701 0,055731851 0,58 0,096089398 lmax 1,787982888 1,129958517 0,157721891 0,037831648 0,58 0,065226979 CI 0,01031746 RC CR 0,58781092 0,017788725 0,63636363 6 0,723506057 2,272591537 0,58 Priority vector lmax 0,978759696 0,967260392 0,924681704 3,075663296 Priority vector lmax 0,428571429 1,285714286 0,428571429 1,285714286 0,142857143 0,428571429 lmax CI 0% RC 0,58 CR 0% Priority vector lmax 0,5 0,442857143 1,33968254 0,387301587 1,16984127 Energy 1/3 1/2 1 0,14285714 3 0,2 0,16666666 0,16984127 0,511111111 Total 2 1/3 2 1/2 6 lmax 3,020634921 Priority vector 0,333333333 0,333333333 0,333333333 CI RC CR 0 SUBCRITERION 2 : Innovation 1 5 7 0,74468085 1 0,78947368 4 0,63636363 6 0,723506057 New clothing 1/5 1 3 0,14893617 0,15789473 7 0,27272727 3 0,19318606 Energy 1/7 1/3 1 0,10638297 9 0,05263157 9 0,09090909 1 0,083307883 0,251061244 Total 1 1/3 6 1/3 11 lmax Priority vector 0,723506057 0,19318606 0,083307883 CI RC 0,58 CR A8 0,892181357 0,814895342 0,882217802 0,818029802 0,964469086 0,945922009 0,891942097 1 A12 0,976381928 0,836260925 0,977098393 0,642974427 0,894160866 0,99004169 0,978952183 0,868879191 0,788325817 0,797210482 0,97054445 0,096089398 A6 0,946259348 0,76081735 0,82813981 0,76395181 0,981452923 1 0,946020088 0,945922009 A7 0,99976074 0,706837438 0,774159898 0,709971898 0,927473011 0,946020088 1 0,891942097 A11 0,946926378 0,865716475 0,993446057 0,672429977 0,923616416 0,96058614 0,949496632 0,898334741 0,817781367 0,826666032 1 A10 0,773592411 0,960949557 0,82011209 0,845763944 0,903049617 0,787252173 0,776162665 0,928331291 0,991115335 1 0,826666032 A9 0,764707745 0,952064892 0,811227424 0,85464861 0,894164951 0,778367507 0,767278 0,919446626 1 0,991115335 0,817781367 0,055731851 A5 0,927712271 0,779364427 0,846686887 0,782498887 1 0,981452923 0,927473011 0,964469086 A8 0,845261119 0,967381734 0,891780798 0,774095236 0,974718325 0,858920881 0,847831374 1 0,919446626 0,928331291 0,898334741 3,111463701 A3 0,774399159 0,93267754 1 0,935812 0,846686887 0,82813981 0,774159898 0,882217802 A4 0,710211159 0,99686554 0,935812 1 0,782498887 0,76395181 0,709971898 0,818029802 A7 0,997429746 0,815213108 0,956050575 0,621926609 0,873113048 0,988910492 1 0,847831374 0,767278 0,776162665 0,949496632 A6 0,986340238 0,826302615 0,967140083 0,633016117 0,884202556 1 0,988910492 0,858920881 0,778367507 0,787252173 0,96058614 A5 0,870542794 0,942100059 0,917062473 0,748813561 1 0,884202556 0,873113048 0,974718325 0,894164951 0,903049617 0,923616416 0,58781092 A2 0,707076699 1 0,93267754 0,99686554 0,779364427 0,76081735 0,706837438 0,814895342 A4 0,619356355 0,806713502 0,665876034 1 0,748813561 0,633016117 0,621926609 0,774095236 0,85464861 0,845763944 0,672429977 2,272591537 A1 1 0,707076699 0,774399159 0,710211159 0,927712271 0,946259348 0,99976074 0,892181357 A3 0,953480321 0,859162532 1 0,665876034 0,917062473 0,967140083 0,956050575 0,891780798 0,811227424 0,82011209 0,993446057 A1 1 0,812642853 0,953480321 0,619356355 0,870542794 0,986340238 0,997429746 0,845261119 0,764707745 0,773592411 0,946926378 A2 0,812642853 1 0,859162532 0,806713502 0,942100059 0,826302615 0,815213108 0,967381734 0,952064892 0,960949557 0,865716475 0,58 F unctional A1 A2 A3 A4 A5 A6 A7 A8 0 3 CRITERION 3 : Social CRITERION 4 : Relational Carbon footprint 1 1/5 0,166666667 0,080943956 Recycling 5 1 0,833333333 0,404719779 Total 6 1 1/5 Local job User resistance SAP purchasing Normalized Priority vector Global priority lmax Local job 1 5 1 0,454545455 0,454545455 4/9 0,454545455 0,031828121 1,363636364 User resistance 1/5 1 1/5 0,090909091 0,090909091 0,090909091 0,090909091 0,006365624 0,272727273 SAP purchasing 1 5 1 0,454545455 0,454545455 0,454545455 0,454545455 0,031828121 1,363636364 Total 2 1/5 11 2 1/5 lmax 3 Priority vector 4/9 0 4/9 CI 0 RC 0,58 CR 0 Brand image Innovation Priority vector Global priority Brand image 1 1 0,5 0,033241022 Innovation 1 1 0,5 0,033241022 Total 2 2 III.CRI T E RI A COM P A R I S O N Economic Environmental Social Relational Functional Normalized Economic 1 1/5 3 5 1 0,132743363 0,103448276 0,230769231 0,333333333 0,176470588 1 1 0,924681704 0,97054445 0,967260392 0,797210482 0,978759696 0,788325817 0,868879191 0,960212619 0,978952183 0,742711506 0,99004169 0,806899506 0,894160866 0,642974427 0,739577046 0,977098393 0,967499653 0,976381928 0,836260925 A9 Environmental 5 1 5 5 3 0,663716814 0,517241379 0,384615385 0,333333333 0,529411765 Social 1/3 1/5 1 1 1/3 0,044247788 0,103448276 0,076923077 0,066666667 0,058823529 Relational 1/5 1/5 1 1 1/3 0,026548673 0,103448276 0,076923077 0,066666667 0,058823529 Functional 1 1/3 3 3 1 0,132743363 0,172413793 0,230769231 0,2 0,176470588 7 1/2 2 13 15 5 2/3 priority vector 0,195352958 0,485663735 0,070021867 0,066482044 0,182479395 IV.ALT E R N A T I V E S PRI O R I T I Z A T I O N Economic Environmental Social Relational Functional Ranking Other product 0,14291939 0,435247079 0,467190043 0,574826161 0,45 0,393177765 New clothing 0,089978214 0,276546098 0,418979134 0,365775653 0,45 0,288486315 Energy 0,767102397 0,288206823 0,113830823 0,059398186 0,09 0,31833592 Total 1 1 1 1 1,00 0,68166408 Priority vector 0,195352958 0,485663735 0,070021867 0,066482044 0,182479395 Carbon footprint Recycling Environmental Other product 0,555926916 0,411111111 0,435247079 New clothing 0,353721034 0,261111111 0,276546098 Energy 0,09035205 0,327777778 0,288206823 Priority 0,166666667 0,833333333 Local job User resistance SAP purchasing Social Other product 0,454545455 0,723506057 0,428571429 0,467190043 New clothing 0,454545455 0,19318606 0,428571429 0,418979134 Energy 0,090909091 0,083307883 0,142857143 0,113830823 Priority 0,454545455 0,090909091 0,454545455 Brand image Innovation Relational Other product 0,579077003 0,570575318 0,574826161 New clothing 0,36848587 0,363065437 0,365775653 Energy 0,052437127 0,066359245 0,059398186 Priority 0,5 0,5 SUBCRITERION 2 : Recycling SUBCRITERION 2 : User resistance I.ALT E R N A T I V E S COM P A R I S O N CRITERION 1 : Economic SUBCRITERION 2 : Purchasing cost Other product New clothing Energy Normalized Priority vector lmax Other product 1 1 5 0,45454545 5 0,45454545 5 0,45454545 0,454545455 1,363636364 New clothing 1 1 5 0,45454545 5 0,45454545 5 0,45454545 0,454545455 1,363636364 Energy 1/5 1/5 1 0,09090909 1 0,09090909 1 0,09090909 0,090909091 0,272727273 Total 2 1/5 2 1/5 11 lmax 3 Priority vector 0,454545455 0,454545455 0,090909091 CI 0 RC 0,58 CR 0 Other product New clothing Energy Normalized Priority vector lmax Other product 1 1 5 0,454545455 0,454545455 0,454545455 0,454545455 1,363636364 New clothing 1 1 5 0,454545455 0,454545455 0,454545455 0,454545455 1,363636364 Energy 1/5 1/5 1 0,090909091 0,090909091 0,090909091 0,090909091 0,272727273 Total 2 1/5 2 1/5 11 lmax 3 Priority vector 0,454545455 0,454545455 0,090909091 CI 0 RC 0,58 CR 0 CRITERION 3 : Social SUBCRITERION 1 : Other product New clothing Energy Normalized Priority vector lmax Other product 1 1 1 0,33333333 3 0,33333333 3 0,33333333 0,333333333 1 New clothing 1 1 1 0,33333333 3 0,33333333 3 0,33333333 0,333333333 1 Energy 1 1 1 0,33333333 3 0,33333333 3 0,33333333 0,333333333 1 Total 3 3 3 lmax 3 Priority vector 0,33333333 3 0,33333333 3 0,33333333 3 CI 0 RC 0,58 CR 0 Other product New clothing Energy Normalized Priority vector lmax Other product 1 1 1 0,33333333 3 0,33333333 3 0,33333333 0,333333333 1 New clothing 1 1 1 0,33333333 3 0,33333333 3 0,33333333 0,333333333 Energy 1 1 1 0,33333333 3 0,33333333 3 0,33333333 0,333333333 1 Total 3 3 3 lmax 3 Priority vector 0,333333333 0,333333333 0,333333333 CI 0 RC 0,58 CR 0 SUBCRITERION 2 : SAP purchasing Other product New clothing Energy Normalized Priority vector lmax Other product 1 1 1 0,33333333 3 0,33333333 3 0,33333333 0,333333333 1 New clothing 1 1 1 0,33333333 3 0,33333333 3 0,33333333 0,333333333 1 Energy 1 1 1 0,33333333 3 0,33333333 3 0,33333333 0,333333333 1 Total 3 3 3 lmax 3 Local job User resistance SAP purchasing Social Other product 0,333333333 0,333333333 0,333333333 0,333333333 New clothing 0,333333333 0,333333333 0,333333333 0,333333333 Energy 0,333333333 0,333333333 0,333333333 0,333333333 Priority 0,182234432 0,702838828 0,11492674 Brand image Innovation Relational Other product 0,442857143 0,466666667 0,446825397 New clothing 0,387301587 0,466666667 0,400529101 Energy 0,16984127 0,066666667 0,152645503 Priority 0,833333333 0,166666667 SUBCRITERION 2 : SAP purchasing Priority vector 0,210606061 0,548484848 0,240909091 CI 0,011111111 RC 0,58 CR 0,019157088 Other product New clothing Energy Normalized Priority vector lmax Other product 1 1 5 0,45454545 5 0,45454545 5 0,45454545 5 0,454545455 1,363636364 New clothing 1 1 5 0,45454545 5 0,45454545 5 0,45454545 5 0,454545455 1,363636364 Energy 1/5 1/5 1 0 0 0 0,090909091 0,272727273 Total 2 1/5 2 1/5 11 lmax 3 Priority vector 0,454545455 0,454545455 0,090909091 CI 0 RC 0,58 CR A9 0,983163411 0,867514513 0,963121806 0,931470428 0,938388 0,940842674 0,924971725 0,900380305 Functional A1 A2 A3 A4 A5 A6 A7 A8 A9 A10 A11 A12 1 0 Local job User resistance SAP purchasing Social Other product 0,588888889 0,210606061 0,454545455 0,480976431 New clothing 0,251851852 0,548484848 0,454545455 Energy 0,159259259 0,240909091 0,090909091 Priority 0,405483405 0,114959115 0,47955748 Brand image Innovation Relational Other product 0,723506057 0,723506057 0,723506057 New clothing 0,19318606 0,19318606 Energy 0,083307883 0,083307883 Priority 0,5 0,5 A7 0,941808314 0,942542788 0,888093531 0,856442153 0,986583726 0,865814399 1 0,97540858 A8 0,917216894 0,967134208 0,863502111 0,831850732 0,961992305 0,841222979 0,97540858 1 A12 0,945892091 0,853652229 0,986400718 0,976186329 0,837304679 0,99004169 0,922740843 0,868879191 0,945535849 0,974806471 0,989023957 1 0,900380305 A11 0,934916049 0,842676186 0,975424675 0,987162372 0,826328636 0,998982267 0,9117648 0,857903148 0,934559806 0,963830428 1 0,989023957 A8 0.91928463528399 0.967929550682061 0.707146408399066 0.942749027510691 0.921365546218487 0.938886151230521 0.928589767914392 1 0,924971725 A10 0,97108562 0,878845758 0,988405753 0,9509928 0,862498207 0,964848161 0,947934372 0,89407272 0,970729377 1 0,963830428 0,974806471 A7 0.990694867369598 0.896519318596453 0.635736176313458 0.985840740403701 0.849955314132879 0.867475919144913 1 0.928589767914392 0,083307883 A6 0,924006085 0,808357187 0,977720868 0,990627753 0,879230674 1 0,865814399 0,841222979 0,940842674 A9 0,999643757 0,908116381 0,95913513 0,921722178 0,89176883 0,935577539 0,977204995 0,923343342 1 0,970729377 0,934559806 0,945535849 A6 0.858170786514511 0.97095660054846 0.768260257168545 0.881635178741212 0.982479394987966 1 0.867475919144913 0.938886151230521 0,19318606 A1 1 0,884351102 0,946285217 0,914633839 0,955224588 0,924006085 0,941808314 0,917216894 0,983163411 A2 0,884351102 1 0,830636319 0,79898494 0,929126513 0,808357187 0,942542788 0,967134208 0,867514513 A3 0,946285217 0,830636319 1 0,968348621 0,901509806 0,977720868 0,888093531 0,863502111 0,963121806 A4 0,914633839 0,79898494 0,968348621 1 0,869858427 0,990627753 0,856442153 0,831850732 A5 0,955224588 0,929126513 0,901509806 0,869858427 1 0,879230674 0,986583726 0,961992305 0,938388 A7 0,976848752 0,930911386 0,936340125 0,898927172 0,914563835 0,912782533 1 0,946138348 0,977204995 0,947934372 0,9117648 A8 0,9229871 0,984773038 0,882478473 0,84506552 0,968425488 0,858920881 0,946138348 1 0,923343342 0,89407272 0,857903148 0,868879191 A5 0.840650181502477 0.953435995536426 0.785780862180579 0.864114573729178 1 0.982479394987966 0.849955314132879 0.921365546218487 0,922740843 A4 0.976535607773299 0.910678578192752 0.649895435909757 1 0.864114573729178 0.881635178741212 0.985840740403701 0.942749027510691 0,931470428 A2 0,907760138 1 0,867251511 0,829838558 0,983652449 0,84369392 0,930911386 0,984773038 0,908116381 0,878845758 0,842676186 0,853652229 A3 0,959491373 0,867251511 1 0,962587047 0,85090396 0,976442409 0,936340125 0,882478473 0,95913513 0,988405753 0,975424675 A4 0,922078421 0,829838558 0,962587047 1 0,813491008 0,986144639 0,898927172 0,84506552 0,921722178 0,9509928 0,987162372 A5 0,891412587 0,983652449 0,85090396 0,813491008 1 0,827346369 0,914563835 0,968425488 0,89176883 0,862498207 0,826328636 A6 0,935933782 0,84369392 0,976442409 0,986144639 0,827346369 1 0,912782533 0,858920881 0,935577539 0,964848161 0,998982267 0,99004169 A3 0.626431043683056 0.739216857717005 1 0.649895435909757 0.785780862180579 0.768260257168545 0.635736176313458 0.707146408399066 0,837304679 A2 0.887214185966051 1 0.739216857717005 0.910678578192752 0.953435995536426 0.97095660054846 0.896519318596453 0.967929550682061 0,976186329 A1 1 0.887214185966051 0.626431043683056 0.976535607773299 0.840650181502477 0.858170786514511 0.990694867369598 0.91928463528399 0,986400718 Functional A1 A2 A3 A4 A5 A6 A7 A8 0,135867817 A1 1 0,907760138 0,959491373 0,922078421 0,891412587 0,935933782 0,976848752 0,9229871 0,999643757 0,97108562 0,934916049 0,945892091 0,383155752 A8 0,944524295 0,988523487 0,927079423 0,96687577 0,989615274 0,735873448 0,976488813 1 A9 0,961487172 0,894534954 0,83309089 0,872887237 0,895626741 0,829861981 0,929522654 0,906011467 Relational A1 A2 A3 A4 A5 A6 A7 A8 A8 0.899713033638621 0.967929550682061 0.948248893204598 0.966278439275397 0.897836134453782 0.968645909832208 0.955659002687947 1 A9 Relational A1 A2 A3 A4 A5 A6 A7 A8 A9 A10 A11 A12 A7 0.855372036326568 0.923588553370009 0.992589890516651 0.989380563412551 0.853495137141729 0.987013092855739 1 0.955659002687947 1 A12 0,683432036 0,755528955 0,764563701 0,568691976 0,690159436 0,729166651 0,625251131 0,697545963 0,543056793 0,712071814 0,939159114 1 A6 0.868358943470829 0.93657546051427 0.97960298337239 0.997632529443188 0.86648204428599 1 0.987013092855739 0.968645909832208 0,906011467 A11 0,744272922 0,816369841 0,825404587 0,629532863 0,751000322 0,790007537 0,686092017 0,758386849 0,603897679 0,7729127 1 0,939159114 A5 0.998123100815161 0.92990658377172 0.84608502765838 0.864114573729178 1 0.86648204428599 0.853495137141729 0.897836134453782 1 Economic Environmental Social Relational Functional Ranking Other product 0,454545455 0,456565657 0,333333333 0,446825397 0,47 0,389306972 New clothing 0,454545455 0,456565657 0,333333333 0,400529101 0,47 0,386830345 Energy 0,090909091 0,086868687 0,333333333 0,152645503 0,07 0,223862682 Total 1 1 1 1 1,00 1 Priority vector 0,188759622 0,16523021 0,542559717 0,053495137 0,049955314 Carbon footprint Recycling Environmental Other product 0,466666667 0,454545455 0,456565657 New clothing 0,466666667 0,454545455 0,456565657 Energy 0,066666667 0,090909091 0,086868687 Priority 0,166666667 0,833333333 SUBCRITERION 2 : User resistance New clothing 1/3 1 2 0,2 0,22222222 2 0,33333333 3 0,251851852 Energy 1/3 1/2 1 0,2 0,11111111 1 0,16666666 7 0,159259259 0,481481481 Total 1 2/3 4 1/2 6 lmax 3,07037037 Priority vector 0,58888888 9 0,25185185 2 0,15925925 9 CI 0,035185185 RC 0,58 CR Other product New clothing Energy Normalized Priority vector lmax Other product 1 1/3 1 0,2 0,18181818 2 0,25 0,210606061 0,634343434 New clothing 3 1 2 0,6 0,54545454 5 0,5 0,548484848 1,662121212 Energy 1 1/2 1 0,2 0,27272727 3 0,25 0,240909091 0,725757576 Total 5 1 5/6 4 lmax 3,022222222 Priority vector 0,223865546 0,155336134 0,401596639 0,097836134 Carbon footprint Recycling Environmental Other product 0,353721034 0,353721034 0,353721034 New clothing 0,555926916 0,555926916 0,555926916 Energy 0,09035205 0,09035205 0,09035205 Priority 0,166666667 0,833333333 A1 1 0,933047782 0,871603718 0,911400065 0,934139569 0,791349152 0,968035482 0,944524295 0,961487172 A2 0,933047782 1 0,938555936 0,978352283 0,998908213 0,724396934 0,9650123 0,988523487 0,894534954 A3 0,871603718 0,938555936 1 0,960203653 0,937464149 0,66295287 0,903568235 0,927079423 A4 0,911400065 0,978352283 0,960203653 1 0,977260496 0,702749217 0,943364582 0,96687577 0,872887237 A5 0,934139569 0,998908213 0,937464149 0,977260496 1 0,725488722 0,966104087 0,989615274 0,895626741 A6 0,791349152 0,724396934 0,66295287 0,702749217 0,725488722 1 0,759384635 0,735873448 A7 0,968035482 0,9650123 0,903568235 0,943364582 0,966104087 0,759384635 1 0,976488813 A10 0,971360222 0,956542859 0,947508114 0,856620162 0,978087622 0,982905163 0,913179317 0,985474148 0,830984979 1 0,7729127 0,712071814 A4 0.865991472914018 0.934207989957458 0.981970453929202 1 0.864114573729178 0.997632529443188 0.989380563412551 0.966278439275397 0,929522654 A9 0,859624757 0,787527838 0,778493092 0,974364816 0,852897357 0,813890142 0,917805662 0,84551083 1 0,830984979 0,603897679 0,543056793 A3 0.847961926843219 0.91617844388666 1 0.981970453929202 0.84608502765838 0.97960298337239 0.992589890516651 0.948248893204598 0,829861981 A5 0,9932726 0,934630481 0,925595736 0,87853254 1 0,960992785 0,935091695 0,992613473 0,852897357 0,978087622 0,751000322 A6 0,954265385 0,973637696 0,96460295 0,839525325 0,960992785 1 0,89608448 0,968379312 0,813890142 0,982905163 0,790007537 A7 0,941819095 0,869722176 0,86068743 0,943440846 0,935091695 0,89608448 1 0,927705168 0,917805662 0,913179317 0,686092017 A8 0,985886073 0,942017008 0,932982262 0,871146014 0,992613473 0,968379312 0,927705168 1 0,84551083 0,985474148 0,758386849 0,697545963 A2 0.931783482956559 1 0.91617844388666 0.934207989957458 0.92990658377172 0.93657546051427 0.923588553370009 0.967929550682061 0,625251131 A1 1 0.931783482956559 0.847961926843219 0.865991472914018 0.998123100815161 0.868358943470829 0.855372036326568 0.899713033638621 0,729166651 Relational A1 A2 A3 A4 A5 A6 A7 A8 0,690159436 0,83309089 A2 0,927903081 1 0,990965254 0,813163021 0,934630481 0,973637696 0,869722176 0,942017008 0,787527838 0,956542859 0,816369841 A3 0,918868335 0,990965254 1 0,804128276 0,925595736 0,96460295 0,86068743 0,932982262 0,778493092 0,947508114 0,825404587 A4 0,885259941 0,813163021 0,804128276 1 0,87853254 0,839525325 0,943440846 0,871146014 0,974364816 0,856620162 0,629532863 0,568691976 A8 0.796526462159698 0.728309945116258 0.720029667946039 0.974478104721512 0.798403361344538 0.668425228639377 0.859036921189072 1 0,764563701 A7 0.655563383348771 0.58734686630533 0.579066589135111 0.833515025910584 0.65744028253361 0.527462149828449 1 0.859036921189072 0,755528955 0,121365546 A1 1 0,927903081 0,918868335 0,885259941 0,9932726 0,954265385 0,941819095 0,985886073 0,859624757 0,971360222 0,744272922 0,683432036 A6 0.871898766479679 0.940115283523119 0.948395560693338 0.693947123917865 0.870021867294839 1 0.527462149828449 0.668425228639377 0,060664112 Economic Environmental Social Relational Functional Ranking Other product 0,09035205 0,353721034 0,480976431 0,723506057 0,28 0,373442836 New clothing 0,555926916 0,555926916 0,383155752 0,19318606 0,64 Energy 0,353721034 0,09035205 0,135867817 0,083307883 0,07 0,164888862 Total 1 1 1 1 1,00 1 A9 0,868607456 0,838692298 0,892274312 0,995023682 0,91605586 0,947631916 0,872196363 0,978955853 S ocial A1 A2 A3 A4 A5 A6 A7 A8 A5 0.998123100815161 0.92990658377172 0.921626306601501 0.823925256623026 1 0.870021867294839 0.65744028253361 0.798403361344538 A9 Social A1 A2 A3 A4 A5 A6 A7 A8 A9 A10 A11 A12 A4 0.822048357438186 0.753831840394745 0.745551563224527 1 0.823925256623026 0.693947123917865 0.833515025910584 0.974478104721512 1 A12 0,576769813 0,857225785 0,649678752 0,905864177 0,810031951 0,572801871 0,530714925 0,868879191 0,688073292 0,766441252 0,842059739 1 A3 0.923503205786341 0.991719722829781 1 0.745551563224527 0.921626306601501 0.948395560693338 0.579066589135111 0.720029667946039 0,461668302 A6 0,821547793 0,885751961 0,84521465 0,957916655 0,868996198 1 0,958985754 0,827579731 0,947631916 A7 0,996411093 0,710888661 0,97992205 0,867220045 0,956140502 0,958985754 1 0,89324051 A8 0,889651603 0,817648151 0,913318459 0,973979535 0,937100007 0,827579731 0,89324051 1 A11 0,734710074 0,984833954 0,807619013 0,936195562 0,967972212 0,730742132 0,688655186 0,973180548 0,846013553 0,924381513 1 0,842059739 A2 0.931783482956559 1 0.991719722829781 0.753831840394745 0.92990658377172 0.940115283523119 0.58734686630533 0.728309945116258 0,978955853 A10 0,810328562 0,909215467 0,8832375 0,860577075 0,9564093 0,806360619 0,764273673 0,897562061 0,92163204 1 0,924381513 0,766441252 A1 1 0.931783482956559 0.923503205786341 0.822048357438186 0.998123100815161 0.871898766479679 0.655563383348771 0.796526462159698 0,872196363 A8 0,707890622 0,988346594 0,780799561 0,963015014 0,94115276 0,70392268 0,661835734 1 0,819194101 0,897562061 0,973180548 0,868879191 A9 0,888696521 0,830847507 0,96160546 0,782209115 0,878041341 0,884728579 0,842641633 0,819194101 1 0,92163204 0,846013553 0,688073292 Social A1 A2 A3 A4 A5 A6 A7 A8 0,766666667 Local job CRITERION 2 : Environmental SUBCRITERION 1 : Carbon footprint Other product New clothing Energy Normalized Priority vector CRITERION 3 : Social CRITERION 4 : Relational Carbon footprint 1 1/5 0,166666667 0,027538368 Recycling 5 1 0,833333333 0,137691841 Total 6 1 1/5 Local job User resistance SAP purchasing Normalized Priority vector Global priority lmax Local job 1 1/5 2 0,153846154 0,142857143 1/4 0,182234432 0,098873062 0,55265567 8 User resistance 5 1 5 0,769230769 0,714285714 0,625 0,702838828 0,381332036 2,18864468 9 SAP purchasing 1/2 1/5 1 0,076923077 0,142857143 0,125 0,11492674 0,06235462 0,34661172 2 Total 6 1/2 1 2/5 8 lmax 3,0879120 88 Priority vector 1/5 5/7 1/9 CI 0,0439560 44 RC 0,58 CR 0,07578628 3 CRITERION 1 : Economic SUBCRITERION 2 : Purchasing cost Other product New clothing Energy Normalized Priority vector lmax Other product 1 1/5 1/5 0,09090909 1 0,11764705 9 0,0625 0,09035205 Carbon footprint 1 1/5 0,166666667 0,025889356 Recycling 5 1 0,833333333 0,129446779 Total 6 1 1/5 Annex E-1: Similarity matrices Annex E-2: Similarity matrices Annex E-3: Similarity matrices 0,27228164 New clothing 5 1 2 0,45454545 5 0,58823529 4 0,625 0,555926916 1,715129234 Energy 5 1/2 1 0,45454545 5 0,29411764 7 0,3125 0,353721034 1,083444742 Total 11 1 2/3 3 1/5 lmax 3,070855615 Priority vector 0,09035205 0,555926916 0,353721034 CI 0,035427807 RC CRITERION 3 : Social Local job User resistance SAP purchasing Normalized Priority vector Global priority lmax Local job 1 3 1 0,428571429 0,333333333 4/9 0,405483405 0,162840773 1,2299182 User resistance 1/3 1 1/5 0,142857143 0,111111111 0,090909091 0,114959115 0,046167194 0,3460317 SAP purchasing 1 5 1 0,428571429 0,555555556 0,454545455 0,47955748 0,192588672 1,4598365 Beginning of life Middle of life End of life E ´ cole Nationale Supérieure des Mines de Saint-E ´ tienne 0,58 CR Total 2 1/3 9 2 1/5 lmax 3,0357864 0,061082427 CRITERION 2 : Priority vector 2/5 1/9 1/2 CI 0,0178932 Environmental SUBCRITERION 1 : RC 0,58 Carbon footprint Other product New clothing Energy Normalized Priority vector lmax Other product 1 1/2 5 0,3125 0,29411764 7 0,45454545 5 0,353721034 1,083444742 CRITERION 4 : Relational CR 0,0308504 NNT: 2019LYSEM030 lmax Other product 1 1 7 0,46666666 7 0,46666666 7 0,46666666 0,466666667 1,4 New clothing 1 1 7 0,46666666 7 0,46666666 7 0,46666666 0,466666667 1,4 Energy 1/7 1/7 1 0,06666666 7 0,06666666 7 0,06666666 0,066666667 0,2 Total 2 1/7 2 1/7 15 lmax 3 Priority vector 0,466666667 0,466666667 0,066666667 CI 0 RC 0,58 CR 0 Brand image Innovation Priority vector Global priority Brand image 1 5 0,833333333 0,044579281 Innovation 1/5 1 0,166666667 0,008915856 Total 1 1/5 6 III.CRI T E RI A COM P A R I S O N Economic Environmental Social Relational Functional Normalized Economic 1 1 1/5 5 5 0,135135135 0,132743363 0,118644068 0,294117647 0,26315789 Environmental 1 1 1/5 3 5 0,135135135 0,132743363 0,118644068 0,176470588 0,26315789 Social 5 5 1 7 7 0,675675676 0,663716814 0,593220339 0,411764706 0,36842105 Relational 1/5 1/3 1/7 1 1 0,027027027 0,044247788 0,084745763 0,058823529 0,05263158 Functional 1/5 1/5 1/7 1 1 0,027027027 0,026548673 0,084745763 0,058823529 0,05263158 7 2/5 7 1/2 1 2/3 17 19 priority vector 0,188759622 0,16523021 0,542559717 0,053495137 0,049955314 IV.ALT E R N A T I V E S PRI O R I T I Z A T I O N CRITERION 3 : Social SUBCRITERION 1 : Local job Other product New clothing Energy Normalized Priority vector lmax Other product 1 3 3 0,6 0,66666666 7 0,5 0,588888889 1,822222222 SUBCRITERION 2 : Recycling New clothing 2 1 5 0,625 0,58823529 4 0,45454545 5 0,555926916 1,715129234 Energy 1/5 1/5 1 0,0625 0,11764705 9 0,09090909 1 0,09035205 Brand image Innovation Priority vector Global priority 0,27228164 Total 3 1/5 1 2/3 11 lmax 3,070855615 Priority vector 0,353721034 0,555926916 0,09035205 CI Brand image 1 1 0,5 0,048918067 Innovation 1 1 0,5 0,048918067 Martha ORELLANO CARRASQUILLA 0,035427807 RC 0,58 CR 0,061082427 Other product New clothing Energy Normalized Priority vector lmax Other product 1 1/2 5 0,3125 0,294117647 0,454545455 0,353721034 1,083444742 New clothing 2 1 5 0,625 0,588235294 0,454545455 0,555926916 1,715129234 Energy 1/5 1/5 1 0,0625 0,117647059 0,090909091 0,09035205 0,27228164 Total 3 1/5 1 2/3 11 lmax 3,070855615 Priority vector 0,353721034 0,555926916 0,09035205 CI Total 2 Economic A1 A2 A3 A4 A5 A6 A7 A8 A9 Economic A1 A2 A3 A4 A5 A6 A7 A8 A9 A10 A11 A12 2 III.CRI T E RI A COM P A R I S O N Economic Environmental Social Relational Functional Normalized Economic 1 3 1/3 3 1 0,176470588 0,375 0,142857143 0,3 0,125 Environmental 1/3 1 1/3 2 2 0,058823529 0,125 0,142857143 0,2 0,25 Social 3 3 1 3 3 0,529411765 0,375 0,428571429 0,3 0,375 Relational 1/3 1/2 1/3 1 1 0,058823529 0,0625 0,142857143 0,1 0,125 Functional 1 1/2 1/3 1 1 0,176470588 0,0625 0,142857143 0,1 0,125 A1 1 0,951080264 0,98017708 0,979453883 0,996245695 0,992054622 0,977600999 0,975222353 A1 1 0,928762044 0,985766222 0,858887643 0,988490119 0,999296101 0,986404514 0,95375633 0,983969776 0,96353845 0,978426822 0,86284794 Economic A1 A2 A3 A4 A5 A6 A7 A8 0,922784043 A2 0,951080264 1 0,970903184 0,930534147 0,954834569 0,959025642 0,973479265 0,975857911 0,873864307 A3 0,98017708 0,970903184 1 0,959630963 0,983931385 0,988122458 0,997423919 0,995045273 0,902961123 A4 0,979453883 0,930534147 0,959630963 1 0,975699578 0,971508505 0,957054882 0,954676236 0,94333016 A5 0,996245695 0,954834569 0,983931385 0,975699578 1 0,995808927 0,981355304 0,978976658 0,919029738 A6 0,992054622 0,959025642 0,988122458 0,971508505 0,995808927 1 0,985546377 0,983167731 0,914838665 A7 0,977600999 0,973479265 0,997423919 0,957054882 0,981355304 0,985546377 1 0,997621354 0,900385042 A8 0,975222353 0,975857911 0,995045273 0,954676236 0,978976658 0,983167731 0,997621354 1 0,898006396 A9 0,922784043 0,873864307 0,902961123 0,94333016 0,919029738 0,914838665 0,900385042 0,898006396 1 A2 0,928762044 1 0,942995822 0,787649686 0,940271925 0,928058145 0,94235753 0,882518374 0,91273182 0,965223593 0,907188866 0,791609984 A3 0,985766222 0,942995822 1 0,844653865 0,997276103 0,985062323 0,999361708 0,939522552 0,969735998 0,977772229 0,964193044 0,848614162 A4 0,858887643 0,787649686 0,844653865 1 0,847377762 0,859591542 0,845292157 0,905131312 0,874917867 0,822426093 0,88046082 0,996039702 A5 0,988490119 0,940271925 0,997276103 0,847377762 1 0,98778622 0,997914395 0,942246449 0,972459895 0,975048331 0,966916941 A1 1 0.950991674580236 0.894838538344478 0.979384427119231 0.903873302304827 0.90852034409847 0.915113680792973 0.88000775608634 A2 0.950991674580236 1 0.845830212924714 0.971607247461005 0.854864976885063 0.859512018678706 0.866105355373209 0.830999430666576 A3 0.894838538344478 0.845830212924714 1 0.874222965463709 0.990965236039651 0.986318194246009 0.979724857551505 A metho dolo gical framewo rk to support sustain able value creatio n in 0.985169217741861 0,851338059 A6 0,999296101 0,928058145 0,985062323 0,859591542 0,98778622 1 0,985700615 0,954460229 0,984673675 0,962834551 0,979130722 0,86355184 A7 0,986404514 0,94235753 0,999361708 0,845292157 0,997914395 0,985700615 1 0,940160844 0,97037429 0,977133936 0,964831337 A4 0.979384427119231 0.971607247461005 0.874222965463709 1 0.883257729424058 0.887904771217701 0.894498107912204 0.859392183205571 A5 0.903873302304827 0.854864976885063 0.990965236039651 0.883257729424058 1 0.995352958206357 0.988759621511854 0.976134453781513 innovative offer design 0,849252455 A8 0,95375633 0,882518374 0,939522552 0,905131312 0,942246449 0,954460229 0,940160844 1 0,969786554 0,917294781 0,975329508 A6 0.90852034409847 0.859512018678706 0.986318194246009 0.887904771217701 0.995352958206357 1 0.993406663305497 0.97148741198787 0,90909161 A9 0,983969776 0,91273182 0,969735998 0,874917867 0,972459895 0,984673675 0,97037429 0,969786554 1 0,947508226 0,994457047 A7 0.915113680792973 0.866105355373209 0.979724857551505 0.894498107912204 0.988759621511854 0.993406663305497 1 0.964894075293366 0,878878165 A10 0,96353845 0,965223593 0,977772229 0,822426093 0,975048331 0,962834551 0,977133936 0,917294781 0,947508226 1 0,941965273 0,826386391 A11 0,978426822 0,907188866 0,964193044 0,88046082 0,966916941 0,979130722 0,964831337 0,975329508 0,994457047 0,941965273 1 0,884421118 A12 0,86284794 0,791609984 0,848614162 0,996039702 0,851338059 0,86355184 0,849252455 0,90909161 0,878878165 0,826386391 0,884421118 1 A8 0.88000775608634 0.830999430666576 0.985169217741861 0.859392183205571 0.976134453781513 0.97148741198787 0.964894075293366 1 Environmental A1 A2 A3 A4 A5 A6 A7 Speciality: Industrial Engineering A8 0,035427807 RC 0,58 CR 0,061082427 5 2/3 8 2 1/3 10 8 priority vector 0,223865546 0,155336134 0,401596639 0,097836134 Environmental A1 A2 A3 A4 A5 A6 A7 A8 Environmental A1 A2 A3 A4 A5 A6 A7 A8 A9 A10 A11 A12 A1 1 0.927344454527303 0.749804449397975 0.953208065178237 0.740769685437626 0.973566579337527 0.705999895184774 0.696105819891408 A9 A2 0.927344454527303 1 0.677148903925278 0.88055251970554 0.668114139964929 0.953777875189776 0.633344349712077 0.62345027441871 0,121365546 IV.ALT E R N A T I V E S PRI O R I T I Z A T I O N A1 1 0,707299754 0,976333144 0,863631138 0,952551596 0,821547793 0,996411093 0,889651603 0,868607456 A2 0,707299754 1 0,73096661 0,843668616 0,754748158 0,885751961 0,710888661 0,817648151 0,838692298 A3 0,976333144 0,73096661 1 0,887297995 0,976218452 0,84521465 0,97992205 0,913318459 0,892274312 A4 0,863631138 0,843668616 0,887297995 1 0,911079542 0,957916655 0,867220045 0,973979535 0,995023682 A5 0,952551596 0,754748158 0,976218452 0,911079542 1 0,868996198 0,956140502 0,937100007 0,91605586 A1 1 0,719544028 0,927091061 0,670905636 0,766737862 0,996032058 0,953945112 0,707890622 0,888696521 0,810328562 0,734710074 0,576769813 A2 0,719544028 1 0,792452967 0,951361608 0,952806166 0,715576086 0,67348914 0,988346594 0,830847507 0,909215467 0,984833954 0,857225785 A3 0,927091061 0,792452967 1 0,743814575 0,839646801 0,923123119 0,881036173 0,780799561 0,96160546 0,8832375 0,807619013 A3 0.749804449397975 0.677148903925278 1 0.796596384219738 0.990965236039651 0.723371028735501 0.956195445786799 0.946301370493433 A4 0.953208065178237 0.88055251970554 0.796596384219738 1 0.787561620259389 0.926774644515764 0.752791830006537 0.742897754713171 Keywords: value creation; collaboration; innovation; sustainability; multi-criteria 0,649678752 A4 0,670905636 0,951361608 0,743814575 1 0,904167775 0,666937694 0,624850748 0,963015014 0,782209115 0,860577075 0,936195562 0,905864177 A5 0,766737862 0,952806166 0,839646801 0,904167775 1 0,76276992 0,720682974 0,94115276 0,878041341 0,9564093 0,967972212 0,810031951 A6 0,996032058 0,715576086 0,923123119 0,666937694 0,76276992 1 0,957913054 0,70392268 0,884728579 0,806360619 0,730742132 A7 0,953945112 0,67348914 0,881036173 0,624850748 0,720682974 0,957913054 1 0,661835734 0,842641633 0,764273673 0,688655186 0,530714925 A8 0.696105819891408 0.62345027441871 0.946301370493433 0.742897754713171 0.955336134453782 0.669672399228934 0.990105924706634 1 0,572801871 A5 0.740769685437626 0.668114139964929 0.990965236039651 0.787561620259389 1 0.714336264775153 0.965230209747148 0.955336134453782 A6 0.973566579337527 0.953777875189776 0.723371028735501 0.926774644515764 0.714336264775153 1 0.679566474522301 0.669672399228934 A7 0.705999895184774 0.633344349712077 0.956195445786799 0.752791830006537 0.965230209747148 0.679566474522301 1 0.990105924706634 decision analysis
	SUBCRITERION 2 : SUBCRITERION 2 : Energy	Innovation Innovation 1/7	1/3	1	0,10638297 9	0,05263157 9	0,09090909 1	0,083307883	0,251061244
	CRITERION 5 : Other product New clothing Energy Total Priority vector CRITERION 5 : New clothing Other product Priority vector Total SUBCRITERION 1 : Total Other product Priority vector New clothing Energy CRITERION 5 :	Functional Other product 1 1/2 1/7 1 2/3 0,570575318 Functional 3 1 0,466666667 Other product 2 1/7 fiber quality Other product 1 1/3 1 0,723506057 1 1/7 Functional	New clothing 2 1 1/7 3 1/7 0,363065437 1 1/3 0,466666667 New clothing 2 1/7 New clothing 6 1/3 1 0,19318606 1 1/7	Energy 7 7 1 15 0,066359245 7 5 0,066666667 Energy 15 Energy 11 7 0,083307883 0,60869565 2 0,30434782 6 0,08695652 2 7 1	Normalized 0,63636363 6 0,31818181 8 0,04545454 5 0,71428571 4 0,23809523 8 Normalized 0,46666666 0,46666666 0,06666666 0,67741935 5 0,22580645 2 Normalized 0,46666666 7 0,46666666 7 0,46666666 7 0,46666666 7 0,06666666 7 0,06666666 7	Priority vector 0,570575318 0,363065437 0,066359245 lmax CI RC CR 0,53846153 8 0,643388869 1,761220905 lmax 1,112867809 0,199736495 0,063642421 RC CR 2,008310686 0 0,38461538 5 0,282839025 0,866162511 0,58 0,58 CI Priority vector lmax 0 0,036912604 lmax 3 3,073825209 Priority vector lmax 3,111463701 lmax 0,46666666 0,466666667 CI 0,055731851 1,4 0,46666666 0,466666667 RC 0,58 1,4 0,06666666 0,066666667 0,2 CR 0,096089398
	SUBCRITERION 1 : SUBCRITERION 1 : Energy	fiber quality fiber quality 1/5	1/7	1	0,04761904 8	0,09677419 4	0,07692307 7	0,073772106	0,222252607
	Other product New clothing Energy Total Priority vector Priority vector Total Total Other product Priority vector New clothing Energy	Other product 1 1 1/5 2 1/5 0,454545455 0,466666667 2 1/7 Other product 4 1/5 1 0,282839025 1 1/7	New clothing 1 1 1/5 2 1/5 0,454545455 0,466666667 2 1/7 New clothing 1 1/2 1 0,643388869 1 1/7	Energy 5 5 1 11 0,090909091 0,066666667 15 Energy 13 7 0,073772106 0,45454545 5 0,45454545 5 0,09090909 1 7 1	Normalized 0,45454545 5 0,45454545 5 0,09090909 1 Normalized 0,45454545 0,45454545 0,09090909 0,46666666 7 0,46666666 7 0,46666666 7 0,46666666 7 0,06666666 7 0,06666666 7	Priority vector 0,454545455 0,454545455 0,090909091 lmax CI RC CR Priority vector 1,363636364 lmax 1,363636364 0,272727273 CR 0 RC 0,58 CI 0 lmax 3 lmax 3,096725804 0 0,58 0 3 lmax 0,46666666 0,466666667 CI 0,048362902 1,4 0,46666666 0,466666667 RC 0,58 1,4 0,06666666 0,066666667 0,2 CR 0,083384313

Nationale Supérieure des Mines de Saint-E ´ tienne NNT : 2019LYSEM030

  L'augmentation des pressions environnementales et sociales nécessite l'adoption de pratiques plus durables dans l'industrie. Pour les entreprises, cela se traduit par la prise en compte dans le processus d'innovation de nouveaux critères liés a ` la création de valeur durable, dans le sens économique, mais aussi environnementale et sociale. L'objectif principal de ce travail de thèse est de fournir un cadre méthodologique aux entreprises pour l'intégration de critères axés sur le développement durable dans leurs processus d'innovation. La contribution de cette thèse est triple. Tout d'abord, un cadre permettant de conceptualiser la valeur créée par une innovation est proposé. Ce cadre s'appuie sur cinq dimensions de la valeur : les trois dimensions du développement durable, économique, environnementale, sociale, auxquelles s'ajoutent deux dimensions, relationnelle et fonctionnelle. Deuxièmement, une approche de modélisation des systèmes est adoptée pour analyser le processus d'alignement entre les attentes des clients en termes de création de valeur et les alternatives possibles en termes de propositions de valeur par les fournisseurs. Enfin, compte tenu de la diversité des parties prenantes impliquées et du caractère multidimensionnelle de la valeur durable, une approche d'aide a ` la décision multicritères et multi-acteurs est adoptée pour évaluer les alternatives réalisables au regard des objectifs de création de valeur. Le cadre proposé est alors appliqué a ` la transformation du système de fourniture de vêtements de sécurité aux employés d'une grande entreprise française (EDF).

	Martha ORELLANO CARRASQUILLA
	Cadre methodologique pour l'analyse de la valeur durable dans la
	conception collaborative d'offres innovantes
	Spécialité : Génie Industriel
	Mots clefs : création de valeur; collaboration; innovation; développement durable; aide
	a ´ la décision multicritéres
	Résumé :

X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X

Characterisation of sustainable value creation

Collaborative innovation for sustainable value creation

5 Types of innovation (what?)

6 Collaborative innovation in today's business to business relationships (how?)

Decision making in multidimensional and multi-stakeholder value 66 creation

Framew ork applicatio n to the case of ICOVET project

Framework applicatio n to the case of ICOVET project

Conclusions and research perspectives

Sous-thèmesQuestions

Acknowledgements

I am convinced that for any achievement in the life, everybody has someone to thank for. 4

GUIDE D'ENTRETIEN (ACHATS)

Interlocuteur (Nom, fonction): L'objet spécifique de cet entretien est de connaitre les processus internes d'achat, approvisionnement, entretien et fin de vie des vêtements de travail chez EDF et leurs relations avec les acteurs externes, ainsi que les opportunités d'innovation visées.

entire development of the ICOVET project. Thanks to Fayol Institute for welcoming me to the adventure of research.

List of Figures