Mourad Harrat

Belkadi

Farouk

Alain Bernard

ICED FUZZY-BASED FRAMEWORK FOR MANAGING INTER-ENTERPRISE COLLABORATIONS IN PSS CONTEXT

Keywords: Inter-enterprise collaboration, Product-Service Systems (PSS), Key Performance Indicators (KPIs), Fuzzy logic

One of the biggest challenges of companies developing new solutions is how to properly manage the different relationships with external partners, especially in the case of Product-Service Systems (PSS). Developing a PSS requires for Original Equipment Manufacturers (OEM) to rethink the organization and roles of the different stakeholders regarding the characteristics of such environments. This paper aims to introduce a methodology to build a framework for inter-enterprise collaboration performance assessment and its corresponding Key Performance Indicators (KPIs). An extensive list of KPIs is established from key factors of collaboration performance and organizational characteristics in PSS context. Finally, further steps of the methodology are discussed where fuzzy techniques are used.

INTRODUCTION

Dealing nowadays with the increasing complexity of products and services, as well as high quality demands forces organisations to collaborate with external partners in order to share efforts, knowledge and skills, so that every partner can focus on his core competences [START_REF] Benhayoun-Sadafiyine | La capacité d'absorption des PMEs intégrées dans des réseaux d'innovation collaboratifs : évaluation à travers une grille de maturité[END_REF][START_REF] Al-Hakim | The role of collaboration and technology diffusion on business performance[END_REF]. The diversity of knowledge and capabilities is more important in the case of Product-Service Systems (PSS) offers. In this context, many authors suggest to manufacturers to request service knowledge from foreign suppliers to build a complete solution [START_REF] Ayala | Knowledge sharing dynamics in service suppliers' involvement for servitization of manufacturing companies[END_REF][START_REF] Bastl | Buyer-supplier relationships in a servitized environment: An examination with Cannon and Perreault's framework[END_REF][START_REF] Lockett | Product Service Systems and supply network relationships: an exploratory case study[END_REF]. To successfully achieve a PSS development project, companies need to reconsider the different coordination routines, roles and scope of competencies regarding the business domain diversity and geographical distribution of stakeholders [START_REF] Wallin | Measuring Innovation Capability -Assessing Collaborative Performance in Product-Service System Innovation[END_REF]. Regarding this complexity, it is necessary for the organization to follow up and evaluate the performance of the interenterprise collaboration, allowing continuous improvements of their processes [START_REF] Boughzala | Evaluating Team Collaboration Quality: The Development and Field Application of a Collaboration Maturity Model[END_REF], and considering the organizational particularities of PSS. Various collaboration assessment models are proposed in literature, as the example of maturity grids [START_REF] Boughzala | Evaluating Team Collaboration Quality: The Development and Field Application of a Collaboration Maturity Model[END_REF][START_REF] Cuenca | Structural elements of coordination mechanisms in collaborative planning processes and their assessment through maturity models: Application to a ceramic tile company[END_REF][START_REF] Magdaleno | A roadmap to the Collaboration Maturity Model (CollabMM) evolution[END_REF], Bayesian networks and approximate sets [START_REF] Rosas | Modeling collaboration preparedness assessment[END_REF], or theory of constraints [START_REF] Tenera | Collaborative Networks Management from a Theory of Constraints Perspective[END_REF]). In the PSS context, some works are presented such as readiness assessment of collaborative network organizations for PSS delivery, using conceptual modelling and graph theory [START_REF] Durugbo | Readiness assessment of collaborative networked organisations for integrated product and service delivery[END_REF], and network uncertainty for PSS delivery using fuzzy Delphi-AHP-TOPSIS methods [START_REF] Wang | Analysing network uncertainty for industrial product-service delivery: A hybrid fuzzy approach[END_REF]. However, the literature focusing in collaboration performance within PSS context is still limited and does not consider all factors really influencing the collaboration process. In addition, collaboration in PSS context is generally extended beyond the development stage, where the collaborators during the design phase try to maintain their relationship along the use phase and bring other suppliers since the PSS offer requests complementary efforts to operate. This paper introduces a new framework to assess inter-enterprise collaboration performance, focusing on the particularities of PSS. For this, we use fuzzy techniques following the process of [START_REF] Ayadi | A decision support system assessing the trust level in supply chains based on information sharing dimensions[END_REF] in his study of assessing trust level in supply chains. In the next section, after introducing the context of our framework, we present the Key Performance Indicators (KPIs) defined as inputs of our assessment model. These KPIs are based on key collaboration performance factors as well as organizational characteristics of PSS business models. Further steps of the methodology are explained in section 3. Finally, we draw a conclusion with some perspectives.

ICED

KPIS DEFINED FOR BUILDING THE COLLABORATION MANAGEMENT FRAMEWORK

In order to achieve performance goals throughout the PSS life-cycle, PSS provider should know how to manage his collaborations. The process presented in Figure 1. covers the PSS development phase, and also the use phase if the same partners from the project are kept.

Figure 1. Process of managing inter-enterprise collaboration performance

Therefore, the ability of the different stakeholders to collaborate in a PSS development project has to be measured in a pre-collaboration assessment. This will lead to the decision to start or no the collaborative project, and a number of improvement actions should be conducted in order to remedy the lacking competences. In further steps of the project, it is necessary to perform an assessment during and postcollaboration, followed by a capitalization step, by using some measures that will be useful for future pre-collaboration assessments. This process (Fig1) contains basic elements that define our collaborations' management framework, which should be generic to different business areas. The first step of building our framework is to define our measures in the form of KPIs, which we develop in the next sub-sections. This goal is achieved on two complementary points of view. Firstly, since the PSS share some similarities with classical product development in terms of processes, methods and resources, a first category of KPIs seems to be generic (section 2.1). These KPIs are identified based on literature survey regarding collaborative processes in general. Secondly, a dedicated literature survey analysing the key characteristics of PSS paradigm results on the identification of an additional list of specific KPIs (section 2.2).

KPIs based on key factors of collaboration performance

Before introducing KPIs to build our assessment model, it is important to identify which factors affect inter-enterprise this performance in an overall context. According to this, [START_REF] Harrat | Towards a modelaing framework of collaboration in PSS development project: A review of key factors[END_REF] presented a literature review which addresses the context of inter-firm collaboration between organizations in a general case, and identified a list of ten collaboration performance factors. They suggest that these factors can be adapted to PSS context, as stakeholders of a PSS project are coming originally from conventional business fields. As this latter study matches our framework, we select from their listed factors four of them according to three criteria: (1) their importance in the context of our study, (2) the number of their citations and (3) the ease of measuring them with KPIs. These factors are: trust, commitment, communication quality and coordination. Thus, the KPI building process was based on these factors. First, for trust factor, the proposed KPIs are: pre and post-transaction costs, collaboration history, and knowledge protection.

Transaction costs:

Transaction Costs (TC) are strongly linked to trustworthiness according to [START_REF] Dyer | The role of trustworthiness in reducing transaction costs and improving performance: Empirical evidence from the United States, Japan, and Korea[END_REF]. These authors defined two types of TC: "ex ante" and "ex post" TC. Ex ante TC are defined as "search and contracting costs". They include the costs generated from searching a desirable partner, negotiating and time spent until agreeing in a contract. In a trusted relationship, negotiation process is more efficient as ICED the buyer is more confident about the authenticity of information given by the partner, and the inclination to guard against opportunistic behaviour is reduced [START_REF] Dyer | The role of trustworthiness in reducing transaction costs and improving performance: Empirical evidence from the United States, Japan, and Korea[END_REF], which will decrease Ex ante TC. On the other hand, ex post TC refer to the costs related to monitoring the agreement and making sure that obligations of each party are respected. [START_REF] Dyer | The role of trustworthiness in reducing transaction costs and improving performance: Empirical evidence from the United States, Japan, and Korea[END_REF] found even a stronger relationship between trust and ex post TC, compared to ex ante TC. Indeed, they argued that when trust is high, the parties will spend less time in monitoring the agreement fulfilment or even blaming the other party for problems. Thus, from this study we adapt our definition about KPIs concerning TC as following:

𝑃𝑟𝑒_𝑡𝑟𝑎𝑛𝑠𝑎𝑐𝑡𝑖𝑜𝑛 𝑐𝑜𝑠𝑡𝑠 = 𝑇𝑖𝑚𝑒 𝑠𝑝𝑒𝑛𝑡 𝑜𝑛 𝑛𝑒𝑔𝑜𝑐𝑖𝑎𝑡𝑖𝑜𝑛 𝑡𝑜𝑡𝑎𝑙 𝑡𝑖𝑚𝑒 𝑜𝑓 𝑡𝑟𝑎𝑛𝑠𝑎𝑐𝑡𝑖𝑜𝑛 𝑃𝑜𝑠𝑡_𝑡𝑟𝑎𝑛𝑠𝑎𝑐𝑡𝑖𝑜𝑛 𝑐𝑜𝑠𝑡𝑠 = 𝑇𝑖𝑚𝑒 𝑠𝑝𝑒𝑛𝑡 𝑜𝑛 𝑚𝑜𝑛𝑖𝑡𝑜𝑟𝑖𝑛𝑔 𝑝𝑜𝑠𝑡_𝑡𝑟𝑎𝑛𝑠𝑎𝑐𝑡𝑖𝑜𝑛 𝑝𝑟𝑜𝑏𝑙𝑒𝑚𝑠 𝑡𝑜𝑡𝑎𝑙 𝑡𝑖𝑚𝑒 𝑜𝑓 𝑡𝑟𝑎𝑛𝑠𝑎𝑐𝑡𝑖𝑜𝑛

History of collaborations:

Collaborations' history is also an important KPI for trust. Many authors suggest that trust takes time to be developed through long-term business relationships and after several transactions [START_REF] Dyer | The determinants of trust in supplier-automaker relationships in the U.S. Japan and Korea[END_REF][START_REF] Belkadi | Collaboration management framework for OEMsuppliers relationships: a trust-based conceptual approach[END_REF]. Longer relationships make partners knowing better each other, and their behaviour become more understandable and predictable [START_REF] Dyer | The determinants of trust in supplier-automaker relationships in the U.S. Japan and Korea[END_REF]. Extensive prior relationship history characterized by successful transactions imply stable relations and a willingness to continue the collaboration for new projects [START_REF] Belkadi | Collaboration management framework for OEMsuppliers relationships: a trust-based conceptual approach[END_REF]. Therefore, we define the following KPI about History of collaboration:

𝐻𝑖𝑠𝑡𝑜𝑟𝑦 𝑜𝑓 𝑐𝑜𝑙𝑙𝑎𝑏𝑜𝑟𝑎𝑡𝑖𝑜𝑛 = 𝑁𝑢𝑚𝑏𝑒𝑟 𝑜𝑓 𝑝𝑟𝑖𝑜𝑟 𝑐𝑜𝑙𝑙𝑎𝑏𝑜𝑟𝑎𝑡𝑖𝑜𝑛𝑠 𝑤𝑖𝑡ℎ 𝑡ℎ𝑒 𝑐𝑜𝑛𝑐𝑒𝑟𝑛𝑒𝑑 𝑝𝑎𝑟𝑡𝑛𝑒𝑟 Knowledge protection: [START_REF] Norman | Protecting knowledge in strategic alliances resource and relational characteristics[END_REF] found that trust significantly reduces knowledge protection supports. She explained that when a company trusts its partner, it will be less dependent to structural mechanisms used to control the information flow and limit the knowledge, as it will rely to the goodwill of the partner who will not use this knowledge in ways that are detrimental to them. On the other hand, an overemphasis on knowledge protection weakens trust and significantly reduces interfirm collaboration [START_REF] Jean | The effects of supplier involvement and knowledge protection on product innovation in customer-supplier relationships: A study of global automotive suppliers in China[END_REF]). The metrics used for knowledge protection are the percentage of information sharing, as an adaptation from [START_REF] Norman | Protecting knowledge in strategic alliances resource and relational characteristics[END_REF].

% 𝑜𝑓 𝑖𝑛𝑓𝑜𝑟𝑚𝑎𝑡𝑖𝑜𝑛 𝑠ℎ𝑎𝑟𝑖𝑛𝑔 = 𝑄𝑢𝑎𝑛𝑡𝑖𝑡𝑦 𝑜𝑓 𝑠ℎ𝑎𝑟𝑒𝑑 𝑖𝑛𝑓𝑜𝑟𝑚𝑎𝑡𝑖𝑜𝑛 𝑄𝑢𝑎𝑛𝑡𝑖𝑡𝑦 𝑜𝑓 𝑎𝑣𝑎𝑖𝑙𝑎𝑏𝑙𝑒 𝑖𝑛𝑓𝑜𝑟𝑚𝑎𝑡𝑖𝑜𝑛

Where information refers to: marketing plans, technical information, and strategic information.

The second factor "commitment", is related to the KPIs: participation, schedule respect and reactivity.

Participation:

On a perspective of commitment, [START_REF] Westphal | Measuring collaboration performance in virtual organizations[END_REF] proposed the degree of participation in meeting or conference calls as a metric for collaboration performance. Participation refers to the active involvement of different parties in planning, problem solving, and decision-making [START_REF] Wibisono | Interaction quality and the influence on offshore IT outsourcing success[END_REF]. Empirically, [START_REF] Lee | Effect of Partnership Quality on IS Outsourcing Success: Conceptual Framework and Empirical Validation[END_REF] found that participation was significantly related to partnership quality, and positively associated with trust, business understanding, and commitment. We adapt this indicator by taking into account partner's participation in the project decisions, in order to consider efficiency of participation, as follows:

% 𝑜𝑓 𝑝𝑎𝑟𝑡𝑖𝑐𝑖𝑝𝑎𝑡𝑖𝑜𝑛 = 𝑁𝑢𝑚𝑏𝑒𝑟 𝑜𝑓 𝑑𝑒𝑐𝑖𝑠𝑖𝑜𝑛𝑠 𝑖𝑛𝑣𝑜𝑙𝑣𝑖𝑛𝑔 𝑝𝑎𝑟𝑡𝑛𝑒𝑟 𝑇𝑜𝑡𝑎𝑙 𝑛𝑢𝑚𝑏𝑒𝑟 𝑜𝑓 𝑡𝑎𝑘𝑒𝑛 𝑑𝑒𝑐𝑖𝑠𝑖𝑜𝑛𝑠

Schedule respect:

Another metric in the perspective of commitment presented by [START_REF] Westphal | Measuring collaboration performance in virtual organizations[END_REF] is concerning deviations from planning. When a partner puts the project in his priorities, he will give importance to respecting time schedules and delivery dates. In particular, parties who exchange high-quality ICED knowledge and are fully committed to the project will be able to avoid delays and reworks [START_REF] Yan | Buyer-supplier collaboration quality in new product development projects[END_REF] . Thus, we adapt this indicator from [START_REF] Westphal | Measuring collaboration performance in virtual organizations[END_REF] as following:

𝑆𝑐ℎ𝑒𝑑𝑢𝑙𝑒 𝑟𝑒𝑠𝑝𝑒𝑐𝑡 = 𝑁𝑢𝑚𝑏𝑒𝑟 𝑜𝑓 𝑑𝑒𝑣𝑖𝑎𝑡𝑖𝑜𝑛𝑠 𝑓𝑟𝑜𝑚 𝑝𝑙𝑎𝑛𝑛𝑖𝑛𝑔 𝑇𝑜𝑡𝑎𝑙 𝑛𝑢𝑚𝑏𝑒𝑟 𝑜𝑓 𝑝𝑙𝑎𝑛𝑛𝑒𝑑 𝑎𝑐𝑡𝑖𝑜𝑛𝑠

Reactivity:

This metric was defined by [START_REF] Cheriti | Conception collaborative : propositions pour construire et piloter des relations performantes avec les fournisseurs[END_REF] to indicate responsiveness of suppliers to different buyer's requests. Reactivity of partners to different other parties' requests is one of signs of commitment and the importance given to the corresponding project. Accordingly, a close and strong relationship with a supplier will enhance his responsiveness [START_REF] Davis-Sramek | Leveraging supply chain orientation for global supplier responsiveness: The impact of institutional distance[END_REF]). Thus, reactivity indicator is calculated as following:

𝐴𝑣𝑒𝑟𝑎𝑔𝑒 𝑟𝑒𝑠𝑝𝑜𝑛𝑠𝑒 𝑡𝑖𝑚𝑒 = 𝑆𝑢𝑚 𝑜𝑓 𝑡ℎ𝑒 𝑑𝑒𝑙𝑎𝑦𝑠 𝑜𝑓 𝑡ℎ𝑒 𝑑𝑖𝑓𝑓𝑒𝑟𝑒𝑛𝑡 𝑟𝑒𝑞𝑢𝑒𝑠𝑡𝑠 𝑇𝑜𝑡𝑎𝑙 𝑛𝑢𝑚𝑏𝑒𝑟 𝑜𝑓 𝑟𝑒𝑞𝑢𝑒𝑠𝑡𝑠
The third factor is communication quality. Its associated KPIs are: effectiveness of meetings and openness of communication channels.

Effectiveness of meetings:

Some indicators were proposed by [START_REF] Wallin | Measuring Innovation Capability -Assessing Collaborative Performance in Product-Service System Innovation[END_REF] in order to measure both quantity and quality of collaboration activities or connections (e.g. meetings). Because it is not enough to measure only the quantity, we need also to explore the quality of collaboration meetings in order to know if they involve collaboration ideation or only exchange of information [START_REF] Wallin | Measuring Innovation Capability -Assessing Collaborative Performance in Product-Service System Innovation[END_REF]), which will gives us an idea about their effectiveness. Therefore, we propose a ratio to calculate the effectiveness of meetings:

𝐸𝑓𝑓𝑒𝑐𝑡𝑖𝑣𝑒𝑛𝑒𝑠𝑠 𝑜𝑓 𝑚𝑒𝑒𝑡𝑖𝑛𝑔𝑠 = 𝑁𝑢𝑚𝑏𝑒𝑟 𝑜𝑓 𝑚𝑒𝑒𝑡𝑖𝑛𝑔𝑠 𝑐𝑜𝑛𝑑𝑢𝑐𝑡𝑖𝑛𝑔 𝑡𝑜 𝑖𝑑𝑒𝑎𝑡𝑖𝑜𝑛 𝑜𝑟 𝑑𝑒𝑐𝑖𝑠𝑖𝑜𝑛 𝑚𝑎𝑘𝑖𝑛𝑔 𝑇𝑜𝑡𝑎𝑙 𝑛𝑢𝑚𝑏𝑒𝑟 𝑜𝑓 𝑚𝑒𝑒𝑡𝑖𝑛𝑔𝑠

Openness of communication channels:

Limitation of communication channels is another way to protect knowledge. A less restricted communication channels is a sign of a good level of trust [START_REF] Norman | Protecting knowledge in strategic alliances resource and relational characteristics[END_REF], and will positively impact on knowledge sharing. Identically to knowledge protection indicator, we measure openness of communication channels as following:

𝑂𝑝𝑒𝑛𝑛𝑒𝑠𝑠 𝑜𝑓 𝑐𝑜𝑚𝑚𝑢𝑛𝑖𝑐𝑎𝑡𝑖𝑜𝑛 𝑐ℎ𝑎𝑛𝑛𝑒𝑙𝑠 = 𝑁𝑢𝑚𝑏𝑒𝑟 𝑜𝑓 𝑎𝑐𝑐𝑒𝑠𝑠𝑖𝑏𝑙𝑒 𝑐𝑜𝑚𝑚𝑢𝑛𝑖𝑐𝑎𝑡𝑖𝑜𝑛 𝑐ℎ𝑎𝑛𝑛𝑒𝑙𝑠 𝑁𝑢𝑚𝑏𝑒𝑟 𝑜𝑓 𝑒𝑥𝑖𝑠𝑡𝑖𝑛𝑔 𝑐𝑜𝑚𝑚𝑢𝑛𝑖𝑐𝑎𝑡𝑖𝑜𝑛 𝑐ℎ𝑎𝑛𝑛𝑒𝑙𝑠
The fourth factor is coordination. The KPIs identified to be related to this factor are: planning adjustment and conflict solving.

Planning adjustment: [START_REF] Westphal | Measuring collaboration performance in virtual organizations[END_REF] proposed "frequency of adjusting/coordinating the planning" as an indicator related to decision synchronization in Virtual Organizations. Adjusting planning will improve coordination between the partners in the project, by avoiding decision conflicts and task duplication. In the event of technology issues, when collaboration partners can no longer focus on formally agreed upon milestones, they must adjust milestones and target dates to ensure adherence to schedules [START_REF] Pemartín | Is the formalization of NPD collaboration productive or counterproductive? Contingent effects of trust between partners[END_REF]. This KPI is defined so:

𝐹𝑟𝑒𝑞𝑢𝑒𝑛𝑐𝑦 𝑜𝑓 𝑝𝑙𝑎𝑛𝑛𝑖𝑛𝑔 𝑎𝑑𝑗𝑢𝑠𝑡𝑚𝑒𝑛𝑡 = 𝑁𝑢𝑚𝑏𝑒𝑟 𝑜𝑓 𝑝𝑙𝑎𝑛𝑛𝑖𝑛𝑔 𝑎𝑑𝑗𝑢𝑠𝑡𝑚𝑒𝑛𝑡𝑠 𝑝𝑒𝑟 𝑚𝑜𝑛𝑡ℎ

Conflict solving:

Resolving conflicts is essential for collaborative projects and has a positive impact on collaboration quality [START_REF] Dietrich | The dynamics of collaboration in multipartner projects[END_REF]. A high level of communication willingness will help project teams to coordinate and resolve conflicts which in turn contribute towards the project success [START_REF] Wu | Investigating the relationship between communication-conflict interaction and project success among construction project teams[END_REF]). Thus, conflicts are solved effectively in a team level and do not need an involvement of the top management. As an adaptation from [START_REF] Westphal | Measuring collaboration performance in virtual organizations[END_REF], we measure the number of problems that could not be solved but need escalation to direction.

ICED

𝐶𝑜𝑛𝑓𝑙𝑖𝑐𝑡 𝑠𝑜𝑙𝑣𝑖𝑛𝑔 = 𝑁𝑢𝑚𝑏𝑒𝑟 𝑜𝑓 𝑝𝑟𝑜𝑏𝑙𝑒𝑚𝑠 𝑛𝑒𝑒𝑑𝑖𝑛𝑔 𝑒𝑠𝑐𝑎𝑙𝑎𝑡𝑖𝑜𝑛 𝑡𝑜 𝑑𝑖𝑟𝑒𝑐𝑡𝑖𝑜𝑛 𝑇𝑜𝑡𝑎𝑙 𝑛𝑢𝑚𝑏𝑒𝑟 𝑜𝑓 𝑒𝑛𝑐𝑜𝑢𝑛𝑡𝑟𝑒𝑑 𝑝𝑟𝑜𝑏𝑙𝑒𝑚𝑠

The proposed indicators build from the most important collaboration factors [START_REF] Harrat | Towards a modelaing framework of collaboration in PSS development project: A review of key factors[END_REF]) are necessary, but not sufficient to assess inter-enterprise collaboration performance for PSS development. Indeed, we need also to explore the PSS organizational context in order to highlight its particularities and collaboration practices, from where we can define new KPIs to build a more extensive framework.

KPIs based on organizational practices within PSS context

The second type of KPIs concerns organizational practices and suggestions which characterize interenterprise collaboration in PSS context. From a selection of 10 articles, PSS organizational practices were proposed by authors through different terms : routines [START_REF] Wallin | Understanding product-service system innovation capabilities development for manufacturing companies[END_REF], characteristics [START_REF] Saccani | Investigating the linkages between service types and supplier relationships in servitized environments[END_REF], tactics and operational practices [START_REF] Reim | Product-Service Systems (PSS) business models and tactics -A systematic literature review[END_REF]…etc. From this small literature review, we could identify some practices and transformed them into KPIs. We present these practices under five main themes: information and knowledge sharing, interoperability and adaptation, contract management, whole cycle-life consideration, and customers interaction data.

Information and knowledge sharing:

According to [START_REF] Bastl | Buyer-supplier relationships in a servitized environment: An examination with Cannon and Perreault's framework[END_REF], servitisation (i.e. the process to transform companies into PSS providers) context needs higher levels of integration of the supply chain. Therefore, information exchange should be open, bidirectional with higher frequency comparing to the context of pure products. Accordingly, [START_REF] Lockett | Product Service Systems and supply network relationships: an exploratory case study[END_REF] suggest that the adoption of PSS business models requires a more intensive information exchange between supply chain members, which implies the necessity to have closer relationships. In the light of these suggestions, we propose two KPIs related to information and knowledge sharing, which are both frequency and reciprocity of information/knowledge sharing:

𝐹𝑟𝑒𝑞𝑢𝑒𝑛𝑐𝑦 𝑜𝑓 𝑠ℎ𝑎𝑟𝑖𝑛𝑔 = 𝑄𝑢𝑎𝑛𝑡𝑖𝑡𝑦 𝑜𝑓 𝑘𝑛𝑜𝑤𝑙𝑒𝑑𝑔𝑒 𝑠ℎ𝑎𝑟𝑖𝑛𝑔 𝑎𝑐𝑡𝑖𝑣𝑖𝑡𝑖𝑒𝑠 𝑝𝑒𝑟 𝑚𝑜𝑛𝑡ℎ 𝑅𝑒𝑐𝑖𝑝𝑟𝑜𝑐𝑖𝑡𝑦 𝑜𝑓 𝑠ℎ𝑎𝑟𝑖𝑛𝑔 = 𝑄𝑢𝑎𝑛𝑡𝑖𝑡𝑦 𝑜𝑓 𝑠ℎ𝑎𝑟𝑒𝑑 𝑘𝑛𝑜𝑤𝑙𝑒𝑑𝑔𝑒 𝑏𝑦 𝑡ℎ𝑒 𝑝𝑎𝑟𝑡𝑦 𝑇𝑜𝑡𝑎𝑙 𝑞𝑢𝑎𝑛𝑡𝑖𝑡𝑦 𝑜𝑓 𝑠ℎ𝑎𝑟𝑒𝑑 𝑘𝑛𝑜𝑤𝑙𝑒𝑑𝑔𝑒

Interoperability and adaptation:

One of the definitions of interoperability is the ability of companies to interact with each other.

Interoperability is achieved if the interaction can at least take place on three levels: data level, application level and business process level (IDEAS 2003). In PSS context, linkages and interactions between systems, procedures, and routines should be more formalized and closely coupled comparing to pure products development environment [START_REF] Bastl | Buyer-supplier relationships in a servitized environment: An examination with Cannon and Perreault's framework[END_REF]. These operational links which facilitate processes and increase their effectiveness, can be implemented the form of integrated information systems that allow parties to exchange schedules, request spare parts, or provide feedbacks on interventions [START_REF] Saccani | Investigating the linkages between service types and supplier relationships in servitized environments[END_REF]. Furthermore, it is suggested that some adaptations to partners' needs are more necessary in the case of PSS business models, with the need of a reciprocity from partners in these adaptations [START_REF] Bastl | Buyer-supplier relationships in a servitized environment: An examination with Cannon and Perreault's framework[END_REF], or even the creation of common processes to manage interdependencies between partners and support interactions between them [START_REF] Windahl | Developing integrated solutions: The importance of relationships within the network[END_REF]. According to these suggestions, we define the following KPIs: the percentage of mutual adaptation to the mode of operation (processes, procedures, practices...) between the partners, as well as the percentage of adequacy of the standards used by both parties:

% 𝑜𝑓 𝑚𝑢𝑡𝑢𝑎𝑙 𝑎𝑑𝑎𝑝𝑡𝑎𝑡𝑖𝑜𝑛 = 𝑁𝑢𝑚𝑏𝑒𝑟 𝑜𝑓 𝑎𝑙𝑖𝑔𝑛𝑒𝑑 𝑝𝑟𝑜𝑐𝑒𝑠𝑠𝑒𝑠 𝑎𝑛𝑑 𝑝𝑟𝑎𝑐𝑡𝑖𝑐𝑒𝑠 𝑇𝑜𝑡𝑎𝑙 𝑛𝑢𝑚𝑏𝑒𝑟 𝑜𝑓 𝑝𝑟𝑜𝑐𝑒𝑠𝑠𝑒𝑠 𝑎𝑛𝑑 𝑝𝑟𝑎𝑐𝑡𝑖𝑐𝑒𝑠 % 𝑜𝑓 𝑎𝑑𝑒𝑞𝑢𝑎𝑐𝑦 𝑜𝑓 𝑠𝑡𝑎𝑛𝑑𝑎𝑟𝑑𝑠 = 𝑁𝑢𝑚𝑏𝑒𝑟 𝑜𝑓 𝑐𝑜𝑚𝑚𝑜𝑛 𝑠𝑡𝑎𝑛𝑑𝑎𝑟𝑑𝑠 𝑇𝑜𝑡𝑎𝑙 𝑛𝑢𝑚𝑏𝑒𝑟 𝑜𝑓 𝑢𝑠𝑒𝑑 𝑠𝑡𝑎𝑛𝑑𝑎𝑟𝑑𝑠

Contract management:

Concerning contractual mechanisms, [START_REF] Bastl | Buyer-supplier relationships in a servitized environment: An examination with Cannon and Perreault's framework[END_REF] highlight that contracts in PSS context should be more detailed in order to capture the high complexity and risk levels in servitized environments, or otherwise to complete contracts with relational mechanisms based on trust. For example, promoting a win/win mentality. Based on a literature review, [START_REF] Reim | Product-Service Systems (PSS) business models and tactics -A systematic literature review[END_REF] presented some PSS tactics on key ICED aspects of contracts: Responsibility and terms of agreements, formalization and complexity, and risk level. These aspects are presented according to each PSS type (i.e. Product-Oriented, PO; Usage-Oriented, UO; and Result-Oriented, RO). Contracts are more complex in the case of PSS comparing to pure products, but it differs from one PSS type to another [START_REF] Richter | On the relation between industrial product-service systems and business models[END_REF]. Indeed, [START_REF] Reim | Product-Service Systems (PSS) business models and tactics -A systematic literature review[END_REF] found complexity lower for PO, medium of UO and higher for RO. This is also the case for risk level for PSS business models, where they are generally related to gains received by the PSS provider, and specifically to higher efforts expected to fulfil the agreement in case of PO, adverse customer behaviour in case of UO, and results delievery in case of RO [START_REF] Reim | Product-Service Systems (PSS) business models and tactics -A systematic literature review[END_REF]. In this regard, complexity and PSS type are introduced in our model as attributes in order to consider the project's context. We also introduce in a KPI for risk level which is related to partner's commitment:

% 𝑜𝑓 𝑐𝑜𝑛𝑡𝑟𝑎𝑐𝑡𝑢𝑎𝑙𝑙𝑦 𝑐𝑜𝑚𝑚𝑖𝑡𝑒𝑑 𝑟𝑖𝑠𝑘 = 𝐴𝑚𝑜𝑢𝑛𝑡 𝑜𝑓 𝑐𝑜𝑚𝑚𝑖𝑡𝑒𝑑 𝑟𝑖𝑠𝑘 𝑏𝑦 𝑡ℎ𝑒 𝑝𝑎𝑟𝑡𝑦 𝑇𝑜𝑡𝑎𝑙 𝑎𝑚𝑜𝑢𝑛𝑡 𝑜𝑓 𝑐𝑜𝑚𝑚𝑖𝑡𝑒𝑑 𝑟𝑖𝑠𝑘 𝑏𝑦 𝑎𝑙𝑙 𝑡ℎ𝑒 𝑝𝑎𝑟𝑡𝑖𝑒𝑠

Whole life-cycle consideration:

Another important characteristic of PSS, is the necessity of organizations to consider the whole lifecycle of the solution when developing a PSS, because development and delivery processes are extended beyond the sale of the product [START_REF] Wallin | Understanding product-service system innovation capabilities development for manufacturing companies[END_REF]. It implies the necessity for firms to understand the entire PSS life-cycle, and to be able to evaluate its related costs and risks [START_REF] Lockett | Product Service Systems and supply network relationships: an exploratory case study[END_REF]. This can include the involvement of maintenance and after-sales services, engineering department and marketing functions in the early stages of the development process [START_REF] Lockett | Product Service Systems and supply network relationships: an exploratory case study[END_REF][START_REF] Resta | Enhancing the Design and Management of the Product-Service System Supply Chain: An Application to the Automotive Sector[END_REF]. It is therefore necessary to involve all supply chain partners in order to perform a complete evaluation of the offer [START_REF] Wallin | Understanding product-service system innovation capabilities development for manufacturing companies[END_REF]. [START_REF] Lockett | Product Service Systems and supply network relationships: an exploratory case study[END_REF] mentioned that this perspective can present certain difficulties. In some cases, costs of replacing parts can be lower than those of repairing and maintenance, taking into accounts the value of raw material and the time taken to repair. Difficulties to evaluate the life-cycle costs of the PSS and risks due to an incorrect estimation are also some obstacles to adopt this perspective [START_REF] Lockett | Product Service Systems and supply network relationships: an exploratory case study[END_REF]). These difficulties were explored by authors who suggest an adapted design process of the solutions throughout their life-cycle [START_REF] Aurich | Life cycle oriented design of technical Product-Service Systems[END_REF], as well as design for maintenance or for services in PSS development [START_REF] Apitz | PSS Organisation: A workbook in the PROTEUS Series[END_REF]). In the light of these suggestions, we introduce a KPI which concern the involvement during the development phase of the various departments present throughout the PSS life-cycle (marketing, engineering, manufacturing, maintenance and after-sales service):

% 𝑜𝑓 𝑑𝑒𝑝𝑎𝑟𝑡𝑚𝑒𝑛𝑡 𝑖𝑛𝑣𝑜𝑙𝑣𝑒𝑚𝑒𝑛𝑡 𝑖𝑛 𝑒𝑎𝑟𝑙𝑦 𝑑𝑒𝑠𝑖𝑔𝑛 = 𝑁𝑢𝑚𝑏𝑒𝑟 𝑜𝑓 𝑝𝑎𝑟𝑡𝑖𝑐𝑖𝑝𝑎𝑡𝑖𝑜𝑛𝑠 𝑜𝑓 𝑡ℎ𝑒 𝑑𝑒𝑝𝑎𝑟𝑡𝑚𝑒𝑛𝑡 𝑖𝑛 𝑒𝑎𝑟𝑙𝑦 𝑑𝑒𝑠𝑖𝑔𝑛 𝑎𝑐𝑡𝑖𝑣𝑖𝑡𝑖𝑒𝑠 𝑇𝑜𝑡𝑎𝑙 𝑛𝑢𝑚𝑏𝑒𝑟 𝑜𝑓 𝑒𝑎𝑟𝑙𝑦 𝑐𝑜𝑙𝑙𝑎𝑏𝑜𝑟𝑎𝑡𝑖𝑣𝑒 𝑑𝑒𝑠𝑖𝑔𝑛 𝑎𝑐𝑡𝑖𝑣𝑖𝑡𝑖𝑒𝑠

Customers' interaction data:

Interactions between the provider and his customers generally increase when the firms are service oriented [START_REF] Reim | Product-Service Systems (PSS) business models and tactics -A systematic literature review[END_REF]. Indeed, customer relationship needs a higher attention in the PSS context [START_REF] Wallin | Understanding product-service system innovation capabilities development for manufacturing companies[END_REF]. As mentioned by [START_REF] Reim | Product-Service Systems (PSS) business models and tactics -A systematic literature review[END_REF], customer interactions differs in intensity depending on the type of PSS. They are regular in intensity for PO and higher for UO because of the need to ensure the usability of the PSS. The intensity of these interactions increases even more for RO regarding the need to keep a continuous contact with the customer [START_REF] Reim | Product-Service Systems (PSS) business models and tactics -A systematic literature review[END_REF]. PSS, by their nature, provide the ability to collect customer data during its operation or use. Thus, the authors recommend in this context the creation of a customer relationship platform accompanied by a regular collection of customer needs [START_REF] Wallin | Understanding product-service system innovation capabilities development for manufacturing companies[END_REF][START_REF] Reim | Product-Service Systems (PSS) business models and tactics -A systematic literature review[END_REF][START_REF] Saccani | Investigating the linkages between service types and supplier relationships in servitized environments[END_REF][START_REF] Avlonitis | PSS Readiness Manual: A workbook in the PROTEUS series[END_REF][START_REF] Windahl | Developing integrated solutions: The importance of relationships within the network[END_REF]. The metric we introduce express the percentage of data collection actions compared to the number of interactions.

% 𝑜𝑓 𝑑𝑎𝑡𝑎 𝑐𝑜𝑙𝑙𝑒𝑐𝑡𝑖𝑜𝑛 = 𝑁𝑢𝑚𝑏𝑒𝑟 𝑜𝑓 𝑑𝑎𝑡𝑎 𝑐𝑜𝑙𝑙𝑒𝑐𝑡𝑖𝑜𝑛 𝑎𝑐𝑡𝑖𝑜𝑛 𝑇𝑜𝑡𝑎𝑙 𝑛𝑢𝑚𝑏𝑒𝑟 𝑜𝑓 𝑐𝑢𝑠𝑡𝑜𝑚𝑒𝑟 𝑖𝑛𝑡𝑒𝑟𝑎𝑐𝑡𝑖𝑜𝑛𝑠 ICED

A METHODOLOGY TO BUILD A FRAMEWORK FOR COLLABORATION PERFORMANCE ASSESSMENT AND MANAGEMENT

In order to build our framework for inter-enterprise collaboration performance assessment and management, we use fuzzy logic techniques, regarding its capacities to counter ambiguity and imprecision problems in calculations [START_REF] Wang | Analysing network uncertainty for industrial product-service delivery: A hybrid fuzzy approach[END_REF], especially in solving socioeconomic problems. In our case, we have qualitative outputs (e.g. trust, commitment…etc.) which have no particular units of measure. Using fuzzy techniques is one solution to deal with this issue by using linguistic terms instead of precise numerical values. The considered inputs of this model at the fuzzification stage are our KPIs defined before. Each KPI is represented by a Membership Function (MF). Then, the system outputs are collaboration performance factors (Figure 2). The proposed methodology is inspired from [START_REF] Ayadi | A decision support system assessing the trust level in supply chains based on information sharing dimensions[END_REF] who used fuzzy techniques to assess trust level between partners is supply chain. To illustrate our work, we present an example of the KPI input "Pre-transaction costs" which is related to the output "trust factor" (Figure 3). We chose a mix of triangular and trapezoidal MF and standard thresholds for limit values of the MFs (0%, 25%, 50%, 75% and 100%) to cover large possibilities. Three MFs are defined to describe the value of transaction costs: Low (0, 0, 25), medium (25, 50, 75) and high (50, 75, 100, 100). The MFs "low" and "medium" are triangular, based on suggestions of [START_REF] Ayadi | A decision support system assessing the trust level in supply chains based on information sharing dimensions[END_REF] who consider this form appropriate to represent human factors and widely used in literature. On the other hand, the MF "high" is trapezoidal as we consider that from a percentage of negotiation time higher or equal to 75% of transaction time, the costs are high with a fuzzy value = 1 (certain). The next step is the creation of inference rules. For this step, the Mamdani's fuzzy inference method is used as it is convenient for human inputs [START_REF] Sivanandam | Introduction to fuzzy logic using MATLAB[END_REF]. Different methods can be used to generate fuzzy rules, such as the involvement of experts by using semi-structured interviews [START_REF] Ayadi | A decision support system assessing the trust level in supply chains based on information sharing dimensions[END_REF]). In the proposed approach, we opt for using a structured questionnaire to collect experts' points of view. Then, the inference rules will be generated from a decision tree, created by the C4.5 learning system, as suggested by [START_REF] Hall | Generation of Fuzzy Rules from Decision Trees[END_REF]. Indeed, these authors mentioned that decision tree theory provides a well-understood mechanism for inducing classification rules from data. To do so, it is necessary to split the continuous inputs and outputs into classes, as we did for Pre-transaction costs (three MF: low, medium and high TC). Using data collected from an online survey, we select the KPIs as attributes and factors (e.g. trust) as the target variable. To create fuzzy rules, we perform a depth search in the decision tree, and each time a path reaches a leaf, a rule is created with the previous nodes ICED by combining them with the "and" [START_REF] Hall | Generation of Fuzzy Rules from Decision Trees[END_REF]. the following rule is formulated as an example in figure 4 The rules can be directly used, or may be further tuned to increase their reliability [START_REF] Hall | Generation of Fuzzy Rules from Decision Trees[END_REF]. For this goal, it is also needed to pay attention to the population responses' number and percentage (mentioned in each node) which match the rule. A post-pruning approach can also be performed in order to remove irrelevant branches from the tree, in addition to the possibility for the expert to intervene in the process of model creation in order to get a better interpretation and understandability of the results [START_REF] Rakotomalala | Arbres de decision[END_REF].

CONCLUSION AND PERSPECTIVES

The objective of this paper is twofold. First, it aims to present the proposed KPIs as necessary to assess inter-enterprise collaboration performance in the context of PSS development. On the other hand, it introduces the early steps of a methodology of building a framework for collaboration performance management. Further steps after the development of the decision support system, are the confrontation of the overall model to real case studies. Several case studies in various business areas are in progress. One of them concerns the development of connected shoes, where deep interviews have been realized with different experts from the involved companies to extract business rules. The ongoing step is to present and deeply discuss the whole model. The objective of this model discussion is to perform some adjustments of the framework regarding the suggestions coming from industrials. Interviews are being performed about the relevance of the membership functions, KPIs, inference rules and the overall consistency of the assessment system.

Figure 2

 2 Figure 2 Fuzzy logic system for collaboration performance assessment

Figure 3

 3 Figure 3 Example of Membership Function "Pre-transaction costs"

:

  IF Risk shared = lower (from partner) AND Planning respect = total AND Participation = (Very High OR High OR Medium) THEN Commitment = High.

Figure 4

 4 Figure 4 Example of decision tree used for fuzzy rules generation


Mourad Harrat
email: mourad.harrat@ls2n.fr

Farouk Belkadi
email: farouk.belkadi@ls2n.fr

Alain Bernard
email: alain.bernard@ls2n.fr

A Methodology to Build a Framework for Collaboration Performance Assessment in PSS Delivery

Keywords: Collaboration, Product-Service Systems (PSS), Assessment

Companies are more and more seeking for external partners in order to manage new solutions at their development and use phases, especially when the type of these solutions is Product-Service Systems (PSS). PSS have some organizational particularities which increase the complexity of collaboration processes. In this context, collaborating efficiently with the different partners is a key aspect to reduce the risk of failure of PSS projects, and is influenced by various organizational factors and practices. This paper proposes a methodology in four steps to build a decision-aid framework supporting collaboration assessment and management in the presented context. Important factors and performance indicators are identified based on literature review and industrial practices. Then, Fuzzy techniques as well as decision trees are used to build the assessment systems. Three case studies are conducted to explore industrial practices and to confront the different elements of the proposed framework, and finally to validate the assessment framework.

Introduction

Product-Service Systems (PSS) can be defined as a combination of tangible products and intangible services which jointly responds to customer's needs [START_REF] Tukker | Eight types of product-service system: eight ways to sustainability?[END_REF]. Compared to pure products, these business models have an increased complexity and require multidisciplinary domains and competences along its whole lifecycle [START_REF] Wallin | Understanding product-service system innovation capabilities development for manufacturing companies[END_REF], which can be hardly held without the involvement of external partners. Thus, PSS contexts necessitate closer relationships with the different stakeholders, entailing a shift from a transactional to relational orientated partnerships [START_REF] Resta | Enhancing the design and management of the product-service system supply chain: an application to the automotive sector[END_REF]. This is due to the organizational differences induced by servitized environments, such as in contract management, life-cycle management, degree of data collection from customer, etc. [START_REF] Wallin | Understanding product-service system innovation capabilities development for manufacturing companies[END_REF]. Consequently, collaborations become a central aspect to manage in order to ensure the success of PSS development and use phases. To achieve effective collaborations in PSS context, two different aspects need to be explored and timely operationalized: [START_REF] Tukker | Eight types of product-service system: eight ways to sustainability?[END_REF] the factors influencing on inter-firm collaboration performance, and (2) the organizational practices suggested in PSS situations. The operationalization of these aspects can be performed by defining some relevant Key Performance Indicators (KPIs) and enabling an assessment process. Most of existing research works which established assessment frameworks for PSS context, focused on aspects such as design, functionalities, sustainability, customer satisfaction, maintenance, etc. [START_REF] Mourtzis | Performance indicators for the evaluation of product-service systems design : a review[END_REF]. In difference with classical New Product Development (NPD) projects, studies addressing collaboration performance assessment in PSS are still limited. For example, some authors dealt with the evaluation of collaborative networks readiness [START_REF] Durugbo | Readiness assessment of collaborative networked organisations for integrated product and service delivery[END_REF]. However, the literature is missing an extensive framework to assess collaboration performance for PSS contexts. To deal with this gap, this paper introduces a methodology for building such framework. The collaboration problem and context are clarified in Sect. 2. Then, the methodology is explained progressively in Sect. 3. An ongoing validation process is detailed in the conclusion.

Inter-firm Collaboration Within PSS Context

Before any partnership, and particularly to carry on PSS development and use phases, a recurring problem for firms is how to choose the relevant partners and how to ensure that these partners are able to participate in a collaborative PSS delivery. This ability translates into a set of capabilities and competences related to PSS which are required for each collaborating party. However, assessing a partner based solely on his competences is not sufficient, because the causes of an occurring problem during the collaboration can be beyond the control of the partner and being more related to the relationship [START_REF] Johnsen | Supply relationship evaluation: the relationship assessment process (RAP) and beyond[END_REF] (Fig. 1).

For example, some important criteria of success as efficient tasks coordination, an appropriate communication frequency, well-established routines of knowledge sharing, and an atmosphere of trust are needed to avoid risks of project failure. This requires an assessment at each step of the collaboration process.

Consequently, an assessment during collaboration is necessary. The assessment framework in this step is not only based on collaboration factors as mentioned above, but also on PSS organizational practices. Indeed, PSS business models have some particularities that we need to consider in this assessment process. One of these particularities is the necessity of a whole life-cycle consideration with long-term relationships with partners [START_REF] Zhang | Effects of social capital on operational performance: impacts of servitisation[END_REF][START_REF] Baines | A Delphi study to explore the adoption of servitization in UK companies[END_REF], as the collaboration process is extended beyond the sale of the product. This implies the necessity to involve all supply chain partners in early design, which may include maintenance and after sales services [START_REF] Wallin | Understanding product-service system innovation capabilities development for manufacturing companies[END_REF][START_REF] Resta | Enhancing the design and management of the product-service system supply chain: an application to the automotive sector[END_REF]. Another particularity is that contractual mechanisms of PSS show higher complexity regarding terms and agreements, with higher risk levels which is shared throughout the life-cycle [START_REF] Reim | Product-Service Systems (PSS) business models and tactics -a systematic literature review[END_REF][START_REF] Bastl | Buyer-supplier relationships in a servitized environment: an examination with Cannon and Perreault's framework[END_REF]. The permanent evolution of the PSS is also another characteristic of PSS, requiring closer interactions with customers [START_REF] Wallin | Understanding product-service system innovation capabilities development for manufacturing companies[END_REF][START_REF] Reim | Product-Service Systems (PSS) business models and tactics -a systematic literature review[END_REF], and higher levels of adapting common standards and processes [START_REF] Bastl | Buyer-supplier relationships in a servitized environment: an examination with Cannon and Perreault's framework[END_REF].

A Methodology for Building a Framework to Assess Collaboration Performance

The proposed methodology takes place in four main steps, which are presented in the following sub-sections. A fifth step which concerns the validation of the framework in is explained in conclusion as a work in progress.

Identification of Factors Impacting Collaboration Performance

The first step was to identify factors leading to successful collaboration. Here, a focus should be done on the performance of relationships between partners rather than the particular partners' performance only [START_REF] Johnsen | Supply relationship evaluation: the relationship assessment process (RAP) and beyond[END_REF][START_REF] Varoutsa | The governance of inter-organisational relationships during different supply chain maturity phases[END_REF]. Thus, we performed a literature review from a selection of 60 articles dealing with collaboration factors, chosen according to three criteria: (1) the addressed subject is about collaboration success factors; (2) the addressed context is collaboration between industrial organizations; and (3) the dependent variables or addressed concepts have a close meaning or similar characteristics to "collaboration performance". Thus, 41 factors were identified and then grouped into main categories. After that we filtered them according to three criteria: (1) the frequency of citation; (2) the adaptation to the context of the framework (inter-organizational collaboration, without including inter-personal factors); and finally (3) the significance of the impact of these factors by checking the consistency of the different studies. The references and more details of this literature review are mentioned by Harrat et al. (2020) [START_REF] Harrat | Towards a modeling framework of collaboration in PSS development project: a review of key factors[END_REF], and cannot be cited in this paper due to its size limitation. This review resulted on 10 retained factors which are: trust, commitment, shared vision and values, shared language, knowledge sharing, shared goals and interests, social network ties, coordination, communication quality, and interdependence.

Case Studies Presentation and Validation Process

In order to validate the list of factors and to consolidate the whole framework, three case studies were conducted by means of 5 different interviews (Table 1). Case A concerns the development project of a connected shoe, with the ability to detect falls and alert the emergency services. Since the latter services are integrated, the solution is considered as a product oriented-oriented PSS.

Case B is about the development project of a robot that ensures the drilling activity in construction sites. This robot is intended to be rented to construction sites according to their drilling needs. It is then considered as a use-oriented PSS.

Case C concerns the development project of a mobile robot providing support for surgical and imagery activities in an operating theater. This robot is sold by the OEM with assistance services, so it is considered as a product-oriented PSS.

Through semi structural interviews, the industrials were first questioned about different aspects, and especially the factors that are in relation with their collaboration performance. Except case C where there were globally no collaborative issues, the other cases present some considerable challenges.

In Case A, some trust issues were mentioned by the interviewee, between the OEM and the electronic design partner. The latter was considering his own constraints and was not able to adapt the solution to the OEM needs. Thus, the relationship was not balanced as described by the interviewee, which leaded the OEM to search for new partners in the project. On the other hand, Case B had a similar problem as Case A, as the specifications of the OEM did not meet the standards of his robot supplier. The ground clearance of the robot had to be high enough to be able to work in varied terrain, which was not in accordance with the standards of the supplier. The latter required a minimum height to ensure the safety of the operators. The OEM ended up accepting this constraint and the design was pursued and a final prototype was developed. At the end, the interviewee mentioned that the prototype was finally "a failure". This lets them to consider preparing a new project in future with a new supplier and a different design.

During the interviews, the industrials were asked to assess the importance of the different factors arose from our literature review. As a result of this assessment, we performed a second filtering of the factors, by keeping the ones considered most important according to the industrials, which are: trust, commitment, communication quality, project coordination and shared language.

KPIs Building and Validation

After validating the list of factors, the next step is to build the corresponding KPIs, by defining quantitative measures as percentages. This form of measure allows us to counter the subjectivity biases of human factors. The KPIs we define are adapted from indicators that are already validated by the literature. For each factor, we use references from both a PSS and a generic perspective to express the KPIs. Post-transaction costs [START_REF] Dyer | The role of trustworthiness in reducing transaction costs and improving performance: empirical evidence from the United States, Japan, and Korea[END_REF] History of collaboration [START_REF] Belkadi | Collaboration management framework for OEM -suppliers relationships: a trust-based conceptual approach[END_REF] Knowledge protection [START_REF] Jean | The effects of supplier involvement and knowledge protection on product innovation in customer-supplier relationships: a study of global automotive suppliers in China[END_REF] Commitment Participation [START_REF] Servajean-Hilst | Necessary governing practices for the success (and failure) of clientsupplier innovation cooperation[END_REF][START_REF] Wibisono | Interaction quality and the influence on offshore IT outsourcing success[END_REF] Commitment to schedule [START_REF] Westphal | Measuring collaboration performance in virtual organizations[END_REF][START_REF] Pemartín | Is the formalization of NPD collaboration productive or counterproductive? Contingent effects of trust between partners[END_REF] Responsiveness [START_REF] Davis-Sramek | Leveraging supply chain orientation for global supplier responsiveness: the impact of institutional distance[END_REF] Percentage of committed risk [START_REF] Bastl | Buyer-supplier relationships in a servitized environment: an examination with Cannon and Perreault's framework[END_REF][START_REF] Zou | Complexity in product-service systems: review and framework[END_REF] Communication quality

Effectiveness of meetings [22]

Openness of communication channels [START_REF] Norman | Protecting knowledge in strategic alliances resource and relational characteristics[END_REF] Frequency of knowledge sharing [START_REF] Bastl | Buyer-supplier relationships in a servitized environment: an examination with Cannon and Perreault's framework[END_REF][START_REF] Kohtamäki | Co-creating value from knowledge-intensive business services in manufacturing firms: the moderating role of relationship learning in supplier -customer interactions[END_REF][START_REF] Weigel | Success factors of service networks in the context of servitization -development and verification of an impact model[END_REF] (continued)

References with a PSS perspective

Reciprocity in knowledge sharing [START_REF] Bastl | Buyer-supplier relationships in a servitized environment: an examination with Cannon and Perreault's framework[END_REF][START_REF] Kohtamäki | Co-creating value from knowledge-intensive business services in manufacturing firms: the moderating role of relationship learning in supplier -customer interactions[END_REF][START_REF] Weigel | Success factors of service networks in the context of servitization -development and verification of an impact model[END_REF] Percentage of customer data collection [START_REF] Wallin | Understanding product-service system innovation capabilities development for manufacturing companies[END_REF] Project coordination

Planning adjustment [START_REF] Westphal | Measuring collaboration performance in virtual organizations[END_REF] Conflict solving [START_REF] Westphal | Measuring collaboration performance in virtual organizations[END_REF][START_REF] Wu | Investigating the relationship between communicationconflict interaction and project success among construction project teams[END_REF] Percentage of involvement of use phase departments in early design [START_REF] Wallin | Understanding product-service system innovation capabilities development for manufacturing companies[END_REF][START_REF] Resta | Enhancing the design and management of the product-service system supply chain: an application to the automotive sector[END_REF] Shared language

Percentage of mutual adaptations [START_REF] Bastl | Buyer-supplier relationships in a servitized environment: an examination with Cannon and Perreault's framework[END_REF][START_REF] Li | Servitization and performance: the moderating effect of supply chain integration[END_REF] Percentage of adequacy of standards [START_REF] Bastl | Buyer-supplier relationships in a servitized environment: an examination with Cannon and Perreault's framework[END_REF] We argue that the KPIs adapted from references with a generic perspective can be to PSS context. Indeed, the activity of the partners in a PSS development project generally come from conventional business fields (e.g. an OEM in automotive industry who wants to add specific services needs complementary skills) [START_REF] Harrat | Towards a modeling framework of collaboration in PSS development project: a review of key factors[END_REF]. In addition, Zhang (2017) [START_REF] Zhang | Effects of social capital on operational performance: impacts of servitisation[END_REF] proved that the effect of social capital (i.e. trust) on operational performance is higher in the PSS context.

On the other hand, the KPIs adapted from references with a PSS perspective highlight some organizational characteristics of PSS that need to be considered.

Yet, the suitability of the KPIs was assessed by interviewees from two previous case studies (Case B and C). The result of this process is presented in Table 2.

Building Membership Functions Using Fuzzy Techniques

The next step of the proposed methodology is the use of fuzzy techniques for the construction of the assessment system. The choice of this tool is leaded by the capacities of fuzzy techniques to counter ambiguity and imprecision problems in calculations, and the possibility to use linguistic terms instead of precise numerical values [START_REF] Ayadi | A decision support system assessing the trust level in supply chains based on information sharing dimensions[END_REF], especially in solving socioeconomic problems. This choice is also inspired from Ayadi et al. (2013) [START_REF] Ayadi | A decision support system assessing the trust level in supply chains based on information sharing dimensions[END_REF], who used fuzzy techniques to assess trust level between partners in supply chain. Thus, we start by defining the membership functions, by considering the KPI as inputs, and the different success factors of collaboration performance as outputs. A mix of triangular and trapezoidal functions is chosen for the representation of the membership function. This choice is leaded by the suitability of these functions to represent human factors [START_REF] Ayadi | A decision support system assessing the trust level in supply chains based on information sharing dimensions[END_REF]. They are also widely used in practice [START_REF] Ayadi | A decision support system assessing the trust level in supply chains based on information sharing dimensions[END_REF][START_REF] Barua | Why trapezoidal and triangular membership functions work so well: towards a theoretical explanation[END_REF], which is explained by [START_REF] Barua | Why trapezoidal and triangular membership functions work so well: towards a theoretical explanation[END_REF] [START_REF] Barua | Why trapezoidal and triangular membership functions work so well: towards a theoretical explanation[END_REF] using an interval-based theory. The different values of membership functions are chosen with an intuition method based on the experience of the authors and will be validated in a further step through in-depth case studies.

We illustrate this step with the example of the input "Effectiveness of meetings" which is one of the KPIs of the output "Communication Quality" (Fig. 2). The input variable is represented by the following formula:

Effectiveness of meetings = (Number of meetings conducting to ideation or decision making)/(Total number of meetings).

Three MFs are defined to describe the value of transaction costs: Low (0, 0, 10, 30), medium [START_REF] Davis-Sramek | Leveraging supply chain orientation for global supplier responsiveness: the impact of institutional distance[END_REF][START_REF] Hall | Generation of fuzzy rules from decision trees[END_REF]40,75) and high (40, 80, 100, 100). In this way, all the presented KPIs as inputs and the factors as outputs have their defined membership functions.

Inference Rules Definition

The next step of the methodology is to generate fuzzy inference rules, by using Mamdani's fuzzy inference method which is considered suitable for human inputs [START_REF] Ayadi | A decision support system assessing the trust level in supply chains based on information sharing dimensions[END_REF]. To improve the reliability of the assessment, the definition of these rules is performed by a combination of two iterations, which correspond to two methods presented in the literature. In the first iteration, we conduct a survey from which we extract data by using decision trees (C4.5 learning system). Decision trees provide a well-understood mechanism for inducing classification rules from data, as suggested by Hall and Lande (1998) [START_REF] Hall | Generation of fuzzy rules from decision trees[END_REF]. Secondly, we involve experts for rules definition and adjustment, by using semistructured interviews, which is a widely presented method and recommended by [START_REF] Ayadi | A decision support system assessing the trust level in supply chains based on information sharing dimensions[END_REF] [START_REF] Ayadi | A decision support system assessing the trust level in supply chains based on information sharing dimensions[END_REF].

In the first iteration, we performed a survey through a structured questionnaire from where we extract data by using the data mining process. Data Collection. For the purpose of data collection, we performed an online survey targeting people who already worked in a multi-partner project for product and/or service delivery. The questionnaire was sent to 353 people from three different networks of engineering schools. Thus, 67 responses were received, which constitutes a response rate of 19%. Respondents were asked to consider 1 to 3 partners in their answers. Among 67, 54 respondents considered 2 partners, while 40 considered 3 partners. This results to a total of 161 partners considered in the responses, which increase the data size to be used in the data mining process. Tables 3 show the composition of the sample. Extraction of Inference Rules. First, from the continuous input and output variables, classes were created to express intervals, which are necessary to build decision trees [START_REF] Hall | Generation of fuzzy rules from decision trees[END_REF]. These classes correspond to the membership functions (e.g., low, medium, high) as shown in the third step of the methodology (Fig. 2).

Decision trees are then generated based on our survey data. The output factors (trust, commitment, communication quality, coordination, shared language) are considered as target variables, and their corresponding KPIs are put as attributes. After that, fuzzy rules are extracted by performing a depth search in the decision tree. The created rules correspond to each time a path reaches a leaf [START_REF] Hall | Generation of fuzzy rules from decision trees[END_REF][START_REF] Das | Decision tree-based analytics for reducing air pollution[END_REF]. This process is illustrated by the following example in the decision tree generated for trust factor.

Based on the selected path from the C4.5 in Fig. 3 The percentages shown in the figure represent the population responses' which match the rule, and should be considered to improve reliability of the rules.

In the second iteration, the ongoing work is to conduct semi-structured interviews with experts from industry to adjust the inference rules. The results allow the generation of rules describing the relation between the KPIs and the factors in a first time, and between the factors and collaboration performance in a second time.

Conclusion and Perspectives

This paper proposes a methodology in four steps to build an assessment model for supporting inter-firm collaborations in PSS development and use phases. After ensuring the ability of partners to collaborate, the contribution of this framework is to assess the inter-firm relationships during the collaborations for PSS development and use phases. To do so, we first defined measures based on literature, and performed three case studies to validate them while analyzing industrial practices in terms of managing collaborations. The assessment system is built using fuzzy logic techniques. Furthermore, inference rules are created using decision trees by collecting data from a survey. The final step is the validation of the introduced framework through in-depth case studies. Indeed, the assessment model is currently being tested with industrials in order to make some adjustments. They are asked to enter values of the inputs to get the output value which is the performance of their collaboration in their PSS project. This assessment will finally allow the capitalization from their collaborations and the estimation of performance for future collaborations. This approach should help industrials to decide which strategy and improvement actions should be executed in order to collaborate effectively and to ensure the success of PSS delivery.

Fig. 1 .

 1 Fig. 1. Assessment cycle of collaboration performance in PSS context

Fig. 2 .

 2 Fig. 2. Illustrative membership functions "Effectiveness of meetings"

  , we formulate the following rule: IF Restriction of Marketing plans = severe AND History of Collaboration = 1 year AND Pre-transaction costs = (medium OR high OR very high) AND Restriction of technical information = (partial OR severe) THEN trust = Medium.

Fig. 3 .

 3 Fig. 3. Example of decision tree used for fuzzy rules generation

Table 1 .

 1 Details of the exploratory case study conducted

	Case	PSS name	PSS type	Interview with Business area Main activity
	Case A Connected	Product-oriented	1-OEM	Leather and	Shoe
		shoe			shoes	manufacturer
				2-Consulting	Electronics	IoT assistance
				Partner
	Case B	Drilling	Use-oriented	1-OEM	Construction	Public works
		robot			and public
					works
				2-Supplier	Robotics	Robot provider
	Case C	Surgery	Product-oriented	Supplier	Robotics	Robot provider
		robot

Table 2 .

 2 KPIs adapted from authors corresponding to collaboration performance factors

	Factors	Corresponding KPIs	References with a	References with a PSS
			generic perspective	perspective
	Trust	Pre-transaction costs	[13]	Same KPIs for social
				capital (e.g. trust,
				commitment) are
				applied in PSS
				perspective, according to
				Zhang (2017) [7]

Table 2 .

 2 (continued)

	Factors	Corresponding KPIs	References with a
			generic perspective

Table 3 .

 3 Composition of the sample

	Geographical position		Solution type
	France	33	49% Product(s) 28	42%
	Africa	12	18% Service(s)	11	16%
	Europe (other) 7	10% Product	14	21%
				oriented
				PSS
	USA	6	9%	Use	3	4%
				oriented
				PSS
	Asia/Oceania	4	6%	Result	11	16%
				oriented
				PSS
	Germany	4	6%
	America	1	1%
	(other)


Pascale Prudent

Axel Assie

Chassery Candice

Folzer Hélène

Laffont-Schwob Isabelle

Maignan Maxime

Masotti Véronique

Noack Yves

Raynal Jean-Claude

Marie Salducci

Dominique

Sidhoum Myriam

Alain Tonetto

Vassalo Laurent

Verlande Maxime

Rabier Jacques

Thanks to all the students who contributed to the project, OHM BMP for their financial support and at the ALTEO company, the city of Vitrolles and CD13 for authorizing access to site Contamination of soil, pine litter (OLn horizon of the year) and bark, was evaluated non-destructively by mobile XRF (Niton XL3t GOLDD). We combined the XRF use in situ and ex situ and ICP-AES measurements after acid mineralization, ex situ to increase the sensitivity of the analysis after grouping individual, sieving the soil then drying , and grinding the soil and plant samples. The physiological state of the pines at the individual and population levels was estimated using a fluorescence and reflectance sensor Multiplex®5 (FORCE-A®, Orsay) on green needles, comparing them with uncontaminated needles from reference site on the territory of the Calanques national park. To evaluate the use of the terrestrial laser scanner (LIDAR Optech ILRIS-3D) to estimate biomass and plant barrier porosity, a 3D model of the bauxite deposit of Mangegarri was performed. 3D models were built with Innovmetric's Polyworks and Cloudcompare Softwares.

Results

The most important detected elements related to industrial process are marked in green (Table 1). Aluminium is more concentrated on the ore storage site of Mangegarri. Iron remaining in the residue after extraction of aluminium are more concentrated in the red mud of Vitrolles. The difference is not significant for Titanium in storage sites. Other traces elements are present on three sites. The only noteworthy point is the lack of detection of an essential nutrient for plants: potassium in deposits of Vitrolles, the most rain-leached area of the sites. 2) Calculation of volume and mass of wood and foliage from the heights and circumferences, obtained from literature references equations after slaughtering trees. Example presented: 12-14 kg of leaf, area of 8-9 m 2 / year 3) Measurement accuracy on small objects has shown that it is possible, according to Steinvall et al. (2004), to estimate the relative tree occlusion by placing several identical targets at increasing depths from the edge of the wood during the LIDAR measurements.

-

  Pine litter and bark are good traps for the red mud particles -Differences in the physiological state of the pines are minimal or can be explained by optical artifacts caused by TiO 2 and FeO 2 . -LIDAR scanning can be used for biomass estimates and relative occlusion -practical conclusions = Pines cover should be preserved for its role of proved barrier, or alternatives plant barriers and mulching must be found CONCLUSION Project Goals and Objectives plant barrier, trace metals and metalloids, non-destructive methods, Aleppo pine Keywords : Role of Aleppo pines as a barrier to the transfer of polluted particles (Fig 1) in the context of the past coal mining activity of Provence territory (Fig 2) : -Measure the transferred elements from ground to litter and pine bark -Health Indices of the green needles -Obtaining a 3D model of the barrier formed by the pine trees on Mangegarri site Trees can act as biological filters, removing a large number of particles in suspension and thus improving air quality in polluted environments. Because of epicuticular wax of pine needle, pine bark crevices and increased cohesive properties of fine dust, particles accumulate during several years in these plant parts. What role play pine forests installed on Provence coal mining territory in trapping airborne particles, specially fine particles related to storage of bauxite and red mud residues? For security and stability of measurements, sites with low heavy truck movements were chosen (Fig 2): the bauxite backup storage of Mangegarri, Vitrolles Stadium site as a red mud repository which ceased operations in 1953. The reference site located next to the neighbourhood of Roy d'Espagne is a control site for low metal pollution.

Fig 2 :

 2 Fig 2: Location of the pine sampled in the study sites (green dots)

  The concentrations of Al, Fe, Cr and Ti measured in bark and litter go in ascending order of the Roy d'Espagne to Mangegarri and Vitrolles (Fig 3). This is explained by the fineness of red mud from Vitrolles (Fig 8) compared to ore Mangegarri and soil of the Roy d'Espagne that promotes their flight and their adsorption and possibly their penetration into the plant parts. Element accumulation factors in bark and litters as % compared to the ground surface, are presented on Fig 4. Results can be grouped into airlifted elements (Al, Fe, Ti) and absorbed by roots (Cu, Zn, Mn, Cr). Significant differences of fluorescence and reflectance indices are measured for the 3 sites but control with a light soil dusting shows the optical effects of deposits only (Fig 6). Titanium oxide has the property of re-emitting light as in the case of the fluorescence pigments of the plant tissues. Moreover iron oxide reflected red light which disturbs the measurement of anthocyanins and chlorophyll. LIDAR applications on the site of Mangegarri may: 1) Conduct to an inventory of Mangegarri by a 3D model (Fig 7)

Fig 3 :Fig

 3 Fig 3: Composition of the main metallic elements in litter and bark of different sites (mg/kg dry weight, ICP-AES)

Table 1 : Soil elemental analysis: average concentration in mg/kg±SD in dry weight, different letters mean significant difference (n=10, p<0.05, Wilcoxon test) and technique used.

 1