Nikolaos Goumagias

Ignazio Cabras

Kiran Jude Fernandes

Feng Li

Alberto Nucciareli

Peter Cowling

Sam Devlin

Daniel Kudenko

A Phylogenetic Classification of the Video-game Industry's Business Model Ecosystem

Keywords: Business Models, Video-game Industry, Cladistics Classification, Evolution

Since 1990, Business Models emerged as a new unit of interest among both academics and practitioners. An emerging theme in the growing academic literature is focused on developing a system that employs business models as a focal point of enterprise classification. In this paper we attempt a historical analysis of the video game industry business model evolution and examine the process through the prism of two-sided market economics. Based on the biological school of phylogenetic classification, we develop a cladogram that captures the evolution process and classifies the industry's business models. The classification system is regarded as a first attempt to provide an exploratory and descriptive research of the video game industry, before attempting an explanatory and predictive analysis, and introduces a system that is not governed by the industry's specific characteristics and can be universally applied, providing a map for researchers and practitioners to test organisational differences and contribute further to the business model knowledge.

Introduction

The term "Business Model" continues to attract significant attention on behalf of both academics and practitioners since 1995. However, contrary to how often the term is used, current literature is far from converging in providing a unanimously accepted definition of what a business model actually is [START_REF] Zott | The Business Model: Recent Developments and Future Research[END_REF]. The lack of consensus among scholars over what exactly a business model is has not prevented them from employing the notion at the centre of management theory and strategic management, opening new paths of research [START_REF] Lambert | Applications of the Business Model in Studies of Enterprise Success, Innovation and Classification: An Analysis of Empirical Research from 1996 to 2010[END_REF]. In this Section we aim first and foremost, based on the literature that governs business models, to establish the theoretical foundations of business model evolution through the three evolutionary principles, namely selection, variation, and replication.

Business models are regarded as something more than a simple recipe or blueprint for organizational change. According to [START_REF] George | The Business Model in Practice and its Implications for Entrepreneurship Research[END_REF], the business model is an opportunitycentric concept while strategic management is an environmental-centric one, rendering business model an integral part of the firm's strategic decisions regarding value creation and capturing. Compared to strategic management, it emphasises on cooperation, partnership and value creation. Consequently strategic management and business models are conceptually complementary [START_REF] Zott | The Fit between Product Market Strategy and Business Model: Implications for Firm Performance[END_REF]. Based on the above, the business model is regarded as a source of innovation and competitive advantage, providing support to the argument that places it at the core of strategic management ( [START_REF] Christensen | The Past and Future of Competitive Advantage[END_REF] and [START_REF] Baden-Fuller | Business Models as Models[END_REF]). In other words, business models are viewed as a unified approach, on behalf of the enterprise, to meet different sets of success criteria both financial and non-financial ones ( [START_REF] Deyoung | The Performance of Internet-Based Business Models: Evidence from the Banking Industry[END_REF] and [START_REF] Kshetri | Barriers to e-commerce and Competitive Business Models in Developing Countries: A Case Study[END_REF]), circumventing the narrow boundaries of enterprises, and in some cases industries, and has attracted much academic interest focusing on industrial and organisational change. Based on the above, it can be safely argued that business models are selected based on survivability maximization terms ( [START_REF] Christensen | The Past and Future of Competitive Advantage[END_REF] and [START_REF] Mccarthy | Organisational Diversity, Evolution and Cladistic Classifications[END_REF]).

We have already discussed that business models can be a source, or facilitate the creation, of sustainable competitive advantage on behalf of the enterprise. Both intrinsic and extrinsic factors force enterprises to change their corresponding business models to realise both short and long-term strategic goals [START_REF] Dereuver | Business Models Dynamics for Start-ups and Innovating e-businesses[END_REF]. The mechanisms that govern this change, usually termed as business model innovation, have also been central to the growing literature. In [START_REF] Giesen | When and How to Innovate your Business Model[END_REF], the authors examined the two sources of change, internal and external, and described these mechanisms in terms of their feasibility and effectiveness. Further work regarding the dynamics of business model innovation includes [START_REF] Massa | Oxford Handbook of Innovation Management: Business Model innovation[END_REF], the authors of which developed a theoretical framework that distinguishes between two interdepended processes, namely design and reconfiguration. The success of the process is governed by experimentation or imitation of other successful examples, usually derived from a given industry. Alternatively, the authors of [START_REF] Bohnsack | Business Models for Sustainable Technologies: Exploring Business Model Evolution in the Case of Electric Vehicles[END_REF] examined the evolution of electric vehicles business models through the prism of path dependencies. Several studies, including [START_REF] Morris | The Entrepreneur's Business Model: Toward a Unified Perspective[END_REF], provide evidence that the innovation process is strongly correlated with superior enterprise performance. Consequently, business models can be regarded as a focal point of replication ( [START_REF] Zott | The Business Model: Recent Developments and Future Research[END_REF]; [START_REF] Zott | The Fit between Product Market Strategy and Business Model: Implications for Firm Performance[END_REF]; [START_REF] Giesen | When and How to Innovate your Business Model[END_REF]; [START_REF] Massa | Oxford Handbook of Innovation Management: Business Model innovation[END_REF]; and [START_REF] Bohnsack | Business Models for Sustainable Technologies: Exploring Business Model Evolution in the Case of Electric Vehicles[END_REF]) and variation as the result of business model innovation ([1]; [START_REF] Lambert | Applications of the Business Model in Studies of Enterprise Success, Innovation and Classification: An Analysis of Empirical Research from 1996 to 2010[END_REF]; [START_REF] Dereuver | Business Models Dynamics for Start-ups and Innovating e-businesses[END_REF]; [START_REF] Morris | The Entrepreneur's Business Model: Toward a Unified Perspective[END_REF] and [START_REF] Ha | Webcasting Business Models of Clicks-and-Bricks and Pure-Play media: A comparative Study of Leading Webcasters in South Korea and the United States[END_REF]).

In this paper we aim to contribute to the literature by employing business models as a conceptual tool and the focal point of enterprise classification. To achieve that, we shift our viewpoint to the biological school of classification, namely cladistics taxonomy, in order to organize an industry's business models into homogenous groups. We employ the dynamic, and relatively young, industry of video games as a typology to apply this new classification approach and examine its effectiveness. The short lifespan of the video-game industry allow us to perform a more detailed and thorough historical analysis of the industry which is essential for the classification process. As we will describe in Section 3, cladistics classification presents a series of scientific advantages and it is a well-developed and philosophically robust taxonomy approach. The output of our analysis, the cladogram, could be regarded as a map of the evolution process of the industry's business models and could be used to identify the factors that affected this process through time. Our results are interpreted via the prism of a two-sided market networking providing empirical evidence that aims to explain the evolution of the industry's business models in order to meet the strategic goals imposed by the two-sided morphology of the industry's market [START_REF] Rysman | The Economics of Two-Sided Markets[END_REF].

Related work

An emerging theme of the literature revolves around business model classification ( [START_REF] Patzelt | Top Management Teams, Business Models, and Performance of Biotechnology Ventures: An Upper Echelon Perspective[END_REF] and [START_REF] Konde | Biotechnology Business Models: An Indian Perspective[END_REF]) providing an initial step towards industry analysis and profiling [START_REF] Ha | Webcasting Business Models of Clicks-and-Bricks and Pure-Play media: A comparative Study of Leading Webcasters in South Korea and the United States[END_REF]. Business model classification is mainly focused on fast growing and technologically driven industries, similar to the video game industry, because they provide a fertile grown for business models' evolutionary dynamics exploration. Most of the classification attempts were directed to biotechnology and pharmaceuticals ( [START_REF] Konde | Biotechnology Business Models: An Indian Perspective[END_REF]; 24] and [START_REF] Patzelt | Top Management Teams, Business Models, and Performance of Biotechnology Ventures: An Upper Echelon Perspective[END_REF]), telecommunication and information industry ( [START_REF] Eriksson | Proposing a Business Model Framework for the e-newspaper[END_REF]; [START_REF] Amberg | E-business Models and Consumer Expectations for Digital Audio Distribution[END_REF]) and e-business models ( [START_REF] Weill | Place for Space: Migrating to e-Business Models[END_REF]; [START_REF] Tapscott | Digital Capital: Harnessing the Power of Business Webs[END_REF]). Regarding, the development of a formal classification framework, in [START_REF] Rappa | Business Models on the Web: Managing the Digital Enterprise[END_REF] the revenue streams are employed as a criterion, while in [START_REF] Morris | Is the Business Model a Useful Strategic concept? Conceptual, Theoretical, and Empirical Insights[END_REF], the authors developed a two-dimensional classification framework based on the strategic perspectives and economic and operational factors of the enterprise. On the other hand, in [START_REF] Baden-Fuller | Business Models as Models[END_REF], a first analogy is attempted between the biological objects of classification, namely species, and enterprises. Finally, [START_REF] Torbay | eBusiness Model Design, Classification and Measurements[END_REF] introduced a multidimensional e-business model classification system, arguing that the two-dimensional ones are far too limiting.

According to [START_REF] Lambert | Applications of the Business Model in Studies of Enterprise Success, Innovation and Classification: An Analysis of Empirical Research from 1996 to 2010[END_REF], most business model classification approaches are driven by the researcher's knowledge and is followed by a case-study based validation ( [START_REF] Kauffman | Tuning into the Digital Channel: Evaluating Business Model Characteristics for Internet Firm Survival[END_REF] and [START_REF] Leem | A Classification of Mobile Business Models and its Applications[END_REF]) or via the contingency theory ( [START_REF] Carper | The Nature and Types of Organizational Taxonomies: An Overview[END_REF] and [START_REF] Patzelt | Top Management Teams, Business Models, and Performance of Biotechnology Ventures: An Upper Echelon Perspective[END_REF]). Consequently, the taxonomy approaches vary significantly among researchers based on their conceptualization and knowledge. In other words, compared to the biological school of classification, these phenetic approaches, which are based on similarities among the objects of classification are highly subjective [START_REF] Mccarthy | Organisational Diversity, Evolution and Cladistic Classifications[END_REF]. One of the first works that aimed to implement cladistics classification in industrial evolution of manufacturing systems was [START_REF] Mccarthy | Organisational Diversity, Evolution and Cladistic Classifications[END_REF] who argued that cladistics taxonomy provides a classification system that is scientifically more appropriate because of its objectivity.

Methodology

In this paper we employ the classification methodology as described in [START_REF] Mccarthy | Organisational Diversity, Evolution and Cladistic Classifications[END_REF]. To facilitate discussion we provide a brief, yet solid description of cladistics classification. Cladistics taxonomy in biology classifies organisms based on identifying their most recent common ancestor. Similarities (dictated by characters and their corresponding character states) among organisms are examined in order to track the evolutionary process. However, the major difference between phenetic classification and phylogenetic classification is that, in the latter, entities are classified based on their most recent common ancestor and characters are used to identify that ancestor.

Initially the industry has to be selected which formulates a form of classification as well [START_REF] Mccarthy | Organisational Diversity, Evolution and Cladistic Classifications[END_REF]. In our case it is the video-game industry that interests us, albeit the business models that aim to create and capture value through the development, publication and distribution of video games no matter the content of the game (entertainment, fun, engagement, education etc.). In this analysis, we employed an elemental definition of what constitutes a business model based on the works of [START_REF] Chesbrough | The Role of the Business Model in Capturing Value from Innovation: Evidence from Xerox Corporation's Technology Spin-off Companies[END_REF], [START_REF] Chesbrough | Business Model Innovation: It's not Just About Technology Anymore[END_REF] and [START_REF] Teece | Business Models, Business Strategy and Innovation[END_REF]. Adopting a more general definition would result in analogies that would erode the descriptive power of our classification. Analogies, in the biological school of classification, are created by grouping entities together using characters inherited from two different ancestors.

Character Development and Selection

In order to determine the characters, a historical analysis is performed to track the milestones of the industry (technological advances, monetisation strategies, customer segments etc.) through the evolution process and identify the appropriate business model characteristics. This process is called Character Search and Selection. The historical analysis was based on published academic papers or reports that describe the operations of various enterprises through history and how they adapted to various environmental and internal factors. We elaborate further on this matter in Section 4.

The selection of a character is validated through a test of homology [START_REF] Dequeiroz | Phylogenetic Taxonomy[END_REF] and character conflict resolution. The process of character conflict resolution is a dynamic one that requires the construction of several conceptual cladograms followed by direct test of homologies. Character conflicts are the main source of creating analogies. Character conflict resolution takes place continually from the point of character determination, selection and conceptual cladogram creation.

The choice among the various conceptual cladograms is governed by the test of parsimony, which means that the clade with the least possible character changes is chosen, based on the parsimony rule which dictates that evolution follows the shortest path. Based on the outgroup comparison, characters are grouped into derived through evolutionary process (variation) and inherited from the most recent common ancestor (outgroup). This process is called "establishing character polarity". Finally, after solving the character conflicts that may occur, the nomenclature is established. In this paper we aimed to define archetypes based on informative and commonly used terms by both academics and practitioners [START_REF] Johns | Video Games Production Networks: Value Capture, Power Relations and Embeddedness[END_REF].

Data

Performing a historical analysis presents a significant challenge in order to avoid subjectivity during the process [START_REF] Gallagher | Innovation and Competition in Standard-based Industries: A Historical Analysis of the U. S. Home Video Game Market[END_REF]. In our work, historical data are used for two purposes. Firstly, we aim to identify the video-game industry business model archetypes, and secondly the characters that are used for classification purposes. We based our approach on the Business model Canvas developed in [START_REF] Osterwalder | Clarifying Business Models: Origins, Present and Future of the concept[END_REF] followed by a video-game industry historical analysis ( [START_REF] Gallagher | Innovation and Competition in Standard-based Industries: A Historical Analysis of the U. S. Home Video Game Market[END_REF]; [START_REF] Readman | Shopping for Buyers of Product Development Expertise: How Video Game Developers stay Ahead[END_REF], [START_REF] Claussen | The Stregth and Ties: Evidence from the Electronic Game Industry[END_REF]; [START_REF] Storz | Dynamics in Innovation Systems: Evidence from Japan's Game Software Industry[END_REF]; [START_REF] Haelfiger | Under the Radar: Industry Entry by User Entrepreneurs[END_REF]; [START_REF] De Vaan | Clustering and Firm Performance in Project-Based Industries: The Case of the Global Video Game Industry, 1972-2007[END_REF] and [START_REF] Cadin | What Can We Learn from the Video Games Industry[END_REF]). The Canvas was also used to facilitate comparison among the different archetypes and as a reference point. Through the historical analysis, we created a time series of case studies and proceeded with a comparative examination focused on Mining for Species and character search and selection. We constructed several conceptual cladograms, followed by a series of parsimony tests. Character conflicts were resolved via a test of homology and the most parsimonious cladogram was chosen. The process of archetypes identification is dynamic, and as more data become available new business model archetypes could be identified. However, as new species become known, they enrich the already existent cladogram along with the newly acquired characters without having to undergo a whole character and species rearrangement. The business model archetypes (or species) we have identified through our analysis are 11: i) Outgroup: Electronics Manufacturing, ii) Arcade Games Manufacturing iii) Console Manufacturing, iv) Console Manufacturing-sales-at-a-loss, v) Publishing, vi) Freemium-game publishing, vii) Independent game-developing, viii) Third-party game-developing, ix) In-house game-developing, x) Second-party game-developing, and xi) Crowd-funded game-developing. The character that were chosen for the classification purposes, based on [START_REF] Osterwalder | Clarifying Business Models: Origins, Present and Future of the concept[END_REF], for systematic reasons are shown in Table 1. For space considerations we will not include a table that contains the character states for each business model archetype of the video-game industry. However, the character evolution (and polarity) can be seen in Figure 1 in the next Section.

Results and Discussion

In this Section we include, and discuss, the factual cladogram that tracks the evolutionary process of the video-game industry's business model archetypes shown in Figure 1. Figure 1 shows the evolution of the video-game industry's business model ecosystem based on their most recent common ancestor. The figure also depicts the evolution of characters through time. Business models are grouped together into two broad categories or families: 1) the Platform Manufacturing and Publishing, and 2) Video-game Developing. We examine the relations among these archetypes and focus our analysis through the prism of two-sided market economics, as part of the networking literature that focuses on the intermediaries of the market [START_REF] Rysman | The Economics of Two-Sided Markets[END_REF].

Arcade Games Manufacturing: This business model is focused on manufacturing platforms dedicated to a single game. The enterprises characterized by this business model were combining characteristics of both publishing and manufacturing in an allin-one approach. The key partners were entertainment hubs and public houses which was the main target group of coin-operated machines similar to pinballs. Due to the increased manufacturing costs and the technological limitation vertical disintegration was impossible during the early days of the industry [START_REF] Johns | Video Games Production Networks: Value Capture, Power Relations and Embeddedness[END_REF]. The vertical disintegration of this family of business models placed the foundations of the video-game market transformation into a two-sided one.

Console manufacturing: with the advent of new technological advances that allowed lower manufacturing costs new platforms, no longer dedicated to a single game, were produced. Console manufacturing business model is focused on maximizing the console sales which are supported by games developed specifically for a given platform preventing cross-platform compatibility. This interdependence between publishing hit-driven titles and player-base maximization was responsible for another business model (sale-at-a-loss), also known as razor-blade, which effectively entails that console manufacturing business model focuses on market infiltration maximization instead of profits [START_REF] Hagiu | Exclusivity and Control[END_REF]; [START_REF] Evans | Invisible Engines[END_REF]. To achieve that, the business model needs to establish networks [START_REF] Johns | Video Games Production Networks: Value Capture, Power Relations and Embeddedness[END_REF] with another business model, namely publishing, operating in a form of two-sided market [START_REF] Rysman | The Economics of Two-Sided Markets[END_REF]. It is safe to argue at this point that multi-sided markets determined the emergence of a symbiotic relationship between more than one business models [START_REF] Sabatier | From Recipe to Dinner: Business Model Portfolios in the European Biopharmaceutical Industry[END_REF]. This business model archetype acts as the intermediary between publishing/developing business models on one hand and customers on the other.

Publishing: the publishing business model is focused on revenue and profit maximization through video-game sales (physically or digitally) following a riskaverse strategy [START_REF] Johns | Video Games Production Networks: Value Capture, Power Relations and Embeddedness[END_REF] that skews the publishing decision making heavily towards hitdriven titles. The apomorphic event took place when the business model discarded the manufacturing character and focused instead on monetisation strategies of physical and digital copies of video games [START_REF] Haddon | The Development of Interactive Games[END_REF]. This business model acts as the major revenue source and financially supports the console manufacturing business models in a symbiotic relationship, as discussed earlier, and the major source of funding for the Video-game Developing business models. Consequently, Intellectual Property (IP) acquisition and creation, internally via in-house development, is very important for the sustainability of this business model [START_REF] Johns | Video Games Production Networks: Value Capture, Power Relations and Embeddedness[END_REF]. A specific aspect of two-sided market, publishers currently operate in, led many publishers to follow a price-discrimination strategy, usually called Freemium Business Model [START_REF] Rysman | The Economics of Two-Sided Markets[END_REF].

Video-game Developing: this family of business models focuses on the development of original or licensed titles creating new video games for all platforms. The group consists of Independent developing, Crowdfunded Developing, Third-party developing, Second-party developing and In-house developing business models. Their evolutionary trajectory is heavily affected by the relationship they develop against publishing business models which act as their major partners for financing and revenue streams. The major goal is survivability maximisation through production costs minimisation. To overcome these challenges, developing business models focus on the production process and key resources when it comes to business model innovation. Independent developing operates usually under the radar [START_REF] Haelfiger | Under the Radar: Industry Entry by User Entrepreneurs[END_REF]. They employ digital distribution channels to directly sell the products to consumers, or via online markets (GoG, Steam, etc.). Third-party developing business models are focused on creating original titles or entering a contract with a publisher. The challenges that developing-studios face during project financing lead to the emergence of a new business model, namely Crowdfunded-developing, which aims to attract funding directly from customers. This initiated a series of domino effects on the production and monetization process of the games and is heavily based on the loyalty of the customer base, which is placed at the centre of production process for feedback and word-of-mouth marketing strategy. Economies of scale usually lead Publishing and developing business models to merge or acquire competitors [START_REF] Johns | Video Games Production Networks: Value Capture, Power Relations and Embeddedness[END_REF]. Second-party developing business models are focused on engaging in dedicated contracts with a single publisher who acts as the financier of the project and the final customer. The studios operating under this business model rarely enjoy production independence and are focused on a hit-driven development strategy. Finally, in-house development studios are effectively owned by publishers in a strategically driven strategy to fuel IP creation but usually they operate in a relatively more autonomous way.

Concluding Remarks

This paper presents a new classification approach, namely cladistics classification. Assuming that business model change is governed by the three principles of evolution: 1) selection, 2) variation and 3) replication, we employ cladistics classification to group business models based on their most recent common ancestor. Other kinds of classification are based on a two-dimensional, phenetic approach, which in one hand informative, but on the other hand lacks the objectivity and overall applicability, cladistics classification offers an objective and philosophically robust alternative when it comes to business model classification.

We perform a historical analysis of the video games industry, which is used as a typology to examine the applicability of the cladistics classification when it comes to business models. The result of the classification process, namely the cladogram, is validated through the lenses of two-sided market economics and networking and we provide some initial evidence about the dynamics of the video-games-industry business model evolution.

As part of the creative industries, video-game industry business model analysis and classification could potentially be of value for cross-industry fertilization of new and innovative business models that could benefit music and film industry alike. Price discrimination and servitization, along with the dynamics of the business model networking, could provide valuable lessons, highly applicable to other creative industries or industries that share similar attributes as the video-games one.

Figure 1 .

 1 Figure 1. The Video-games Industry Cladogram: Business model archetypes are grouped together based on their most recent ancestor. Numbers represent the characters that have been inherited or developed through the evolutionary process.

Table 1 .

 1 List of classification characters and character coding.

	Code	Character	Code Character
	1	Platform manufacturing	19	Outsourcing publishing
	2	Console manufacturing	20	Price discrimination
	3	Selling-at-a-loss revenue stream	21	In-game advertisement
	4	Own distribution channels	22	Digital distribution
	5	Third-party distribution channels	23	Outsourcing digital distribution channels
	6	Own development studios	24	Multidisciplinary development team
	7	Outsourcing game development	25	Exclusive publishing agreements
	8	Localisation services	26	Development Independence
	9	Video games development	27	Revenue stream via royalties
	10	Layout design and printing	28	More than one publishing contracts
	11	Intellectual Property (IP) acquisition	29	Small, close-knitted teams
	12	IP creation	30	Use of middleware
	13	Universal development support	31	Exit strategy
	14	Production risk minimisation strategy	32	Cost minimisation strategy
	15	High marketing costs	33	Engine released as open-source
	16	Hit driven strategy	34	Crowd-funding
	17	Royalty payments	35	Self-funding
	18	Hardcopy sales	36	No platform-manufacturing
			37	Owned by publisher

Acknowledgments

We acknowledge the financial support from the EPSRC and ESRC Digital Economy Programme: NEMOG -New Economic Models and Opportunities for Digital Games, grant number EP/K039857.


Ozgul Unal

Hamideh Afsarmanesh
email: h.afsarmanesh@uva.nl

Samuil Angelov
email: s.angelov@uva.nl

An Agile Innovation Framework Supported through Business Incubators

Keywords: Business incubators supported innovation, innovation framework, innovation process, innovation in VBEs and VOs

des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

Introduction

Small and medium enterprises (SMEs) increasingly feel the pressure of global competition. To survive through the current market conditions, they need to respond to customers' demands much more efficiently and effectively than ever before. One approach to achieve this goal is through continuous improvement, and another through innovation in products and services. As defined in [START_REF] Frankelius | Questioning two myths in innovation literature[END_REF], "An innovation is something original, new, and important -in whatever field -that breaks in to (or obtains a foothold in) a market or society".

In spite of the large amounts of effort and interest presented in the literature related to this area, it is reported that most innovation projects fail. The main reasons, a number of which are also expressed in [START_REF] Dooley | Developing a software infrastructure to support systemic innovation through effective management[END_REF][START_REF] Pyka | Innovation Networks: Theory and Practice[END_REF] include the following:

• Innovating organization's goals are ineffectively deployed into actions.

• Organization does not have an enabling innovation management framework.

• Financial resources are not sufficient for developing the prototype of the idea.

• Planning, design, and development of the innovations are poor.

• Access to the required information and knowledge is poor.

• ICT support is not efficiently and/or sufficiently used.

• Inter-and intra-organizational collaboration is not sufficiently exploited.

• The processes of finishing the innovation project and introducing its results to customers are slow. • There is no mechanism to monitor and assess the whole innovation process. A number of research efforts have focused on overcoming some of the listed problems, although with some limitations, as discussed in Section 2. But the biggest and the most common problem for innovation as reported by entrepreneurs and SMEs alike is the lack of necessary resources and know-how to properly develop their ideas. Business incubators possess the required expertise and therefore can support in this process. However, an innovation enabling framework which can be provided through the incubators to the entrepreneurs and SMEs is still missing.

Taking into consideration the common problems and challenges in innovation efforts, and focusing on aspects not yet addressed by the literature on related research, this paper proposes an enabling agile innovation framework. This framework is based on the concepts introduced in Virtual Organization Breeding Environment (VBE) [START_REF] Camarinha-Matos | Collaborative Networks in Support of Service-Enhanced Products. Adaptation and Value Creating Collaborative Networks[END_REF][START_REF] Afsarmanesh | On management of 2nd generation Virtual Organizations Breeding Environments[END_REF] and in Virtual Organizations (VOs) [START_REF] Camarinha-Matos | A framework for virtual organization creation in a breeding environment[END_REF] paradigms, and introduces an innovation process as well as a set of assisting tools and methodologies to be used during the execution of this process. The business incubators domain is considered as the main domain for applying our innovation framework.

The remaining of this paper is structured as follows. Section 2 provides information about related work. Section 3 describes our framework and its main components. Section 4 provides an example, to show how an innovative idea gets processed by the steps of our proposed framework and the main outputs of the innovation process. Finally, Section 5 concludes the paper.

Related Work and Open Issues

This section provides the main examples of related research in this area. They are grouped here into four categories, based on the main focus area addressed by them, including: 1) open innovation, 2) collaborative innovation and innovation networks, 3) the role of VO/VBE, and 4) the role of ICT.

The first group of related work focuses on open innovation. For example, [START_REF] Lee | Open innovation in SMEs-An intermediated network model[END_REF] and [START_REF] Van De Vrande | Open innovation in SMEs: Trends, motives and management challenges[END_REF] focus on open innovation in SMEs. Open innovation is primarily introduced by Henry Chesbrough [START_REF] Chesbrough | Open Innovation: The new imperative for creating and profiting from technology[END_REF], who defines it as follows:

"Open innovation is a paradigm that assumes that firms can and should use external ideas as well as internal ideas, and internal and external paths to market, as the firms look to advance their technology."

The second group of related work focuses on collaborative innovation. The idea of innovation networks and collaborative innovation networks has become popular during the recent years and thus become the focus of research efforts, such as [START_REF] Johnsen | Managing collaborative innovation in complex networks: Findings from exploratory interviews[END_REF] and [START_REF] Berasategi | A comprehensive framework for collaborative networked innovation[END_REF]. A Collaborative Innovation Network (CoIN) is defined by its original proposer, Peter Gloor [START_REF] Gloor | Swarm Creativity: Competitive Advantage Through Collaborative Innovation Networks[END_REF], as follows:

"A cyberteam of self-motivated people with a collective vision, enabled by the Web to collaborate in achieving a common goal by sharing ideas, information, and work."

The third group of related work focuses on the role of VBE and VO paradigms in innovation. The VBE and VO are two main types of Collaborative Networks (CNs) that have drawn considerable amount of attention. A VBE [START_REF] Camarinha-Matos | Collaborative Networks in Support of Service-Enhanced Products. Adaptation and Value Creating Collaborative Networks[END_REF][START_REF] Afsarmanesh | On management of 2nd generation Virtual Organizations Breeding Environments[END_REF] represents a long term alliance established among large number of organizations. VBE provides the necessary conditions and mechanisms to its members to support them with their need to potentially configure goal-oriented Virtual Organizations (VOs) [START_REF] Camarinha-Matos | A framework for virtual organization creation in a breeding environment[END_REF]. A VO is established among a number of VBE members, when an emerged opportunity can be supported through their collaboration and joining their forces and resources.

VBE and VO have been considered by only a few efforts in the context of innovation. In [START_REF] Wi | Virtual organization for open innovation: Semantic web based inter-organizational team formation[END_REF], VO paradigm is used in the formation of virtual teams. In [START_REF] Eschenbächer | Strategies for Distributed Innovation management in virtual organisations In[END_REF], the authors address the need for a methodological support on how to structure and conduct innovation processes in VOs. They propose VBE as the facilitator for an agile strategic innovation management for VOs.

The fourth group of related work comprises the efforts focusing on the role of ICT in innovation. In addition to emphasizing the importance of ICT, proposing ICTbased innovation support infrastructures has been the focus of a number related research efforts, such as [START_REF] Scupola | Open innovation and role of ICT in business-to-business services: Empirical Evidence from Facility Management Services[END_REF] and [START_REF] Dooley | Developing a software infrastructure to support systemic innovation through effective management[END_REF].

Although there are large numbers of innovation related research efforts, most of them focus only on a single aspect related to innovation, such as: open innovation, or collaborative innovation network. Furthermore, although there are a few efforts addressing VO/VBE paradigms as key enablers for agile innovation process, the details of how these paradigms can be used for innovation is not yet investigated. A comprehensive approach for innovation is needed that encompasses a framework, based on innovation related paradigms, and providing both well-defined innovation process and guidelines on which tools and mechanisms to use at each step.

Proposed Agile Innovation Framework

Considering the reasons for the failure of most innovation projects and the limitations of other innovation related efforts in the literature, we propose a framework that combines technologies and conceptual paradigms to provide a comprehensive solution. This framework consists of two main building blocks: 1) innovation process definition, and 2) a set of tools/mechanisms to facilitate the execution of the process. More details are provided in Sections 3.1 and 3.2. The main underlying paradigms of this framework are the VBE and VO, which support the collaborative and open innovation paradigms. The main advantages of VBEs/VOs for the success of the innovation efforts are as follow:

• As [START_REF] Berasategi | A comprehensive framework for collaborative networked innovation[END_REF] states, VBE can support the exploitation of local competencies and resources by an agile and fast configuration of the most adequate set of partners for each innovation project. This also enables producing economically viable solutions for innovative ideas. • Trust management mechanisms are provided in VBEs, which enhances the cooperation/collaboration among member organizations, once within the VOs. • VBE supports well defined roles and policies. Furthermore, mechanisms and guidelines for VO creation and collaboration are well defined; these act as agility enablers, and can be applied to convince organizations to collaborate.

• Continuous monitoring of VBE members' qualifications helps with both upholding competency level and gap identification to take corrective actions. • Issues such as sharing only the necessary resources with other appropriate partners and IPR are well established in VBEs and support member autonomy. • VBEs provide an effective common ICT infrastructure, which is indispensable for successful innovation projects, supporting needed agility in VO formation. Considering these advantages, the framework proposed in this paper is based on the VBEs and VOs as key enablers. Furthermore, we have selected businessincubator-supported innovation as the main application domain. There are many entrepreneurs and SMEs that have innovative ideas, but do not have the necessary experience and resources to develop them. Business incubators provide the necessary means to support successful development of ideas into products. As part of this support, it is also necessary to provide innovators with a framework that consists of a guideline and a set of suggested tools/mechanisms to be used during the innovation process, which makes business incubator supported innovation a good-fit application domain for our framework.

Since the framework is based on the VBE, it is assumed that the incubators are also members of the VBE. Furthermore, when signing a contract with business incubators, the innovators (being entrepreneurs or SMEs) also become a member of this VBE. Many other production and delivery companies and financial organizations constitute the other members of the VBE. Innovation VOs interact with customers throughout the innovation process in order to involve them at all phases.

Innovation Process

To improve understandability of innovation process, first a number of terms used in this process are defined. A Goal is defined by an innovator to represent the main aim of an innovative idea. The innovator may divide/decompose a goal into Subgoals, in order to make it easier to achieve the goal. A Subproduct is a smaller unit of a product. A Competency for an organization corresponds to one capability or capacity.

The innovation process proposed and described below is rooted in and represents an enhancement of the results reported in multiple resources, such as the Stage-Gate Model [START_REF] Cooper | Winning at New Products[END_REF]. This process specifies the actions to be taken throughout the innovation process, and is therefore of great value to be provided by business incubators to inexperienced entrepreneurs and SMEs. As we assume that ideas are already defined, some steps of the pre-development activities of New Product Development process (e.g. opportunity identification, opportunity analysis, idea genesis, and idea selection [START_REF] Koen | Providing clarity and a common language to the "fuzzy front end[END_REF]), are not included in this process. Innovation process, provided by business incubators to innovators as an explanation of what to do at each step, as depicted in Figure 1, includes the following sixteen steps: 1. Subgoals definition: Innovators decompose the goal into subgoals. The needed research and development activities are carried out and a prototype (e.g. physical) is produced at this step. 13. Testing: The developed prototype is tested to make sure that it works properly. 14. Evaluation: Prototype is evaluated by VBE members, through discussion forums. 15. Commercialization: Production is launched and final product is distributed to the market. Advertisements are also placed at this step. 16. VO Dissolution: Since the goal of the VO is reached, it is dissolved.

When a VO is created at Step 8, then the VO Operation phase starts, which needs to be continuously monitored. Therefore, a Monitoring activity runs in parallel to steps 9-15.

After the dissolution of the innovation VO, a number of activities need to be continuously carried out by the innovators initiating the process, such as evaluating the product, monitoring the market, and analyzing internal/external value and cost. Furthermore, although the VO is dissolved after the initial production of the idea, other types of VOs might need to be created later on, for example for mass production.

In addition to the main innovation process explained above, there are also some auxiliary processes (e.g. managing trust related data, managing member data, and managing competence data [START_REF] Camarinha-Matos | Specification of support services for management of long-term base network[END_REF]) of which their details are outside the scope of this paper.

Supporting Tools/Mechanisms

In order to facilitate the execution of the innovation process, automated tools and mechanisms are needed. For innovation purposes, two main types of systems can be considered as part of the innovation framework.

One type of assisting system can address the management of novel ideas. Such a system may consist of tools that can for instance be used for idea mining and/or determining the idea uniqueness. Since we assume that innovators already have unique novel ideas, the idea management falls outside the current scope of our work.

Another type of system can address Creation/operation of innovation VOs inside the VBEs. As shown in Figure 2, our designed VO Creation/Operation System consists of: 1) Competence Matching: At Step-6 of the innovation process, innovators identify the competencies that are required to successfully achieve the subgoals. Since these competencies are specified in the terminology (or keywords) of innovators, at Step-7 they need to be matched against the competencies defined in the VBE, to find most suitable partners. P erforming this match manually by human is time consuming and error prone. The Competence Matching component can achieve this automatically by exploiting a number of syntactic and semantic matching algorithms and thus facilitates rapid formation of the innovation VO. Due to potential syntactic/semantic conflicts between these two specifications of competencies, user intervention might be required after the matching process has produced its results. 2) Trustworthiness Evaluation: Competence matching results in a list of potential VO members, which then gets refined based on their trustworthiness. The component for evaluation of organization trustworthiness can be built on top of the TrustMan system [START_REF] Msanjila | On development of TrustMan system assisting configuration of temporary consortiums[END_REF], developed previously. 3) Negotiation Support: After the potential most-fit members of the innovation VO have been identified, a negotiation round takes place. First, the negotiation objects, which require agreements, are defined. Then potential members discuss about these objects through collaboration tools such as chat and forum. The results are reflected in the VO contracts. This component utilizes the Negotiation Wizard developed within the ECOLEAD project [START_REF] Camarinha-Matos | Towards a framework for creation of dynamic virtual organizations[END_REF]. 4) Performance Evaluation: During the operation phase of the life cycle of the innovation VO, performance of its members needs to be continuously monitored and measured. This is important for the success of the innovation VO. For this purpose, a set of Key Performance Indicators (KPIs) need to be defined and the performance of each member needs to be measured against these indicators, which would be addressed in future work. The innovation VO Creation/Operation System is further extended with a number of VBE-related subsystems. The subsystems (indicated as related subsystems in Figure 2), are developed in two EU-funded projects, namely ECOLEAD [START_REF] Camarinha-Matos | Towards a framework for creation of dynamic virtual organizations[END_REF] and GloNet [START_REF] Camarinha-Matos | Collaborative Networks in Support of Service-Enhanced Products. Adaptation and Value Creating Collaborative Networks[END_REF]. Since these subsystems are auxiliary and considering space limitations, no details are provided on them, but the related information can be found in [START_REF] Camarinha-Matos | Specification of support services for management of long-term base network[END_REF].

An Example Case (Intelligent Buildings)

This section provides an example from the intelligent buildings domain (based on [START_REF] Sharples | A Multi-Agent Architecture For Intelligent Building Sensing and Control[END_REF]) to illustrate the main outputs of the innovation process. For space reasons, only the main steps of the innovation process and a partial sample list of competencies are addressed here.

Imagine the following being considered by some innovators. In buildings, each occupant has his/her own preferences related to the temperature and light. An advanced service supported in an intelligent building system, which consists of sensors (e.g. temperature detectors) and devices (e.g. heaters), may learn these preferences over time. When a person enters a room in a building, it should be detected who entered the room, so that the temperature and the light parameters can be automatically adapted according to his/her preferences. In simpler cases, such as in the case of an environmental change (e.g. the weather gets dark) the conditions should be adapted accordingly. For an intelligent building, it is also important to react rapidly and correctly in an emergency situation. For example, when a fire starts in a room, this needs to be immediately detected and shared with other parts of the system in other rooms, which requires that all sensors and devices are connected through a network. Similarly, if the weather is dark during a fire situation, the light level needs to be increased for faster evacuation.

Based on the scenario explained above, the following main goal corresponding to the innovative idea can be defined by the innovators:

Goal: The rooms of a building should adapt both to the needs of its occupants and the circumstances, including adapting the lighting and temperature, to support the needs of the person currently in the room as well as to better respond to an emergency situation, such as a fire. Then, the following subgoals can be defined by innovators:

Subgoal 1: Ensure that a person entering a room can be identified. Subgoal 2: Ensure that temperature and lighting preferences/needs of persons living in the building are learned over time. Subgoal 3: Ensure that a room can automatically adapt to its current occupant's light and heat parameters, so that the occupant is satisfied in the environment. Subgoal 4: Ensure that a fire situation can be immediately diagnosed and reacted upon, by providing a more suitable lighting.

After subgoals have been defined, a market research is carried out to identify the functional and non-functional requirements for the intelligent building systems (not addressed with more details due to space limitations). Then, draft solutions for the systems are designed to meet the requirements. Different solutions may result in different subproducts needed for its realization. For example, one solution may need sub-products including: Agents, Sensors (temperature, light level, movement, smoke), Effectors (heating, lighting, doors, windows, alarm), Network connection, and Software (to gather information from sensors, to generate a response).

After a solution has been selected, required competencies are identified by innovators in order to achieve the corresponding subgoal. An example list of competencies is: 1) Software design, 2) Development, 3) Testing, 4) Mobile robot control techniques, 5) Sensor manufacturing, 6) Sensor development, 7) Networks supporting.

Then, the competency matching software component helps to automatically match the innovators' specified competencies to the VBE competencies. Based on the match results, a preliminary list of VO members is identified. In relation to this example, we assume that VBE competencies are the ones shown after the ";" symbol, in the first column of Table 1. We also assume that organizations A, B, C, D, E, F, G, andH Due to space reasons, we do not discuss the remaining steps of the innovation process, as these are related to the operation of the VO.

Conclusion and Future Work

An agile innovation framework is proposed in this paper. This framework is especially meant for innovators supported by business incubators and aims to guide the innovators through the innovation process on what to do and which tools / mechanisms to use at each step. Considering the many benefits that VBE and VO provide for the innovation process, they form the base of the framework.

As part of the future work, the plan is to implement the Competence Matching Component and to make the necessary adaptions to the Trustworthiness Evaluation and Negotiation Support Components developed in the ECOLEAD Project. Then, the Performance Evaluation Component is planned to be implemented. For that purpose, first the KPIs will be defined, which will then be used by the Performance Evaluation Component to compute the innovativeness of the VO members. The related data stored during the life cycle of a VO can then be used when developing the future VOs, in the same way that trust data are used.

2 . 3 . 4 .

 234 Market research: Based on the subgoals, market research is carried out in order to identify the needs and constraints. Requirements definition: Requirements for each subgoal are defined. Draft solutions design: Draft(s) of possible solution(s), which meet the defined requirements, are generated at this step e.g. by means of brainstorming. Draft list of required subproducts might be identified at this step. 5. Leading solution selection: Considering the market needs and resource requirements (e.g. finances, time, people, materials, etc.), a number of metrics is defined for selecting the most suitable solution. Then, solutions are ranked and the first ranked solution is selected. 6. Required competencies definition: For each subgoal, competencies required for accomplishing the selected solution are identified. The terminology used by innovators might be syntactically and/or semantically different from the competencies specified in the VBE. 7. Competency matching & potential partners identification: Required competencies are automatically matched against the competencies of the VBE members in order to identify the potential partners in the innovation VO. 8. Innovation VO creation: The trustworthiness of the potential partners is evaluated to shortlist them. Then, a negotiation round takes place to identify the most suitable partners. The VO plan is detailed out and a contract is signed by each of the selected partners, which essentially marks the official launch of the VO. 9. Subgoal prioritizing and planning: It is identified by the VO members (including innovators) in which order the subgoals shall be achieved. Then, a detailed plan for the whole development process is made. 10. Detailed solution design: For each subgoal, a detailed solution is designed and subproduct(s) to be utilized or developed are identified. 11. Checking if VO's evolution is necessary: If new competencies are required according to the detailed solution and none of the VO partners possess this competency, than VO enters into an evolution phase.

Fig. 1 .

 1 Fig. 1. Innovation Process

Fig. 2 .

 2 Fig. 2. Components of the VO Creation/Operation System

  have those VBE Competencies that are shown in the second column of the table.

Table 1 .

 1 Competency Matching and Potential VO Members Identification.

	Results of Competency Matching	Which Organizations have	Potential
	(Defined competency;VBE Competency)	which VBE Competencies	VO
			Members
	(Software design;Software analysis and design)	Software analysis and	A, B, C,
	(Development;Software development)	design: A, B	D, E, F,
	(Testing;Software testing)	Software development: A, B,	G, H
	(Mobile robot control techniques;Mobile robots)	C
	(Sensor manufacturing;Sensor manufacturing)	Software testing: A, B, C
	(Sensor development;Sensors development)	Mobile robots: D
	(Networks supporting;Computer networks)	Sensors manufacturing: E, F
		Sensor development: F, G
		Computer networks: H

Acknowledgments

The work on this paper is partially supported by the FP7 project GLONET.


Paula Urze

António Abreu

System Thinking to Understand Networked Innovation

Keywords: System Thinking, Innovation, Knowledge Transfer, Collaborative Networks

scientifiques de niveau recherche, publiés ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

Introduction

Nowadays, globalization has been the main driving force that makes companies run after high levels of performance and competitiveness [START_REF] Tidd | Managing Innovation: Integrating Technological, Market and Organizational Change Hong Kong[END_REF]. According to several authors the business environment has faced dramatic challenges in recent years, where one of the most relevant sources of competitive advantage is innovation capacity [START_REF] Argote | Knowledge Transfer in Organizations: Learning from the Experience of Others[END_REF]. The development of complex products or services requires access to several distinct types of knowledge that companies do not usually hold [START_REF] Urze | Knowledge transfer assessment in a co-innovation network, Collaborative Networks in the Internet of Services[END_REF] [START_REF] Urze | Circulation of Knowledge in a co-innovation network: An assessment approach[END_REF]. As a result, companies can improve their knowledge either from their own assets, making sometimes-high investments, or from the knowledge that may be mobilized through other companies based on a collaborative process [START_REF] Abreu | Understanding Social Capital in Collaborative Networks[END_REF]. However, recent studies point out that a growing number of innovations introduced in the market come from networks of companies that are created based on core competences of each company.

In fact, there is an intuitive assumption that in a turbulent market companies can develop emerging business opportunities and deal with cost/time competitively through an openinnovation environment.

However, it has been difficult to prove its relevance due to the lack of models that support the tools that explain the synergies created in a collaborative environment, which may lead to the reinforcement of innovation flows in a "healthy" collaborative environment [START_REF] Abreu | Towards a methodology to measure the alignment of value systems in collaborative networks[END_REF].

The aim of this paper is to present a case study of a Portuguese collaborative network, Brisa co-innovation network, and to discuss the appropriateness of the system thinking approach to understand the dynamics of the processes for innovation in depth.

Knowledge Transfer to Support Co-innovation

Knowledge has always played an important role in the economy, but only over the last few years has its relative importance been recognized, exactly when its value started growing. Currently, knowledge and the capability to create and utilize it are considered to be the main source of a company's sustainable competitive advantage.

Due to the centrality of knowledge in contemporary society, a shift in our understanding on innovation in business organizations -whether technological, product or strategic innovation, or organizational innovation -is required [START_REF] Nonaka | A Dynamic Theory of Organsational Knowledge Creation[END_REF]. Innovation is strongly connected to knowledge: it can be an outcome of novel pieces of knowledge or a novel combination of existing pieces of knowledge; it can also be created during the process of innovation. For example, innovation is a fundamental way of organizational knowledge creation, since it is a process in which the organization creates and defines problems and then actively promotes new knowledge to solve them. As argued by Choo and Bontis [START_REF] Choo | Knownledge Intellectual Capital, and Strategy, The Strategic Management of Intellectual Capital and Organisational Knowledge[END_REF], a company generates knowledge value from what it knows, through the organizational processes of knowledge creation, knowledge transfer and use of knowledge. Actually, the last decades have shown a generalized concern on the study on how companies create knowledge and how they operate its transfer, in particular.

In knowledge creation, a company generates new knowledge from the conversion and externalization of its tacit, embedded knowledge. The knowledge transfer is shared with a business organization through different functional groups, geographical locations and time periods. Knowledge is transferred between organizations through alliances and networks as well. In terms of knowledge use, the company integrates and coordinates its different types of knowledge in order to produce goods and services. Tacit knowledge plays a crucial role in knowledge creation; codified or explicit knowledge facilitates knowledge transfer; "common knowledge" (common language, shared meanings, overlapping knowledge) or common understanding of the goals and purpose orients knowledge use.

Over time a company incorporates a set of knowledge and skills that is unique to its learning and experience. This stock is the company's intellectual capital, and it includes human, structural and relational capital that exists within its employees, organizational routines, intellectual property and relationships with customers, suppliers, distributors and partners. The stock of intellectual capital is continuously improved through new learning on multiple levels: the individual, the organization and networking organizations of which the company is part.

Moreover, there are contexts where knowledge sharing and transfer constitute a strategic move. Business organizations that belong to highly networked and strongly linked industries, where technologies and markets are still evolving, may strategically share knowledge in order to (1) promote and enable the development of complementary products and services, (2) influence the development of common platforms, dominant designs and de facto or formal standards, and (3) increase a critical mass of customers and users. Industries that experience externalities, where the value and the usefulness of a good or service depend on the installed base of connected users, may choose to share knowledge with customers, competitors and collaborators [START_REF] Choo | Knownledge Intellectual Capital, and Strategy, The Strategic Management of Intellectual Capital and Organisational Knowledge[END_REF]. In addition to network externality effects, companies sharing knowledge may also gain the advantage of increasing benefits by developing a dominant position in an industry or by being an early market leader. The strategic challenge, then, consists on knowing what knowledge to transfer and retain as part of the company's value.

System Thinking Approach to Understand Innovation Dynamics

The tendency to apply tools where the analysis of reality is mainly based on a linear approach, where the system behavior and its dynamic is explained based on a series of events of one-way relationships, as well as the predisposition to ignore feedbacks and delays might be an obstacle to understand the dynamics of processes for innovation in depth. Furthermore, in a co-innovation context where someone changes a component without considering the interrelationships can cause fixes that backfire, and instead of solving the original constraints, unconsciously increases the barriers to innovation. According to several researches [START_REF] Ford | Why Good Projects Go Bad: Managing Development Projects Near Tipping Points[END_REF][START_REF] Sterman | Business Dynamics -Systems Thinking and Modeling for Complex World[END_REF], the behavior of any system is determined by causal structure rather than specific events. The complexity associated to the behavior of a system usually arises from the interactions (feedback) among the components of the system and not from the complexity of the components themselves. Based on this approach, any system can be described by a set of components that have complex interrelations occurring between them, many of which take the form of feedback loops. It means that a component A may influence a component B, which in turn influences component A at a later point. The feedback loops can be positive (or self-reinforcing) or negative (or self-correcting). However, either types of loop can be good or bad, depending on the perspective in which it is analyzed. In order to support the analysis of system behavior, the system thinking approach includes a number of tools that cover several purposes and can be classified in four categories [START_REF] Daniel | Systems Thinking Tools, A Users Reference Guide[END_REF], as shown in Figure 1.

System Archetypes

The system archetypes provide a basic form to describe generic stories and scenarios that can be applied to distinct contexts and environments. Each archetype is built based on a causal loop diagram, and offers a common language to understand the behavior and dynamics of a particular system over time.

According to some authors [START_REF] Rahn | Fear and Greed: A Political Archetype[END_REF][START_REF] Senge | The Fifth Discipline Fieldbook: Strategies and Tools for Building a Learning Organization[END_REF], the most common system archetypes and their storyline are the following: Success to the Successful -This archetype suggests that the success of a company, project, product, and so forth does not always come from competences but might be due to an initial or starting condition. When two entities compete for a common and limited resource, the entity that initially received the majority of the allocation of resources, fostering in this way its initial success, will receive more resources in the future, increasing its success at the expense of the other. Consequently, the entity that is initially less successful starves for resources and eventually fades out. Limits to Growth (also known as Limits to Success) -In most real cases, there are commonly some constraints that limit growth, such as resource limits, market saturation, knowledge constraints, and so forth. This archetype suggests that an effort may be initially the cause of the success of an entity. However, the effort reaches a constraint that is inhibiting further growth, slowing down the overall performance over time.

Accidental adversaries -This archetype describes a scenario in which, initially, two entities begin a relationship with the best of intentions, with the purpose of maximizing their respective strengths and minimizing their weaknesses, and based on a "healthy" collaborative environment in order to carry out an objective that cannot be achieved separately. However, the problem arises when one or both parties take action, which in their perspective seems perfectly reasonable, and accidentally undermine their partner's success. The impact of these harmful actions may simply create a sense of frustration and antipathy between the parties, though still partners, or it may get to the point of turning them into hostile adversaries. Tragedy of the Commons -This archetype describes a scenario where several entities acting in rational self-interest perform activities with the purpose of maximizing their benefits by depleting a common resource. The "tragedy" occurs when the resource capacity is exceeded. The impact of these damages on the Commons may either limit the benefits to the level at which the resource is replenished, or lead to the collapse of the activities performed by all entities in the system. Growth and Underinvestment -This archetype suggests that when a resource approaches its limit, as market saturation, the life cycle of a product, technology or process is reaching an end. The growth of an entity can only be sustained with investments on more capacity -for an enterprise it means the development of resources, capabilities, competences, and so forth in order to ensure its competitive advantage. However, assuming that the decision not to invest was immediately made and during this period performance degradation occurred; if this pattern is not recognized, the decrease of performance might be used as a justification not to invest in the needed capacity. Attractiveness Principle -This archetype suggests that, in most real cases, there are multiple restrictions inhibiting the growth or development of some activities, such as in an innovation process, and the solution is to manage the attractiveness of each. Since it is usually impossible to deal with restrictions in the same way and/or all cannot be addressed due to limited resources, it is necessary to decide which restrictions should be eliminated first. Fixes that Fail (also known as Fixes that backfire) -This archetype illustrates a scenario that occurs when a problem symptom exists, and a quick fix is applied with positive results in the short term. However, the solution adopted creates side effects that were not evident at first, worsening the problem in the long term and consequently requiring more fixes. Escalation -This archetype describes a scenario where the parties believe that just one of them can benefit (win), even in a co-innovation process. In this scenario, there is no absolute goal but instead a relative goal of staying ahead of the other members with the purpose of protecting and/or furthering the company's own best interests. The impact of this harmful behavior may either create a sense of frustration and antipathy between the parties, though still partners, or get to the point of harming their organizations and reducing the value to customers and stakeholders, or even turn them into hostile adversaries. Shifting the Burden (also known as Addiction) -This archetype illustrates the tension between a solution to solve a problem symptom based on a short-term approach, which solves temporarily the problem (symptomatic solution), and a long-term approach based on a fundamental solution. However, there is frequently a tendency to apply a temporary solution since it is relatively quick and low cost, while a delay is associated to the fundamental solution due to the development of competences, financial limitations, or other constraints. Nonetheless, the implementation of the temporary solution reduces the symptom, which might induce the development of unforeseen side effects, dissipating the need to use the fundamental solution.

Figure 2 illustrates the potential relationships between some "classic" system archetypes discussed above and adapted from [START_REF] Senge | The Fifth Discipline Fieldbook: Strategies and Tools for Building a Learning Organization[END_REF] for co-innovation.

Innovation Dynamics Analysis Using the System Thinking Approach

Methodology

The research has been developed at the largest Portuguese highway1 , and is based on two main projects developed by Brisa, namely E_TOLL -Electronic Tolling System and ALPR -Advanced License Plat Recognition.

Brisa identified E_TOLL and ALPR as the most relevant projects in terms of innovation. On a first stage, companies and other institutions (technology centers, universities) involved in the projects were contacted and invited to cooperate with our research. Empirical data stems from two main sources: in-depth interviews conducted with key participants belonging to the network, and a brief survey. The involvement of various partners in the network is critical in order to foster a spirit of openness and cooperation in this fundamental process.

Brisa Case Study.

The Brisa company currently operates a network of eleven highways on a concession basis, with a total length of around 1096 km, constituting the main Portuguese road links. Given its importance and dimension, Brisa owns several companies specialized in motoring services and aimed at improving the quality of the service provided to customers and increasing its own operating efficiency. The Brisa co-innovation network is a long-term collaborative network.

In order to analyze the sustainability of Brisa co-innovation network, as first approach, an effort to find some similarity to the most common aforementioned system archetypes was made. Taking into account the data collected and the archetypes' causal loop diagram, the choice fell on Shifting the Burden archetype, whose causal loop diagram is illustrated in Figure 3a, and on an adjustment of the Tragedy of Commons, whose causal loop diagram is illustrated in Figure 3b.

The application of Shifting the Burden archetype to Brisa supports the proposition that in order to respond to market demands (problem symptom) Brisa had to make a choice between a symptomatic solution that was based on product and service purchase, or develop competences to support innovation (fundamental solution).

However, the development of competences requires access to several distinct types of knowledge that Brisa needed to develop, and this process has a significant time delay before it has an effect on the original problem symptom (respond quickly to market needs). This disadvantage led Brisa to choose the acquisition of products and services (symptomatic solution). Over a long period of time, Brisa's managers believed that the problem symptom was supposedly solved by applying the symptomatic solution as the acquisition of products and services caused a decrease in the original problem symptom, keeping it in balance. Additionally, the recurrent use of the symptomatic solution induces the development of unforeseen side effects, which reinforce the justification not to invest in the fundamental solution. However, in order to increase its competitiveness, Brisa's managers decided to invest in the fundamental solution, promoting new knowledge from their own assets as well as from knowledge mobilized through other companies and organizations, such as universities and government institutes based on an open-innovation environment. Nowadays, Brisa co-innovation network is a long-term collaborative network that has more than 30 members from several domains and business activities (e.g., research institutions, universities, associations, governmental entities, start-ups, business angels, and suppliers), and its sustainability can be explained based on an adjustment of the Tragedy of the Commons. The original causal loop diagram that explains the pattern of this archetype, previously described, includes two reinforcing loops on the outside that represent individual efforts and benefits, and two balancing loops on the inside that represent collective efforts and benefits. However, an adaptation of this archetype can illustrate another useful scenario where the synergies created in a collaborative environment lead to the reinforcement of innovation flows, and the co-innovation benefits (knowledge creation) are greater than the sum of individual knowledge creation due to the establishment of a concerted effort. In this adapted archetype the reinforcing loops are on the inside and represent collective efforts and benefits, and the balancing loops are on the outside and represent individual efforts and benefits.

Furthermore, from the aggregation of the two archetypes a reinforcing loop arises (side effect, fundamental solution, Brisa's effort on knowledge creation, Brisa's stock of knowledge, and collaborative stock of knowledge), which reinforces the justification to invest in the fundamental solution.

5.

This work discussed the system thinking approach and the general system archetypes applied to co-innovation in a collaborative context.

The development of models to understand the dynamics of co-innovation processes in depth in collaborative environments will not only help to better understand this area, but also contribute to a wider adoption of the collaborative network paradigm as a way to develop capabilities that will enable companies to respond quickly to market needs. Some preliminary steps in this direction, inspired in system thinking concepts, were presented. Initial results illustrate the applicability of the suggested approach. The application of archetypes to Brisa network reinforces the choices made by the company. The results seem to bring benefits in terms of developed synergies in a collaborative environment, which promotes innovation flows.

Further steps are necessary toward the elaboration of a robust tool as well as to its validation.

Figure 1 -

 1 Figure 1 -System Thinking Tools

Figure 2 -

 2 Figure 2 -System Archetype relationships

Figure 3 (

 3 Figure 3 (a, b) -Causal Loop Diagram

The present results are based on research work developed under the project -DIINOV DINÂMICAS DE TRANSFERÊNCIA DE CONHECIMENTO EM REDE DE INOVAÇÃO, FCT/UNL, BRISA, ISEL/IPL,

Acknowledgments

This work was partially supported by BRISA Innovation and Technology (BIT) through a research and development project.


Pierluca Di Cagno

Bianca D'agostinis

Barbara Livieri

Bianca D ' Agostinis

Organizational Sustainability and Value Creation in Collaborative Networks

Keywords: Collaborative Networks, Value Creation, Sustainability, e-3 value, Value exchanges, Relational rents

des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

Introduction

In the actual economic context, Collaborative Networks (CNOs) represents a lunchpad for the enhancement of firms' competitiveness and for the creation of socioeconomic and environmental benefits. CNOs can be seen as a system made by several "entities that are largely autonomous, geographically distributed, and heterogeneous in terms of their operating environment, culture, social capital and goals […]", enabled by new technologies [START_REF] Camarinha-Matos | Collaborative networks: Value creation in a knowledge society[END_REF]. In this scenario, nodes of a CNO share information, resources and competencies with the aim of create new value through the broadening of enterprise boundaries. However, the sustainability of CNOs, from not only a financial perspective but also from the organizational one is the premise for value creation. Indeed, collaboration implies mutual trust and commitment, giving relevance to behavioral and managerial principles, ethic codes, collaboration culture and incentive systems. Several authors have studied the role of trust and commitment in inter-organizational settings [START_REF] Essa | The Influence of Information and Control on Trust Building in Buyer-Supplier Negotiations[END_REF][START_REF] Bierly | Explaining Alliance Partner Selection: Fit, Trust and Strategic Expediency[END_REF], however, at the best of our knowledge, no one of them studied these factors with a systematic approach that led to modeling and requirements. Nonetheless, CNOs are complex entities, whose understanding is not immediate, therefore it becomes necessary to understand and model the determinants of value creation in CNOs [START_REF] Camarinha-Matos | A comprehensive modeling framework for collaborative networked organizations[END_REF].

In this work, we propose a model of sustainability and value creation within CNO. In particular, we represent these aspects by means of UML and e3-value, an ontology based methodology used to define requirements for software systems taking into account the value exchange among different individuals. In this way, we were able to model and analyze value exchanges and co-creation in Collaborative Networks.

The works is structured as follows. Section II is for the analysis of related works concerning the use of e3value. In Section III we pose the basis for our model, which we present, by means of a visual representation, in Section IV. In Section V we propose a case study. Finally, in Section VI we discuss our model and the application to the case study and we draw conclusions.

Related Works

The advent of e-business has led to the necessity of the development of e-business models. The e-business model has to address the formulation of requirements through a rigorous method [START_REF] Gordijn | Designing and evaluating e-business models[END_REF]. In this scenario, Gordijn and Akkermans [START_REF] Gordijn | Designing and evaluating e-business models[END_REF][START_REF] Gordijn | Requirements Engineering Techniques for e-Services[END_REF] proposed a multi-viewpoint approach for the business model development: a) value viewpoint, that represents the value creation and exchange process; b) process viewpoint, that represents business process and tasks; c) Information System viewpoint, that describes the Information Systems required for business processes. From a value point of view, e3-value is commonly used for the modeling of value exchanges. The e3-Value is in fact an ontology-based methodology for defining business models for business networks [START_REF] Gordijn | Designing and evaluating e-business models[END_REF] incorporating concepts from requirements engineering and conceptual modeling (including a graphical notation). Its main focus is on identifying and analyzing how value is created, exchanged and consumed within a multi-actor network. Hence, taking the economic value perspective and visualizing what is exchanged, i.e. which kind of economic value, and by whom [START_REF] Akkermans | Value-based requirements engineering: exploring innovative e-commerce ideas[END_REF]. An economic value exchange, and consequently the e3-value ontology as a whole, is based on the principle of reciprocity emphasizing the dual character of business transactions. This "give and take"-approach, described by means of specific "value-exchange diagrams", denotes that every actor offers something of value, such as money, physical goods, services, or capabilities, and gets a value in return. In this scenario moneyexchange aspects are included in the value-exchange diagrams, and this semi-formal description is very useful for business analysis [START_REF] Gordijn | Designing and evaluating e-business models[END_REF] but also for requirement specification on ePayments and for other aspects (decision making, user profiling, market segmentation, …) directly connected to monetization in eServices. This approach can bring several benefits, such as better communication among actors, improvement of the decision making process and a more complete view of business operations and business perspective. In particular, when applied to CNOs can help in the understanding of value exchanges among partners and external actors, thus extending existing reference models, such as ARCON.

A Collaboration Model: Theoretical Foundation

In literature, several types of partnerships among firms have been identified, characterized by the deepness of the sharing relations and by the integration level of firms.

In particular, Camarinha-Matos and Afsarmanesh [START_REF] Camarinha-Matos | Collaborative networks: Value creation in a knowledge society[END_REF][START_REF]FInES Task Force on Collaborative Networks and SOCOLNET: Taxonomy of Collaborative Networks Forms[END_REF] identified the following integration levels: (a) networking, which consists of the information exchange for mutual benefits, with no common goals; (b) coordination, which consists of the coordination of autonomous tasks, connected to a common goal; (c) cooperation, which consists in resource and information sharing, with the aim of achieving compatible goals; (d) collaboration, which is the highest integration level and consists of the sharing of information, resources and responsibility in order to organize and develop activities for a common goal.

Only in this last sense we can talk of collaborative network which have been defined as "a network consisting of a variety of entities that are largely autonomous, geographically distributed, and heterogeneous in terms of their operating environment, culture, social capital and goals, but that collaborate to better achieve common or compatible goals, and whose interactions are supported by computer network". [START_REF] Camarinha-Matos | Collaborative networks: Value creation in a knowledge society[END_REF]. CNOs enable several benefits, among which the increase in the success rate of enterprises, also in turbulent markets, and the increased capability to achieve shared goals [START_REF] Camarinha-Matos | Collaborative networks: Value creation in a knowledge society[END_REF]. Indeed, through alliances, it is possible to enhance enterprise size, gain access to new markets and to external know-how, create synergies, share resources and risks, integrate firms' resources with the ones of partners and enhance innovation processes, with a result of increased value creation [START_REF] Lavie | The Competitive Advantage of Interconnected Firms: An Extension of the Resource-Based View[END_REF]. Collaboration among enterprises enable the finding of resources not easily accessible on the market or that cannot be easily created. Also, the interactions among partners can be generated the relational capital [START_REF] Burt | The network structure of social capital[END_REF], defined as a set of relations among firms which facilitate the exploitation of economic activities. Resources are exchanged when this is mutually convenient and there is mutual trust, which exists when: a) partners confide in a reliable and transparent exchange of resources; b) a firm believes that other partners are pursuing actions that are beneficiary also for the firms itself and c) that these actions are not prejudicial [START_REF] Anderson | A model of distributor firm and manufacturer firm working partnerships[END_REF]. Indeed, trust has been seen as "the cornerstone of strategic partnership" [START_REF] Spekman | Strategic supplier selection: understanding long-term buyer relationships[END_REF], whereas the lack of trust can bring to the failure of the alliance [START_REF] Sherman | Are strategic alliances working?[END_REF] and whereas if associated with commitment can bring to "outcomes that promote efficiency, productivity and effectiveness" [START_REF] Morgan | The commitment-trust theory of relationship marketing[END_REF].

In the field of strategic alliances, trust is often a cognition-based trust, which comes from rational choices based on information, rather than from emotional bonds between individuals (affect-based trust), that follow in case of recurring interactions between firms. In particular, cognition-based trust comes from previous interactions, reputation on the market, ecological and ethical responsibility, organizational context, similarities in firms' characteristics. The searching for trust based relations have to rationales: a) CNOs with a high level of trust are more likely to succeed and to create value; b) relations among partners with a high level of trust requires much less time and commitment to be managed [START_REF] Kwon | Factors affecting the level of trust and commitment in supply chain relationships[END_REF]. For these reasons, the partner selection is often based on previous interactions, reputation and potential degree of conflict [START_REF] Kwon | Factors affecting the level of trust and commitment in supply chain relationships[END_REF].

Recognizing the importance of model frameworks for CNO, the ARCON model was developed by [START_REF] Camarinha-Matos | A comprehensive modeling framework for collaborative networked organizations[END_REF][START_REF] Camarinha-Matos | Collaborative Networks: Reference Modeling[END_REF]. In the model, four endogenous elements are analyzed, namely structural dimension, componential dimension, functional dimension, behavioral dimension. The behavioral dimension regards the principles, policies and rules of governance that guide who operated within the CNO in order to make it more efficient [START_REF] Mcallister | Affect-and cognition-based trust as foundations for interpersonal cooperation in organizations[END_REF]. Indeed, CNO governance is particularly relevant, since it's a requirement for the effective monitoring and control of relations. Inter-organizational relations create a not-planned operative context, which at the same time is not entirely spontaneous [START_REF] Benassi | Governance factors in a network process approach[END_REF]. Moreover, another relevant element is risk, which has been analyzed towards three perspectives. In [START_REF] Boon | The dynamics of interpersonal trust: Resolving uncertainty in the face of risk[END_REF] firms choose to collaborate in order to face market risks; in [START_REF] Mcallister | Affect-and cognition-based trust as foundations for interpersonal cooperation in organizations[END_REF] risk is the result of CNOs, while in [START_REF] Das | Trust, control, and risk in strategic alliances: An integrated framework[END_REF] trust derives from risk and, at the same time, is affected by trust. However, cooperation could lead to a reputational risk, coming from non-socially responsible behavior of partners that could affect the whole CNO.

In short, the advantages of CNOs are fully exploited only when there is trust among partners, an adequate governance, ethical codes and a culture of collaboration.

4

SuMCNOs: A CNOs Sustainability Model

Method

For the development of our model, we selected UML as means to represent general factors and variable, and e3-value for the analysis of value exchanges in CNOs, since it's a business ontology specifically designed for the analysis of value constellations [START_REF] Gordijn | Designing and evaluating e-business models[END_REF]. After reviewing more than 50 papers related to CNOs, published on international conferences and journals, we identified three variables that have a great impact on value creation. We modeled these variables with a UML class diagram. To this purpose, we considered the nodes of the networks, the CNOs and the variables that impact on value creation as classes, since a class is an abstraction of things (or instances): in other words, classes represent a whole set of objects that share methods and attributes [START_REF] Rumbaugh | Unified Modeling Language Reference Manual, The[END_REF]. Moreover, we analyzed the value exchanges within networks by means of e3value. To this aim, we modeled CNOs as composite actors made by other business actors. Accordingly to e3value standard notation, we show the value activities that contribute to reaching the CNOs goals as value activities, while the value exchanges have been depicted as connection between value ports, assigned to each actor. Finally, we applied this model to a case of study, for which we draw the corresponding e-3 value diagram. All the diagrams are drawn with Microsoft Visio and e3value Editor.

Model representation

This section provides a representation of our proposal, in order to exemplify our modeling approach. In the first part of the model, based on UML, we represent the determinants that impact on value creation and exchange within CNOs. As stated in the theoretical foundation section, the main aspects concern trust, resource sharing and commitment. For the purpose of this study, we intend value as the result of the activities of the individual firm and of the collaboration with other entities. In this sense, the value refers not only to financial benefits, but also to socio-environmental ones. In Fig. 1, we represent the candidate classes and the candidate associations of our model. In particular, each Node is part of a CNO; both Node and CNO are children of the parent class BusinessEntity, which is a generalization of their concepts. Also, nodes share Resource, which is a generalization of TangibleResource, FinancialResource and IntangibleResource. To the primary association between Node and Resource, we tied an association class Sharing since the association is, in turn, associated with other classes. In a similar way, to the primary association between Node and CNO, we tied an association class Participating since the association itself has some attributes, namely Trust, Commitment and RelationalCapital. We choose to represent these attributes as classes, in order enable the association with other classes. In more detail, Trust is affected by several factors, whereas the Factor class is a generalization of InternalFactor, which is an attribute of the association class Participating, and Exter-nalFactor. RelationalCapital, which is an attribute of Participating, is also associated with the class BusinessEntity. Tying RelationalCapital both to the class Participating and to the class BusinessEntity enables its attribution to the level on which the information is available.

Moreover, RelationalCapital is enabled by: ─ Trust and Commitment, which are attributes of the class Participating:

this relation doesn't need to be represented, since are all attributes of the same association class, therefore the association it's implicit; ─ The Sharing of resources: if nodes don't share their resources, it's difficult to find relational capital, since it's strictly linked with how much firms work togheter.

The associate class Sharing, in turn, is enabled by Commitment and Trust, as explained in Section III. The second part of the model is represented by means of e3 value ontology, through which we depict the value exchanges inside and outsides the collaborative network. To this purpose, we take into account two types of CNOs and, in particular, a supply chain and a horizontal strategic alliance.

In Fig. 2, value exchanges in a supply chain are represented. SupplyChain is a composite actor made by the actors Supplier and InternalCustomer. Supplier has a value activity Production and sell its products and services (value link) to InternalCustomer, who in exchange pay the price (money) to the supplier. Supplier also sells its product towards ExternalCustomer: the benefits of the CNO with respect to a market-driven environment is that products and services within the alliance can be sold at a lower price or can be more specific for the customer's needs. Also, InternalCustomer has a value activity Production and sell its final products and services to FinalCustomer. The social benefit is that CNO, under certain circumstances, enhance products quality and reduce prices. Moreover, exchanges within a horizontal alliance are represented. As depicted in Fig. 3, the value exchanges don't happen between the partners of the CNOs, but between the nodes and the CNO itself, whereas the benefits for nodes are usually intangibles. For the purpose of the analysis of value creation, we will analyze a specific project realized by the CNO regarding the safety of bathing establishments. The projects enabled services of medical aid and first support with AED (Automated External Defibrillator). In order to achieve this result, the network bought 41 defibrillators and offered courses for about 150 staff operators. As depicted in Fig. 3, Node1 and Node2 pay a fee in order to access to the project, whilst NetworkOfBathingEstablishments buys from AEDSupplier 41 defibrillators and from CouseErogator a service (course offering), under the payment of a fee. Finally, Net-workOfBathingEstablishments offers this service and the defibrillators to Node1 and Node2. This enables Node1 and Node2to offer more services to their clients, which in return will get a safer environment also for elderlies and for people with health problems. In this case, trust mechanisms between nodes have been enabled by the continuous interaction among partners and by the network manager, who helped in the switch from a internal-based culture, where every external entity is a competitor, towards a collaborative culture, where each node is seen as relevant part for value creation for the CNO and for the creation of social benefits.

Discussion and Conclusions

In this paper, we propose a model for collaborative networks that takes into account both the factors affecting value creation and the value exchanges within the network.

In particular, we described by means of UML the role of commitment and trust in the participation relationship and the variables that affect these two factors. Also, we analyzed through e3value the value exchanges within CNOs taking into account two different scenarios, namely a supply chain and a horizontal strategic alliance. Finally, we used e3value ontology in order to describe a case study of a horizontal network between bathing establishments. Whilst previous research only analyzed single ena-bling factors or value chains, we jointly examined these perspectives and we developed a model, named SuMCNOs, which can be easily applied to different cases in order to understand the sustainability of CNOs. Future works will include the extension of the scenarios investigated.

Fig. 1 .

 1 Fig. 1. UML class diagram representing value creation in CNOs

Fig. 2 .

 2 Fig. 2. Representation of value exchanges in CNOs

Fig. 3 .

 3 Fig. 3. Representation of value exchanges of horizontal strategic alliances

Fig. 4 .

 4 Fig. 4. Representation of the value exchanges in the Network of Bathing Establishments