Conference Agenda

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Session Overview
20-PM2-05: ST4.1 - the Design of New Industrial Ecosystems
Thursday, 20/June/2019:
2:45pm - 4:15pm

Session Chair: Pascal Le Masson, MINES ParisTech - PSL
Session Chair: Gordon MULLER-SEITZ, Technische Universität Kaiserslautern
Session Chair: Susanne Ollila, Chalmers University of Technology
Location: Amphi Curie

Session Abstract

Recent works on business model innovation (Schneckenberg and Velamuri 2018) (Spieth et al. 2014; Demil and Lecocq 2010) and ecosystems (Jacobides et al. 2018) have underlined the variety of configurations, roles and strategic positioning in the contemporary industry. They raised the critical issue of designing these ecosystems: is it possible to design a technological core to become a platform leader? who are the actors capable of designing an ecosystem? And also: what are the required managerial competencies? What kind of leaders? What kind of work division and value division? What kind of collaborations?

On the other hand, the study of design regimes and innovation dynamics has shed lights on new actors and new forms of interactions supporting intensive innovation dynamics at ecosystem level (Lange et al. 2013; Le Masson et al. 2012; Ollila and Yström 2016). These works underline that new ecosystem dynamics call for new forms of relationships between economic actors, based on the capacity to collectively explore the unknown. In particular it can lead to new forms of relationships between industrial ecosystem, society and scientific research. These works also relied on recent advances in design methods, design theory and even design cognition (Agogué et al. 2012) to improve the analytical framework and experiment with new methods and organizational forms.

This track will study these actors in charge of new ecosystem dynamics. Papers can be based on the empirical study of the actors; the track also welcomes theoretical papers that could help rediscuss the nature of the relationship in this process of ecosystem design, a relationship that probably goes far beyond the usual economics transaction. The track also welcomes methodological papers that propose new instruments and new techniques to help study ecosystems design.


- research / industry relationship for double impact;

- managing collective innovation for industry 4.0

- platform emergence and platform overthrown

- design regimes

- prescription and ecosystem dynamics

- cognitive approach of ecosystem dynamics

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The structure of a science-based innovation ecosystem in a peripheral region: The case of ArcticNet

Ashlee-Ann Pigford1, Gordon Hickey1, Laurens Klerkx2

1McGill University, Canada; 2Wageningen University, The Netherlands


The Canadian Arctic is characterized by a series of unprecedented and simultaneous changes resulting in complex environmental challenges that require innovative solutions. As a result, the Canadian government has invested in scientific research intended to foster innovation ecosystems, largely through networked approaches due to the Arctic’s large geographic area.


It is generally understood that innovation ecosystems are organized around private firms that interact with other firms, universities and societal actors to co-create value for key stakeholders[1]. However, attempts to promote innovation ecosystems in the Canadian Arctic have revolved around decentralized research networks versus firms given that the traditional actors in an innovation ecosystem (e.g. universities and firms) are underrepresented in the region[2].

The literature suggests that there is broad a lack of clarity around how innovation ecosystems are organized and how they change over time[3,4] or respond to social movements[5]. Efforts to examine the structure and evolution of innovation ecosystems have mainly focused on the central role of the firm[6] despite the recognition that innovation ecosystems are composed of embedded networks of actors[1] with each actor performing core roles[4]. Thus, more attention needs to be paid to the organization and co-evolution of all network actors within an innovation ecosystem[1].

Literature Gap

Efforts to support the design of innovation ecosystems are complicated by an incomplete understanding about how innovation ecosystems are organized and evolve[3, 4]. This gap is illustrated in the Canadian Arctic where, despite efforts to promote innovation ecosystems through science-based platforms there is limited insight into innovation processes[7, 8].

Research Questions

Recognizing that network organization and evolution are important considerations for nurturing an innovation ecosystem, this research seeks to identify the configuration of actors in a science-based innovation ecosystem (i.e. which actors are being connected? in what ways?) and how do relationships change over time (i.e. how does the network evolve?).


We present a case study from the Canadian Arctic to examine the organization and evolution of a science-based innovation ecosystem. ArcticNet is a Canadian Network of Centres of Excellence (NCE) that links academia, industry and government[9]. This research first identifies ArcticNet’s network attributes and properties and how they change through time and across boundaries (e.g. organizational, jurisdictional and geographic) using network analysis techniques, which provides a tool to capture the structural aspects of actors connected through relationship[10]. Interviews with network stakeholders are also used to provide insights into the context and events that may have contributed towards network evolution.

Empirical Material

The case study focuses on a 14-year period (2003-2018) of ArcticNet. As one of the largest sources for arctic-specific research funding in Canada, ArcticNet has brought together transdisciplinary teams (e.g. scientists, managers, Inuit organizations, northern communities, government, firms) to study the impacts of climate change in the coastal Canadian Arctic with the goal of informing the development of adaptation strategies and national policies[9]. As a science-based innovation ecosystem, ArcticNet is designed around a core of academic actors.

Research Ethics Board approval (file 44-0618) was received on 15 June 2018 for network analysis and qualitative interviews. Secondary source data were identified through consultation with ArcticNet in summer of 2018. Data were obtained from the ArcticNet secretariat projects database and cross-referenced with the online summaries available on the ArcticNet website for each project. Data were extracted for the Project Leaders (PL), Network Investigators (NIs), Collaborators, and Research Staff. Students are excluded from this analysis. Demographic data related to members’ institution, province and northern affiliation were extracted. Network data were generated using data for funded research projects from 2003-2018. Data visualizations and analysis were created using UCINET software. Semi-structured qualitative interviews lasting 1.5 hours were conducted with key stakeholders to contextualize network data.


A preliminary network analysis was produced to inform this abstract. This research reports on the structural and relational evolution of actors in the ArcticNet network between 2003 and 2017, which is broken into four funding phases (Phase1 2004-08; Phase2 2008-10; Phase3 2010-15; Phase4 2015-2018). From a structural perspective, the network grew over time and new organizations continued to join. The number of unique organizations in the network doubled over time (Phase1 n= 98; Phase4 n=207), with participation from organizations in multiple sectors: Academic (Canadian and International), Government, Private Sector, Non-profit and Northern actors. Northern actors are classified by ArcticNet as a unique sector, which is reflected in our analysis. When the relationships between organizations across the ecosystem were mapped (i.e. relationships between funded projects), the number of network ties doubled from Phase 1 to Phase 4 and measures of network density decrease from Phase 1 to Phase 2, suggesting that while the network has grown, it has not reached saturation. Qualitative data help to contextualize observed changes in the network structure over time, suggesting that the growth parallels broader social events and movements, including the International Polar Year and an increasing demand for northern organizations to participate in research processes.

Contribution to Scholarship

Findings illustrate how a transdisciplinary research network was organized and evolved in the Canadian Arctic, offering two important insights for the design of science-based innovation ecosystems. First, this research suggests that it may be possible to effectively design innovation ecosystems with an academic core given that ArcticNet actors effectively organized around academic organizations rather than firms. Secondly, the study contributes insight into the evolution of innovation ecosystems by mapping network changes over time. In this regard, once established, the network continued to grow its membership, suggesting that its open design facilitated network expansion; however, qualitative data suggests that this phenomenon may be due in part to contextual influences.

This research also contributes to the literature by applying network analysis to explore the configuration of organizational actors, how they coordinate across boundaries and how their relationships evolve over time in the Canadian Arctic context for the first time.

Contribution to Practice

Ultimately, this research presents an opportunity to inform ongoing efforts to design polices that promote science-based innovation ecosystems in regions like the Canadian Arctic, which lack the traditional configuration of actors involved in firm-centered innovation ecosystems. Recognizing that Canada has committed substantial public resources to support networked approaches to science in the Arctic, findings suggest that such approaches are capable of linking diverse actors (often in new configurations) to form dynamic and evolving innovation ecosystems.


Building on the key questions posed in track 4.1 this research presents an empirical study on the organization and evolution of relationships between academic-government-industry-society actors in a Canadian Arctic innovation ecosystem. Findings present a picture of what a science-based innovation ecosystem organized around an academic core could look like.


1. Aarikka-Stenroos, L. and P. Ritala, Network management in the era of ecosystems: Systematic review and management framework. Industrial Marketing Management, 2017. 67: p. 23-36.

2. Abele, F., Chapter 4 State Institutions and the Social Economy in Northern Canada. Northern Communities Working Together: The Social Economy of Canada's North, 2015: p. 74.

3. Suominen, A., M. Seppänen, and O. Dedehayir, A bibliometric review on innovation systems and ecosystems: a research agenda. European Journal of Innovation Management, 2019. 22(2): p. 335-360.

4. Dedehayir, O., S.J. Mäkinen, and J.R. Ortt, Roles during innovation ecosystem genesis: A literature review. Technological Forecasting and Social Change, 2018. 136: p. 18-29.

5. Almpanopoulou, A., P. Ritala, and K. Blomqvist. Innovation ecosystem emergence barriers: Institutional perspective. in Proceedings of the 52nd Hawaii International Conference on System Sciences. 2019.

6. Järvi, K., A. Almpanopoulou, and P. Ritala, Organization of knowledge ecosystems: Prefigurative and partial forms. Research Policy, 2018. 47(8): p. 1523-1537.

7. Healy, A., Innovation in Circumpolar Regions: New Challenges for Smart Specialization. Northern Review, 2017: p. 11.

8. Exner-Pirot, H., The Arctic as a Region of Innovation, in Arctic Summer College Yearbook. 2018, Springer. p. 21-31.

9. Coutinho, A. and N. Young, Science transformed? A comparative analysis of ‘societal relevance’rhetoric and practices in 14 Canadian Networks of Centres of Excellence. Prometheus, 2016. 34(2): p. 133-152.

10. Schlattmann, S., Capturing the collaboration intensity of research institutions using social network analysis. Procedia Computer Science, 2017. 106: p. 25-31.

Re-inventing corporate innovation through incubation. The VINCI Leonard case study.

Pierrick Bouffaron, Benoît Weil, Pascal Le Masson

MINES ParisTech, PSL Research University, France


Corporate incubators are living illustrations of nascent yet fast-growing operational engagement of firms towards startups. While innovation departments focus on stimulating corporations’ endogenous growth, incubators may be seen as vehicles fostering exogenous growth, reducing the relationship with the host firm to providing finance and mentoring. Our research challenges this duality.


Innovation management literature shows that incubators and accelerators may play key roles in identifying entrepreneurial opportunities and supporting early innovation activities [1-2]. Research into incubator classification has been largely documented [3-4], and their impact on large firms challenged [5-6]. Today, corporate entrepreneurship literature explains that differences in organizational structures, practices and objectives of incubators have hampered the definition of unified conceptual frameworks. Some authors have produced complex models for the evaluation of incubators, describing them as fuelling exogenous growth [7-8]. Ideally, these evaluations should draw on both scholarly knowledge and practitioners' expertise [9]. Recent works report important relationships to firms, suggesting that incubators also trigger endogenous growth [10-12]. As such, their performance may depend on the way corporations design and run them, as well as the factors (if any) that influence operations. This research also draws from design and strategic management literature to reflect on firms’ disruptive innovation capability [13-16].

Literature Gap

Innovation management literature essentially associates incubators with exogenous growth but fails at taking the reverse perspective. Looking through the lens of endogeneity, this research analyzes how incubators may embody a new form of corporate innovation department with increased means of action, hence challenging this exogenous-endogenous duality.

Research Questions

How does corporate incubation support endogenous growth of host firms, contributing to disruptive innovations in their business ecosystem?

What structural and operational specifics characterize corporate incubators compared to innovation departments?

Can we demonstrate that corporate incubation fuels endogenous growth in desirable ways, playing the role of venture-based internal innovation platforms?


Building on a longitudinal qualitative research (18 months), we investigate the innovation capability management in a large construction firm, VINCI. In 2017, VINCI launched a global incubator called Leonard, looking at extracting value through employee- and startups-powered corporate innovation. 30 internal and external ventures beneficiated from Leonard support between September 2017 and December 2018. A systematic analysis of their sequential journey through the incubation process is led. The first author of this paper is a reflexive practitioner [17] who designed and ran Leonard over the study period, bringing his experience and a unusual set of data to the research work.

Empirical Material

Within Leonard, based on a specifically-designed process of selection and support spanning one year, the incubation programs encourage existing employees, firm partners and external ventures to submit ideas, frame them into a product or a service, iterate until validating a value proposition with customers, deduce a business model and test them on the market. New products and services, the creation of business units, joint ventures as well as the excubation of ventures are sought. Being the incubator manager, the first author was able to collect a very large amount of internal data from different sources, from field notes, communications, as well as through interviews and regular meetings with stakeholders. The study case is therefore particularly relevant. On the 30 studied internal and external ventures, the evolution paths of the projects through their incubation journey are traced and compared with a triple – strategic, managerial and operational – perspective. A database of the projects’ incubation process and stages is built, looking at the nature and maturity of the product or service, team, venture and the involvement of the governance in the decision-making process. The author witnessed hands-on all strategic decisions of the firm, including those impacting its endogenous business ecosystem.


The Leonard study case demonstrates that corporate incubators can act as a flexible innovation vehicle serving the firm top management in complementary ways: informing new market trends, attracting and repositioning talents, identifying and accelerating strategic fits between – internal-internal, internal towards external, external towards internal - ventures, and offering test beds to hatch ventures with different levels of maturity. The constantly-challenged strategic posture of the firm top management makes it possible to influence the way the corporate incubator help build ventures to form, develop, accelerate and position itself within or outside the corporation. Therefore, the research work shows a detailed study case where a corporate incubator does have an endogenous impact, which means that the designed incubator framework strongly supports the capacity of the host firm to act in disruptive ways. Reflecting on the firm and governance strategic postures towards the incubated ventures and their related ecosystems, the conclusions do challenge the “endogenous versus exogenous” growth status quo.

Contribution to Scholarship

The research work contributes to bridge the gap between corporate entrepreneurship and innovation management literature, while fueling our understanding of corporate incubators. The described multiple-pathway incubation framework offers flexibility to the firm’s top management to dynamically choose among strategic postures: shaping the incubated venture, adapting to the incubated venture, reserving the right to play, mixing or duplicating these postures following the current business ecosystem. Thus, for each selected project, decision spaces are constantly created over time. Distinct from traditional corporate innovation departments that aim at endogenous growth but lack the business ecosystem perspective, we assert that incubators may be the future of corporate innovation dynamics. Combining both endogenous and exogenous growth, they indeed have the capacity to lead to more disruptive innovations.

Contribution to Practice

Considering the rise in interest among large firms to set up their own incubators and the considerable resource investments required for doing so, the research provides a number of practical suggestions to guide practitioners involved in designing and running such programs. The Leonard study case shows that incubation stages are to be implemented in distinct ways, depending on the maturity of the idea, concept, product, team and venture, and decision space. The multi-pathway framework integrates all possible firm’s objectives, from boosting the creation of ventures to nurturing ecosystems, hence representing a new sort of strategic management and decision-making tool.


Firms live and improve their entrepreneurialness through a range of activities, ranging from the creation of innovation departments, corporate venturing and strategic renewal programs. The research work shows that corporate incubators represent new platforms and new forms of interactions supporting intensive innovation dynamics at ecosystem level.


[1] Albort-Morant, G., Ribeiro-Soriano, D. (2016). A bibliometric analysis of international impact of business incubators. J. Bus. Res. 69(5) 1775–79.

[2] Patton, D., 2014 (2014). Realising potential: the impact of business incubation on the absorptive capacity of new technology-based firms. Int. Small Bus. J., 32(8) 897–917.

[3] Allen, D., McCluskey, R. (1990). Structure, policy, services and performance in the business incubator industry, Entrepreneurship Theory Practice, 15(2) 61–77.

[4] Barbero, J.L., Casillas, J.C., Ramos, A., and Guitar, S. (2012). Revisiting incubation performance: How incubator typology affects results. Technological Forecasting & Social Change 79 (2012) 888–902.

[5] O'Connor, G.C., DeMartino, R. (2006). Organizing for Radical Innovation: An Exploratory Study of the Structural Aspect of RI Management Systems in Large Established Firms. Journal of product innovation management, 23(6), 475-497

[6] Hatchuel, A., Garel, G., Le Masson, P., and Weil, B. (2009). L’'intrapreneuriat, compétence ou symptôme ? Vers de nouvelles organisations de l'innnovation. Revue Française de Gestion, 35(195), 159-74.

[7] Mian, S. (1997). Assessing and managing the technology business incubator: an integrative framework, J. Bus. Venturing, 12(4), 251–85.

[8] Bigliardi, B., Dormio, I., Nosella, A., and Petroni, G. (2006). Assessing Parks performances: directions from selected Italian case studies, Technovation, 26(4), 489–505.

[9] Van Burg, E., Romme, A.G.L., Gilsing, V.A., and Reymen, I.M.M.J. (2008). Creating university spin-offs: a science-based design perspective. J. Prod. Innovat. Manag., 25 (2). 114-128.

[10] Kohler, T. (2016). Corporate accelerators: Building bridges between corporations and startups. Business Horizons, 59(3), 347-357

[11] Shankar, R.K., Shepherdb, D.A. (2018). Accelerating strategic fit or venture emergence: Different paths adopted by corporate accelerators. Journal of Business Venturing, 0(0).

[12] Weiblen, T., Chesbrough, H. W. (2015). Engaging with startups to enhance corporate innovation. California Management Review, 57(2), 66-90.

[13] Cooper, R. G. 1990. “Stage-gate systems: a new tool for managing new products”. Business horizons, 33(3), 44-54.

[14] Courtney, H., Kirkland, J., Viguerie, P. (1997). Strategy under uncertainty. Harvard Business Review, 75(6), 67–79.

[15] Le Masson, P., Hatchuel, A., Le Glatin, M., Weil, B. (2018). Designing decisions in the unknown: towards a generative decision model for management science. European Management Review, Wiley, In press.

[16] Le Glatin, M., Le Masson, P., Weil, B. (2017). Decision design and re-ordering preferences: the case of an exploration project in a large firm. International Conference on Engineering Design, Aug 2017, Vancouver, Canada. <>. <hal-01529620v2>

[17] Visser, W. (2010). Schön: Design as a reflective practice. Collection, Parsons Paris School of art and design. Art + Design Psychology, 21-25.

Ecosystems dynamics and designs : insights from the evolution of the meta-ecosystem of innovation dedicated to video games in Montréal

Chahira Mehouachi1, Patrick Cohendet2, Laurent Simon2

1Institut Supérieur de Gestion, Paris, France; 2HEC Montréal, Montréal, Canada


Our research deals with the the construct of ecosystem which have gained momentum in the literature. This powerful metaphor portraying extended organic networks offers the promise of renewed and more inclusive analysis of the dynamics of value creation, appropriation and use. It also raises many debates and research questions.


We mobilize an extended literature review which defines ecosystems and provides insights about their different types (business, innovation..) and the issues related to their management, design and dynamics of change (Iansiti and Levien, 2004, Koenig, 2012 ; Autio et Thomas, 2014 ; Valkokari, 2015, Tsujimoto et al., 2018 ; Attour A. et Lazaric N., 2018).

We adopt a holistic and an integrative approach, labeled by Tsujimoto & al., (2018) as the multi-actor network perspective. One of its main purposes is to investigate the existence, and otherwise, the roles of ecosystem designers/managers. It advocates for research about the patterns of decision-making, the chains of behaviors, and the voluntary strategizing and managerial actions that can influence and drive the evolution/decline of an ecosystem. As a corollary, it also calls for investigations that shed light on the mechanisms of change and the processes through which ecosystems can be triggered, (co) created, steered and managed.

Literature Gap

The research on ecosystems’ creation and design is still in its infancy. Yet, understanding the organizing principles and behavioral rules and norms that regulate the interactions within the ecosystem is necessary. Only recently, researchers begun investigating the capability of certain actors to proactively create and design new ecosystems.

Research Questions

This research tackles the question of the ecosystem creation and design through a dynamic lens by exploring how a meta-ecosystem of innovation emerged and took shape through the interactions of different stakeholders and the constitution, and amalgamation of different types of firm-centered ecosystems.


We adopted an abductive approach and an embedded and qualitative case study investigating the ecology of ecosystems dedicated to the video games industry in Montréal. An inquisitive look into this creative milieu reveals an intertwining ecology of ecosystems constituting a complex meta-ecosystem of innovation. We adopt a chronological approach considering the particular order of emergence of these ecosystems and how they relate to each other. Our data analysis was conducted through an abductive process, based on a new grid of analysis to fathom how these heterogeneous and encased ecosystems took shape and were transformed into a meta-ecosystem of innovation.

Empirical Material

The primary data was collected through observations and in-depth semi-structured interviews, with employees, managers and public representatives working in the video game industry. These interviews (approximately one hour each) were all tape-recorded and transcribed. The datasets were gradually put together: i) Between March 2009 and November 2010, a preliminary study was carried out by the research team on a sample of 16 video game studios from diverse national contexts (mainly France and Canada) and involved many managers who intervened directly in the formation and evolution of the innovation ecosystem dedicated to the video games industry in Montréal. For this study, a total of 47 semi-structured interviews were achieved in order to investigate the general mechanisms driving the innovation dynamics within the video games industry. ii) To get a deeper understanding of the video games networks and dynamics in Montréal, the research team followed up with a series of qualitative case study analyses, carried out from 2009 to 2016. An extensive case study was also led by one of the co-authors in the local studio of Ubisoft. Since 2009, this co-author organized many creativity sessions on the management of local ecosystems and conducted several action-research projects with Montreal video game companies.


Our analysis allowed us to identify three major transformations that have driven the evolution of the meta-ecosystem of innovation in the video games industry in Montréal: the process begun by the deliberate implementation of a triggering seed and the establishment of a business ecosystem by Ubisoft Montréal. Two major transformations occurred afterwards: the first intervened through the expansion of this business ecosystem into a firm-centred innovation ecosystem whereas the second transformation, propelled by the successive implementations of direct competitors to Ubisoft, led to the formation of an entire ecology of firm-centred ecosystems of innovation and their amalgamation into a meta-ecosystem of innovation.

We describe each of these transformations, how it occurred, its underlying mechanisms and manifestations. For each transformation, we provide details about the four following aspects and about how they changed: (1) the features of the ecology of ecosystems: its nature and its constitutive structure, (2) the logic of interactions and nature of interdependencies linking the different components of this structure (3), the logic of action and (4) the governance and logic of control which prevailed. We also paid a close attention to two the collective capabilities of the local milieu and the middleground composing and driving its dynamics.

Contribution to Scholarship

The present study contributes to the growing literature about the processes of emergence/creation, evolution and design of ecosystems. We provide a contingent analysis of the processes driving the evolution of a meta-ecosystem of innovation while taking into account the nature of the ecology of ecosystems which were involved, their underlying web of interdependencies and the nature of the intervening actors. Throughout our investigation we shed also light into the logic of action, interaction and coordination and control that drive these processes thus contributing to highlight the agency arrangements and the regulating schemes that were mobilized during the emergence and evolution of the meta-ecosystem of innovation dedicated to the video games industry in Montréal. Besides, we add to the knowledge about how different forms of ecosystems relate to each other and notably how an agglomeration of heterogeneous, yet inter-related, organizations might evolve from one form of an ecosystem to another.

Contribution to Practice

The results of our study can help managers to proactively manage their ecosystem. By offering detailed insights about how different aspects of an ecosystem co-evolve (namely, its underlying distribution of interdependencies, the logics of action, interaction, coordination and control driving its evolution), our study provides guidance about the design of the ecosystem as a whole and the development of meta-collective capabilities at the ecosystem-level. We also highlight particular mechanisms which can be mobilized for the design of ecosystems of innovation and the articulation of different types of ecosystems.


By investigating the issues of creation, design and evolution of ecosystems of innovation, our study contribute to highlight some critical issues associated to a new figure and space for innovation, namely the ecosystems. This construct is mainly concerned with the processes of value creation, appropriation and use, notably through innovation.


Attour A. et Lazaric N. (2018), « From knowledge to business ecosystems : Emergence of an entrepreneurial activity during knowledge replication », Small Business Economics, In press, 1-13.

Autio, E., & Thomas, L. (2014). Innovation Ecosystems. The Oxford Handbook of Innovation Management, 204-288.

Iansiti, M., & Levien, R. (2004). Strategy as ecology. Harvard Business Review, 82(3), 68-81.

Koenig, G. (2012). Research note: Business Ecosystems Revisited, M@n@gement, 15(2), 208-224.

Tsujimoto, M., Kajikawa, Y., Tomita, J., & Matsumoto, Y. (2018). A review of the ecosystem concept—Towards coherent ecosystem design. Technological Forecasting and Social Change, 136, 49-58.

Valkokari K. (2015), « Business, innovation, and knowledge ecosystems: how they differ abd how to survive and thrive within them », Technology Innovation Management Review, 152(4), 91-119.

Creating value from data in an ecosystem: building and expanding relationships between data and seemingly distant usages

Raphaelle Barbier, Benoit Weil, Pascal Le Masson

Mines ParisTech, France


Based on a historical case study in the Earth Observation field, this paper aims at bringing new insights on the emergence of a data-centered ecosystem, highly depending on an original way of creating value to data.


In recent years, the flow of data has increased in almost every business, industry and research area. This “big data” phenomenon has largely been discussed in the literature, shedding light on its definition, opportunities and challenges (Gandomi et Haider 2015)

More specifically, recent research has studied how organizations handle this new flow of data to create value from it. Two main situations are commonly reported. In the first situation, the organization has access to new data and aims at creating value from them, by improving its own processes, services and products (Del Vecchio et al. 2018), or directly selling data to external parties (Trabucchi et al. 2018). In the second situation, the organization starts with a target value and looks for data to generate it, resulting in the construction of a whole process to get these data. (Trabucchi et Buganza 2019)

Literature Gap

In both situations, the organization needs to build a relationship between sets of data and a final value, by building specific business models and also by building mathematical functions (models) to generate value from data. The literature implicitly considers the models as given, thus hiding how they are designed.

Research Questions

Therefore, our approach is to focus on the role of designing models in the value creation process, leading us to address the following questions: how can these models be designed by the organization to create value from data? What are the consequences of this design process on the organization’s ecosystem?


Our research work is based on a historical case study. As suggested by (Siggelkow 2007), it is leveraged to rediscuss basic notions, especially value creation from data in a ecosystem.

Our case study describes a specific context where an organization had both access to new data and a target value, and had to build a relationship between them. In this situation, the organization did not need to create a specific business models to get access to either data or value. Thus, this configuration seems particularly adapted to specifically examine the design process of models which seems overlooked in research studies.

Empirical Material

Our case study consists in a European project in the Earth Observation field (which aims at understanding the physical and biological systems on the planet thanks to data gathered through multiple sources such as airborne, in-situ sensors, or satellites). Within this project that took place in the 80s, three different research institutes developed models in order to better estimate solar radiation reaching the ground (target value) thanks to data coming from satellites (new data).

The different strategies to design models and their impacts on the ecosystem evolution were analyzed thanks to interviews with one of the researchers who worked on the project, as well as second hand documents (reports of the European Commission and scientific papers describing the methods).


The results of our research are twofold. First we have been able to identify and characterize three distinct approaches to design models, (one purely statistical, a second purely physical and a third one as an original mix of physical and statistical). Second, the dynamics of the ecosystem have proved to be highly dependent on the approach of the model-design process.

Contribution to Scholarship

These results allow us to bring new insights on the way organizations create value from data, especially unveiling the crucial role of designing models.

This research also highlights another way ecosystems can be created: not only through the way business models are built but also through the way models building the relationship between data and value are designed.

Contribution to Practice

Several managerial implications could be discussed at several levels. First for practitioners in companies, it is worth noticing the importance of having trained people able to design models and discuss them. Practical tools would also be needed in order to manage this activity.

Second, for practitioners in science, it is also important to keep the model-design process apparent, and not to apply directly value creation methods that are more adapted to business data (such as marketing data).


The research focuses on the dynamics of ecosystems that aim at creating value from data.


Del Vecchio, Pasquale, Alberto Di Minin, Antonio Messeni Petruzzelli, Umberto Panniello, et Salvatore Pirri. 2018. « Big Data for Open Innovation in SMEs and Large Corporations: Trends, Opportunities, and Challenges ». Creativity and Innovation Management 27 (1): 6‑22.

Gandomi, Amir, et Murtaza Haider. 2015. « Beyond the Hype: Big Data Concepts, Methods, and Analytics ». International Journal of Information Management 35 (2): 137‑44.

Siggelkow, Nicolaj. 2007. « PERSUASION WITH CASE STUDIES ». Academy of Management Journal, 5.

Trabucchi, Daniel, et Tommaso Buganza. 2019. « Data-Driven Innovation: Switching the Perspective on Big Data ». European Journal of Innovation Management 22 (1): 23‑40.

Trabucchi, Daniel, Tommaso Buganza, Claudio Dell’Era, et Elena Pellizzoni. 2018. « Exploring the Inbound and Outbound Strategies Enabled by User Generated Big Data: Evidence from Leading Smartphone Applications ». Creativity and Innovation Management 27 (1): 42‑55.