Conference Agenda

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Session Overview
20-PM1-05: ST4.1 - the Design of New Industrial Ecosystems
Thursday, 20/June/2019:
1:00pm - 2:30pm

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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Platform Leaders’ Ecosystem Strategies for Industrial Internet of Things (IIoT): Dynamic Capabilities and Coopetition

Claudia Werker1, Doris Pastor-Torres2, Christian Hopp2

1Delft University of Technology, Netherlands, The; 2RWTH Aachen University, Germany


By bridging the digital and physical product world (Jeschke, Brecher, Song, & Rawat, 2017) IIoT platforms have been upending the manufacturing industry. Platforms link various agents from different backgrounds through shared architectures and governance rules (IDC, 2016) which form the platform ecosystem (Gawer & Cusumano, 2002).


Coopetition has become the rule not the exception when it comes to ecosystems (Adner, 2017). Agents of IIoT platforms have to collaborate and compete with complementors and customers as well as with agents of other platforms to keep innovating while testing (potential) customers’ preferences (IDC, 2016; Ollila & Yström, 2016; Wareham, Fox, & Cano Ginor, 2014). Consequently, platform leaders’ focus shifts to coopetition.

Dynamic capabilities provide firms with competitive advantage (Schilke, 2014). This effect is strongest under intermediate levels of dynamism and still significant under high dynamism. Platform leaders use dynamic capabilities to deal with coopetition within and between ecosystems. Dynamic capabilities include sensing, seizing as well as transforming (Teece, 2018). Platform leaders sense by identifying the technological opportunities of IIoT platforms, seize by embedding their digital business model in an ecosystem strategy, transform by realigning the structure and culture of the IIoT ecosystem.

Literature Gap

Coopetition within and between platform ecosystems as well as dynamic capabilities are increasingly well understood (see Section on relevant literature). We combine these strands of literature to answer our research questions.

Research Questions

RQ1: What business models and ecosystem strategies do IIoT platform leaders employ? What business models do their partners employ?

RQ2: How do the strategies of platform leaders depend on their dynamic capabilities?

RQ3: How do platform leaders deal with the dynamics of coopetition in ecosystems, particularly regarding their dynamic capabilities?


Our qualitative analysis is based on a review of the relevant literature and employs both source triangulation (see Section on empirical material) as well as researcher triangulation as all co-authors have been systematically involved in searching for sources, carrying out the interviews as well as analysing the interviews and other sources.

Empirical Material

We use two major kinds of sources: (1) interviews with proponents of three German industrial platform leaders distinctly different governance structures: Platform A organizes its platform leadership within the management authority of their own company, platform B is a spin-off and keeps its sponsoring company at arm’s length, platform C forms a cooperative of shareholder partners. (2) We use information from the literature and internet to add to and to check the information obtained in the interviews.


@RQ1: While platform leaders themselves use digital business models and ecosystem strategies, their partners are at different stages of digitalization. Complementors, i.e. software providers and app providers operate digital. They are scarce forming a serious bottleneck in further developing IIoT platforms. In contrast, customers vary in their degree of digitalisation. Some are fully digitalised. Yet particularly the smaller ones operate analogue and hesitate to go digital as their workforce fear for job losses.

@RQ2: The ecosystem strategies of the platform leaders heavily rely on their dynamic capabilities. While both platform A and B build on the strong competitive position of their mother respectively sponsoring company, platform C builds on that of their partner shareholders in their specific market segments.

@RQ3: Platform leaders further develop their dynamic capabilities to deal with coopetition within and outside their platform. Platforms A and C focus mainly on those customers ready to go fully digital, thereby using their dynamic capabilities of sensing and seizing. In contrast, platform B deals with a large share of customers at the beginning of their digital transformation. Consequently, its platform leader currently concentrates on consulting these firms, thereby using its dynamic capabilities of transforming both themselves and their customers.

Contribution to Scholarship

We contribute to the understanding of how platform leaders can manage highly volatile IIoT platforms by combining the strands of literature on coopetition with the dynamic capability approach. By doing so, we can identify the competitive advantages and the bottlenecks of IIoT platforms. Moreover, we show that platform leaders develop their dynamic capabilities to deal with the emerging coopetition with various partners by exploiting existing and updating their digital business models and ecosystem strategies.

Contribution to Practice

Two major bottlenecks materialize in our research results: (1) finding a sufficiently large number of complementors for which none platform leader has a quick solution and (2) facing a large share of customers which are not yet ready to go digital for which one of the platform leaders we interviewed found a solution by offering tailor-made consultancy services.


We contribute to track 4.1 by analysing various ecosystem strategies of platform leaders and exploring the challenges they face in dealing with partners of various degrees of digitalisation. Moreover, we show how platform leaders use and develop their dynamic capabilities to deal with coopetition within and outside the platform ecosystem.


Adner, R. (2017). Ecosystem as Structure: An Actionable Construct for Strategy. Journal of Management, 43(1), 39-58.

Gawer, A., & Cusumano, M. A. (2002). Platform leadership: How Intel, Microsoft, and Cisco drive industry innovation Boston (MA) U.S.A.: Harvard Business School Press.

IDC. (2016). Industrial Data Platforms - Key Enablers of Industry Digitization. Retrieved from

Jeschke, S., Brecher, C., Song, H., & Rawat, D. B. (2017). Industrial Internet of Things. e-book, Switzerland: Springer.

Ollila, S., & Yström, A. (2016). Exploring Design Principles of Organizing for Collaborative Innovation: The Case of an Open Innovation Initiative. Creativity and Innovation Management, 25(3), 365-377.

Schilke, O. (2014). On the contingent value of dynamic capabilities for competitive advantage: The nonlinear moderating effect of environmental dynamism. Strategic Management Journal, 35(2), 179-203. doi:doi:10.1002/smj.2099

Teece, D. J. (2018). Business models and dynamic capabilities. Long Range Planning, 51(1), 40-49. doi:10.1016/j.lrp.2017.06.007

Wareham, J., Fox, P. B., & Cano Ginor, J. L. (2014). Technology Ecosystem Governance. Organization Science, 25(4), 1195-1215. doi:10.1287/orsc.2014.0895

Disentangling the relationship between ecosystem design and governance modes in economically weak regions: An exploratory analysis

Christina Dienhart, Bastian Kindermann, Torsten-Oliver Salge

RWTH Aachen University, Germany


Regional innovation ecosystems are increasingly in the focus of scholarly attention due to their importance for structural development. Especially in regions that are economically underdeveloped, more research is warranted to fully understand and emphasize their innovation potential. This paper investigates design and governance modes of ecosystems in economically weak regions.


The literature relevant for this study spans three disciplinary domains. First, innovation ecosystems are investigated as they offer a novel way to sustainably orchestrate different actors around a focal value proposition (Adner, 2017; Jacobides et al., 2018). Especially those located in economically weak regions have been shown to be different from “normal ecosystems” due to characteristics like network density, structure and innovation activities (e.g. Tödtling & Trippel, 2005). Second, various studies have analyzed how ecosystems are designed. This includes inter alia reflecting on the actors, their roles and inter-relationships and their interconnections with external factors (Dattée et al., 2018). Third, this study uses insights from ecosystem governance research (Dhanaraj & Parkhe, 2006; Wareham et al., 2014). Extant knowledge on the topic particularly emphasizes the roles of formal and informal governance mechanisms as two distinctive dimensions pertaining to the degree of formalization and the level of enforcement (Dyer & Singh, 1998).

Literature Gap

While extant knowledge on ecosystem governance is largely based on analyses of vibrant industrial settings, insights from structurally weak regions are scarce. This lack is surprising as ecosystems in such regions differ meaningfully in multiple ways. Given their considerable importance for structural development, more research is warranted.

Research Questions

We aim at uncovering the relationship between ecosystem design and the distinct governance mechanisms orchestrators employ to manage members. More precisely: How are ecosystems in economically weak regions designed? What are effective governance modes for ecosystems in economically weak regions? How does the design of these ecosystems shape their governance?


Our qualitative research design is built on an inductive case-study approach in accordance with the exploratory nature of the study. Based on an initial understanding of innovation ecosystems in economically weak regions through a small pre-study, we are focusing on exploring different design modes and underlying governance mechanisms through data triangulation. Primary data will be collected through semi-structured interviews whereas secondary data will be based on media documentation, website analysis and an analysis of documents provided by the interviewees.

Empirical Material

The data collection will be based on a new funding program of the German Federal Ministry of Education and Research (BMBF) that has been launched in 2018. The program “Innovation and Structural Transformation” promotes the development of regional innovation ecosystems. The program aims at supporting the formation of innovation ecosystems for structural change in economically weak regions in the east of Germany. Target groups are consortia that span disciplinary, industrial, institutional and administrative boundaries.

Our paper is based on 32 initiatives that have been handed in after a first application phase. Their innovation areas are covering a wide range of fields including modernization of agricultural and nutritional science, new mobility and driving concepts for future traffic as well as health care in rural areas. The consortia are from different regions in the east of Germany including former lignite regions, costal outback’s and mountain regions. Being initiated by research institutes, universities and/or SMEs, the initiatives differ in many aspects while aiming at reaching a common goal: structural change through the establishment of regional innovation ecosystems that span the innovation potential of their region.


Building on existing studies on regional innovation ecosystems and their different designs and governance mechanisms, we develop a research agenda for ecosystems in economically weak regions to shift scholarly attention from the analysis of only vibrant industrial sectors. By taking a closer look at the relationship between the design and governance of ecosystems, we will disentangle potential combinations of the two concepts. Based on these findings, we will identify specific configurations of ecosystem designs and governance modes.

Contribution to Scholarship

Our findings allow us to make two main conceptual contributions to the emerging literature on regional innovation ecosystems and to broader discussions on ecosystem design and governance. First, the paper sheds light on the underexplored phenomenon of innovation ecosystems in economically weak regions. In doing so, we are answering calls for more research in this field and are underlining the importance of differentiation between ecosystems in vibrant industrial sectors and those in economically weak regions. Second, our paper provides a differentiated perspective on ecosystems design and governance. We are delineating relationships between ecosystem design and governance and provide insights into their inter-dependence. Based on our findings, we create novel insights that are spanning the fields of innovation ecosystems, regional development and governance / orchestration.

Contribution to Practice

Policymakers are increasingly focusing on innovation ecosystems in their regional development strategies. Particularly in economically weak regions, economic decline might be actively reconstituted through the help of public policy innovation ecosystem incentives.

Disentangling the relationship between ecosystem design and governance mode of economically weak regions is an important contribution to avoid pitfalls of an innovation policy approach drawing its inspiration from the ideal type regional innovation systems. We hope that based on our research, innovation policies can be better designed and the management of innovation ecosystems in such regions better understood.


Regional innovation ecosystems are increasingly recognized as drivers of innovation, technological progress and economic development, which in turn are associated with job creation, wage growth and structural transformation (Acs et al., 2008). Hence, this research lies at the heart of the innovation challenge of bridging research, industry and society.


Acs, Z.J., Desai, S., & Hessels, J. (2008). Entrepreneurship, economic development and institutions. Small Business Economics, 31(3), 219–234.

Adner, R. (2017). Ecosystem as Structure: An Actionable Construct for Strategy. Journal of Management, 34(1):39-58.

Dattée, B., Alexy, O. & Autio, E. (2018). Maneuvering in Poor Visibility: How Firms Play the Ecosystem Game when Uncertainty is High. Academy of Management Journal, 61(2): 466–498.

Dhanaraj, C., & Parkhe, A. (2006). Orchestrating innovation networks. Academy of Management Review, 31(3), 659–669.

Dyer, J.H., and H. Singh. 1998. The relational view: Cooperative strategy and sources of interorganizational competitive advantage. Academy of Management Review, 23(4): 660-679.

Jacobides M. G., Cennamo C. & Gawer A. (2018). Towards a theory of ecosystems. Strategic Management Journal, 39:2255–2276.

Tödtling, F. & Trippel, M. (2005). One size fits all? Towards a differentiated regional innovation policy approach. Research Policy, 34:1203–1219.

Wareham J., Fox, P. B. & Giner, J. L. C. (2014). Technology Ecosystem Governance. Organization Science, 25(4):1195-1215.

A typology of business models transformation in the marketing of emerging technologies

Serena Flammini, Letizia Mortara

University of Cambridge, United Kingdom


To develop and commercialise innovation, companies need to weave together the competences and resources of different players. This is done through the formation of ecosystems (Adner 2016). The types of ecosystems created to develop an innovation differ from the ones built to commercialised it? (Clarysse et al. 2014)


Firms can commercialise an innovation orchestrating “value constellations” across an entire group (ecosystem) of innovation participants. This allows the whole group of partners to create and capture value from the innovation (Vanhaverbeke and Cloodt 2006)). This type of value constellation is known as a business ecosystem (BE - Clarysse et al. 2014).

However, partners can create and capture value also while developing an innovation through the creation of knowledge ecosystems (KE). For example, new ventures developing a technological innovation might benefit from the development of collaborations with local universities, research organizations and other firms (Clarysse et al. 2014; Aksenova et al. 2018).

Some studies do not find links between the construction of BE and KE (Clarysse et al 2014 and Askenova et al. 2018). In contrast, Attour and Lazaric (2018) found that KE can lead to the emergence of a platform embodying a BE.

Literature Gap

We still do not whether linkages exist between KE and BE (Clarysse et al. 2014; Aksenova et al. 2018; Tsujimoto et al. 2018)

Research Questions

This paper asks “how do companies link a knowledge ecosystem with a business ecosystem?”


We analyse the different shapes assumed by value constellations for KE and BE along the process (i.e. from the development to the commercialisation) of innovations based on an emergent radical technology (3D printing). Cases were selected from the food preparation (3D Food Printing) and organ/tissue generation (Bio-printing). The different nature of the case studies context/industries increases the potential generalisability of the study.

Empirical Material

Building on previous research in the field under observation, we used a multiple case study approach to link theory with practice (e.g.(Cortimiglia, et al., 2016; Lubik and Garnsey 2016). To perform the cross-case study analysis, in-depth semi-structured interviews with a well-defined focus (Eisenhardt 1989) were used to collect data, systematically gathering episodic and empirical information (Eisenhardt and Graebner 2007).

We observed the types of linkages between KE and BE of 14 organisations in the two industries, through the lens of modularity theory, which outlines six possible standard changes called “modular operators”: a splitting, substitution, augmenting, inverting excluding and porting (Aversa et al. 2015).

This approach allowed to identify data of 28 ecosystem links across the two set of case studies. Data were captured between 2014 and 2018. We used the ecosystem as a suitable unit of analysis for the study. An average of 2 interviews per company jointly with a set of follow-up discussions with the informants.

The interviews were conducted asking the informants about past (retrospective perspective) and present (current perspective) events. To increase the validity of the study, the interviews were supported by archival data analysis.


The six types of KE – BE modular changes in value constellations are often multilayered. For instance, firms can adopt an overall splitting link - i.e. one KE0 leads to the development of two BE1;2. However, the types of relationships between KE0 and BE1 and KE0 and BE2 can differ based on the types of value propositions offered by BE1 and BE2. If an ecosystem is formed to develop knowledge to build a 3D printing appliance (i.e. KE0) this can lead to the development of two different types of ecosystems (i.e. modular operator: splitting): one that offers 3D printing appliances (i.e. BE1) and another one that offers 3D printing services (i.e. BE2). The relationship between KE0 and BE1 and KE0 and BE2 can be different. While the knowledge to build a 3D printing appliance (i.e. KE0) foster the development of an ecosystem that commercialise 3D printing appliances (BE1) but it keeps working and feeding new insights to BE1 (i.e. modular operator: augmenting). Instead, this same knowledge (i.e. KE0) can be used to form another ecosystem that provides 3D printing services (BE2), which do not need the support of the KE0 any further (i.e. modular operator: substituting).

Contribution to Scholarship

We linked the modularity theory and ecosystems. We realised the various ways in which the KE transforms into a BE.

Contribution to Practice

By outlining the different types of shapes that can be assumed by constellations in linking KE and BE in the innovation process, this work provides useful implication not only to advance in theory, but they can be useful also to managers. Hence, this work supports managers to understand which ecosystems strategies could be adopted for a technology commercialisation process and the circumstances to prefer a typology of link over another one.


This work is relevant for the R&D Management Conference as it focuses on the core area of the conference which is the innovation management field. In particular, the work is focused on knowledge and innovation ecosystems, main element of the track 4.1.


Adner, Ron. 2016. “Ecosystem as Structure: An Actionable Construct for Strategy.” Journal of Management 43 (1): 39–58. doi:10.1177/0149206316678451.

Aksenova, Kiviniemi, Kocaturk, and Lejeune. 2018. “From Finnish AEC Knowledge Ecosystem to Business Ecosystem Lessons Learned from the National Deployment of BIM.” Construction Management and Economics. doi:10.1080/01446193.2018.1481985.

Attour, Amel, and Nathalie Lazaric. 2018. “From Knowledge to Business Ecosystems: Emergence of an Entrepreneurial Activity during Knowledge Replication.” Small Business Economics, no. 1962: 1–13. doi:10.1007/s11187-018-0035-3.

Aversa, Paolo, Stefan Haefliger, Alessandro Rossi, and Charles Baden-Fuller. 2015. “From Business Model to Business Modelling: Modularity and Manipulation.” Business Models and Modelling 33 (October): 151–85. doi:10.1108/S0742-332220150000033022.

Clarysse, Bart, Mike Wright, Johan Bruneel, and Aarti Mahajan. 2014. “Creating Value in Ecosystems: Crossing the Chasm between Knowledge and Business Ecosystems.” Research Policy 43 (7). Elsevier B.V.: 1164–76. doi:10.1016/j.respol.2014.04.014.

Cortimiglia, Marcelo, Antonio Ghezzi, and Alejandro Frank. 2016. “Business Model Innovation and Strategy Making Nexus: Evidence from a Cross-Industry Mixed-Methods Study.” R&D Management 46 (3): 414–32. doi:doi: 10.1111/radm.12113.

Eisenhardt, Kathleen M. 1989. “Building Theories from Case Study.” Academy of Management Review 14 (4): 532–50.

Eisenhardt, Kathleen M, and Melissa E Graebner. 2007. “THEORY BUILDING FROM CASES : OPPORTUNITIES AND CHALLENGES Diverse.” Academy of Management Journal 50 (1): 25–32. doi:Article.

Lubik, Sarah, and Elizabeth Garnsey. 2016. “Early Business Model Evolution in Science-Based Ventures: The Case of Advanced Materials.” Long Range Planning 49 (3). Elsevier Ltd: 393–408. doi:10.1016/j.lrp.2015.03.001.

Tsujimoto, Masaharu, Yuya Kajikawa, Junichi Tomita, and Yoichi Matsumoto. 2018. “A Review of the Ecosystem Concept — Towards Coherent Ecosystem Design.” Technological Forecasting and Social Change 136 (July 2017). Elsevier: 49–58. doi:10.1016/j.techfore.2017.06.032.

Urmetzer, Florian, Andy Neely, and Veronica Martinez. 2016. “Business Ecosystems: Towards a Classification Model.” 5th World Congress on Production and Operations Management (P&OM 2016), no. April.

Vanhaverbeke, Wim, and M Cloodt. 2006. “Open Innovation in Value Networks.” Open Innovation: Researching a New Paradigm, no. March: 258–81. doi:10.1111/j.1467-8691.2008.00502.x.

The role of amateur communities and middleground ecosystems in the emergence of micro-computing in the early 1970

Gilles Garel

Conservatoire national des arts et métiers, France


The paper provides a comparative analysis of the amateur communities that, at the same time in the United States and in France, contributed to the first developments in microcomputing and in particular to the emergence of two pioneering companies. How were Micro-soft and SMT Goupil generated from the community ecosystem?


Management research must be grounded on this historical and sociological material. The article mobilizes second-hand historical sources on the computer part, which are widely available in the history literature. The paper also use literature on communities from Tönnies, Lave and Wenger to Cohendet and Simon (specialy their "under, middle, upperground" grid). We look at the literature on the emergence of industries: technological change and industrial evolution (Aldrich and Fiol, 1994), approaches that address the evolution of industries, including industrial life cycle theory (Abernathy and Utterback 1978) or the ecology of organizations (Hannan and Freeman 1977).

Literature Gap

Emerging industries are difficult to study because it is often difficult to identify emerging industries before they have become mature. In both cases, for explaining the emergence of Microsoft and SMT we coin and develop the concept of "booting community" enriching the Cohendet and Simon upper-middle,-under grid.

Research Questions

How does a business emerge from a community ecosystem?

What is an amateur community?

What are the different types of amateur communities?

What is a “boot community”?


This qualitative article mobilizes second-hand historical sources on the computer part, which are widely available in the history literature. The article also capitalizes on the recent experience of a Mooc -massive on line open course- (XX, “Innovation Factory” at the “arts et métiers (arts and crafts) museum” in Paris) dedicated to innovation processes with one week devoted to the history of microcomputing.

Empirical Material

Second-hand historical sources and literature review.


- The paper gathers some background information that led to the emergence of microcomputers. With the first machines, communities will develop around software programming and improvement and adaptation to different contexts of use.

- the paper also defines and compares the emergence and the role of two communities: American hobbyists on one side and French amateurs on the other.

- It finally discusses on the dynamic of communities, acting ex ante as an underground ecosystem, gradually structuring (until they become firms) themselves via a middleground, notably around amateur clubs. While Microsoft was born out of an “anti-community power grab”, the emergence of SMT is a process of institutionalizing the community.

Contribution to Scholarship

The concept of "booting community". It is indeed from the communities that companies (in both cases, Microsoft and SMT) are created, but in a different relationship with the communities each time: a power grab against the community in one case and a progressive institutionalization in the other. Once firms are established, the entire institutional ecosystem of microcomputing is set up; more and more companies are developing a commercial activity. Our community-original or initial approach can be resituated in three different strategies and three innovation contexts corresponding to this period of the emergence of the microcomputer industry. This expansion displaces and enriches the ecosystem approach.

Contribution to Practice

The entrepreneur can choose between several emergence strategies:

- the strategy of the isolate in a large company (ex. IBM PC in 1981),

- the strategy of the isolated start-up (REE and Micral-N by François Gernelle, who created the first microcomputer in 1973), here, it is precisely the absence of an appropriate ecosystem that isolates innovation and hinders its diffusion and recognition, the path of the isolated start-up, cut off from amateur communities, universities and industrialists has deprived the French pioneers of microcomputing of global commercial success despite a technological advance.

- the strategy of amateur community (emergent or deliberate).


It is relevant to complement and deepen community approaches to innovation ecosystems. Amateur communities are nowadays very much studied in open innovation relationships with, in particular, customer communities. The prospect of understanding the emergence of new businesses from amateur communities is an enrichment of the innovation approach.


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