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Marcel Bogers, U. of Copenhagen & U. of California Berkeley, marcel@ifro.ku.dk
Jonathan Sims, Joel West
What Is an Ecosystem? Incorporating 25 Years of 
Ecosystem Research
Authors
Marcel Bogers, U. of Copenhagen & U. of California Berkeley, marcel@ifro.ku.dk
Jonathan Sims, Babson College, jsims@babson.edu
Joel West, Keck Graduate Institute, kgi@joelwest.org
Marcel Bogers, U. of Copenhagen & U. of California Berkeley, marcel@ifro.ku.dk
Jonathan Sims, Joel West
11080 
- 1 - 
What Is an Ecosystem? Incorporating 25 Years of Ecosystem Research 
 
ABSTRACT 
 Ecosystems are increasingly recognized as crucial for the success of a firm’s innovation 
strategy and business model. They are also a topic attracting increasing academic interest, with 
more than 300 articles published in top journals since 1992, most in the past five years. Based on 
an examination of this research, we propose a new definition that links the central goal of an 
ecosystem — joint value creation — to three constructs: goals of ecosystem members, the 
network of relations between these members, and the interdependence of their respective goals. 
We show how the four components of this definition allow ecosystem researchers to incorporate 
insights across a wide range of previously excluded studies of ecosystems and related topics. 
From this, we summarize the research opportunities made possible by this more inclusive 
definition, including research on each of the components, the interconnection between 
components, and with the ecosystem used as a level of analysis. 
 
Marcel Bogers, U. of Copenhagen & U. of California Berkeley, marcel@ifro.ku.dk
Jonathan Sims, Joel West
11080 
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What Is an Ecosystem? Incorporating 25 Years of Ecosystem Research 
 
INTRODUCTION 
 For more than 25 years, scholars and consultants have advised managers to view their 
cooperation with other firms by analogy to a natural ecosystem (Moore, 1993, 1996; Iansiti & 
Levien, 2004; Adner, 2006, 2012). This advice points to the cooperative and interdependent way 
that firms perform activities such as creating and supporting new products. Such an ecosystem 
perspective has become increasingly important with platform-based business models enabled by 
a modular division of labor (Kenney & Zysman, 2016; Jacobides, Cennamo & Gawer, 2018). At 
the same time, ecosystems also provide an important option for firms to harness external partners 
for value creation as part of an open innovation strategy (Vanhaverbeke & Cloodt, 2006; West, 
2014; Bogers et al, 2017). 
 Empirical research during this period has documented the importance of ecosystems across a 
wide range of contexts. Firms were successful developing computing platforms — which shrunk 
from room sized mainframes to desktop computers to pocket smartphones — by cultivating a 
network of third party suppliers of software and other complements (Bresnahan & Greeinstein, 
1999; Gawer & Cusumano, 2002; West & Mace, 2010). Retailers coordinate complex supply and 
distribution networks to maximize availability and minimize cost (Iansiti & Levien, 2004). The 
Internet has enabled new forms of two-sided markets that match a web of geographically 
dispersed buyers and sellers (Eisenmann et al., 2006), and also create virtual communities that 
create value that can be captured in a variety of ways (Armstrong & Hagel, 2000; Hanna et al., 
2011). Conversely, researchers have shown how the ecosystem concept explains the 
interdependence of economic actors in a specific geographic area, such as a regional 
entrepreneurial cluster (Finegold, 1999). 
 Recently, interest in ecosystems has exploded among academic researchers: more than 300 
articles were published on business ecosystems from 1992-2018, with two-thirds in the past five 
Paula Chimenti
Marcel Bogers, U. of Copenhagen & U. of California Berkeley, marcel@ifro.ku.dk
Jonathan Sims, Joel West
11080 
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years. However, the cumulative benefit of this research has been limited by inconsistent 
definitions of what an ecosystem is. Some have emphasized the biological metaphor, some 
honed in on a particular type of ecosystem — such as a computing platform or regional economy 
— while still others have studied ecosystems without using the term at all. Despite recent 
attempts to more narrowly define the ecosystem concept (Adner, 2017; Jacobides et al., 2018), 
we instead suggest that a broader and more integrative perspective is needed to bring together 
disparate streams of related ecosystem research into a more comprehensive framework. 
 After conducting a systematic review of this growing body of ecosystems research, we 
propose a new definition of ecosystem as “an interdependent network of self-interested actors 
jointly creating value.” This definition includes four components, linking three operational 
constructs — interdependence, network and self-interested actors — to the most commonly 
described success criterion for an ecosystem: to jointly create value in a way that no single actor 
would be able to do. The remainder of this paper discusses how each of these four components 
(interdependence, network, self-interested actors, creating value) has been used in previous 
research. In particular, it shows how the three operational constructs of this definition — the 
goals of ecosystem members, the network of relations between these members, and the 
interdependence of these members and their goals — both explain the activities of these 
ecosystems and how they link to the fourth component, ecosystem success. 
 The advantage of this definition is that it is on the one hand concise and precise — making it 
easy to build on — while it on the other hand encompasses a wider range of ecosystem research 
than previous definitions, including the role of individual or nonprofit members and research on 
regional entrepreneurial ecosystems. Thereby, it will better allow for integrating various related 
streams of research into an overarching framework upon which researchers can build their future 
studies in this domain. At the same time, the four components of the definition will specifically 
allow systematically incorporating research on each component from research beyond what has 
Paula Chimenti
Paula Chimenti
Marcel Bogers, U. of Copenhagen & U. of California Berkeley, marcel@ifro.ku.dk
Jonathan Sims, Joel West
11080 
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so far been narrowly defined as “ecosystems” — more consistent with the modular process of 
open science (Langlois & Garzarelli, 2008) than earlier, more integral definitions. 
 For managers, this framework increases the clarity of the disparate management advice that 
has been offered over the past decades, by focusing on the four components common across all 
forms of ecosystems. For researchers, we suggest it provides three potential benefits. First, it 
allows systematic incorporation of research across a wide range of empirical contexts — 
research on ecosystems, research fitting this definition published under other names (such as 
platforms or value networks) and other contexts that only match our definition. Second, the 
framework suggests new opportunities for future research linking these constructs to each other 
or to ecosystem success. Finally, a formal definition of what an ecosystem is facilitates research 
at the level of the ecosystem rather than its components to enable a more comprehensive 
understanding of the antecedent, mechanisms and outcomes of ecosystems per se. 
PRIOR ECOSYSTEM RESEARCH 
Literature Search and Sample Development 
 Ecosystems are of increasing interest among business researchers. The Social Science 
Citation Index (SSCI) lists 924 business or management articles from 1992-2018 that mention 
ecosystem as a topic (i.e., title, abstract or author-provided keywords),iphone-dominates-smartphone-profits/ 
Kallinikos, J., Aaltonen, A., & Marton, A. (2013). The Ambivalent Ontology of Digital 
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Kapoor, R., & Lee, J. M. (2013). Coordinating and competing in ecosystems: How 
organizational forms shape new technology investments. Strategic Management 
Journal, 34(3), 274-296. 
Kenney, M., & Zysman, J. (2016). The rise of the platform economy. Issues in Science and 
Technology, 32(3), 61-69. 
Kilamo, T., Hammouda, I., Mikkonen, T., & Aaltonen, T. (2012). From proprietary to open 
source—Growing an open source ecosystem. Journal of Systems and Software, 85(7), 1467-
1478. 
Kim, Y., Kim, W., & Yang, T. (2012). The effect of the triple helix system and habitat on 
regional entrepreneurship: Empirical evidence from the US. Research Policy, 41(1), 154-166. 
Landsman, V., & Stremersch, S. (2011). Multihoming in two-sided markets: An empirical 
inquiry in the video game console industry. Journal of Marketing, 75(6), 39-54. 
Langley, A. (1999). Strategies for theorizing from process data. Academy of Management 
Review, 24(4), 691-710. 
Langlois, R. N., & Garzarelli, G. (2008). Of hackers and hairdressers: Modularity and the 
organizational economics of open-source collaboration. Industry and Innovation, 15(2), 125-
143. 
Lee, C., & Coughlin, J. F. (2015). Perspective: Older adults' adoption of technology: an 
integrated approach to identifying determinants and barriers. Journal of Product Innovation 
Management, 32(5), 747-759. 
Lee, G., & Raghu, T. S. (2014). Determinants of mobile apps' success: evidence from the App 
Store market. Journal of Management Information Systems, 31(2), 133-170. 
Lin, Z., Yang, H., & Arya, B. (2009). Alliance partners and firm performance: resource 
complementarity and status association. Strategic Management Journal, 30(9), 921-940. 
Linden, G., Kraemer, K. L., & Dedrick, J. (2009). Who captures value in a global innovation 
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Marcel Bogers, U. of Copenhagen & U. of California Berkeley, marcel@ifro.ku.dk
Jonathan Sims, Joel West
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Markman, G. D., Gianiodis, P. T., Phan, P. H., & Balkin, D. B. (2005). Innovation speed: 
Transferring university technology to market. Research Policy, 34(7), 1058-1075. 
Markus, M.L., Steinfield, C.W., & Wigand, R.T. (2006). Industry-wide information systems 
standardization as collective action: the case of the US residential mortgage industry. MIS 
Quarterly, 439-465. 
Massa, L., Tucci, C. L., & Afuah, A. (2017). A critical assessment of business model research. 
Academy of Management Annals, 11(1), 73-104. 
Mathias, B. D., Huyghe, A., Frid, C. J., & Galloway, T. L. (2018). An identity perspective on 
coopetition in the craft beer industry. Strategic Management Journal, 39(12), 3086-3115. 
McIntyre, D. P., & Srinivasan, A. (2017). Networks, platforms, and strategy: Emerging views 
and next steps. Strategic Management Journal, 38(1), 141-160. 
Moore, J.F. (1993). Predators and prey: a new ecology of competition. Harvard Business 
Review 71 (3), 75-86. 
Moore, J.F. (1996). The Death of Competition: Leadership and Strategy in the Age of Business 
Ecosystems. New York: HarperBusiness. 
Moore, J.F. (2006). Business ecosystems and the view from the firm. Antitrust Bulletin, 51(1), 
31-75. 
Nambisan, S., & Baron, R.A. (2013). Entrepreneurship in Innovation Ecosystems: 
Entrepreneurs’ Self-Regulatory Processes and Their Implications for New Venture Success. 
Entrepreneurship Theory and Practice, 37 (5), 1071-1097. 
Nicotra, M., Romano, M., Del Giudice, M., & Schillaci, C. E. (2018). The causal relation 
between entrepreneurial ecosystem and productive entrepreneurship: A measurement 
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Normann, R., & Ramirez, R. (1993). From value chain to value constellation: Designing 
interactive strategy. Harvard Business Review, 71(4), 65-77. 
O’Mahony, S. (2003). Guarding the commons: how community managed software projects 
protect their work. Research Policy, 32(7), 1179-1198. 
O’Mahony, S. (2007). The governance of open source initiatives: what does it mean to be 
community managed? Journal of Management & Governance, 11(2), 139-150. 
O’Mahony, S., & Ferraro, F. (2007). The emergence of governance in an open source 
community. Academy of Management Journal, 50(5), 1079-1106. 
O’Mahony, S., & Karp, R. (2017). “From proprietary to collective governance: How platform 
participant strategies adapt,” paper presented at Platform Strategy Research Symposium, 
Boston, July 13. 
Ormans, L. (2016). 50 Journals used in FT Research Rank. September 12. URL: 
https://www.ft.com/content/3405a512-5cbb-11e1-8f1f-00144feabdc0 
Pagani, M. (2013). Digital business strategy and value creation: Framing the dynamic cycle of 
control points. MIS Quarterly, 37(2), 617-632. 
Parker, G. & van Alstyne, M. W. (2000) Information Complements, Substitutes, and Strategic 
Product Design. November 8, URL: https://ssrn.com/abstract=249585 
Parker, G., van Alstyne, M. V., & Jiang, X. (2017). Platform ecosystems: How developers invert 
the firm. Management Information Systems Quarterly, 41(1), 255-266. 
Perrons, R.K. (2009). The open kimono: How Intel balances trust and power to maintain 
platform leadership. Research Policy, 38(8), 1300-1312. 
Pfeffer, J., & Fong, C. T. (2004). The business school ‘business’: Some lessons from the US 
experience. Journal of Management Studies, 41(8), 1501-1520. 
Paula Chimenti
Marcel Bogers, U. of Copenhagen & U. of California Berkeley, marcel@ifro.ku.dk
Jonathan Sims, Joel West
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Phelps, C.C. (2010). A longitudinal study of the influence of alliance network structure and 
composition on firm exploratory innovation. Academy of Management Journal, 53(4), 890-
913. 
Pierce, L. (2009). Big losses in ecosystem niches: How core firm decisions drive complementary 
product shakeouts. Strategic Management Journal, 30(3), 323-347. 
Pitelis, C. (2012). Clusters, entrepreneurial ecosystem co-creation, and appropriability: a 
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Porter, M. E. (1985). Competitive advantage: creating and sustaining superior performance. 
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Porter, M. E. (2000). Location, competition, and economic development: Local clusters in a 
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Powell, W. W. (1990). Neither Market Nor Hierarchy. Research in Organizational Behavior, 12, 
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Qiu, Y., Gopal, A., & Hann, I. H. (2017). Logic pluralism in mobile platform ecosystems: A 
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225-249. 
Radziwon, A., Bogers, M., & Bilberg, A. (2017). Creating and capturing value in a regional 
innovation ecosystem: A study of how manufacturing SMEs develop collaborative solutions. 
International Journal of Technology Management, 75(1): 73-96. 
Raja, J. Z., Bourne, D., Goffin, K., Çakkol, M., & Martinez, V. (2013). Achieving customer 
satisfaction through integrated products and services: An exploratory study. Journal of 
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Rochet, J. C., & Tirole, J. (2003). Platform competition in two-sided markets. Journal of the 
European Economic association, 1(4), 990-1029. 
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capabilities, and strategic commitments. Industrial and Corporate Change, 3(3), 655-685. 
Rosenkopf, L., Metiu, A., & George, V. P. (2001). From the bottom up? Technical committee 
activity and alliance formation. Administrative Science Quarterly, 46(4), 748-772. 
Rysman, M. (2009). The economics of two-sidedmarkets. Journal of Economic 
Perspectives, 23(3), 125-43. 
Saloner, G. (1990). Economic issues in computer interface standardization. Economics of 
Innovation and New Technology, 1(1-2), 135-156. 
Sandström, C. G. (2016). The non-disruptive emergence of an ecosystem for 3D Printing—
Insights from the hearing aid industry's transition 1989–2008. Technological Forecasting and 
Social Change, 102, 160-168. 
Saxenian, A. (1994). Regional advantage. Boston, MA: Harvard Business School Press. 
Shah, S. K. (2006). Motivation, governance, and the viability of hybrid forms in open source 
software development. Management Science, 52(7), 1000-1014. 
Simcoe, T. (2012). Standard setting committees: Consensus governance for shared technology 
platforms. American Economic Review, 102(1), 305-36. 
Sims, J., Gichoya, J., Bhardwaj, G., & Bogers, M. (2018). Write Code, Save Lives: How a 
Community Uses Open Innovation to Address a Societal Challenge. R&D Management. 
DOI: 10.1111/radm.12338 
Marcel Bogers, U. of Copenhagen & U. of California Berkeley, marcel@ifro.ku.dk
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Spaeth, S., von Krogh, G., & He, F. (2015). Perceived Firm Attributes and Intrinsic Motivation 
in Sponsored Open Source Software Projects. Information Systems Research, 26(1), 224-237. 
Spigel, B. (2017). The Relational Organization of Entrepreneurial Ecosystems. Entrepreneurship 
Theory and Practice, 41 (1), 49-72. 
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critique. European Planning Studies, 23(9), 1759-1769. 
Staudenmayer, N., Tripsas, M., & Tucci, C. L. (2005). Interfirm modularity and its implications 
for product development. Journal of Product Innovation Management, 22(4), 303-321. 
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371-384. 
Teece, D. J. (1986). Profiting from technological innovation: Implications for integration, 
collaboration, licensing and public policy. Research Policy, 15(6), 285-305. 
Thomas, L. D., Autio, E., & Gann, D. M. (2014). Architectural leverage: putting platforms in 
context. Academy of Management Perspectives, 28(2), 198-219. 
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Research, 26 (2), 266-281. 
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Systems, 32(4), 40-77. 
Tiwana, A., Konsynski, B., & Bush, A. A. (2010). Research commentary—Platform evolution: 
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innovation, industry structure, and organizational capabilities: Evidence from modern patent 
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W. Vanhaverbeke & J. West, eds., Open innovation: Researching a new paradigm, Oxford: 
Oxford University Press, 258-281. 
Venkatraman, N., & Lee, C.-H. (2004). Preferential linkage and network evolution: A conceptual 
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Corporate Change, 16(2), 293-315. 
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Motivation and social practice in open source software development. MIS Quarterly, 36(2), 
649-676. 
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resource combinations. Strategic Management Journal, 28(13), 1291-1317. 
Wareham, J., Fox, P.B., & Giner, J.L. (2014). Technology Ecosystem Governance. Organization 
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Weiss, M., & Gangadharan, G. R. (2010). Modeling the mashup ecosystem: Structure and 
growth. R&D Management, 40(1), 40-49. 
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Marcel Bogers, U. of Copenhagen & U. of California Berkeley, marcel@ifro.ku.dk
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West, J. (2003). How open is open enough? Melding proprietary and open source platform 
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Vanhaverbeke & J. West, eds., New frontiers in open Innovation, Oxford: Oxford University 
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West, J., & Dedrick, J. (2000). Innovation and control in standards architectures: The rise and 
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West, J., & Gallagher, S. (2006). Challenges of open innovation: The paradox of firm investment 
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West, J., & Mace, M. (2010). Browsing as the killer app: Explaining the rapid success of Apple's 
iPhone. Telecommunications Policy, 34(5-6), 270-286. 
West, J., & O’Mahony, S. (2008). The role of participation architecture in growing sponsored 
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West, J., & Sims, J. (2018). How Firms Leverage Crowds and Communities. In A. Afuah, C. 
Tucci, and G. Viscusi, eds., Creating and Capturing Value through Crowdsourcing, Oxford: 
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Zhu, F., & Iansiti, M. (2012). Entry into platform-based markets. Strategic Management 
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Marcel Bogers, U. of Copenhagen & U. of California Berkeley, marcel@ifro.ku.dk
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FIGURES AND TABLES 
Figure 1: Papers Published Mentioning “Ecosystem” in Topic, 1992-2018 
 
 
 
0
10
20
30
40
50
60
70
80
90
100
19
92
19
93
19
94
19
95
19
96
19
97
19
98
19
99
20
00
20
01
20
02
20
03
20
04
20
05
20
06
20
07
20
08
20
09
20
10
20
11
20
12
20
13
20
14
20
15
20
16
20
17
20
18
Marcel Bogers, U. of Copenhagen & U. of California Berkeley, marcel@ifro.ku.dk
Jonathan Sims, Joel West
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Figure 2: Relations Among Constructs in Ecosystem Concept 
 
 
Paula Chimenti
Marcel Bogers, U. of Copenhagen & U. of California Berkeley, marcel@ifro.ku.dk
Jonathan Sims, Joel West
11080 
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Table 1: Journals Included in SSCI Search 
Academy of Management Journal (3) 
Academy of Management Review (3) 
Accounting, Organizations and Society (1) 
Administrative Science Quarterly (1) 
American Economic Review (1) 
California Management Review (12) 
Entrepreneurship Theory and Practice (4) 
Harvard Business Review (18) 
IEEE Transactions on Engineering 
Management (2) 
Industrial and Corporate Change (7) 
Information Systems Research (9) 
International Journal of Technology 
Management (27) 
Journal of Business Ethics (5) 
Journal of Business Venturing (2) 
Journal of Financial Economics (1) 
Journalof International Business Studies (4) 
Journal of Management (1) 
Journal of Management Information Systems 
(4) 
Journal of Management Studies (8) 
Journal of Marketing (3) 
Journal of Product Innovation Management (7) 
Journal of the Academy of Marketing Science 
(2) 
Long Range Planning (1) 
Management Science (6) 
Marketing Science (1) 
MIS Quarterly (14) 
Operations Research (1) 
Organization Science (7) 
Organization Studies (1) 
Production and Operations Management (1) 
R & D Management (10) 
Research Policy (17) 
Research-Technology Management (13) 
Review of Financial Studies (1) 
Sloan Management Review (1) 
Strategic Entrepreneurship Journal (8) 
Strategic Management Journal (18) 
Technological Forecasting and Social Change 
(65) 
Technovation (12) 
 
Journals from the FT 50 list are shown in italics. The number of relevant ecosystem articles is 
shown in parentheses (N=302). 
 
Paula Chimenti
Marcel Bogers, U. of Copenhagen & U. of California Berkeley, marcel@ifro.ku.dk
Jonathan Sims, Joel West
11080 
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Table 2: Representative Definitions of “Ecosystem” in Prior Research 
 Components 
Citation Definition In
te
rd
ep
en
–
d
en
ce
 
N
et
w
o
rk
 
S
el
f-
In
te
re
st
ed
 
A
ct
o
rs
 
V
al
u
e 
C
re
at
io
n
 
Moore, 
1993 
“…companies coevolve capabilities around a new innovation: 
they work cooperatively and competitively to support new 
products, satisfy customer needs, and eventually incorporate 
the next round of innovations.” (75) 
√ √ √ 
Moore, 
1996 
“…an economic community supported by a foundation of 
interacting organizations and individuals – the organisms of 
the business world. This economic community produces 
goods and services of value to customers, who are themselves 
members of the ecosystem. The member organism also 
include suppliers, lead producers, competitors, and other 
stakeholders. Over time, they coevolve their capabilities and 
roles, and tend to align themselves with the direction set by 
one or more central companies. Those companies holding 
leadership roles may change over time, but the function of 
ecosystem leader is valued by the community because it 
enables members to move toward shared visions to align their 
investments, and to find mutually supportive roles.” (126) 
√ √ √ √ 
Iansiti & 
Levien, 
2004 
“characterized by a large number of loosely interconnected 
participants who depend on each other for their mutual 
effectiveness and survival.” (8) 
√ √ √ √ 
Adner, 2006 
“… are characterized by three fundamental types of risk: 
initiative risks – the familiar uncertainties of managing a 
project; interdependence risks–the uncertainties of 
coordinating with complementary innovators; and integration 
risks–the uncertainties presented by the adoption process 
across the value chain.” 
√ √ 
Teece, 2007 
“…the community of organizations, institutions, and 
individuals that impact the enterprise and the enterprise’s 
customers and supplies.” (1325) 
 √ √ 
Boudreau & 
Hagiu, 2009 
“a collection of (many) firms engaged in joint production, 
whose choices and actions are interdependent” (168) 
√ √ √ 
Pierce, 2009 
“… where technological, product, and strategic changes by 
one enterprise have widespread implications for firm 
performance and survival. Large networks of firms can 
revolve around corporations, both through formal contracting 
and symbiotic relationships.” 
√ √ √ √ 
Paula Chimenti
Marcel Bogers, U. of Copenhagen & U. of California Berkeley, marcel@ifro.ku.dk
Jonathan Sims, Joel West
11080 
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 Components 
Citation Definition In
te
rd
ep
en
–
d
en
ce
 
N
et
w
o
rk
 
S
el
f-
In
te
re
st
ed
 
A
ct
o
rs
 
V
al
u
e 
C
re
at
io
n
 
Clarysse et 
al., 2014 
“… are characterized by a large number of loosely 
interconnected participants dependent on each other for their 
mutual performance. Each participant is specialized in a 
specific activity and it is the collective efforts of many 
participants that constitute value, while efforts individually 
have no value outside the collective effort.” 
√ √ √ √ 
Basole et 
al., 2015 
“The ecosystem perspective, adapted from the biological and 
ecological sciences, is based on the premise that industries 
consist of a heterogeneous and continuously evolving set of 
constituents that co-create value and are co-dependent for 
survival … ecosystems are shaped and driven by a broader 
societal, technological, economic and regulatory context.” 
√ √ √ √ 
Tiwana, 
2015a 
“… are comprised of a fluid mix of firms not bound by 
authority relationships, but an ecosystem-wide vision that is 
not necessarily shared by all developers” 
 √ √ √ 
Acs et al., 
2017 
“…entrepreneurial ecosystems are highly variegated, multi-
actor and multi-scaler phenomenon...” 
√ 
Adner, 2017 
“… the alignment structure of the multilateral set of partners 
that need to interact in order for a focal value proposition to 
materialize.” 
√ √ √ √ 
Brown & 
Mason 2017 
“a set of interconnected entrepreneurial actors, entrepreneurial 
organizations, institutions and entrepreneurial processes 
which formally and informally coalesce to connect, mediate 
and govern the performance within the local entrepreneurial 
environment” 
√ √ √ √ 
Spigel, 2017 
“… the union of localized cultural outlooks, social networks, 
investment capital, universities, and active economic policies 
that create environments supportive of innovation-based 
ventures.” 
√ √ 
Hannah & 
Eisenhardt, 
2018 
“Although ecosystems are not networks, both share a similar 
tension between competition and cooperation …firms in 
ecosystems balance cooperation to create value and 
competition to capture value.” 
√ √ √ √ 
Jacobides et 
al., 2018 
“ecosystems are groups of firms that must deal with either 
unique or supermodular complementarities that are 
nongeneric, requiring the creation of a specific structure of 
relationships and alignment to create value.” 
√ √ √ √ 
Nicotra et 
al., 2018 
“a set of interdependent factors (or, as we call them, eco-
factors) coordinated in a way that enables entrepreneurship.” 
√ √ 
 
Marcel Bogers, U. of Copenhagen & U. of California Berkeley, marcel@ifro.ku.dk
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Table 3: Previous Causal Relationships for Ecosystem Constructs 
 Examples of Variables 
Construct Aspect Independent or Moderator Variable Mediating Variable Dependent Variable 
Member self-interested 
goals 
Sponsor 
Firm 
Aligning heterogenous interests (West & 
Wood, 2013); hybrid strategies (West, 
2003); organization design (Baldwin, 2012); 
commitment mechanisms (Gawer & 
Henderson, 2007) 
Vision of ecosystem fit, architecture, 
and coalition building (Gawer and 
Cusumano, 2014) 
Ecosystem health (Iansiti 
and Levien, 2004); influence 
(West & Wood, 2013) 
Other Firms Creating complementary innovations 
(Moore, 2006) 
Limiting the scope of firm-to-firm 
interactions (Davis, 2016) 
Firm performance 
(Ceccagnoli et al., 2012) 
Nonprofit 
Governance (O’Mahony & Ferraro, 2007); 
in-person interactions (Fleming & 
Waguespack, 2007) 
Building consensus (Simcoe, 2012); 
facilitating continued contributions 
(Sims et al., 2018) 
Community growth (Kilamo 
et al., 2012); alliance 
formation (Rosenkopf et al., 
2001) 
Individuals Motivation (Boudreau & Lakhani, 2009) Individual reputation (Dellarocas, 
2010) 
Entrepreneurial success 
(Mathias et al., 2018) 
Interdependence 
between members 
Cooperative Fair cooperation (Huber et al., 2017) Coordination costs (Tiwana, 2015b) 
Alliances (Rosenkopf et al., 
2001) 
Competitive 
Market turbulence, strategic choices (Pierce, 
2009); number of apps and componenets 
(Lee & Raghu, 2014); app market 
competition (Cennamo & Santalo, 2013) 
Locus of competition (Gawer & 
Phillips, 2013); competitive 
interactions (Davis 2016) 
Platform overlap 
(Eisenmann et al., 2011) 
Coopetition Strategic choices (Hannah & Eisenhardt, 
2018) 
Co-evolutionof cooperation and 
competition (Moore, 1993) 
Platform leadership (Perrons 
2009) 
Network of member 
relationships 
Structure 
Challenges in components and complements 
(Adner & Kapoor, 2010); density overlap 
and embeddedness (Venkatraman & Lee, 
2004); number of complementors (Boudreau 
& Jeppesen, 2015); network effects 
(Eisenmann et al., 2011) 
Evolution of ecosystem extension 
(Tiwana, 2015a) 
Sustainability, scale and 
scope of ecosystem (Jha et 
al., 2016) 
Governance 
Platform governance (Tiwana et al., 2010); 
business models support (Gawer & 
Cusumano, 2014); allocation of IP rights 
(West & O’Mahony, 2008; Ceccagnoli et 
al., 2012); phase of ecosystem growth 
(Colombelli et al., 2017) 
Joint governance (Davis, 2016) 
Control and autonomy 
(among various 
mechanisms) (Wareham et 
al., 2014); nature of 
production and leadership 
(O’Mahony & Ferraro, 
2007) 
 
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	11080_Cover.rtf
	11080.pdfof which 88.9% were 
published in the last decade. 
 To develop a systematic sample of this burgeoning field, we searched for phrases in SSCI 
using the topic field, limiting our search to the 50 journals used for the Financial Times business 
school rankings (Ormans, 2016). These rankings reflect an international perspective on business 
scholarship (Pfeffer & Fong, 2004) and thus the FT50 list provides a measure of internationally 
recognized high-quality journals (Burgess & Shaw, 2010). To these 50 journals, we added 10 
other journals that publish highly cited innovation articles (California Management Review, 
IEEE Transactions on Engineering Management, Industrial and Corporate Change, 
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International Journal of Technology Management, Journal of Product Innovation Management, 
Long Range Planning, R&D Management, Research-Technology Management, Technological 
Forecasting and Social Change, and Technovation). 
 Searching SSCI for the ecosystem topic in these 60 journals, we identified 329 papers 
published from 1992 to 2018. Of these, 65.7% (216) were published in the last five years of this 
period (Figure 1). 
 
 After reviewing the abstracts (and when necessary the papers), we removed 27 articles that 
were not related to business ecosystems, typically on environmental or natural ecosystems. With 
these papers removed, we dropped the 19 journals (all from the FT list) without any ecosystem 
articles, including all but one of the accounting, finance and operations journals on the FT list. 
This left us with 302 articles from 41 journals, as summarized in Table 1. 
 
 We found that this systematic sample overemphasized certain industry contexts (particularly 
ICT) and underemphasized key ecosystem dynamics. Consistent with other studies (e.g., 
Biemans et al., 2015; Lee & Coughlin, 2015), we then used supplemental approaches to refine 
the sample. First, we identified potential papers using a combination of forward and backward 
citations from existing papers, adding articles that make key empirical (West & Wood, 2013; 
O’Mahony & Karp, 2017) or conceptual points (Moore, 1996; Baldwin, 2012; Adner et al., 
2013). We also added key articles that fit Adner’s (2017) four related perspectives on 
interdependence (i.e., platforms, value networks, multi-sided markets and business models) that 
appeared to most closely overlap the definition of an ecosystem. 
 Using these articles, we then examined them to identify prior definitions of “ecosystem”. 
Using NVivo qualitative analysis software, we searched the text of the articles for any explicit or 
implicit mention of a definition of ecosystem. Table 2 includes examples of the definitions we 
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identified in our analysis. 
 
Developing an Integrative Definition of “Ecosystem” 
With these definitions, we further reviewed the conception of ecosystems as presented by 
these articles. From this, we sought to capture these prior conceptions with a succinct definition 
that would encompass this body of work. This led to the nine-word definition of an ecosystem as 
an interdependent network of self-interested actors jointly creating value. The definition includes 
four components, linking three operational constructs — interdependence, network and self-
interested actors — to the most commonly described success criterion for an ecosystem: to 
jointly create value in a way that no single actor would be able to do (Adner, 2006). 
Overall, we believe this provides a succinct but encompassing definition that is not tied to a 
particular empirical context. As such, it parallels Eisenhardt and Graebner’s (2007: 30) 
observation that “parsimony, robustness, and generalizability characterize superior theory” 
while, consistent with the modular nature of scientific progress (Langlois & Garzarelli, 2008), 
this modular definition will allow more cumulative knowledge building among ecosystem 
scholars. 
 As shown in Table 2, many of the early definitions ignore one or more of these four 
components of the ecosystem concept. More recently, several definitions overlap all four 
components while using different language (Adner, 2017; Brown & Mason, 2017; Hannah & 
Eisenhardt, 2018; Jacobides et al., 2018). However, by focusing solely on firms, most of these 
definitions ignore the central role often played by not-for-profit actors such as universities (Kim 
et al., 2012) or nonprofit foundations (O’Mahony, 2003), as well as the potential role of 
individuals (Aaltonen & Seiler, 2015). 
 Our goals differ from those of two recent ecosystem reviews that focused on specific subsets 
of the ecosystem literature. While thorough, Adner’s (2017) review emphasized rather than 
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incorporated differences across the ecosystem literature. First, it argued that other concepts such 
as value networks and platforms are outside the scope of ecosystems. Second, it proposed that 
the “ecosystem as structure” prospective is more useful than the “ecosystem as affiliation” used 
in the vast majority of previous ecosystem studies. Unlike Adner (2017), we believe it is possible 
(and desirable) to consider both membership and structure in the same study. 
 More recently, Jacobides et al. (2018) emphasized a platform perspective on researching 
ecosystems. In their view, ecosystems are enabled by the interfaces that make possible modular 
technical architectures and a division of labor (Baldwin & Clark, 2000). In their definition, only 
networks with strong complementarities can be considered ecosystems. 
 In contrast, we believe it is more useful to adopt an over-arching perspective on ecosystems 
that incorporates (rather than separates) these divergent streams. While the approaches of Adner 
(2017) and Jacobides et al. (2018) can provide sharper insights for a subset of ecosystem 
research, we believe the more inclusive and modular approach — informed by a systematic 
review and thus grounded in a more complete view of past ecosystem research — will allow 
researchers to incorporate insights from a wider range of prior research. This research includes 
not only the 302 ecosystem papers in the formal sample and supplemental papers described 
above, but also several streams of closely related research. Together, these bodies of research 
provide complementary insights. 
Considering Related Streams of Ecosystem Research 
 In the decades since Moore (1993), hundreds of articles have referenced this original 
definition, but others have researched ecosystems under using other names and contexts. Here 
we discuss four related streams that overlap the proposed definition: value networks, platforms, 
two-sided (or multi-sided) markets, and entrepreneurial ecosystems; the first three were also 
identified as related constructs by Adner (2017). The first two built on Teece’s (1986) 
conception of complementary assets, as represented by third party software (Saloner, 1990). 
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 Value Networks. This stream began when Rosenbloom (Rosenbloom & Christensen, 1994; 
Christensen & Rosenbloom, 1995; Chesbrough & Rosenbloom, 2002) extended the linear 
definition of Porter’s (1985) “value chain” concept by adding lateral and complementary value-
creating relationships. It was initially defined as “a system of producers and markets serving the 
ultimate usersof the products or services to which a given innovation contributes” (Rosenbloom 
& Christensen, 1994: 657). Similar ideas have been expressed in research on a “value 
constellation” (Normann & Ramirez, 1993; Vanhaverbeke & Cloodt, 2006), a “value net” 
(Brandenburger & Nalebuff, 1996), a “value web” (Jaworski et al., 2000; Chesbrough, 2011) or a 
“development web” (Staudenmayer et al., 2005). All focus on those cases when value cannot be 
created by a single firm, but instead depends on a network of actors to create value; such 
research tends to ignore the interdependence of the multiple actors (beyond the need for the 
network sponsor to attract members to the network). This networked value creation is also 
incorporated in those conceptions of a business model that explicitly reference value networks 
(e.g., Chesbrough & Rosenbloom, 2002; Zott et al., 2011). 
 Platforms. The second related stream is the information and communications technology 
(ICT) platform. Extending earlier research on compatibility standards and complementary assets, 
Bresnahan & Greenstein (1999) computing platforms in terms of technical interfaces that enable 
the independent development of components; in this model, the value proposition of a new 
platform competes with that of existing platform(s) in an attempt to gain market adoption, 
moderated by the buyer’s cost of switching between platforms.1 Subsequent research emphasized 
the importance of interfaces in modularity (Baldwin & Clark, 2000), the control of interfaces 
(West & Dedrick, 2000) and the role these interfaces play in structuring the relationships 
 
1 As the use of “platform” proliferated to unrelated contexts, later research referred to these ICT-style 
platforms as an “industry platform” (Gawer, 2009, 2014; Gawer & Cusumano, 2014) or “platform 
ecosystem” (Autio et al., 2014). 
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between platform members (Baldwin & Woodard, 2009). Over time, such platforms were 
defined in terms of an architecture of technical interfaces (Baldwin & Clark, 2000), an ecosystem 
of complementary product suppliers (Gawer & Henderson, 2007) and the role of one or more 
firms leading both the technical and ecosystem design (Gawer & Cusumano, 2002; Eisenmann et 
al., 2009). In the view of Jacobides and his colleagues (2018: 2266), these interfaces are what 
create a need for coordination (and thus interdependence), distinguishing ecosystems from other 
networks that lack such interdependence. 
 Two other streams include research that, in some cases, correspond to the proposed 
ecosystem definition. One is research on Two-sided Markets (Rochet & Tirole, 2003), also called 
“two-sided networks” (Parker & van Alstyne, 2000) and “multi-sided markets” (Evans, 2003). 
Most platforms function as two-sided markets, in that platform suppliers both seek to win 
adoption by both end users and suppliers of the complementary products (Eisenmann, Parker & 
van Alstyne, 2006, 2009); some cases correspond to multi-sided markets when there are multiple 
classes of complementary assets (West & Wood, 2013). Beyond platforms, many two-sided 
markets do not create value other than by matching buyers and sellers (Evans, 2003). Also, many 
two-sided markets are transactional and not relational and thus are not structured to allow for (let 
alone enable) interdependence, but such interdependence can be found in online communities 
(Boudreau & Lakhani, 2009; West & Sims, 2018). 
 Entrepreneurial Ecosystems. A final major stream — often neglected in other ecosystem 
reviews — has been the use of the ecosystem metaphor to describe a regional entrepreneurial 
ecosystem, which accounts for dozens of articles on the ecosystem topic during this period.2 
Typically these studies examine a high-technology cluster (Bahrami & Evans, 1995; Finegold, 
 
2 Seven of these articles were in the sample from the top 60 journals. We also identified supplemental 
articles in regional studies and entrepreneurship journals, including seven articles in a special issue of 
Small Business Economics (Acs et al., 2017). 
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1999; Pitelis, 2012) or the linkage between universities and local companies (Cohen, 2006; Stam, 
2015; Hayter, 2016). Such local clusters have a network of firms, connected to nonprofit 
organizations, and other shared infrastructure such as university training, investors and 
professional services. In many cases, the actor interdependence is between firms that both utilize 
and provide demand for a shared infrastructure that helps create a fertile location to launch 
businesses (Finegold, 1999). However, many clusters do not jointly create value for a particular 
class of customer. Joint value creation can be found in an industry-specific cluster, where firms 
are interdependent through complementarities of supply, marketing and reduced coordination 
costs (Porter, 2000); only rarely have these clusters been discussed using ecosystem concepts 
(Ahn & Meeks, 2008). 
MEASURING ECOSYSTEM SUCCESS 
 With joint value creation as one of the four components of the proposed ecosystem 
definition, central to this definition is success at the ecosystem level. Previous research has noted 
that the raison d’être for an ecosystem is “to create value that no single firm could have created 
alone” (Adner, 2006: 100). However, while conceptually important, such value creation is 
difficult to measure in practice: at best, qualitative ecosystem studies have offered observations 
or predictions of value creation without measurement (van der Borgh et al., 2012; Pagani, 2013). 
Outside of ecosystems, other research suggests approaches to measure value creation of 
ecosystem activities, including customer satisfaction (Raja et al., 2013) and experiments (Franke 
& Piller, 2004). 
 Perhaps most commonly, market share has been used as a proxy measure for value creation, 
in both qualitative (West & Mace, 2010) and quantitative studies (Adner & Kapoor, 2010). 
Rather than market share, when there is only one technology and ecosystem, the equivalent 
measure is market penetration (Sandström, 2016). While this often the only measure available, it 
often makes it difficult to distinguish between the ecosystem’s value creation and the market 
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power (such as marketing expenditures) used to promote adoption. Similarly, while survival is a 
measure of ecosystem success or failure (e.g., West & Wood, 2013), it both has similar 
confounds and offers less granularity of measurement. Along these lines, some research has 
focused on measures of ecosystem health — such as the number of firms or employees in the 
ecosystem — rather than any measure of the results of the ecosystem activities (e.g., Finegold, 
1999; Auerswald & Dani, 2017).3 
 Other measures of success for an ecosystem may be defined in terms of the success of the 
actors that are members of the ecosystem — which are discussed below. 
RESEARCH ON THREE KEY CONSTRUCTS 
Of the four components of the proposed ecosystem definition, three are operational constructs 
that jointly determine ecosystem success: the goals of the ecosystem members, their 
interdependence and the attributes of the network. Here we synthesize prior research to provide a 
conceptualization and existing operationalizations for each construct (and various aspects of each 
construct) and discuss how these constructs (and aspects) have been used in causal research — 
both qualitative and quantitative — as either an independent or moderatingvariable (predictor), a 
mediating variable, or dependent variable (outcome). These are summarized in Table 3. 
 
Goals of Ecosystem Members 
The success of an ecosystem depends on the actions of self-interested actors that join the 
network; thus, getting members to joint an ecosystem requires understanding the motivations of 
these potential members, specifically how participation relates to achieving their particular goals. 
 
3 The number of participants is a measure of value creation for advertising-supported two-sided 
markets (Evans, 2003; Rysman, 2009). However, the interdependence in these contexts tends to be 
weak, raising the question as to whether these should be considered ecosystems (Jacobides et al., 
2018). 
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While the members of an ecosystem will generally be working to advance the success of the 
overall ecosystem, usually their self-interest is a higher priority. Below we discuss four types of 
self-interested actors explored by previous studies: sponsoring firms, member firms, nonprofit 
organizations and individuals. 
 Firms Sponsoring the Ecosystem. The most researched category examines firms that sponsor 
the ecosystem. Here we use “sponsor” to refer to the organization(s) that through some 
combination of resources, leadership and control are in the unique position to both support and 
benefit from ecosystem success. The term is commonly used for ICT-related ecosystems, 
whether for product compatibility standards (Antonelli, 1994; Besen & Farrell, 1994), open 
source software communities (Shah, 2006; Spaeth et al., 2015; O’Mahony & Karp, 2017) or IT 
platforms (Rochet & Tirole, 2003; West, 2003; Eisenman et al., 2009; West & Wood, 2013; 
Parker et al., 2017).4 
 The success of sponsors leveraging an ecosystem depends upon their approach, from 
external-facing activities such as aligning the interests of different players (West & Wood, 2013) 
and building coalitions (Gawer & Cusumano, 2014), to internal actions such as managing their 
own commitment to the ecosystem (Gawer & Henderson, 2007), and building an organizational 
design that supports engagement (Baldwin, 2012; West, 2003). Secondly, success for sponsor 
firms relies upon managers understanding the unique characteristics of the ecosystem itself (Zhu 
& Iansiti, 2012). 
 Such a focus on the benefits of ecosystem success accruing to the sponsor is a constant theme 
from the very earliest of managerially-oriented research on ecosystems (Moore, 1993, 1996; 
 
4 With our desire to integrate prior research, we intend for the term to encompass a wide range of 
approaches that differ between industries or among ecosystems within a given industry. Other 
researchers have selected terms to designate a specific form of sponsorship, such as a “leader” 
(Moore, 1993; Gawer & Cusumano, 2002), “owner” (Gawer & Henderson, 2007) or “hub” (Jacobides 
et al., 2018). Based on the degree of control of an ecosystem, Iansiti and Levien (2004) distinguish 
between “keystone”, “dominator” or “niche” sponsors. 
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Gawer & Cusumano, 2002; Iansiti & Levien, 2004; Adner, 2006). However, while the market 
share of the sponsor is often equivalent to that of the ecosystem, we are unaware of more than 
anecdotal evidence of the financial benefits accruing from ecosystem sponsorship (e.g., Jones, 
2017). 
 Other Member Firms. While the success of a sponsor firm may depend upon the success of 
other member firms, these are separate constructs, measured separately and not perfectly 
correlated. On the one hand, merely participating in an ecosystem has been positively linked to 
firm performance (Ceccagnoli et al., 2012). In these settings, firms facilitate the success of their 
peers by creating complementary innovations (Moore, 2006), while paying attention to the scope 
of their interactions with other ecosystem participants (Adner, 2006; Davis, 2016). 
 On the other hand, despite early discussions of the interdependence of ecosystem members 
(e.g., Iansiti & Levien, 2004), evidence suggests that ecosystem leaders tend to focus on their 
own success rather than carefully monitoring the success of other ecosystem members (West & 
Wood, 2013); only rarely has research on ecosystems examined the success of these other 
members (e.g., Pierce, 2009). At the same time, all members of the ecosystem are dependent on 
each other — possibly through multilateral dependencies (Jacobides et al., 2018) — where the 
focal firm in the ecosystem needs to adjust its strategy based on the performance of other firms 
in the ecosystem (Ansari et al., 2016; Kapoor & Lee, 2016). 
 To explain the dynamics between ecosystem members, Davis (2016) focused on the multi-
partner nature of the ecosystem, which includes dyads or larger groups that include other firms as 
third-party contributors. Others have shown that not only the sponsor but also other firms (or 
entrepreneurs) change their roles across phases of ecosystem development (Moore, 1993; Jha et 
al., 2016). Still other research highlights the specific characteristics of member firms, such as 
capabilities embedded in the supplier network (Hong & Snell, 2013), the contributions of third-
party complementors (Ceccagnoli et al., 2012), or the participation of complementors as partners 
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in co-creating value (Huber et al., 2017). 
 Nonprofit Organizations. While the actions of firms and individuals are frequently associated 
with leveraging an ecosystem to advance their self-interests, non-profit organizations often 
depend upon an ecosystem for their survival. Examples include standard-setting bodies, 
universities, and non-profits affiliated with open-source software communities. 
 Standard setting bodies exist to support their members by advancing common technological 
processes (Brunsson et al., 2012; Fleming and Waguespack, 2007; Rosenkopf et al., 2001). Their 
survival and growth are dependent upon understanding and managing multiple ecosystem 
members with different priorities. This requires building consensus among members who are 
themselves competing with each other (Simcoe, 2012), in addition to harnessing both market 
forces and government regulations (Wiegmann, et al., 2017). 
 Non-profit organizations supporting open source communities would not exist if not for the 
ecosystem of contributors and users (both firms and individuals) that make software 
development and distribution possible. Success in these settings is typically measured by the 
growth of the community (Kilamo et al., 2012). Self-interests critical for this success include 
maintaining the long-term motivations of contributors (Shah, 2006; Von Krogh et al., 2012) and 
nurturing a steady flow of contributions (Sims et al., 2018). As the non-profit grows, success 
relies on the coordination afforded by democratic governance structures (O’Mahony and Ferraro, 
2007). 
 Finally, universities play an increasingly relevant role in business ecosystems through 
technology-transfer initiatives. While the longevity of a host university makes their survival 
more likely, growth of such initiatives is a function of an ability to facilitate the involvement of 
faculty and shorten time to commercialization (Markman et al., 2005). 
 Across these examples, non-profits must not only understand needs of disparate ecosystem 
members, but also the different norms under which they operate. Standard-setting bodies 
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triangulate the interests of member firms, government policy and market forces (Wiegmann et 
al., 2017), while non-profits affiliated with open source software and universities act as 
connectors or promotors for their constituents (O’Mahony & Karp, 2017). 
 Individuals. Individuals influence an ecosystem in two ways. First, the sponsor and member 
organizations are represented by individuals driven by their own self-interests (Slesky and 
Parker, 2005), and technology is increasing the relevance and influence of individual players 
(Hanna et al., 2011). In these settings, intrinsic motivations and cooperative relationships 
between individuals are essential to individual participation in the ecosystem (Boudreau and 
Lakhani, 2009; Spaeth et al., 2015; Mathias et al., 2018). At the same time, to advance their self-
interests, individuals need to pay particular attention to creating a positive reputation (Dellarocas, 
2010). 
 Second, in some ecosystems, some or all of the value is created by individuals who are not 
employees or otherwise part of an incorporated organization. One category of such ecosystems is 
that which depends on user-generated content, such as modern social media platforms 
(Kallinikos et al., 2013). Another is the use of crowdsourcing, which utilizes geographically 
dispersed individuals to solve a problem for a corporate sponsor (Boudreau & Jeppesen, 2015; 
West & Sims, 2018). While many crowdsourcing approaches focus on solving a specific task 
(and thus do not have a definable overall mission of ecosystem value creation), some are 
organized to solve a specific larger problem; an example is when government agencies or 
academic researchers aggregate individual contributions using a process of “crowd science” 
(Franzoni & Sauermann, 2014). Finally, in the app economy, individuals play an increasingly 
important role in value creation, as with the nascent entrepreneurs who contribute to a 
smartphone app store and thus the value created by the corresponding ecosystem (Qiu et al., 
2017). 
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Interdependence Between Members 
The value creation for an ecosystem depends on the contributions of the actors. On the one hand, 
all ecosystem members have a stake in its success.5 On the other hand, the nature of the 
relationship between the actors — particularly whether their respective goals are competing or 
complementary — will influence how (or how well) they will work together to achieve that 
success. Here we consider three modes of interdependence. 
 Cooperative Interdependence. In some ecosystems, the main interaction is cooperative, 
particularly when their value creation efforts are more complementary (Jacobides et al., 2018). In 
many cases, the key actors in the ecosystem have complementary pre-existing business 
relationships that allow win-win outcomes, such as between customer and supplier (Moore, 
1993) or platform sponsor and complementor (Gawer, 2014). While unused in ecosystem 
studies, research on competitive strategy has come up with measures of firm complementarity 
(e.g., Wang & Zajac, 2007; Lin et al., 2009). 
 Alternately, such a cooperative approach may be easier for firms that — at least when it 
comes to revenues — are largely unrelated. The most commonly researched such example is the 
entrepreneurial ecosystem, where firms are competing for attention (with employees and 
investors) but not revenues. Such an assumption may be unrealistic in more populous regional 
ecosystems (notably Silicon Valley) or industry-specific regional ecosystems (Bahrami & Evans, 
1995). However, in smaller ecosystems — particularly those defined by ties to a research 
university as the anchor tenant — concerns for ecosystem health often dwarf those of possible 
secondary competition (Pitelis, 2012). 
 Competitive Interdependence. The original definition of business ecosystems emphasized 
 
5 Here we ignore the case where members of an ecosystem might gain more benefit from its failure 
than its success. An example would be Google (sponsor of the Android mobile phone ecosystem) 
providing its mapping app to Apple’s iPhone ecosystem, which Apple originally viewed as a 
complement but later as a competitor (Gawer, 2014). 
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competition between ecosystems (Moore, 1993): the sponsor of an ecosystem is more successful 
as the ecosystem members provide more products and services. However, as the metaphor 
suggests, the entry of new firms into an ecosystem may reduce the resources available to existing 
firms. Early work in organizational ecology examined such effects of crowding and carrying 
capacity upon firm survival, either with (Utterback & Suarez, 1993) or without firm learning 
(Carroll, 1985). 
 In addition to competition between firms as a whole, competition may also be between firm 
participation in a specific ecosystem. For example, while a video console sponsor may hope (or 
pay) for even a temporary exclusive on a popular game titles, the leading independent members 
of each console’s ecosystem will multi-home, i.e., offer their titles across all the major platforms 
(Eisenmann et al., 2006; Landsman & Stremersch, 2011). 
 Finally, the competitive interdependence of firms affects their success in niches within the 
ecosystem. Recent work on third party software ecosystems (i.e., app stores) has shown that, all 
things equal, more competitors meant apps were less successful (Lee & Raghu, 2014). 
Exploratory work suggests that some forms of network governance (i.e., tighter control by the 
sponsor) will deter competing firms from joining an ecosystem (West, 2003; West & O’Mahony, 
2008). 
 Coopetitive Interdependence. By their nature, many ecosystems require close cooperation to 
jointly create value; at the same time, in some industries that value creation depends on the 
participation of direct competitors. Thus, ecosystem management requires both cooperation and 
competition between ecosystem participants (Kapoor & Lee, 2013). 
 In such cases, different facets of this coopetition will be more salient. For example, in their 
study of cooperative computer peripheral interfaces, Ranganathan and his colleagues (2018) 
found that direct competitors exhibit more urgency for cooperation in highly competitive markets 
where they seek to create value — but less urgency where they already have complementary 
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Paula Chimenti
Marcel Bogers, U. of Copenhagen & U. of California Berkeley, marcel@ifro.ku.dk
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resource endowments that might be threatened by new standards. 
Network Structure and Governance 
An ecosystem connects the interdependent actors through a network, which essentially describes 
the collective arrangement between the interconnected members (Iansiti & Levien, 2004; Adner, 
2017; McIntyre & Srinivasan, 2017; Jacobides et al., 2018). Most research addresses either the 
structure or governance of the network, while some research addresses the relationships or 
differences between these two aspects of an ecosystem network (Tiwana et al., 2010). 
 Structure of Network Relationships. At its most basic level, a network is defined by the 
structure of the relationships between the ecosystem members (Adner, 2017). In some research, 
the structure is implied, with the most common pattern being third parties selling to customers 
(Boudreau, 2010). In other cases, it is explicit (Markus et al., 2006; Adner & Kapoor, 2016) or 
one of the independent or dependent variables of the study (Adner & Kapoor, 2010; Weiss & 
Gangadharan, 2010;Jha et al., 2016). Network structure has been operationalized by focusing on 
issues such as its architecture (Tiwana et al., 2010), social network characteristics (Venkatraman 
& Lee, 2004), and number and types of actors (Jha et al., 2016). 
 Research on the structure aspect of the ecosystem focuses on several attributes, such as 
modularity and complementarities (Autio et al., 2014; Jacobides et al., 2018), density overlap 
and embeddedness (Venkatraman & Lee, 2004), network effects and switching costs (Boudreau 
& Jeppesen, 2015; Eisenmann et al., 2011), or cultural, social and material attributes more 
generally (Spigel, 2017). Other research focuses on what may affect the attributes of the 
network, such as the underlying technical architecture (Adner, 2006; Autio et al., 2014; Tiwana 
et al., 2010). Yet other research focuses on the outcome of the network, such as value that is 
created through the network (Adner & Kapoor, 2010; Ceccagnoli et al., 2012). At the same time, 
some research focuses on more dynamic aspects of the ecosystem network, such as ecosystem 
creation (Dattée et al., 2018), joining and leaving (Tiwana 2015b), convergence and generativity 
Paula Chimenti
Paula Chimenti
Marcel Bogers, U. of Copenhagen & U. of California Berkeley, marcel@ifro.ku.dk
Jonathan Sims, Joel West
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(Yoo et al., 2012), and member quantity and quality (Jha et al., 2016). 
 Governance of Network Relationships. At its core, the governance of the network is what 
positions an ecosystem in the broader spectrum from control to coordination, in between a 
hierarchical organization and a market (Powell, 1990; Demil & Lecocq, 2006; Felin & Zenger, 
2011; Gawer, 2014). The interdependent nature of the relationships across ecosystem members 
also requires some form and degree of governance, whether decentralized or centralized. The 
former can be implemented using customary market and contractual approaches, although most 
ecosystem research does not explicitly study these governance modes per se. The latter — a 
more formal and centralized form of coordination — is usually what is meant when studies 
explicitly mention “governance.” 
 While ecosystem governance is typically contrasted with hierarchically managed 
organizations, the detailed attributes of membership or participation rules are poorly understood 
(Jacobides et al., 2018). When focusing on the explicit governance of the relationships within the 
network, some research examines the effect of the governance choices upon the ecosystem (West 
& O’Mahony, 2008; Tiwana et al., 2010; Jansen & Cusumano, 2013). In other cases, research 
identifies it as a given but does not consider its effects (Spaeth et al., 2015), or the governance is 
unmentioned, as when it is unrelated to the research questions (Ceccagnoli et al., 2012). 
 Potential antecedents of governance choices include the nature of production and leadership 
(O’Mahony & Ferraro, 2007) while outcomes include supporting the business models of member 
companies (Gawer & Cusumano, 2014) and the allocation of IP rights (West & O’Mahony, 
2008; Ceccagnoli et al., 2012). Only limited research has examined the moderators of ecosystem 
governance; one such moderator is the phase of ecosystem growth (Colombelli et al., 2017). 
Moreover, ecosystem governance has been described as the way in which a network can manage 
the tensions between various attributes of the involved actors (Wareham et al., 2014; West & 
Gallagher, 2006). At the same time, managing these tensions will be difficult for new companies 
Marcel Bogers, U. of Copenhagen & U. of California Berkeley, marcel@ifro.ku.dk
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that depend on the participation of much larger companies for ecosystem success (West, 2014). 
Some research addresses how a network can partially mitigate these tensions, for example by 
breaking up the architecture of the ecosystem and creating dyads or triads of collaborations 
(Davis, 2016) or by enacting dynamic control (Dattée et al., 2018). 
 Governance choices have been operationalized in terms of support for viewpoint diversity 
(O’Mahony, 2007), participation and decision rights (West & O’Mahony, 2008), collaboration 
rules and participation contracts (Boudreau & Hagiu, 2009), cross-ownership ties (West & 
Wood, 2013) and certification (Wareham et al., 2014). Much of the early research focuses on the 
benefits of the ecosystem to its sponsor; as such, this research emphasizes how the sponsor 
controls the ecosystem to maximize these benefits (Moore, 1993; Gawer & Cusumano, 2002; 
Iansiti & Levien, 2004; Adner, 2006, 2012). In other cases, the implicit governance does not 
have strong sponsor control, but instead has limited coordination functions performed by the 
sponsor(s), such as in regional or entrepreneurial ecosystems that may include formal or informal 
institutions (Autio et al., 2014; Feldman & Lowe, 2015; Spigel, 2017). 
 On the one hand, the nature of control remains important, whether central control by the 
ecosystem sponsor (Iansiti & Levien, 2004), or governance distributed more broadly across the 
network (von Hippel, 2007; Wareham et al., 2014). On the other hand, ecosystem governance 
may include a number or combination of mechanisms that allow for a balance of control and 
coordination, for example through self-regulation, social governance, contracts, standards and 
markets (e.g., Nambisan & Baron, 2013; Davis, 2016; Vakili, 2016; Parker et al., 2017) — 
implying more or less openness across the ecosystem (cf. West, 2003; Holgersson et al., 2018; 
Jacobides et al., 2018). 
RESEARCH AGENDA: UNDERSTANDING AND LINKING KEY CONSTRUCTS 
The cumulative process of scientific research requires a consistent definition of concepts and 
constructs, something largely missing from prior ecosystem research. Both are provided by the 
Marcel Bogers, U. of Copenhagen & U. of California Berkeley, marcel@ifro.ku.dk
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proposed definition of an ecosystem as an interdependent network of self-interested actors jointly 
creating value. In contrast to other recent ecosystem reviews (Adner, 2017; Jacobides et al, 
2018), we believe that this more inclusive definition — informed by a systematic review of the 
past 25 years of ecosystem research — will allow incorporating a broader range of past and 
future research. At the same time, the modular definition of an ecosystem in terms of four 
identified components — three constructs and a success measure — offers a concrete way to 
incorporate research findings both from within and without ecosystem studies. Together, this 
approach suggests a foundation for future research to broaden and deepen our understanding of 
ecosystems. 
 Here we highlight three facets of a proposed research agenda: understanding these constructs, 
examining the relationships between these constructs, and studying ecosystems that are 
comprised of such constructs. By proposing this research agenda, we call for a more systemic 
and integrative perspective on studying ecosystem in order to both increase the validity of this 
research and better understand the boundary conditions of what is (and what is not) an 
ecosystem. 
Studying the Core Ecosystem Constructs 
The above definitions of the three ecosystem constructs — the goals of ecosystem members with 
a focus on their self-interest, the network of relations between these members, and the 
interdependence of these members and their goals — clarify how they have been used in 
previous research, facilitate integration between empirical contexts and suggest opportunities for 
future measurement and causal predictions. 
 The first step for future ecosystem studies is to explicitly articulate their study’s definition of 
an ecosystem, whether or not they study all attributes of the definition or just a part of it, and 
whether they merely use the existingdefinition or rather expand it. By doing so, they can also 
indicate what part of the definition they are studying (e.g., variance or causal relationships) and 
Marcel Bogers, U. of Copenhagen & U. of California Berkeley, marcel@ifro.ku.dk
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what part they are holding constant. In our modular definition, this would correspond to the 
constructs (and aspects) presented earlier in Table 3, and a direct or indirect measure of 
ecosystem success. 
 Table 3 also summarizes how each construct and aspect has been used as an independent, 
moderating, mediating or dependent variable in ecosystem research. Such a synthesis of 
antecedents, consequences and moderators allows us to assess prior theory (Damanpour, 1991), 
and agreeing upon constructs and their measures is important for theory development and 
synthesis (Langley, 1999; Ahuja et al., 2008). To increase internal validity, future research 
should thus seek to identify valid measures, relationships and mechanisms for each of the 
constructs and variables — while drawing on both core ecosystem research and related streams 
of ecosystem research described earlier. Such a synthesis also suggests opportunities for future 
research for each of these constructs. 
 Member self-interested goals. Previous research suggests a linkage between actor-level 
capabilities interacting to create an ecosystem-level advantage (Hannah & Eisenhardt, 2018). But 
beyond contributing to the ecosystem’s joint value creation, each member will also need to find 
mechanisms to capture part of that value (Ritala et al., 2013; Radziwon et al., 2017; Chesbrough 
et al., 2018). Meanwhile, research on two-sided markets suggests how ecosystems might harness 
(or align) the competing interests of multiple categories of members (Eisenmann et al, 2006). 
 Interdependence between members. Complementarity of interests is what distinguishes 
ecosystems from other forms of governance (Jacobides et al., 2018), and greater 
complementarities make it easier to align interests (Kapoor & Lee, 2013). However, future 
research needs to operationalize and measure complementarity — both pairwise and for the 
overall network — and then relate that (perhaps moderated by governance or network size) to 
ecosystem performance. 
 Network of member relationships. The structure and the governance of a network are closely 
Paula Chimenti
Marcel Bogers, U. of Copenhagen & U. of California Berkeley, marcel@ifro.ku.dk
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related, but such relationships have been presented at an anecdotal or conceptual level (Iansiti & 
Levien, 2004; Gawer & Henderson, 2007; West & O’Mahony, 2008; Adner, 2017); more 
research is needed to establish the systematic relationship between these two aspects of the 
network construct. Meanwhile, when it comes to ecosystem success, the assumption is that a 
larger or denser network creates more value (e.g., Auerswald & Dani, 2017); however, are there 
moderators of such value creation? 
 Finally, due to lack of data the success of an ecosystem has often been operationalized by 
market share (or even size) rather than value creation. The total revenues from ecosystem sales 
can used to represent the total value created, but such data is not always available. Linden et al. 
(2009) demonstrate how value creation in a value network can be estimated using publicly 
available data, and similar creativity is needed to better measure value creation. 
Examining Linkages Between Constructs 
 In addition to relating to ecosystem success, these three constructs (and their respective 
measures) act and interact as part of the design and operation of an ecosystem. However, we 
know very little about the more detailed underlying causal mechanisms that connect these 
constructs and variables (cf. Sutton & Staw, 1995). The linkages shown in Figure 2 summarize 
the possible relationships between these constructs. Here we highlight research opportunities for 
each of the corresponding linkages. 
 
Between Member Goals and Interdependence. Based on this framework, future research can 
better explain how the efforts of self-interested actors interact with the type of interdependence 
to create a successful ecosystem outcome (Boudreau, 2010; Clarysse et al., 2014). Given the 
interdependence between the members, their goals need to be coordinated to create alignment 
across the ecosystem while some level of control will also be needed to make this process more 
efficient and effective (Moore, 1996; Iansiti & Levien, 2004; Adner, 2006; Boudreau, 2010; 
Marcel Bogers, U. of Copenhagen & U. of California Berkeley, marcel@ifro.ku.dk
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Gawer & Cusumano, 2014). At the same time, future research should further explore how value 
creation and capture is determined by multilateral interdependencies across ecosystem members 
(Chesbrough et al., 2018; Jacobides et al., 2018). 
 Between Interdependence and Network. While some research (e.g., West & O’Mahony, 
2008) has suggested that governance choices affect the nature of interdependence — specifically 
the willingness of competitors to join — is there a converse relationship from interdependence to 
governance? For that matter, does the nature of interdependence predict which actors will join, or 
the size or the structure of the network? Finally, one would expect that the complementarity 
within the network itself will determine the type and degree of interdependence that is required 
(Teece, 1986; Adner & Kapoor, 2010; van der Borgh et al., 2012) but more research is needed 
here. 
Between Network and Member Goals. In principle, governance is used to make sure that 
both collective and individual goals are met (Wareham et al., 2014; West & O’Mahony, 2008). 
However, research has yet to contrast different governance forms or quantify these effects. Here, 
linking to related research streams can be of particular value as those streams have already 
examined some of the linkages identified here — for example by embedding a modular 
perspective on ecosystem governance (Baldwin & Clark, 2000; Jacobides et al., 2018) or by 
emphasizing transactional attributes of a two-sided market (Boudreau & Lakhani, 2009; West & 
Sims, 2018). 
Ecosystems as the Unit of Analysis 
A key objective of this critique is to argue for more comparability and external validity that has 
been lacking in much of the ecosystem literature. One reason for a lack of progress and 
integration is that much research on ecosystem has been framed in connection to a particular 
phenomenon, empirical context or ecosystem type, such as innovation ecosystems (Adner, 2006; 
Nambisan & Baron, 2013; Chesbrough et al., 2014), platform ecosystems (Boudreau, 2010; 
Marcel Bogers, U. of Copenhagen & U. of California Berkeley, marcel@ifro.ku.dk
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Ceccagnoli et al., 2012; Gawer & Cusumano, 2014), business ecosystems (Iansiti & Levien, 
2004; Clarysse et al., 2014), entrepreneurial ecosystems (Brown & Mason, 2017; Colombelli et 
al., 2017; Nicotra et al., 2018), and regional ecosystems (Saxenian, 1996; Acs et al., 2017). 
 Such phenomenon-centered research could be abstracted by treating the ecosystem as the 
main unit of analysis, thereby also improving the comparability, generalizability and 
conditionality of the studies in this domain. This will allow for a better connection to the original 
conceptualization (Moore, 1993, 1996), leveraging the biological metaphor upon which the 
concept is based (Iansiti & Levien, 2004), and improving the overall theorizing and 
conceptualization (Adner, 2017; Jacobides et al., 2018). Specifically, by treating the ecosystem 
as the main unit of analysis, future research can more clearly identify and describe which 
constructs that comprise the ecosystem concept they address in their respectivestudies (or which 
ones are not in the scope of their study), whether and how related streams (based on adjacent 
phenomena) may be connected to the ecosystem concept, and ultimately what the exact boundary 
conditions are to describe the successful functioning of an ecosystem (or when it fails). 
At the same time, while this proposed definition is grounded in the ecosystem literature, it 
also connects to literatures on multi-sided markets (Economides & Katsamakas, 2006; 
Eisenmann et al., 2006, 2009; Boudreau & Hagiu, 2009), coopetition (Brandenburger & 
Nalebuff, 1996; Bouncken et al., 2015; Hannah & Eisenhardt, 2018), alliances and networks 
(Faems et al., 2008; Phelps, 2010), business models (Zott et al., 2011; Massa et al., 2017), and 
open innovation (Vanhaverbeke & Cloodt, 2006; Dahlander & Gann, 2010; West, 2014; West & 
Bogers, 2014; Bogers et al., 2017). With taking the ecosystem as the main unit of analysis, 
ecosystem scholars have a unique opportunity to connect many of these disparate fields of 
management research by linking theoretical perspectives, bridging levels of analysis, and 
leveraging rigorous research designs. This will not only increase the insights into what an 
ecosystem is but also use that understanding to advance research and practice in related domains. 
Marcel Bogers, U. of Copenhagen & U. of California Berkeley, marcel@ifro.ku.dk
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CONCLUSION 
This paper shows how cumulative knowledge building in ecosystem research has been hampered 
by differences over definitions of what an ecosystem is. Through a review and synthesis of prior 
ecosystem studies, after identifying four key components found in these studies, we offer a more 
expansive and inclusive definition that provides several benefits for future research. First, the 
definition allows leveraging ecosystem research conducted under another name in various 
empirical contexts, and incorporating that research to identify similarities and differences. 
Second, the modular definition comprises four main components — three key constructs and the 
ultimate success measure — within any ecosystem, and thus suggests research opportunities 
linking these constructs to each other and to the overall ecosystem success. Finally, a more 
precise definition facilitates empirical studies of ecosystems at the level of the ecosystem — 
facilitating the use of the ecosystem as the main unit of analysis for future research. 
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Paula Chimenti
Paula Chimenti
Paula Chimenti
Marcel Bogers, U. of Copenhagen & U. of California Berkeley, marcel@ifro.ku.dk
Jonathan Sims, Joel West
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