The wisdom of ecosystems: A transactive memory theory of knowledge management in entrepreneurial ecosystems

Date01 July 2020
DOIhttp://doi.org/10.1002/kpm.1635
Published date01 July 2020
RESEARCH ARTICLE
The wisdom of ecosystems: A transactive memory theory of
knowledge management in entrepreneurial ecosystems
Philip T. Roundy
Marketing and Entrepreneurship, University of
Tennessee at Chattanooga, Chattanooga,
Tennessee
Correspondence
Philip Roundy, Marketing and
Entrepreneurship, University of Tennessee at
Chattanooga, Gary W. Rollins College of
Business, 615 McCallie Avenue, Chattanooga,
TN 37403-2504.
Email: philip-roundy@utc.edu
The contextual turn in entrepreneurship research has shifted scholars' attention to
the place-based forces that shape entrepreneurship in vibrant entrepreneurial eco-
systems, such as Silicon Valley, Stockholm, and Bangalore. Studies find that an impor-
tant component of ecosystems is the knowledge they contain about the
entrepreneurship process. However, the critical questions of how entrepreneurs
overcome challenges associated with acquiring tacit knowledge, how entrepreneurs
leverage their ecosystems to organize knowledge, and what factors influence an eco-
system's ability to serve as a knowledge repository remain unexamined. To formulate
a theory explaining how entrepreneurs use their ecosystems to facilitate knowledge
management and organizational learning, insights from group cognition are adapted
to introduce the concept of entrepreneurial ecosystem transactive memory. It is the-
orized that ecosystem-level characteristics, including diversity, coherence, connectiv-
ity, prosociality, and interdependence, influence an ecosystem's transactive memory
structure and processes. By examining the linkages between ecosystem characteris-
tics and transactive memory, a more nuanced understanding of the cognitive dynam-
ics of entrepreneurial ecosystems is provided. The theoretical model charts a path for
interdisciplinary research on knowledge management in entrepreneurial ecosystems
and generates implications for practitioners.
1|INTRODUCTION
Entrepreneurial ecosystems (EEs) are the interconnected agents, insti-
tutions, and forces that promote and support entrepreneurship in geo-
graphic areas (Autio, Nambisan, Thomas, & Wright, 2018; Spigel &
Harrison, 2018; Stam, 2015). Vibrant EEs with high levels of entrepre-
neurial activity, such as London and S~
ao Paulo, are receiving intense
attention from academics and practitioners because of the belief that
thriving EEs are engines for economic and community development
(Acs, Stam, Audretsch, & O'Connor, 2017; Berger & Kuckertz, 2016;
Brown & Mason, 2017; Malecki, 2018; Roundy, 2019). There is also
growing acknowledgment among scholars that entrepreneurship is an
activity embedded in a dense web of location- and context-specific
forces (Magliacani & Madeo, 2018; Welter, 2011). Studies have
focused on teasing apart the place-based forces in ecosystems, identi-
fying EEs' social, cultural, and material components, and generating
insights into the development of EEs (Kuckertz, 2019; Mack &
Mayer, 2016; Spigel, 2017; Thompson, Purdy, & Ventresca, 2018).
Despite this progress, little is known about how EE characteristics
influence participants' cognition.
An under-explored pathway through which EEs influence cogni-
tion is by being environments ripe with entrepreneurial knowledge.
Knowledge is a critical resource for entrepreneurs and acquiring, orga-
nizing, and utilizing knowledge about the entrepreneurship process is
central to creating and scaling ventures (Audretsch & Keilbach, 2007;
uit Beijerse, 2000). Indeed, it is by integrating multiple knowledge
sources that entrepreneurs identify unobserved opportunities and
learn capabilities (Boccardelli & Magnusson, 2006; Hoang &
Antoncic, 2003; Spigel & Harrison, 2018). Knowledge is a key ele-
mentand systemic conditionof EEs (Stam, 2015, p. 1765) and the
vibrancy of an ecosystem is a function of how freely knowledge about
opportunities, technologies, and the entrepreneurship process flows
through the system's networks (Auerswald & Dani, 2017; Bruns,
Bosma, Sanders, & Schramm, 2017).
Received: 17 March 2020 Accepted: 19 March 2020
DOI: 10.1002/kpm.1635
234 © 2020 John Wiley & Sons Ltd Knowl Process Manag. 2020;27:234247.wileyonlinelibrary.com/journal/kpm

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