Access to this full-text is provided by Springer Nature.
Content available from Review of Managerial Science
This content is subject to copyright. Terms and conditions apply.
Vol.:(0123456789)
Review of Managerial Science (2022) 16:157–187
https://doi.org/10.1007/s11846-021-00440-5
1 3
ORIGINAL PAPER
Towards anetwork‑based view ofeffective entrepreneurial
ecosystems
StephanieScott1 · MathewHughes2· DomingoRibeiro‑Soriano3
Received: 30 March 2020 / Accepted: 2 January 2021 / Published online: 4 February 2021
© The Author(s) 2021
Abstract
We conceptualize entrepreneurial ecosystems as fundamentally reliant on networks
and explore how and under what conditions inter-organizational networks lead
an entrepreneurial ecosystem to form and evolve. It is widely accepted that entre-
preneurial ecosystems possess a variety of symbiotic relationships. Research has
focused considerable efforts in refining the structure and content of resources found
within these networked relationships. However, merely focusing on actor-level char-
acterizations dilutes the notion that social relationships change and are complex.
There has been little conceptual treatment of the behavioral and governance fac-
tors that underpin how quality interactions composing an entrepreneurial ecosystem
develop and change over time. In response, we provide a longitudinal ethnographic
study examining how ecosystems are managed and evolve in their relational con-
figurations and governance at critical junctures. Using mixed methods and data col-
lected over 3years, we reveal a cyclical process of relational development central to
the initiation, development, and maintenance phases of a valuable entrepreneurial
ecosystem. We contribute to a conceptualization of effective ecosystems as reliant
on networks, we reveal the behavior and governance characteristics at play in the
entrepreneurial ecosystem during each phase of its evolution.
Keywords Entrepreneurial ecosystems· Relational governance· Longitudinal·
Network theory· Networks· Effective ecosystems· Ecosystem evolution
* Stephanie Scott
s.a.scott@durham.ac.uk
Mathew Hughes
m.hughes2@lboro.ac.uk
Domingo Ribeiro-Soriano
Domingo.ribeiro@uv.es
1 Durham University Business School, University ofDurham, DurhamDH13LB, UK
2 School ofBusiness andEconomics, Loughborough University, LoughboroughLE113TU, UK
3 IUDESCOOP, Universitat de Valencia, Valencia, Spain
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
158
S.Scott et al.
1 3
Mathematics Subject Classification 90B5· 915BB· 90B90
1 Introduction
Entrepreneurship plays a pivotal role in economic growth (Davidson etal. 2006;
Mason and Brown 2013). High-growth entrepreneurial ventures are prized for
their ability to innovate new products and services, improve wealth, enhance liv-
ing standards, and contribute to communities in general (Uyarra and Ramlogan
2016). As such, political bodies and governments worldwide view entrepreneur-
ship as a cornerstone to any national economic growth and resilience agenda
(see for example the OECD, UK Industrial Strategy 2017, USA Comprehensive
Economic Development Strategy, among many others). The imperative is clear:
identifying, supporting, and investing in cultivating entrepreneurial outputs is
essential for economic growth, and entrepreneurial ecosystems are viewed as a
potential solution to fostering the economic imperative of entrepreneurship (Stam
and Spigel 2018). This has led to a tendency among policymakers to import prac-
tices seen among thriving ecosystems (i.e., various funding mechanisms/incen-
tives, platforms, policy) on the assumption that such practices are somehow ‘best’
while omitting interdependencies (Harrison and Leitch 2010; Motoyama and
Watkins 2014; Spigel 2017). However, while there has been progress in creating
and understanding the various mechanisms and frameworks needed for entrepre-
neurial environments to foster high-growth ventures, there is considerable evi-
dence that some regional ecosystems are more conducive to the production of
successful ventures than others (Li etal. 2015; Spigel 2017). The inconsistency
in the effectiveness of entrepreneurial ecosystems suggests that merely a focus
on structural attributes is but one piece of the puzzle. For instance, scholars have
long recognized that entrepreneurship does not thrive in isolation (Mezias and
Kuperman 2001). We view entrepreneurial ecosystem performance as fundamen-
tally reliant on a relations and features of their governance. However, research on
behaviors, inter-dependencies and relational governance in entrepreneurial eco-
systems remains substantially underdeveloped and represents a crucial barrier to
understanding when and why ecosystems flourish or flounder. (Aarikka-Stenroos
and Ritala 2017; Kang etal. 2019; Scott etal. 2019; Spigel 2017). We attempt to
address this critical oversight and contribute to a network-based view of entrepre-
neurial ecosystems (Spigel 2017).
Traditional studies acknowledge that entrepreneurial outcomes rely on interac-
tions within broader social, cultural, and environmental contexts (Feldman and
Florida 1994; Isaksen 2016, 2018; Ferreira etal. 2019). For example, a stream of
entrepreneurial ecosystem research has developed an understanding of the social
contextual factors thatinfluence entrepreneurial outputs (Beliaeva et al. 2019).
Within this stream, authors focus their efforts on the factors that influence access
to and use of interactions within complex and broader social environments. While
promising results have emerged, this body of work is still in its infancy (Mueller
and Jungwirth 2016; Kang et al. 2019). Central to this research is the emerg-
ing pattern among descriptive accounts of the dependency the entrepreneurial
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
159
1 3
Towards anetwork‑based view ofeffective entrepreneurial…
ecosystems have on local conditions (Cavalo et al. 2018). These studies draw
attention to the complex nature of network composition (Oerlemans etal. 2001).
Network composition (i.e., its structure and content) is a priority to understanding
when an ecosystem thrives or flounders. However, the focus on the components
of these environments has led to an oversimplification of how the relationships
held between entities create or prevent entrepreneurship. These studies generally
depict relationships as merely a link to knowledge access or financial resources.
Instead, ecosystem theory should focus on how these relations are governed to
produce and reproduce vibrant, wealth-creating new ventures. A relational and
network view of entrepreneurial ecosystems helps differentiate between the
content and structure of the network as reproducible elements to more in-depth
examinations of how governance behaviors truly create and support an ecosys-
tem. Nevertheless, there remains a significant lack of studies that probe the net-
working activities and relational elements explaining how and under what condi-
tions inter-organizational networks lead an entrepreneurial ecosystem to form and
evolve.
This study responds to this gap by answering two related research questions nec-
essary for a relational and network view of entrepreneurial ecosystems: (1) How
does an entrepreneurial ecosystem evolve and mature productively across phases
over time? (2) What relational governance mechanisms influence ecosystem adapta-
tion at each phase? Data from a three-year, longitudinal, mixed-method research
study of an established and influential university-business partnership forming a
valuable entrepreneurial ecosystem in its region is used to explore the processes
and governance features generating a vibrant ad wealth-creating entrepreneurial
ecosystem. Breaking form tradition, we conceptualize entrepreneurial ecosystems
as fundamentally reliant on networks. We provide a conceptual and empirical treat-
ment of the behavioral and governance factors that underpin how quality interac-
tions composing an entrepreneurial ecosystem develop and change over time. We
further provide a longitudinal ethnographic study examining how this ecosystem
is managed and how it evolves in its relational configurations and governance at
critical junctures. We contribute much-needed new information on the factors that
influence the development of relationship governance structures and the evolution
of an entrepreneurial ecosystem across distinct phases. In doing so, we contribute
to a conceptualization of effective ecosystems as reliant on networks and shed new
light on ecosystem relationships. Collectively, these insights contribute to advancing
a network-based view of entrepreneurial ecosystems as called for by Spigel (2017).
2 Theoretical background andliterature
2.1 A relational perspective onentrepreneurial ecosystems
The ecosystem concept has gained traction across a broad range of entrepreneur-
ship- and innovation-focused disciplines in recent years (Russell and Smorod-
inskaya 2018; Spigel 2017). Borrowing principles from biological studies, the
ecosystem concept can be broadly characterized as complex interactive systems
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
160
S.Scott et al.
1 3
(Autio and Thomas 2013) that sustain ‘life’ through evolving conditions, cycles,
and energy flows (Scarigella and Radziwon 2017). In the lexicon of entrepre-
neurship, authors essentially agree that the durability and performance of any
given ecosystem are influenced by varying resources (Garnsey and Leong 2010),
environmental conditions (Breitenecker etal. 2016; Sun et al. 2019), and enti-
ties (Pilinkienė and Mačiulis 2014). However, while the structure and content of
various ecosystems are similar across studies, evidence suggests that engagement
within these complex systems vary due to actor-level perceptions (Scott et al.
2019), roles (Valkokari 2015), and decision-making behaviors (Kapoor and Lee
2013). Stated differently, the vibrancy and the wealth-creating potential of an
ecosystem relies on interaction first and foremost.
High-growth ventures, especially the high-technology variety, burn through
resources at a relatively fast rate (Hughes etal. 2020). These firms may not have
the internal capacity to generate the knowledge required for timely new ven-
tures (Perez-Luno etal. 2011), respond to market changes (Rothwell 1994), or
the capabilities needed to compete within risky initiatives (Powell 1990). These
firms have long recognized the benefits of interacting with actors in their environ-
ment to access resources and acquire or attract entrepreneurial activities (Scott
etal. 2019; Yin etal. 2020). Nevertheless, they hold an innate potential to access
unique resources, expertise, or technologies from various external organizations
(Hughes etal. 2007; Inkpen and Tsang 2005; Kogut and Zander 1992; Reagans
and McEvily 2003; Scott etal. 2019). Stated differently, their ability to gener-
ate successful new ventures lies in their ability to effectively navigate, enact, and
exploit opportunities made available within networks.
Thinking of entrepreneurial ecosystems as networks depict pathways to access-
ing resources and finance (Powell 2002), for knowledge spill-overs with other
like-minded firms or supporting institutions (Owen-Smith and Powell 2004),
and the easing of institutional barriers (Feldman and Francis 2004). However, a
network view of entrepreneurial ecosystems carries two vital implications that
resolve deficiencies in structure- and content-based views of ecosystems: that
ecosystems simply present the opportunities for such benefit but not necessarily
their access (Hughes etal. 2007; Scott etal. 2019). A network (or relational) per-
spective on entrepreneurial ecosystems places interdependencies and interactions
among actors as core to explaining why one ecosystem outperforms another. This
perspective can also shed light on why the idea of drawing ‘best’ practice from
one ecosystem to another is flawed without those interdependencies and can help
predict what governance mechanisms are needed to steer interaction across time.
As Spigel (2017, p.50) notes, “entrepreneurial ecosystems need to be more than
a label for regions with high rates of entrepreneurship. Rather, ecosystem theory
should focus on the internal attributes of ecosystems and how different configura-
tions of these attributes reproduce the overall ecosystem and provide resources to
new ventures that they could not otherwise access.” Entrepreneurial actors resi-
dent in entrepreneurial ecosystems must transcend their organizational borders
(Chesbrough 2003, 2007; Chesbrough etal. 2006; Huizingh 2011; Sisodiya etal.
2013). However, scholars are yet to unveil deeply how entrepreneurial actors
might enact and maintain relationships within entrepreneurial ecosystems and
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
161
1 3
Towards anetwork‑based view ofeffective entrepreneurial…
ever-changing environments (Autio and Thomas 2013). An interaction element is
essential.
Entrepreneurial actors engage with various ecosystems to address resource and
knowledge needs (Kapoor and Lee 2013; Xu etal. 2018; Russell and Smorodinskaya
2018). However, entrepreneurial ecosystems are different from both an innovation
ecosystem (one typically oriented toward co-innovation) and a knowledge ecosys-
tem (one typically oriented toward knowledge access, diffusion, and transfer) (e.g.,
Aarikka-Stenroos and Ritala 2017; Kapoor and Lee 2013; Pilinkienė and Mačiulis
2014; Mazzucato and Robinson 2018; Scaringella and Radziwon 2017; Velkokari
2015; Xu etal. 2018). Entrepreneurial ecosystems represent interdependent actors
and factors coordinated to enable productive entrepreneurship within a particu-
lar region or territory (Stam and Spigel 2018). Effective entrepreneurial behavior
then must transcend beyond network structures (Aarikka-Stenroos and Ritala 2017;
Hughes etal. 2014; Rapp and Olbrich 2020; Scott et al. 2019; Spigel 2017). The
coordination of complex social and human behavior is required to generate knowl-
edge necessary for different outputs (Kogut and Zander 1992; Nonaka 1994; Rodan
and Galunic 2004). Networks can be considered the glue that enables and unlocks
the power of entrepreneurial ecosystem, and its essential elements require further
examination. A coordination (or orchestration) element is essential.
2.2 Networks inentrepreneurial ecosystems
Many potential partners can be embedded in entrepreneurial ecosystems, including
nascent entrepreneurs, SMEs, venture capitalists, lead users, end consumers, uni-
versities and scientists, mentors and dealmakers, and the like (Keupp and Gassman
2009; Spigel 2017; Scott etal. 2019). The benefit of engaging within a network lies
within the flexible ability for an actor to remain as a semi-autonomous node in their
area of specialism (Bluedorn etal. 1994) while also accessing resources that would
either be unavailable, inaccessible, or difficult to access (Daata 2011; Powell 1990).
When entrepreneurial actors can access or transmit ideas and other forms of knowl-
edge within networks of relationships, spillovers can occur. More ideas and knowl-
edge are shared or accessed among the actors comprising the network (or ecosys-
tem) (Daata 2011; Schroder 2020). This flow of knowledge and resources holds the
potential for actors to learn faster (Dyer and Hatch 2004) and innovate better (Chang
etal. 2006; Mooi and Frambach 2012). Through creating borderless organizations
and building inter-organizational cooperation (Kim etal. 2010), networks can help
circulate resources and knowledge (both explicit and tacit), enhance innovation and
learning, and facilitate entrepreneurship (Aldrich and Zimmer 1986; Hoang and
Antoncic 2003; Koka and Prescott 2002; Spigel 2017; Zardini etal. 2020).
The importance of social networks to entrepreneurship is well-documented (e.g.,
Hoang and Antoncic 2003; Nijkamp 2003; Stuart and Sorenson 2007). However,
accessing and releasing the resources, knowledge, new relationships, finance, oppor-
tunities (among the many other purported benefits of networks and ecosystems) is
contingent upon the careful coordination of complex human and social elements,
and behavior (Hughes etal. 2007, 2014; Kogut and Zander 1992; Rodan and Galunic
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
162
S.Scott et al.
1 3
2004). An entrepreneurial ecosystem succeeds when its entrepreneurial dimension
(the process by which for creating new goods and services are explored, evaluated,
and exploited) is elevated by its interaction dimension (that entrepreneurship takes
place in a community of interdependent actors) (Stam and Spigel 2018) are satisfied.
Ecosystem relationships require careful orchestration or else be left to happenstance
or chance.
Network theory focuses on the interdependent nature of actors (nodes) and the
relational linkages (ties) to determine the flow of resources (e.g., social capital and
knowledge) within a network of relationships (Wasserman and Faust 1994). Salient
networks in an entrepreneurial ecosystem are both inter-organizational and inter-per-
sonal (e.g., Sedita 2008). The act of resource diffusion occurs through the relational
links to the node (Robertson etal. 2012; Pentland 2014). This is essentially a behav-
ioral problem and, as such, network governance is important as it defines the various
social mechanisms at play that impinge on behavior (Jones etal. 1997). Such behav-
iour is also vulnerable to the context of the relationship and partner selection (Shah
and Swaminath 2008) and difficulties in aligning cultures between actors (Herzog
and Leker 2010).The process of unlocking access to knowledge and resources and
enabling their transfer in value-creating ways depends on actors’ network behav-
ior. It so represents a behavioral feature of networks (Ng and Feldman 2010). In
any entrepreneurial ecosystem then, opportunities for entrepreneurship and entre-
preneurial innovation must be enacted by individuals/actors whose behavior elic-
its trust, reciprocity, and the will to make available and transfer the knowledge and
resources necessary for value creation (Hughes etal. 2014; Scott etal. 2019; Spigel
2017). Contrary to policymakers’ practice to cherry-pick over ‘best’ practices from
seemingly successful entrepreneurial ecosystems in different territories or regions,
how an actor accesses resources (etc.) may be relationally specific and determined
by local (network) conditions in the entrepreneurial ecosystem.
2.3 Relational governance andnetwork orchestration
Relationships represent multi-faceted forms of cooperation and are dependent on
mutual benefit, trust, interaction, and open communication channels aimed at shar-
ing risk and resources in a way that extends beyond contracts (Powell 1990; Zaheer
etal. 1998). Relational governance is strongly associated with providing an environ-
ment conducive to resources and knowledge exchange (Carmeli and Azeroual 2009).
In general, governance is understood to be how an organized social and collective
entity is created, directed, and reinforced to develop normative behaviors. Ulti-
mately, the realization of value depends on the extent to which the relationship(s)
between actors impacts their implicit ‘value’ for transacting the resources available
within the network (Adler and Kwon 2002; Hughes and Perrons 2011; Inkpen and
Tsang 2005; Nahapiet and Ghoshal 1998). A further body of literature associates
these relational capabilities with productive entrepreneurial and innovative out-
comes (e.g., Kale etal. 2000; Mooi and Frambach 2012; Sisodiya etal. 2013; Spi-
gel 2017). Cooperation and trust build over time (Huemer 2014), and recent studies
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
163
1 3
Towards anetwork‑based view ofeffective entrepreneurial…
have called for a focus on relational (Scott etal. 2019; Hughes et al. 2014) and
developmental (Ng and Feldman 2010) behaviors to explain why one set of relation-
ships, or network, becomes more productive than another even when replicating the
properties of its structure or content.
Extended to an entrepreneurial ecosystem, then, the social aspect of the
network(s) within the ecosystem matter is whether it can productively contribute to
the actors’ agency within it (Scott etal. 2019). Treating an entrepreneurial ecosys-
tem in isolation from network theory suggests that an ecosystem’s mere structure
and content inherently creates wealth devoid of an agency from the actors them-
selves. We challenge this assumption and argue that the relational organization of
the entrepreneurial ecosystem matters (Spigel 2017). First, while an actor’s network
position can determine their influence on the network (Schepis et al. 2014), the
whole of the network matters for governance and learning (Makadok 2003) because
degrees of knowledge heterogeneity influence performance (Hughes et al. 2014;
Rodan and Galunic 2004) and the outcomes that may be drawn from the network
(McEvily and Zaheer 1999). The relational component of trust takes time to develop
and depends on how actors behave with one another. Trust provides the ability to
unlock access to (or share) resources and knowledge with others regardless of the
ecosystem’s structure or content (e.g., Bouncken etal. 2020; Scott etal. 2019). Sec-
ond, the levels of uncertainty avoidance and protection of proprietary information
in inter-firm collaboration have the potential to inhibit behavior, further empha-
sizing the importance of relational governance (Kale et al. 2000; Barr and Glynn
2004; Zaheer and Venkatraman 1995) in ways that encourages knowledge sharing
and to facilitate entrepreneurial and innovation outcomes. Most studies employing
social capital theory acknowledge trust and reciprocity within interactions to be cru-
cial relational components in the generation of social capital. By working together,
actions are driven by common (instead of competitive) interests that can serve to
improve conditions across several stakeholders involved in the relationship (Scott
etal. 2019). Concurrently, trust in business relationships as extends from individu-
als’ behaviors within and among organizations rather than from the organizations
themselves (Zaheer etal. 1998). Differentiating between individual and organiza-
tional levels holds implications for the transmission of ideas and knowledge flows
(Ganseen and Hess 1997).
Given Zaheer etal.’s (1998) observation about trust and the execution of relation-
ships taking place at the individual as opposed to a firm level, trust and norms are
potentially a more effective governance mechanism than contracts in the success-
ful and effective management of relationships. Network behavior leads an actor to
maintain unique and idiosyncratic patterns of network linkages and the significant
differential exposure to knowledge and ideas. Despite an implicit acceptance among
existing studies that the social capital needed to unlock learning is behaviorally
driven, there is a general absence of understanding into that behavior, its govern-
ance, and its orchestration (Granovetter 1973; Hughes etal. 2014; Ng and Feldman
2010; Stuart and Sorenson 2007).
In essence, sufficient trust motivates parties to share scarce resources (Kwon
et al. 2013), which helps form dense networks necessary for productive entrepre-
neurship (Aldrich and Zimmer 1986), and dense links are forged regionally by
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
164
S.Scott et al.
1 3
frequent interactions (Schutjens and Völker 2010). Orchestrators (such as mentors,
dealmakers, and other actors) can encourage these interactions. However, we posit
their sustenance and growth depend on governance mechanisms regulating produc-
tive behavior among actors in the networks inside the entrepreneurial ecosystem. A
relational governance perspective is therefore essential to improve understanding of
productive entrepreneurial ecosystems.
Our research objective is to delve into the relational and network perspective
of entrepreneurial ecosystems, building on calls by Aarikka-Stenroos and Ritala
(2017), Scott et al. (2019) and Spigel (2017), necessary because the behavior of
actors within the ecosystem and networks that form among them are central to the
movement and transmission of resources and knowledge. In effect, without scholarly
knowledge of network and relational governance in entrepreneurial ecosystems, we
are left with the flaw currently exhibited by policymakers: the tendency to mimic
apparent ‘best’ practices in ecosystems in other regions or territories on the assump-
tion that structure and content create value. They do not. Instead, they merely offer
opportunities to do so, but whether these are realized or not depends on actors’
behavior within an ecosystem and the governance of those relations (e.gScott etal.
2019; Hughes etal. 2007, 2014).
3 Research design andmethodology
To generate data to understand entrepreneurial ecosystems as networks and rela-
tional governance, we use an ethnographic study following a longitudinal research
design (Hanneman and Riddle 2005; Carrington and Scott 2011). We supplemented
this design with other mixed-method data collection to enable multilevel triangu-
lation and continued data collection until the point of theoretical saturation (Yin
1994). We used a continual comparison method to identify and collect evidence of
the components for managing interactions between entities, sub-units, and corre-
sponding actors (Gephart 2004). This allowed the researchers to identify theoretical
similarities to engage with subsequent analytical categorization more accurately.
The study ran from October 2013 to January 2017, representing a longitudinal
study (Eisenhardt 1989; Yin 2013) to understand how relationships within the eco-
system evolved and how changes occurred within and among those relationships
(Van de Ven 2007). This method afforded a rich treatment of the phenomenon
(Siggelkow 2007).We selected the case for theoretical sampling purposes. The case
represents a highly regarded, award-winning university-business partnership that has
become the foremost and influential element of stimulating entrepreneurial ecosys-
tem activity within its region in England. The business organization studied oper-
ates on a global scale in the fast-moving consumer goods industry. The university
organization is a strong institution of international repute. The inter-organizational
relationship, and the ecosystem that ultimately formed, initiated through a period
of pilot studies in 2011. Between 2011 and 2012, many aspects of the relationship’s
micro-level functioning emerged organically and in response to various internal and
external stimuli. Recognizing the value and potential future performance future col-
laboration could provide, the relationship developed a governance board to sustain
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
165
1 3
Towards anetwork‑based view ofeffective entrepreneurial…
its vitality. It is at this stage that data collection began. How this business-university
partnership interacts within the regional ecosystem has since been highly lauded by
members of the ecosystem and broader external entities and world governments. At
the time of data collection, the relationship had generated over £20M and leveraged
over £10M in governmental and research council support. It is considered an exem-
plar case study for industrial engagement and has been lauded amongst policymak-
ers’ highest tiers across the globe. From 2011 through 2016, the relationship led to
66 funded entrepreneurship and innovation projects with 162 individuals embedded
in the focal ecosystem. These projects were scaled across various knowledge transfer
and acquisition targets and included individuals collaborating on projects in chem-
istry, physics, biology, psychology, business, mathematical sciences, and history.
Many funded projects were conducted in collaboration with external local SMEs,
entrepreneurs, and research institutes, collectively growing the ecosystem.The rela-
tionship also involved technology transfer, finance, and legal professionals. While
the relationship initially formed due to geographic proximity and the potential to
access shared resources, its development eventually led to the inclusion of actors
from the United Kingdom, United States, Germany, Italy, and Singapore. It became
one of the foremost entrepreneurial ecosystems within the region.
Over the 3-year duration of the project, data were arranged into a chronology of
core events and exhibited behaviors to provide an overview of evolutionary pro-
cesses. While we acknowledge the duality and inseparability of network structure
and agents, this study is primarily focused on conceptualizing the factors that drive
governance between entities in the ecosystem as described above. Given the level
of influence that this particular relationship represented and that the conceptualiza-
tion of a relational perspective on entrepreneurial ecosystems is thin (Spigel 2017),
this study adopted anexploratory stance. We sought to identify individual behaviors
within the network to further our understanding of various outcomes and phases in
developing the entrepreneurial ecosystem (Wasserman and Faust 1994; Cross and
Parker 2004; Kadushin 2012; Carrington and Scott 2011). The intention was to
identify behaviors and features of relational governance associated with outcomes
within networks throughout the entrepreneurial ecosystem to make recommenda-
tions for future examination (Glaser and Strauss 1967; Eisenhardt 1989). The means
to which governance coordination occurs is multi-faceted as well, with several dif-
ferent means to which social norms are communicated. The means to which multi-
method data collection occurred are described within the next section.
3.1 Data collection
The in-depth access provided by the stakeholders to this study awarded rare insights
into the relational exchanges, behaviors, and functioning of the ecosystem. The first
phase of data collection used snowballing techniques to uncover critical network
members (Prell 2011). Participant observations occurred throughout the setting
(Schwartz and Schwartz 1955; Gold 1958; Bryman 2001; Yin 2013) from monthly
and quarterly executive board meetings, interviews, and a series of informal interac-
tions. Additional data were collected from direct observations of monthly technical
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
166
S.Scott et al.
1 3
meetings, allowing a more passive means of observing the relationship. The goal
was to observe but not interfere with interaction patterns (Silverman 2015; Yin
2013).Furthermore, access to all relational management and coordination documen-
tation from the study’s onset allowed for a further longitudinal lens. Secondary data
were collected from internal documents, presentation materials from workshops and
conferences, and information displayed in the public domain, such as press releases,
books, articles, and website information. This procedure enabled triangulation
(Glass 1976) and served as augmenting evidence to identify corroboratory versus
contradictory evidence (Wasserman and Faust 1994). The secondary data access
provided the opportunity to explore the level of network involvement and communi-
cations between members in an objective way.
3.1.1 Participant observations
Approximately 76h of participant observations were recorded. This data collection
method ran between 2013 and 2016 and included 15 semi-structured interviews,
14 executive board meetings, 9 respondent validation meetings, and 4 research dis-
semination meetings. This method was designed to capture an understanding of
participants’ roles and histories within the relationship. Therefore, this form of data
collection focused on the senior members of the focal relationship, including direc-
tors, technical managers, and functional managers from both sides of the relation-
ship. Eight participants from the business organization were sampled. The sample
included two global directors, a finance manager, two scientific partnership leads
based in the UK, one global director, one regional director, and one scientific part-
nership lead. The sample included four head of subject departments, a director of
research, and two technology transfer directors on the university side.
The semi-structured interviews and informal follow-up meetings were con-
structed to have open-ended questions and focused on the network’s inner work-
ing and identifying key events that led to its formation and evolution. This allowed
the participants to communicate their perspectives with minimal interference from
the researchers (Silverman 2015). Key informants remained in contact for further
data validation throughout all research phases (Gephart 2004; Miles and Huberman
1994). A further nine informal interactions were recorded due to the highly valuable
continued insights the participants provided throughout the project and respondent
validation. This primary data collection approach allowed the researchers to engage
in the relationship appropriately (Yin 1994). Approximately 23 h of participant
observation techniques were recorded over the three-year duration of the projects.
All recorded interviews were later transcribed as part of the data reduction process
and coding procedure. Field notes were transferred to digital logs.
Furthermore, participant observations occurred through the attendance to four-
teen monthly and quarterly executive and partnership governance meetings. These
regular meetings included the attendance of most UK-based informants previ-
ously described and continued throughout the project. The primary focus of these
meetings was on strategic planning and resource allocation for future initiatives
and addressing potential institutional pressures by reviewing and responding to
external communications. This data collection technique allowed the researcher
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
167
1 3
Towards anetwork‑based view ofeffective entrepreneurial…
to derive deeper meaning from the observations as it allowed the opportunity to
ask questions and allow for moderate participation in the research setting (Sil-
verman 2015; Miles and Huberman 1994). These meetings were not recorded,
but field notes were permitted. There were approximately 42h of data collection
recorded in this data collection method. Additionally, annual respondent valida-
tion events and research dissemination were delivered four times and included
another 11h of data validation and insights.
3.1.2 Direct observations
Approximately 50h of direct observations were recorded as well. Direct obser-
vations were collected through the attendance to technology transfer workshops
and included a broader scope of actors than those observed within the partici-
pant observations. The projects and content discussed at these meetings revealed
technical contributions and insights from several local, regional, and international
firms. Key members of the governing Board, observed in the participant observa-
tions, were regularly present, including the two scientific leads from the business
organization and three head of subject department leads. This further included a
broad scope of participants across various roles, including 27 academic principal
investigators, 6 organizational, technical scientists, and 18 Ph.D. candidates. The
direct observations allowed the researcher to retain a passive role while observ-
ing interaction patterns and activities in a natural setting (Miles and Huberman
1994). This allowed the researcher to observe the interaction patterns among the
actors within the setting without interfering in the event’s overall design (Silver-
man 2015). This form of observation benefits from fewer risks of socially desir-
able responses by the participants (Myer and Goes 1988) and allows the story
to unfold without the researcher imposing influence on the activities being con-
ducted. This allowed the researcher to remain detached from the participants
being studied and allowed for a more objective view of how governance was com-
municated throughout the broader social structure.
3.1.3 Secondary data
A total of 223 internal documents, presentation materials from workshops and
conferences, and information displayed in the public domain, such as press
releases, books, articles, and website information, were collected. These docu-
ments were intended for the management and coordination of the relationship and
provided a lens into the coordination and organization of the relationship. The
re-analysis of existing information characterizes secondary data for answering
the questions at hand (Glass 1976). The benefit of retrieving the archival docu-
ments was that they augment evidence for other sources to reflect the corrobora-
tory versus contradictory evidence (Wasserman and Faust 1994). The collection
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
168
S.Scott et al.
1 3
of archival documents allowed the researcher to retrieve objective data regarding
members of the network and the relations that exist per contractual coordination.
3.2 Analysis methods
We compiled all the data into a unified database, tabularized it, and labeled it
according to emerging first-order themes, date, and source (Miles and Huberman
1994; Gioia et al. 2013). The data was evaluated through thematic analysis tech-
niques and induction (Miles and Huberman 1994; Yin 1994; Creswell 2009).
We then formed a chronology of events in the evolution of the entrepreneurial
ecosystem and its networks. This chronology aided in analyzing the episodes of net-
work evolution that occurred since the origin of the relationship. Taking a longitudi-
nal lens then, all data were compiled and drafted into a historical development and
timeline (Silverman 1993). A common theme to understanding the inner working
of this overarching university-business relationship and the emerging entrepreneur-
ial ecosystem was that its scale grew organically andin a more fragmented way, as
emphasized by senior participants. This chronology revealed several critical events
over time and led us to identify four significant tipping points triangulated by archi-
val documents and participants’ accounts. These were crucial points when the entre-
preneurial ecosystem and its internal networks responded to internal and external
pressures. This analysis identified patterns that reflected a level of stability, devel-
opment, and adaptation/coordination through significant events across the timeline.
This historical recount of the relational development was contrasted with Cross and
Parker’s (2004) notion of network evolution. This approach reveals the co-evolution
in which the ecosystem was built and the endogenous processes contributing to its
effectiveness (Wasserman and Robins 2005).
Thematic analysis (Miles and Huberman 1994) is used to examine the qualita-
tive data generated from the study’s exploratory phase. This enabled new patterns
to be discovered (Yin 1994) and identify and make sense of the relational activi-
ties and mechanisms between different stakeholder groups (Faria and Wensley
2002). This also enabled a more careful exploration of the interaction between
the evidence and existing theory to emerge (Strauss and Corbin 1990; Hughes
and Perrons 2011). Throughout the data collection and the iterative process of
identifying themes continued until theoretical saturation and further analysis no
longer yielded fresh insights (Yin 1994). The early phases focused on the “con-
tinual comparison between the actors and their subunits based on the theoretical
similarities and differences” (Gephart 2004: 459). The research utilized multiple
points for qualitative data collection, such as semi-structured interviews, partici-
pant observations of monthly technical meetings, field notes collected at regu-
lar board meetings, relationship-themed presentations, and informal networking
events. This allowed for the convergence of the variables of interest and relied on
converging multiple sources of evidence. The benefits of using this approach in
the early stages are the development of theoretical propositions that further guide
the data collection exercises (Yin 1994). This allowed for new theoretical con-
cepts to emerge from the field and allowed the researcher to modify and broaden
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
169
1 3
Towards anetwork‑based view ofeffective entrepreneurial…
the initial categories through iterative and constant comparison (Silverman 2015).
It is the belief that is adopted by many qualitative researchers who seek to illus-
trate the contextual details of an investigation during the inductive phase, and
that would otherwise be overlooked utilizing objective (e.g. quantitative) meth-
ods alone. These themes allowed the researcher to identify the prevalence of the
compositional characteristics, the network’s size, idiosyncratic pockets, and sub-
groups within the network. This analysis also aided in identifying the different
relational contexts in which actors interacted with each other, and therefore pro-
vided the basis for understanding the complexity of the relational linkages that
characterize this network. The coding process is illustrated at the relevant point in
the next section.
4 Analysis andresults
4.1 Evolution ofthenetworks withintheecosystem
The first set of evidence confirms that networks are not static (Hughes and Perrons
2011; Nonaka 1994), driven by the oscillation of new members by members leaving
or joining, and internal and external (stakeholder) pressures. These change the com-
position of network structure and content and influence the resources and knowledge
available and their sharing. Thus, the entrepreneurial ecosystem evolves through dif-
ferent stages of flux and stability. Prior research suggests that the ability to connect
and share valuable insights depends on several social-psychological factors (Scott
etal. 2019), organizational climates, and various external factors that often change
(Bluedorn etal. 1994). Because of this, studies have sought to identify network type
and the complexity of the content diffused through its structure (Rodan and Galunic
2004; Inkpen and Tsang 2005). The content of networks provides essential deter-
minants for understanding the value created by relational activities (Hansen et al.
2001). However, despite several attempts, the partners in this entrepreneurial eco-
system could not repeat its success in other territories. Rodan and Galunic (2004)
proposed that a relationally embedded approach can provide insight into social
capital creation, and McEvily and Zaheer (1999) contend that the unique patterns
of network linkages expose actors to personal pockets of knowledge that cannot be
replicated. Irrespective of structure and content, it became clear in our case entre-
preneurial ecosystem that the defining character behind value creation was partici-
pant behavior and the governance of that behavior. Ultimately networks only pro-
vide value creation opportunities through the transfer of knowledge and resources
(Hughes et al. 2007). Knowledge transfer can be enabled theoretically by various
forms of relational governance (Inkpen and Tsang 2005). For example, scientific
members emphasized:
It has potential value to your area of research or ultimately within your area of
business. It’s kind of a virtuous cycle. The more you do the more of the stories
and things that kind of happen, the awareness sort of spreads within the com-
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
170
S.Scott et al.
1 3
pany. Stuff starts coming to me, rather than me pushing it and I start grabbing
it. – Participant 9
We have productivity gains, not cost gains, i.e., we can reach a project comple-
tion in three years not six. This is clearly a benefit to industry. – Participant 2
The complexity of solving real world, multi-scale research problems…
[requires] breadth of Knowledge and [a] number of brains on a project. – Par-
ticipant 11
Firms, networks, and relationships evolve over time and in response to changing
environments. Through interactions within changing states, we observed a dynamic
process in which its observable state has a temporality defined by specific behaviors
and relational governance. We present the stages of the evolution of networks and
the entrepreneurial ecosystem itself in Fig.1.
4.1.1 Pre‑existing conditions forexchange
The findings revealed several contingencies before the entrepreneurial ecosys-
tem formalized between the university and business partners and its stakeholders.
These included prior academic-industry experience, institutional pressures, and con-
strained resources. Also, the mere development of a formal relationship between
both partners did not give rise to an ecosystem. Initial relationships between the
university and the multinational company gave rise to networks between the two.
These networks grew to include new internal and external actors, locally, region-
ally, nationally, and internationally, growing both the physical size of the emerging
entrepreneurial ecosystem and its reach. The relationship absorbed these new part-
ners and evolved into an ecosystem as it developed internal and external legitimacy
with stakeholders and behavior, and relations among partners grew. Simple network
Fig. 1 Network evolution in entrepreneurial ecosystems
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
171
1 3
Towards anetwork‑based view ofeffective entrepreneurial…
structure or content lenses would overlook that an ecosystem is only as vibrant as
how actors collaborate or not within and across the ecosystem. This is fundamental
to why the university–business partnership could not replicate its success in other
territories.
The evolution of the networks and, ultimately, the entrepreneurial ecosystem
further relied on governance. For example, initial relationships began with ad hoc
contractual agreements replaced by a single master agreement with small additional
agreements where necessary. This act reduced uncertainty for ecosystem partners,
particularly over expectations, recourse, and intellectual property. However, con-
tracts are inherently incomplete and restricting, calling for relational governance.
The extent to which diverse partners can encounter challenges in alignment gives
rise to the necessary use of intermediaries (Huizingh 2011; Wilson Report 2012).
For example, while assessing economic objectives is an essential aspect of align-
ment, it is an incomplete analysis when conducted in isolation of each actor’s goals
and priorities (Larson 1992). In an entrepreneurial ecosystem of diverse partners and
actors, divergence is expected and embraced, not assimilated. In our case ecosystem,
university and business partners had very different objectives (e.g., economic ver-
sus scientific or utilitarian), and those goals differed yet again as more external and
internal partners joined (or left) the ecosystem (especially at regional and national
levels). Governance mechanisms adjusted to this reality to increase the vibrancy and
number of relationships and not restrict them or else suffocate the oxygen fueling
wealth creation in the entrepreneurial ecosystem itself. For example, an interviewee
commented:
I think the IP terms are a more practical issue. But, I think that a bigger one is
the more heart of it is the cultural difference. It’s where the academics place
the importance of industrial science. It’s very different in the UK than it is
here. It’s hugely different. American universities a long time ago now, got a
bug in their bonnet about monetizing their intellectual property and they do a
horrible job of monetizing their developments. – Participant 7
These actions gave rise to new challenges as networks, and the ecosystem
evolved. A significant factor that impacted this relationship were the variances in
anticipated knowledge generation and research objectives to create a (sufficient)
common ground.Senior leaders repeatedly spoke of “win–win relationships” as the
gold standard, but what constituted that success differed across actors and partners.
The alignment of organizational cultures and management practices (e.g., oppor-
tunity identification, definition, creation, coordination, and outcomes) (Kogut and
Zander 1992), organizational climates for knowledge sharing and promoting accept-
ance and acclimation of innovation (Bock etal. 2005; Myer and Goes 1988), and
knowledge combination capabilities and relational capabilities (Carmeli and Azer-
oual 2009) all emerged among our findings.
As illustrated in Fig.1, relational and contextual features differ in each phase of
development and emerged as a response to tipping points and critical challenges
encountered at each phase. Each stage of ecosystem development is characterized
by a point of evolution that shifts the relational development to a new development
phase. For example, in the Initiation phase, the need for institutional buy-in across
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
172
S.Scott et al.
1 3
the major partners required formal governance mechanisms such as contracts and
clear expectations. In the Development phase, these gave way to relational mecha-
nisms of trust and behaviors to enable recruitment and vibrant collaboration. The
Maintenance phase required formalization of monitoring through key performance
indicators (KPIs), more formal resource allocation to steer the direction of produc-
tive relationships, and oversight as a mechanism to generate internal legitimacy (that
the ecosystem was delivering wealth creation). The renewal phase required recon-
figuration and recruitment to revive the ecosystem and ensure new potential rela-
tionships could emerge among many new internal and external actors (including
businesses, dealmakers, funders, government bodies, etc.). At this stage, generat-
ing external stakeholder legitimacy required evidence and success stories measured
against performance evaluation relevant to those external stakeholders’ goals. For
example, an interview noted:
I certainly think that there are cultural leverages in the way that British gov-
ernment funds research and drives alliances. – Participant 8
The case evidence cautions against over-relying on deterrence-based (mechani-
cal) trust mechanisms emphasized in the university-business literature. Deterrence-
based trust emerges from the knowledge that a partner will not behave opportunisti-
cally because of the known costly sanctions that will follow.Deterrence-based trust
is contractual and based on a distinct set of guidelines about penalties for malfeasant
behavior (Gulati 1995). Contracts deter opportunistic behavior. However, in excess,
rigid contracts, formal structures, and institutionalized rules can limit knowledge
creation (Allen and Strathem 2003; Kadushin 2012). Knowledge-based, relational
trust, instead, is based on social norms and is crucial when behaviors, events, and
outcomes cannot (and should not) be fully predicted and accounted for within con-
tracts or else limit the scope for realizing entrepreneurship intended in entrepreneur-
ial ecosystems.
We now discuss each phase of ecosystem evolution.
4.2 Phases ofecosystem evolution
The analysis revealed four major tipping points that resulted in further develop-
ment stages: Initiation, Relationship Building (or Development), Maintenance,
and Renewal. The transition from each phase was characterized by critical points
that demanded actions causing a shift in focus to maintain the vitality of the rela-
tional exchange for continued value and wealth creation within the ecosystem. The
successful transition to further stages in network development depends on taking
appropriate responses and actions at each tipping point. Each phase presented a
new challenge that required complex social processes to be coordinated, which held
implications for network structure and operational focus. First, we observed some
degree of self-organizing processes at play in the ecosystem’s construction and
growth, especially across Phases 1 (Initiation) and 2 (Development). As networks
of relationships among actors within the entrepreneurial ecosystem grew in self-
organizing and organic ways, this network fragmentation benefited the ecosystem’s
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
173
1 3
Towards anetwork‑based view ofeffective entrepreneurial…
development. It allowed new pockets of relationships to emerge to attend to new and
novel opportunities. A rigid approach network structure would have constrained this
serendipity. However, that same fragmentation created consequences in Phases 3
(Maintenance) and 4 (Renewal). In Phase 3, fragmentation complicated the need to
establish and evidence the entrepreneurial ecosystem’s performance to internal and
external stakeholders (e.g., as a way to recruit more resources, recruit more partici-
pants, expand its regional and national socio-economic and political influence and
prominence, etc.). This created a need to formally track the value and wealth created
through the time of the entrepreneurial ecosystem. In Phase 4, the introduction of
rigid monitoring mechanisms, KPIs, and planning in Phase 3 had the initial effect of
diluting actors’ capacity to adapt to new opportunities, necessitating change. Sub-
networks primarily drove renewal within the ecosystem, and the need to orchestrate
new relationships as the number of actors and partners within the ecosystem grew.
These insights further reiterate a difference between composition (structure and con-
tent) and behavior.
4.2.1 The initiation phase
The potential for conflicts about knowledge ownership and commercialization of
developed technologies characterized the Initiation phase. Underpinning this con-
flict was a common dissatisfaction between the university and business partners in
defining a sustainable business model for their overarching relationship and, funda-
mentally, what type of ecosystem they ultimately wanted to germinate. To be clear,
both partners valued their roles as regional leaders, and local enterprise partnerships
were important stakeholders to both organizations and to the nascent ecosystem they
sought to establish.This process of conflict, negotiation, and agreement provided a
common language necessary to initiate the ecosystem (Fig.2).
A further complication stemmed from the tendency for relationships to have
idiosyncratic contracts for each new project or relationship, the implication being
that within any one relationship, many different legal contracts could be in place,
each accounting for a specific project. The governance and project management
•Development of a common language and an
emphasis on mutual needs; leading to meani ngful
communication and joint satisfaction
•Internal engagement and re cruitment to create
critical mass; create buy-in
Initiation
•Fast problem-solving
•Development of Governance Board
•Master Agreement and Contracts
•Project Formalization
•Key Performance Indicators
Legitimacy
Building
Institutional
Engagement
Mechanical Trust
Development
1
st
Order Concept 2
nd
Order Theme
Fig. 2 Initiation phase thematic analysis
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
174
S.Scott et al.
1 3
complexity this creates is inefficient and unattractive to grow an overall univer-
sity-business relationship or intent to germinate a regional entrepreneurial eco-
system. To minimize the negotiation process, the governance of the overarching
relationship, and accelerate project development and approval, the focal uni-
versity and multinational company established a ‘master agreement’ to govern
knowledge ownership, intellectual property, and technology commercialization
on a scale that covers the partner organizations rather than any one individual.
This governance approach is unusual and not standard practice but allowed the
network to grow in size and scale very quickly, sub-networks to emerge organi-
cally, and new relationships to form in fast response to new opportunities. For
example, in the first year of the relationship alone, 7 innovation projects were set
up, and over the course of the next four years, a further 55 innovation projects
were established. As an interviewee noted:
Another thing that the partner does really well is that they are really good at
bringing together all of those disparate parties and finding common ground
that everyone wanted to work together and had passion to do so. That doesn’t
always happen. – Participant 7
Apart from the transaction cost advantages, there are institutional advantages to
this form of coordination mechanism. Specifically, the master agreement contract
creates mechanical trust that simplifies new project development, allowing the focus
to shift squarely to more strategic issues rather than diverting attention to a lengthy
contract negotiation process and the micro-management of projects after that. It
deters destructive opportunism while being flexible enough to enable new collabo-
rations to form a ready governance framework. This is a further component of the
‘rules of the game’ established within the early stages of the relationship that ena-
bled far greater scope for value creation for all parties. It also lent credibility and
prestige to the relationship in its early years, encouraging more individuals (inter-
nally) to become involved in the relationship. This allowed for accelerated access
to resources and project formation and allowed both partners to respond to new
opportunities to drive growth and recruit new members (i.e., hitherto unconnected
employees for both organizations) into the relationship.For example, interviewees
observed:
One of the things that struck me is the desire to collaborate and to collaborate
on very applied science. So, that was the very first thing. In North America, I
would say that we are very big, very big country with lots of diverse ways of
operating and very diverse opinions about what universities should be about.
Whether they should be about applying the science for commercializing tech-
nology or whether they should be all about the fundamental understanding of
the science. – Participant 7
One [task] was that they shared these technology needs and they were given
under headings. One of the things that we were able to do was to spend some
time mapping where our expertise lie within each one of those themes. And
then to align the right people to talk to them about those things. That is an
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
175
1 3
Towards anetwork‑based view ofeffective entrepreneurial…
example of what we did upfront to identify where the fit was. Find common
ground, not just with the organization but with the individual. – Participant 11
I’m a businessman. What matters most to me is products on the shelf. It takes
over 6 months for other universities to get a project going. This organization is
faster. This is the model that we think we need, I am not going to come in here
and drop a check on your table, I need you to work with me to find the value
between your organization and mine. – Participant 2
Must be really buttoned up from the beginning. The thing about this is that you
are really going to need to go buy-in. Monitoring is difficult. There needed to
trust and confidence in order to get the projects running. - Participant 4
Formalizing the ecosystem occurred in Phase 2.
4.2.2 The development phase
The development phase constituted a significant effort at relationship building and
focused on building internal awareness of knowledge-based resources and trust
among the actors. This phase developed in response to the early momentum and
success of initial interactions and projects. This stage focused on establishing the
knowledge domains and effectively communicating the capacity for bringing in
additional expertise. This stage reflected a level of vulnerability and learning, which
encourages trustworthiness among the two main partner organizations. This devel-
oped knowledge-based trust, forming norms of commitment and learning through
dialogue and setting expectations (Fig.3).
Six months after the initial set up, additional members from the business
came to the university campus to discuss their research objectives and goals.
They provided a broad overview of their organization’s current challenges in
a presentation to members of the University departments. Following the pres-
entation, individual academics could submit applications that proposed vari-
ous approaches to addressing and solving those challenges. An interview par-
ticipant recalled that “Everyone had a fair chance to be involved, but only a
1
st
Order Concept 2
nd
Order Theme
•Goal Alignments
•Objective discussions and technology mappingDevelopment
Phase
•Workshops facilitated a sense of collaborative
and collective effort
•Communication patterns and routines
•Network Recruitment
•Broader Access and Knowledge Diversity
•Technology Interpretation
Normative
Behavior
Relational Trust
Development
Knowledge
Acquisition/Transfer
Fig. 3 Development phase coding procedure
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
176
S.Scott et al.
1 3
few proposals were selected.”—Participant 9 This allowed the challenges to be
refined and academics to be involved in the development of solutions.This was
the beginning of the formation of a larger entrepreneurial ecosystem. The initial
network of relationships was confined to a specific scientific area and now grew
to incorporate more diverse experts and disciplines. This cascade is important
as it grew the potential wealth creation opportunities for both parties and the
possibility for serendipitous exchange. Concurrently, actors generated a greater
sense of each other’s resources and knowledge and consolidated communication,
shared language, and goals. This step also allowed participating actors to under-
stand knowledge resources on a micro-level. A series of workshops were funda-
mental to this endeavor and serve as an initial, basic form of network orchestra-
tion that established each partners needed (and thus goals).An employee noted:
“The workshop takes the premise that a ‘stretchy’ technology can be thought of
as a platform that has enabled the company to defend and grow its position in a
market and/or enter or disrupt a market it hadn’t before.” – Participant 1.
As networks and sub-networks grew in number, the entrepreneurial ecosys-
tem itself formally took hold. Due to the new ecosystem’s burgeoning size and
scale, members needed to become aware of the knowledge content and exper-
tise available throughout. Initially, access was communicated through key gate-
keepers that acted to increase connections across the network. This eventually
translated to the members developing relationships amongst themselves, aiding
in the development of the ecosystem. The frequency of interaction between the
partners gave light to behaviors. This helped to ensure that the knowledge shar-
ing behaviors, levels of commitment, and the interpretation of the results shared
were aligned with each other’s expectations and goals.
One informant commented about an instance when the partner was working
on a technique that had previously been proven ineffective by their research.
This technique would not be sufficient for solving the challenge outlined in the
project and this member of the relationship commented that: “Although some
time was lost, the partner reacted and shared prior results.”This communica-
tion indicated vulnerability yet trustworthiness:
We had a technical issue recently where X truly thought what they wanted
to go do was the right thing to go do, but I had a difference of opinion and
I knew that my technical expert had a difference of opinion. So, then we
had the discussion and things got fixed. And things moved forward but that
can be, anytime that you are dealing with an external entity or someone,
even though we have a good relationships with them, it’s not like we work
with them every day in the same space. Participant 5
Developing knowledge- and competence-based trust, procedures and expec-
tations were essential in the Development phase. These steps led to norms of
commitment, dialogue, and improved expectations (including about frequency
of exchanges or meetings) to emerge as mechanisms to reinforce and encour-
age further collaborations. The development of normative behaviors facilitated
these shared expectations within the network, and the resources could be shared.
These steps transformed the university-business relationship from a small
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
177
1 3
Towards anetwork‑based view ofeffective entrepreneurial…
network of relationships into an ecosystem of far greater potential. The realiza-
tion of that potential and the maintenance of its success became the focus of
Phase 3.
4.2.3 The maintenance phase
The maintenance phase focused on the continual encouragement of collaborative
behaviors and knowledge support. This growth in scale had increased the complexi-
ties in managing and maintaining the ecosystem from a relational perspective. This
tipping point called for greater oversight, monitoring, and recording to capture risk
and success factors appropriately. For example, although each of the project objec-
tives and goals were crafted purposefully, the scale of the relational exchange now
at play in the ecosystem, the drawing in of new external partners, and the potential
for more purposeful collaboration across all members of the ecosystem needed a
formalized method for continued alignment (Fig.4).
This Maintenance phase focused on refining and more widely communicating the
knowledge resources embedded within the ecosystem to create value and wealth.
A necessary task was to enhance explicit knowledge stocks levels and use standard
tools to improve communication. There was also a focus on developing documents
and case studies that could be used as a platform for sharing knowledge among a
more significant number of individuals, record and report success, and increasing
the profile of this entrepreneurial ecosystem to external stakeholders. As the com-
plexity of the relationship grew, the potential impact of each organization’s activi-
ties grew. As many of the projects were built autonomously and organically, finding
common ground for analyzing (and communicating) successes became essential.
The Board’s coordination efforts set up to manage the initial relationship grew
to manage the composition and governance of the ecosystem actively. While there
was a desire to ensure that activity among members was stable, a supplementary
objective was to support resource allocation by coordinating the growing number
of internal and external participants brought into the ecosystem. As new members
1
st
Order Concept 2
nd
Order Theme
•Enhanced monitoring and reporting
•Enhanced focus on growth and continued
momentum.
•Enhanced focus on the further opport unities and
scale.
Maintenance
Phase
•Risk and success factors evaluated
•Negotiations of performa nce evaluations and
mutual benefits.
•Enhanced communication of resources
embedded within
•Distribution of explicit knowledge stocks
Formalized KPIs
Oversight
Resource Allocation
and Distribution
Fig. 4 Maintenance Phase Coding Procedure
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
178
S.Scott et al.
1 3
became involved, the Board needed to identify and delegate members to acclimate
and standardize practices.As a company representative noted:
Trust in needed to be confident in [making] investment, strong collaborations
allow [for this]. If not, there would always be hesitation. An important mecha-
nism is to build trust. But, with X it’s an opportunity trade-off to get richer
value. – Participant 1
For example, the management board recognized that a level of success from cur-
rent projects was related to the technical transfer meetings hosted once a month. The
scientific staff engaged in technical transfer meetings to discuss and problem-solve
issues on active projects.For instance:
The fellow that we are working with is a relatively new addition to the organi-
zation. Very enthusiastic to do the partnership. He actually brought some
of these ideas on how it might get additional resources on to the project. He
brought those to us and works very well with us to do that. Participant 5
However, the power of initial relationships risked the exclusion of abundant
opportunities brought by new members. For example, any network, or ecosystem
by extension, faces risks of becoming path-dependent and losing momentum during
this phase. There were concerns that management practices could be developed too
tightly and preclude collaboration—the balance between calculated risks and foster-
ing innovativeness through separating the administrative and entrepreneurial tasks
and coordinated that through a single management board. The management board
needed to ensure that the network was strategically and intentionally curated to con-
tinue building on its success. This meant accommodating a greater number of new
internal and external partners while being cognizant of their goals. Concurrently,
participation in the technical meetings, for example, was declining as junior mem-
bers oscillated out of the relationship (e.g., on project completion). Moreover, there
was evidence that people became too connected to the same individuals, reducing
their exposure to different knowledge sources, and depleting the ecosystem’s poten-
tial to sustain its vibrancy and vitality (in entrepreneurship and innovation terms).
4.2.4 The renewal phase
The entrepreneurial ecosystem had only just entered the Renewal phase. The strik-
ing aspect of our findings was how rapidly the ecosystem had evolved to this phase.
The Renewal stage emphasizes opportunity identification through new ecosystem
partners and new project proposals. In many ways, it is a corollary of the prob-
lem presented in the Maintenance phase that certain ecosystems (especially one
driven by technology and science) run this risk of path dependencies in the net-
works that underpin the vibrancy, vitality, and wealth of the ecosystem itself. This
phase was enacted in response to the evidence of stabilization within the network
and the loss of momentum that occurred as entrepreneurial and innovation projects
were completed. Prior ties became latent or dormant (a phenomenon highlighted
by Hughes and Perrons 2011). The Board and members of the relationship focused
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
179
1 3
Towards anetwork‑based view ofeffective entrepreneurial…
on rejuvenating the momentum experienced in the early phases of the ecosystem’s
development and ultimately renew and rejuvenate the ecosystem. This led to pur-
poseful attempts introducing new projects to regain lost momentum, and purposeful
recruitment of new internal and external members. At this stage, generating linkages
with new external, non-competing partners became an essential act. For example,
the partners looked to establish research consortiums with new organizations and
universities:
[We sought] to develop new application ideas for 10 well-developed technolo-
gies in the current field of application or in other fields... [and] progress tech-
nology application opportunities. – Participant 9
A final yet critical theme that emerged in this investigation was the need to con-
tinually engage with external institutional forces and continually manage legitimacy
through all network development phases. The group needed to define the necessary
tools to communicate the ‘how’ and the ‘why’ effort should be expended on devel-
opment to a broader audience, indicating that the network activity extends beyond
the partner organizations and has an impact beyond the boundaries of the relational
exchange (Fig.5).
5 Discussion andconclusions
The literature on entrepreneurial ecosystems is still in relative infancy, but a persis-
tent, albeit underappreciated theme is their effective functioning over time (Garn-
sey and Leong 2008; Beliaeva etal. 2019). Overlooking this aspect of entrepre-
neurial ecosystems has led to an excessive focus on the structure and content of
entrepreneurial ecosystem at a cost to a relational view of entrepreneurial ecosys-
tems and their governance (Aarikka-Stenroos and Ritala 2017; Kang et al. 2019;
Scott et al. 2019; Spigel 2017). This oversight has had two effects. First, policy-
makers continue to rely on importing practices seen among thriving ecosystems on
the assumption that such practices are somehow ‘best’. This has led, unwittingly,
1
st
Order Concept 2
nd
Order Theme
•Purposeful attempts to re -invigorate latent ties
•Lost momentum in scaled growth
•Consortium membershipsRenewal
•Technology mapping and stakeholder legitimacy
•Scanning the environment for fu rther
partnerships and resources.
Performance
Evaluations
Network
Reconfiguration
Opportunity
Recognition
Fig. 5 Renewal phase coding procedure
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
180
S.Scott et al.
1 3
to neglect interdependencies and behavior among actors as the vital mechanism by
which the structure and content of an ecosystem are advantaged on or not (Harrison
and Leitch 2010; Motoyama and Watkins 2014; Spigel 2017). Second, this has led
to a static treatment of how entrepreneurial ecosystems emerge from networks of
inter-organizational ties and the behaviors and the governance mechanisms needed
at each phase of its evolution to maintain the vibrancy, vitality, and wealth creation
of the ecosystem. In addressing this oversight, we shed new light on factors that are
rooted in behavior and governance instead of local conditions (Cavalo etal. 2018;
Scott etal. 2019) or the social context or ecosystem composition alone (e.g., Beli-
aeva etal. 2019; Mueller and Jungwirth 2016; Kang etal. 2019). We provide three
contributions to research on entrepreneurial ecosystems.
First, we answer Spigel’s (2017) call for a relational perspective on entrepreneur-
ial ecosystems. Departing from traditional studies, we depict entrepreneurial ecosys-
tems as consisting of multiple networks as a solution to limitations in structure- and
content-based views of ecosystems. Ecosystems present resource and knowledge
exchange opportunities and value creation, but not necessarily their access or value
realization. A failure to treat ecosystems as networks leads to the danger of treat-
ing any region with high rates of entrepreneurship as an ecosystem (Spigel 2017),
but without understanding why those regions can productively create wealth over
other regions. This deficit was apparent in our case ecosystem, where the core part-
ners originating the university-business relationship that ultimately germinated the
ecosystem could not replicate its success elsewhere. Their inability to do sat in con-
trast to structure and content ideas, both reasonable to duplicate, drawing attention
to behavior as the complicating feature (immutable and less pliable to replication).
Behavioral interaction provides an answer for how entrepreneurial actors might
enact and maintain relationships within effective entrepreneurial ecosystems and
ever-changing environments (Autio and Thomas 2013). An interaction element is
essential and reveals the role of behavior as the essential mechanism in the vitality,
vibrancy, and wealth creation of an entrepreneurial ecosystem.
Second, further departing from existing studies, we show that this behavior
is not universal but changes across phases in the evolution of an entrepreneurial
ecosystem. The importance of networks to entrepreneurial outcomes is well-doc-
umented (e.g., Hoang and Antoncic 2003; Nijkamp 2003; Stuart and Sorenson
2007). However, accessing and releasing the resources, knowledge, new rela-
tionships, finance, opportunities (among the many other purported benefits of
networks and ecosystems) is contingent on network behavior and its coordina-
tion through relational governance (Hughes etal. 2007, 2014; Kogut and Zander
1992; Rodan and Galunic 2004; Scott etal. 2019). We reveal the phases of evolu-
tion, the challenges and tipping points at each stage, and shed light on the behav-
iors and relational governance mechanisms necessary to enrich the entrepreneur-
ial ecosystem and precipitate movement to its next phase of growth. Insofar as
entrepreneurial ecosystems represent a set of interdependent actors, a structure or
content view of ecosystems sees wealth creation solely as a composition problem
(the right ‘ingredients’, for instance). However, our findings emphasize that fac-
tors must be coordinated to enable productive entrepreneurship within a particu-
lar region or territory following Stam and Spigel (2018). Building on this, what is
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
181
1 3
Towards anetwork‑based view ofeffective entrepreneurial…
apparent in our findings that networking behavior in the first two phases (Initia-
tion and Development) was driven towards establishing a common language then
innovating projects and growing connections across the emerging ecosystem to
generate internal legitimacy among partners and actors. Contract-based govern-
ance gave way to trust-based relational governance. Networking behaviors in the
next two phases (Maintenance and Renewal) led to consolidated networks that
increased the degree of redundancy, requiring the management board to orches-
trate new relationships and aggressively expand and refresh the number of actors,
especially new external partners. This indicates a significant shift in the com-
position of the network necessitated due to actors’ behavior creating unforeseen
redundancies that depleted, not enhance, entrepreneurship and innovation. The
renewal manifests as a response to that problem and, perhaps surprisingly, arrived
far faster than we expected.
Third, implicit in the findings was the formation and use of social capital to
unlock access to resources and knowledge and unlock collaborations for productive
innovation projects among partners. We conclude that a distinguishing factor of an
ecosystem versus a network is that this social capital encourages a focal network
to grow, but new sub-networks emerge that further enrich the vibrancy and vital-
ity of the ecosystem. Managing legitimacy within and amongst the various internal
and external stakeholders is essential. Scholars contend that relationships’ success
or failure depends on the existing similarities between actors and organizations. Our
findings suggest that these were necessary conditions as a catalyst for forming the
underlying university-business relationship. To be clear, our case organizations had
intended for an entrepreneurial ecosystem to emerge as a fruit of their initial collab-
oration. However, the joining of two fundamentally different organizations created
a challenge around goals, expectations, and common language as a prelude to pro-
ductive cooperative behavior among individual agents. Research supports that there
is a level of strategy development with external partners. The impact of cultural
variations between organizations can activate a tendency for uncertainty avoidance,
emphasizing the importance of alignment and relational development behaviors
(Barr and Glynn 2004). Our findings demonstrate that actions driven by common
instead of competitive interests can serve to improve conditions across several stake-
holders involved in the emerging ecosystem (Scott etal. 2019). However, the organi-
zation must then generate trust within the set of relationships it holds with another
actor or set of actors for wealth creation to materialize. The focal organizations in
our case ecosystem formed a master agreement to encourage cooperation to form,
from which trust could then develop among individuals as knowledge- and compe-
tence-based relational governance mechanisms (e.g., Zaheer and Venkatraman 1995;
Zaheer etal. 1998). While a common language and set of expectations were estab-
lished in the Initiation phase, the entrepreneurial ecosystem’s vibrancy and vital-
ity could only be maintained by managing and orchestrating the network behavior
of actors first, then supplementing the composition of the ecosystem’s membership.
Absence of behavior and structure and content considered in conjunction with each
other rather than in isolation, we detected pockets of insularity, redundancy, bottle-
necks within the system that precipitated an immediate need for ecosystem renewal.
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
182
S.Scott et al.
1 3
This forms our final contribution and provides a new understanding of the rise and
decline of an entrepreneurial ecosystem over time.
Collectively, our contributions provide fundamental building blocks for a theory
and conceptualization of a network-based view of entrepreneurial ecosystem sensi-
tive to how behavior and governance must change during the phases of ecosystem
evolution.
5.1 Limitations andfuture research
The opportunity to conduct a longitudinal, in-depth study of a single entrepreneur-
ial ecosystem and its foremost actors and partners offered significant opportunities
to understand an entrepreneurial ecosystem’s evolution and effectiveness. How-
ever, some limitations impinge on the work. First, our focus on a single entrepre-
neurial ecosystem prevents us from deriving additional insights and conclusions
on its wider theoretical generalizability to ecosystems of different forms, composi-
tion, or purpose, or territory. Second, the data collection techniques and analyses
within this study followed a robust research design, allowing for a multilevel tri-
angulation opportunity. However, questions remain about whether the findings will
repeat across other contexts and which of those findings are embedded within the
‘local’ ecosystem only. Third, our design foregoes the possibility of a cross-case
analysis to explore similarities or differences in our findings. We attenuated this
matter by acquiring insights into how the failed attempts of the focal university-
business partnership at the heart of this entrepreneurial ecosystem replicate their
success in other territories. Therefore, we have some confidence that our insights
help justify the relational dimension as central to the unique wealth-creating power
of an entrepreneurial ecosystem in line with the failure of policymakers to import
successful so-called best practices seen among thriving ecosystems (Harrison and
Leitch 2010; Motoyama and Watkins 2014; Spigel 2017). We contend that omitting
behavior, governance, and the interdependencies among actors explain this failure.
Further research is needed to contemplate this problem further. Fourth, our analysis
of the case entrepreneurial ecosystem’s evolution identified distinct phases and tip-
ping points in which it was necessary to establish legitimacy with internal and exter-
nal stakeholders. As this emerged organically from our data in post data collection
analyses, we did not investigate this phenomenon more thoroughly. We recommend
that future investigations directly adopt legitimacy theory to analyze the challenges
of legitimizing the entrepreneurial ecosystem more broadly to internal and external
stakeholders and the longitudinal functioning of this phenomenon.
Open Access This article is licensed under a Creative Commons Attribution 4.0 International License,
which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as
you give appropriate credit to the original author(s) and the source, provide a link to the Creative Com-
mons licence, and indicate if changes were made. The images or other third party material in this article
are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the
material. If material is not included in the article’s Creative Commons licence and your intended use is
not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
183
1 3
Towards anetwork‑based view ofeffective entrepreneurial…
directly from the copyright holder. To view a copy of this licence, visit http://creat iveco mmons .org/licen
ses/by/4.0/.
References
Aarikka-Stenroos L, Ritala P (2017) Network management in the era of ecosystems: systematic review
and management framework. Ind Mark Manag 67:23–36
Adler P, Kwon S (2002) Social capital: prospects for a new concept. Acad Manag Rev 27(1):17–40
Aldrich H, Zimmer C (1986) Entrepreneurship through social networks. In: Sexton DL, Smiler RW (eds)
The art and science of entrepreneurship. Ballinger, Cambridge, pp 3–23
Allen P, Strathem M (2003) Evolution, emergence, and learning in complex systems. Emergence
5(4):8–33
Autio E, Thomas L (2013) Innovation ecosystems: implications for innovation management? In: Dodgson
M, Phillips N, Gann DM (eds) The Oxford handbook of innovation management. Oxford Univer-
sity Press, Oxford
Barr PS, Glynn MA (2004) Cultural variations in strategic issue interpretation: relating cultural uncer-
tainty avoidance to controllability in discriminating threat and opportunity. Strateg Manag J
25:59–67
Beliaeva T, Ferasso M, Kraus S, Damke E (2019) Dynamics of digital entrepreneurship and the innova-
tion ecosystem: a multilevel perspective. Int J Entrep Behav Res. https ://doi.org/10.1108/IJEBR
-06-2019-0397
Bluedorn AC, Johnson RA, Cartwright DK, Barringer BR (1994) The interface and convergence of the
strategic management and organizational environment domains. J Manag 20(2):201–262
Bock G, Zmud R, Kim Y, Lee J (2005) Behavioral intention formation in knowledge sharing: examining
the roles of extrinsic motivators, social-psychological forces, and organizational climate. MIS Q
29(1):87–111
Bouncken R, Fredrich V, Kraus S (2020) Configurations of firm-level value capture in coopetition. Long
Range Plan 53(1):101869
Breitenecker R, Harms R, Weyh A, Maresch D, Kraus S (2016) When the difference makes a differ-
ence—the regional embeddedness of entrepreneurship. Entrep Reg Dev 29:71–93
Bryman A (2001) Social research methods. Oxford University Press, Oxford
Carrington P, Scott J (2011) The Sage handbook of social network analysis. Sage Publishers, London
Carmeli A, Azeroual B (2009) How relational capital and knowledge combination capability enhance the
performance of work units in a high technology industry. Strateg Entrep J 3:85–103. https ://doi.
org/10.1002/sej.63
Cavalo A, Ghezzi A, Balocco R (2018) Entrepreneurial ecosystem research: present debates and future
directions. Int Entrep Manag J. https ://doi.org/10.1007/s1136 5-018-0526-3
Chang SJ, Chung C, Mahmood I (2006) When and how does business group affiliation promote firm
innovation? A tale of two emerging economies. Organ Sci 17(5):637–656
Chesbrough H (2003) Open innovation: the new imperative for creating and profiting from technology.
Harvard Business Review Press, Boston
Chesbrough H, Vanhaverbeke W, West J (2006) Open innovation: researching a new paradigm. Oxford
University Press, Oxford
Chesbrough H (2007) Open business models: how to thrive in the innovation, landscape. Harvard Busi-
ness Review Press, Boston
Creswell J (2009) Research design: qualitative, quantitative, and mixed methods approaches, 3rd edn.
Sage, Thousand Oaks
Cross R, Parker A (2004) The hidden power of social networks. Harvard Business School Press, Boston
Daata A (2011) Review and extension on ambidexterity: a theoretical model integrating networks and
absorptive capacity. J Manag Strategy 2(1):2–22
Davidson P, Delmar F, Wiklund J (2006) Entrepreneurship and the growth of firms. Edward Elgar Pub-
lishing, Cheltenham
Dyer J, Hatch N (2004) Using supplier networks to learn faster. MIT Sloan Manag Rev 2004:57–63
Eisenhardt KM (1989) Building theories from case study research. Acad Manag Rev 14(4):532
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
184
S.Scott et al.
1 3
Faria A, Wensley R (2002) In search of ‘interfirm management’ in supply chains: recognizing contradic-
tions of language and power by listening. J Bus Res 55:603–610
Ferreira J, Fernandes C, Kraus S (2019) Entrepreneurship research: mapping intellectual structures and
research trends. RMS 13:181–205. https ://doi.org/10.1007/s1184 6-017-0242-3
Feldman M, Florida R (1994) The geographic sources of innovation: technological infrastructure and
product innovation in the United States. Assoc Am Geogr 84(2):210–229
Feldman MP, Francis JL (2004) Homegrown solutions: fostering cluster formation. Econ Dev Q
18(2):127–137
Garnsey E, Leong YY (2010) Combining resource-based and evolutionary theory to explain the genesis
of bio-networks. Ind Innov 15(6):669–686
Ganseen S, Hess R (1997) Dimensions and levels of trust: implications for commitment to a relationship.
Mark Lett 8(4):439–448
Gephart R (2004) From the editors: qualitative research and the Academy of Management Journal. Acad
Manag J 47(4):454–462
Gioia D, Corley K, Hamilton A (2013) Seeking qualitative rigor in inductive research: notes on the Gioia
methodology. Organ Res Methods 16(1):15–31
Glaser B, Strauss A (1967) The discovery of grounded theory: strategies for qualitative research. Sociol-
ogy Press, Mill Valley
Glass G (1976) Primary, secondary, and meta-analysis of research. Am Educ Res Assoc 5(10):3–8
Gold R (1958) Roles in the sociological field observations. Soc Forces 36(3):217–223
Granovetter M (1973) The strength of weak ties. Am J Sociol 78:1360–1380
Gulati R (1995) Does familiarity breed trust? The implications of repeated ties for contractual choice in
alliances. Acad Manag J 38(1):85–112
Hanneman R, Riddle M (2005) Introduction to social network methods. University of California,
Riverside
Hansen M, Podolny J, Pfeffer J (2001) So many ties, so little time: a task contingency perspective on cor-
porate social capital in organizations. Soc Capital Organ 18:21–57
Harrison R, Leitch C (2010) Voodoo institution or entrepreneurial university? Spin-off companies, the
entrepreneurial system and regional development in the UK. Reg Stud 44(9):1241–1262
Herzog P, Leker J (2010) Open and closed innovation: different innovation cultures for different innova-
tion strategies. Int J Technol Manag 52:322–343
Hoang H, Antoncic B (2003) Network-based research in entrepreneurship: a critical review. J Bus Ventur
18(2):165–187
Huemer L (2014) Creating cooperative advantage: the roles of identification, trust, and time. Ind Mark
Manag 13:564–672
Hughes M, Ireland R, Morgan R (2007) Stimulating dynamic value: social capital and business incuba-
tion as a pathway to competitive success. Long Range Plan 40:154–177
Hughes M, Hughes P, Morgan RE, Hodgkinson IR, Lee Y (2020) Strategic entrepreneurship behaviour
and the innovation ambidexterity of young technology-based firms in incubators. Int Small Bus J.
https ://doi.org/10.1177/02662 42620 94377 6
Hughes M, Morgan R, Ireland R, Hughes P (2014) Social capital and learning advantages: a problem of
absorptive capacity. Strateg Entrep J 8:214–233
Hughes M, Perrons K (2011) Shaping and reshaping social capital in buyer-supplier relationships. J Bus
Res 64:164–171
Huizingh EKRE (2011) Open innovation: state of the art and future perspectives. Technovation 31:2–9
Inkpen A, Tsang E (2005) Social capital, networks, and knowledge transfer. Acad Manag Rev
30(1):146–165
Isaksen A (2016) Cluster emergence: combing pre-existing conditions and triggering factors. Entrep Reg
Dev 28(9–10):704–723
Isaksen A (2018) From success to failure, the disappearance of clusters: a study of a Norwegian boat-
building cluster. Camb J Reg Econ Soc 11:241–255
Jones C, Hesterly W, Borgatti S (1997) A general theory of network governance: exchange conditions and
social mechanisms. Acad Manag Rev 22:911–945
Kadushin C (2012) Understanding social networks: theories, concepts, and findings. Oxford University
Press, Oxford
Kale P, Singh H, Perlmutter H (2000) Learning and protection of proprietary assets in strategic alliances:
building relational capital. Strateg Manag J 21:217–237
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
185
1 3
Towards anetwork‑based view ofeffective entrepreneurial…
Kang Q, Li H, Cheng Y, Kraus S (2019) Entrepreneurial ecosystems: analyzing the status quo. Knowl
Manag Res Pract. https ://doi.org/10.1080/14778 238.2019.17019 64
Kapoor R, Lee J (2013) Coordinating and competing in ecosystems: how organizational forms shape new
technology investments. Strateg Manag J 34(3):274–296. https ://doi.org/10.1002/smj.2010
Keupp M, Gassman O (2009) Determinants and archetype users of open innovation. R&D Manag
39(4):331–341
Kim KK, Park SH, Ryoo SY, Park SK (2010) Inter-organizational cooperation in buyer-supplier relation-
ships: both perspectives. J Bus Res 63:863–869
Kogut B, Zander U (1992) Knowledge of the firm, combinative capabilities, and the replication of tech-
nology. Organ Sci 3(3):383–396
Koka B, Prescott J (2002) Strategic alliances as social capital: a multidimensional view. Strateg Manag J
23:795–816
Kwon S-W, Heflin C, Ruef M (2013) Community social capital and entrepreneurship. Am Sociol Rev
78(6):980–1008. https ://doi.org/10.1177/00031 22413 50644 0
Larson A (1992) Network dyads in entrepreneurial settings: a study of the governance of exchange rela-
tionships. Adm Sci Q 37:76–104
Li M, Goetz S, Partridge M, Fleming D (2015) Location determinants of high-growth firms. Entrep Reg
Dev 28:97–125
Makadok R (2003) Doing the right thing and knowing the right thing to do: why the whole is greater than
the sum of its parts. Strateg Manag J 24:1043–1055
Mason C, Brown R (2013) Creating good public policy to support high-growth firms. Small Bus Econ
40(2):211–225
Mazzucato M, Robinson D (2018) Co-creating and directing innovation ecosystems? NASA’s chang-
ing approach to public-private partnerships in low-earth orbit. Technol Forecast Soc Change
136:166–177
McEvily B, Zaheer A (1999) Bridging ties: a source of firm heterogeneity in competitive capabilities.
Strateg Manag J 20:1133–1156
Mezias S, Kuperman J (2001) The community dynamics of entrepreneurship: the birth of the American
film industry, 1895–1929. J Bus Ventur 16(3):209–233
Miles M, Huberman M (1994) Qualitative data analysis: a sourcebook of new methods. Sage Publica-
tions, London
Mooi EA, Frambach RT (2012) Encouraging innovation in business relationships—a research note. J Bus
Res 65:1025–1030
Motoyama, Y. & Watkins, K. Examining the connections within the start up ecosystem. Kauffman
Research Series on City, Metro, and Regional Entrepreneurship (2014).
Mueller E, Jungwirth C (2016) What drives the effectiveness of industrial clusters? Exploring the impact
of contextual, structural, and functioning determinants. Entrep Reg Dev 28(5–6):242–447
Myer A, Goes J (1988) Organizational acclimations of innovations: a multilevel contextual analysis. Acad
Manag 31(4):897–923
Nahapiet J, Ghoshal S (1998) Social capital, intellectual capital, and the organizational advantage. Acad
Manag Rev 23(2):242–266
Ng T, Feldman D (2010) The effects of organizational embeddedness on development of social capital
and human capital. J Appl Psychol 95(4):696–712
Nijkamp P (2003) Entrepreneurship in a modern network economy. Reg Stud 37(4):395–405. https ://doi.
org/10.1080/00343 40032 00007 4424
Nonaka I (1994) A dynamic theory of organizational knowledge creation. Organ Sci 5(1):14–37
Oerlemans L, Meeus M, Boekema F (2001) Firm clustering and innovation: determinants and effects.
Reg Sci 80(3):337–356
Owen-Smith J, Powell W (2004) Knowledge networks as channels and conduits: the effects of spillovers
in the Boston Biotechnology Community. Organ Sci 15(1):5–21
Pentland A (2014) Social physics: how good ideas spread—the lessons from new science. Penguin Pub-
lishers, New York
Perez-Luno A, Medina CC, Lavado AC, Rodriguez GC (2011) How social capital and knowledge affect
innovation. J Bus Res 64:1369–1376
Pilinkienė V, Mačiulis P (2014) Comparison of different ecosystem analogies: the main economic deter-
minants and levels of impact. Procedia Soc Behav Sci 156:365–370
Prell C (2011) Social network analysis: history, theory, methodology. Sage Publishing, London
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
186
S.Scott et al.
1 3
Powell W (1990) Neither market or hierarchy: network forms of organization. Res Organ Behav
12:295–336
Powell TC (2002) The philosophy of strategy. Strateg Manag J 23:873–880. https ://doi.org/10.1002/
smj.254
Rapp D, Olbrich M (2020) Our predictive entrepreneurial action in uncertain, ill-structured conditions.
RMS. https ://doi.org/10.1007/s1184 6-020-00411 -2
Reagans R, McEvily B (2003) Network structure and knowledge transfer: the effects of cohesion and
range. Adm Sci Q 48:240–267
Robertson P, Casali G, Jacobson D (2012) Managing open incremental process innovation: absorptive
capacity and distributed learning. Res Policy 41:822–832
Rodan S, Galunic C (2004) More than network structure: how knowledge heterogeneity influences mana-
gerial performance and innovativeness. Strateg Manag J 25:541–562
Rothwell R (1994) Toward the fifth-generation innovation process. Int Mark Rev 11:7–31
Russell M, Smorodinskaya N (2018) Leveraging complexity for ecosystemic innovation. Technol Fore-
cast Soc Change 136(c):114–131
Scarigella L, Radziwon A (2017) Innovative entrepreneurial business ecosystems: old wine in new bot-
tles. Technol Forecast Soc Change 136:59–87
Schutjens V, Völker B (2010) Space and social capital: the degree of locality in entrepreneurs’ contacts
and its consequences for firm success. Eur Plan Stud 18(6):941–963. https ://doi.org/10.1080/09654
31100 37014 80
Schwartz MS, Schwartz CG (1955) Problems in participant observation. Am J Sociol 4(4):343–353
Scott S, Hughes M, Kraus S (2019) Developing relationships in innovation clusters. Entrep Reg Dev
31:22–45
Schepis D, Purchase S, Ellis N (2014) Network position and identity: a language-based perspective on
strategizing. Ind Mark Manag 43(4):582–591
Schroder D (2020) Without actors there is no action: how interpersonal interactions explain routine
dynamics. RMS. https ://doi.org/10.1007/s1184 6-020-00408 -x
Sedita S (2008) Inter-personal and inter-organizational networks in the performing arts. Ind Innov
15(5):493–511
Shah R, Swaminathan V (2008) Factors influencing partner selection in strategic alliances: the moderat-
ing role of alliance context. Strateg Manag J 29:471–494
Siggelkow N (2007) Persuasion with case studies. Acad Manag J 50:20–24
Silverman D (1993) Interpreting qualitative data: methods for analyzing talk, text, and interaction. Sage
Publications, Thousand Oaks
Silverman D (2015) Interpreting qualitative data. Sage Publications, London
Sisodiya SR, Johnson JL, Gregoire Y (2013) Inbound open innovation for enhanced performance: ena-
blers and opportunities. Ind Mark Manag 42:836–849
Spigel B (2017) The relational organization of entrepreneurial ecosystems. Entrep Theory Pract 41:49–72
Stam E, Spigel B (2018) Entrepreneurial ecosystems. In: Blackburn R, De Clercq D, Heinonen J (eds)
The SAGE handbook of small business and entrepreneurship. Sage, London
Strauss A, Corbin J (1990) Basics of qualitative research: grounded theory procedures and techniques.
Sage Publications, Thousand Oaks
Stuart T, Sorenson O (2007) Strategic networks and entrepreneurial ventures. Strateg Entrep J
1(3–4):211–227
Sun SL, Zhang Y, Cao Y, Dong J, Cantwell J (2019) Enriching innovation ecosystems: the role of govern-
ment in a university science park. Glob Transit 1:104–119
The Wilson Review (2012) A review of business-university collaboration. Department for Business,
Innovation and Skills, London
Uyarra E, Ramlogan R (2016) The impact of cluster policy on innovation. In: Edler J, Cunningham P,
Gök A, Shapira P (eds) Handbook of innovation policy impact. Edward Elgar Publishing, Chelten-
ham, pp 196–238
Van de Ven AH (2007) Engaged scholarship: a guide for organizational and social research. Oxford Uni-
versity Press, Oxford
Valkokari K (2015) Business, innovation, and knowledge ecosystems: how they differ and how to survive
and thrive with them. Technol Innov Manag Rev 5(8):17–24
Wasserman S, Faust K (1994) Social network analysis. Cambridge University Press, New York
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
187
1 3
Towards anetwork‑based view ofeffective entrepreneurial…
Wasserman S, Robins G (2005) An introduction to random graphs and p*. In: Carrington PJ, Scott J,
Wasserman S (eds) Models and methods in social network analysis. Cambridge University Press,
Cambridge
Xu G, Wu Y, Minshall T, Zhou Y (2018) Exploring innovation ecosystems across science, technology,
and business: a case of 3d printing in China. Technol Forecast Soc Change 136:208–221
Yin RK (1994) Case study research: design and methods, 2nd edn. Sage Publications, Thousand Oaks
Yin RK (2013) Case Study Research: Design and Methods: Applied Social Research Methods. Sage Pub-
lications, Thousand Oaks, CA
Yin M, Hughes M, Hu Q (2020) Entrepreneurial orientation and new venture resource acquisition: why
context matters. Asia Pac J Manag. https ://doi.org/10.1007/s1049 0-020-09718 -w
Zaheer A, McEvily B, Perrone V (1998) Does trust matter? Exploring the effects of inter-organizational
and interpersonal trust on performance. Organ Sci 9(2):141-159
Zaheer A, Venkatraman N (1995) Relational governance as an inter-organizational strategy: an empirical
test of the role of trust in economic exchange. Strateg Manag J 16:373–392
Zardini A, Ricciardi F, Bullini Orlandi L (2020) Business networks as breeding grounds for entrepre-
neurial options: organizational implications. RMS 14:1029–1046
Publisher’s Note Springer Nature remains neutral with regard to jurisdictional claims in published
maps and institutional affiliations.
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
1.
2.
3.
4.
5.
6.
Terms and Conditions
Springer Nature journal content, brought to you courtesy of Springer Nature Customer Service Center
GmbH (“Springer Nature”).
Springer Nature supports a reasonable amount of sharing of research papers by authors, subscribers
and authorised users (“Users”), for small-scale personal, non-commercial use provided that all
copyright, trade and service marks and other proprietary notices are maintained. By accessing,
sharing, receiving or otherwise using the Springer Nature journal content you agree to these terms of
use (“Terms”). For these purposes, Springer Nature considers academic use (by researchers and
students) to be non-commercial.
These Terms are supplementary and will apply in addition to any applicable website terms and
conditions, a relevant site licence or a personal subscription. These Terms will prevail over any
conflict or ambiguity with regards to the relevant terms, a site licence or a personal subscription (to
the extent of the conflict or ambiguity only). For Creative Commons-licensed articles, the terms of
the Creative Commons license used will apply.
We collect and use personal data to provide access to the Springer Nature journal content. We may
also use these personal data internally within ResearchGate and Springer Nature and as agreed share
it, in an anonymised way, for purposes of tracking, analysis and reporting. We will not otherwise
disclose your personal data outside the ResearchGate or the Springer Nature group of companies
unless we have your permission as detailed in the Privacy Policy.
While Users may use the Springer Nature journal content for small scale, personal non-commercial
use, it is important to note that Users may not:
use such content for the purpose of providing other users with access on a regular or large scale
basis or as a means to circumvent access control;
use such content where to do so would be considered a criminal or statutory offence in any
jurisdiction, or gives rise to civil liability, or is otherwise unlawful;
falsely or misleadingly imply or suggest endorsement, approval , sponsorship, or association
unless explicitly agreed to by Springer Nature in writing;
use bots or other automated methods to access the content or redirect messages
override any security feature or exclusionary protocol; or
share the content in order to create substitute for Springer Nature products or services or a
systematic database of Springer Nature journal content.
In line with the restriction against commercial use, Springer Nature does not permit the creation of a
product or service that creates revenue, royalties, rent or income from our content or its inclusion as
part of a paid for service or for other commercial gain. Springer Nature journal content cannot be
used for inter-library loans and librarians may not upload Springer Nature journal content on a large
scale into their, or any other, institutional repository.
These terms of use are reviewed regularly and may be amended at any time. Springer Nature is not
obligated to publish any information or content on this website and may remove it or features or
functionality at our sole discretion, at any time with or without notice. Springer Nature may revoke
this licence to you at any time and remove access to any copies of the Springer Nature journal content
which have been saved.
To the fullest extent permitted by law, Springer Nature makes no warranties, representations or
guarantees to Users, either express or implied with respect to the Springer nature journal content and
all parties disclaim and waive any implied warranties or warranties imposed by law, including
merchantability or fitness for any particular purpose.
Please note that these rights do not automatically extend to content, data or other material published
by Springer Nature that may be licensed from third parties.
If you would like to use or distribute our Springer Nature journal content to a wider audience or on a
regular basis or in any other manner not expressly permitted by these Terms, please contact Springer
Nature at
onlineservice@springernature.com
Content uploaded by Stephanie Scott
Author content
All content in this area was uploaded by Stephanie Scott on Feb 04, 2021
Content may be subject to copyright.
Content uploaded by Stephanie Scott
Author content
All content in this area was uploaded by Stephanie Scott on Jan 27, 2021
Content may be subject to copyright.
