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Accelerator Expertise: Understanding the Intermediary Role of Accelerators in the Development of the Bangalore Entrepreneurial Ecosystem

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Accelerator Expertise: Understanding the Intermediary Role of Accelerators in the Development of the Bangalore Entrepreneurial Ecosystem

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To understand the intermediary role of accelerators in the developing regional entrepreneurial ecosystem of Bangalore, we analyze data from 54 interviews with accelerator graduates, accelerator managers, and other ecosystem stakeholders, and from 49 websites, 13 online video interviews, 26 online news sources and 301 pages of policy documents. Specifically, we adopt a socially-situated entrepreneurial cognition approach to theorize how accelerator expertise, existing at a meso-level, intermediates between (micro-level) founders and the (macro-level) ecosystem. In our model, four types of accelerator expertise—connection, development, coordination, and selection—together increase stakeholders’ commitment to the entrepreneurial ecosystem, leading to venture validation (success or failure) and ecosystem additionality. These findings indicate that accelerators contribute to ecosystems in a way that is distinct from, but supportive of, building individual ventures. http://onlinelibrary.wiley.com/doi/10.1002/sej.1281/abstract
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ACCELERATOR EXPERTISE:
UNDERSTANDING THE INTERMEDIARY ROLE OF ACCELERATORS IN THE
DEVELOPMENT OF THE BANGALORE ENTREPRENEURIAL ECOSYSTEM
Ketan Goswami*
Richard Ivey School of Business
University of Western Ontario
1255 Western Road
London, ON N6G 0N1, Canada
kgoswami.phd@ivey.ca
J. Robert Mitchell
Richard Ivey School of Business
University of Western Ontario
1255 Western Road
London, ON N6G 0N1, Canada
rmitchell@ivey.uwo.ca
Suresh Bhagavatula
Indian Institute of Management, Bangalore
Bannerghatta Road, Bangalore, India
Pin Code: 560 076
suresh.bhagavatula@iimb.ernet.in
Keywords: Accelerators, entrepreneurial ecosystems, entrepreneurial expertise, ecosystem
intermediation
* Corresponding author ABSTRACT
Research summary
To understand the intermediary role of accelerators in the developing regional entrepreneurial
ecosystem of Bangalore, we analyze data from 54 interviews with accelerator graduates,
accelerator managers, and other ecosystem stakeholders, and from 49 websites, 13 online video
interviews, 26 online news sources and 301 pages of policy documents. Specifically, we adopt a
socially-situated entrepreneurial cognition approach to theorize how accelerator expertise,
existing at a meso-level, intermediates between (micro-level) founders and the (macro-level)
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This article has been accepted for publication and undergone full peer review but has not
been through the copyediting, typesetting, pagination and proofreading process, which
may lead to differences between this version and the Version of Record. Please cite this
article as doi: 10.1002/sej.1281
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ecosystem. In our model, four types of accelerator expertise—connection, development,
coordination, and selection—together increase stakeholders’ commitment to the entrepreneurial
ecosystem, leading to venture validation (success or failure) and ecosystem additionality. These
findings indicate that accelerators contribute to ecosystems in a way that is distinct from, but
supportive of, building individual ventures.
Managerial summary
Accelerators are a new form of entrepreneurial support organization. These organizations
typically focus on developing individual start-ups, but we find that they also help develop
entrepreneurial ecosystems. They do so by acting as a bridge between start-ups and the broader
entrepreneurial environmental resources, by 1) helping form connections, 2) helping develop
individual start-ups, 3) helping coordinate the right match among the various players in the
ecosystem, and 4) helping select mentors and founders with the appropriate motivation and
knowledge. As these accelerators apply this expertise in this go-between role, they help build
commitment to the broader ecosystem. Furthermore, they enable success (or fast failure) of
individual start-ups and do so in a way that develops the overall entrepreneurial capacity of the
broader entrepreneurial ecosystem.
Silicon Valley’s entrepreneurs failed to recognize the connection between the institutions they
had built and their commercial success … What appeared to both actors and the outside world
to be the outcome of individual entrepreneurial achievement and competitive markets was in
fact the result of a complex, highly social process rooted in an industrial community (Saxenian,
1994: 56-57).
INTRODUCTION
Notwithstanding the heroic portrayals of individual founders (e.g., Steve Jobs) or individual
firms (e.g., Google), research supports an “ecosystem”-based view of entrepreneurship (Adner
and Kapoor, 2010; Autio and Thomas, 2014; Moore, 1993). This view takes into account the
dynamic interplay between macro-institutional factors and micro-individual actions (Van De
Ven, 1993). As Saxenian (1994) highlighted, institutions situated in such broader ecosystems
influence the success of entrepreneurial ventures. Past research has demonstrated the importance
of institutions such as universities, incubators and government agencies in connecting various
actors in an ecosystem (see Etzkowitz, 2008). Beginning with the establishment of YCombinator
in 2005, accelerators represent another emerging institution that can play a transformative role in
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the development of ventures and entrepreneurial ecosystems (Cohen and Hochberg, 2014;
Gonzalez-Uribe and Leatherbee, 2015; Pauwels et al., 2016).
Because accelerators are a nascent phenomenon in entrepreneurship (Cohen, 2013b), much
of the recent research has sought to understand what they are, what they do and whether they
deliver on the promise to accelerate ventures (Hallen, Bingham and Cohen, 2014). Accelerators
have been defined as “fixed-term, cohort-based programs, including mentorship and educational
components, that culminate in a public pitch event, often referred to as a ‘demo-day’” (Cohen
and Hochberg, 2014: 4). They are distinct from the broader policy tool known as Technology
Business Incubation (TBI), which generally focuses on promoting technology transfer and
diffusion of products, and which may or may not use accelerators as one of the many
mechanisms for meeting these goals (Lamine et al., 2016; Mian, Lamine and Fayolle, 2016). For
example, science parks and university technology transfer departments may also serve this
purpose (Mian et al., 2016). Accelerators are further distinct from incubators in their structure
and focus (see Cohen, 2013b; Pauwels et al., 2016). While incubator participation is often longer
in duration, not necessarily competitive and is often funded through rental income or government
funding for non-profits (Cohen, 2013a; Mason and Brown, 2014), the general purposes of
accelerators include: (1) “identification of investment opportunities”, (2) “matching [of]
customers with start-ups” and (3) “stimulation of start-up activity and economic development”
(Clarysse, Wright and Van Hove, 2016; Pauwels et al., 2016: 8).
Despite significant progress toward understanding the structural (what) elements of
accelerators—such as their components (Cohen, 2013b; Gonzalez-Uribe and Leatherbee, 2015;
Mejia and Gopal, 2015) and purposes (Clarysse, Wright and VanHove, 2015; Yusubova and
Clarysse, 2016)—there remains a limited understanding of their process (how) elements (see
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Yusubova and Clarysse, 2016). Specifically, there is limited understanding regarding how
accelerators can simultaneously develop both entrepreneurial ventures and regional
entrepreneurial ecosystems (see Cohen and Hochberg, 2014)? Further, while there is extensive
research on incubators’ role in developing entrepreneurial ecosystems (Clarysse et al., 2005; Dutt
et al., 2016; Mian, 1997; Phan, Siegel and Wright, 2005), there is limited research addressing
accelerators’ role in developing entrepreneurial ecosystems (see Clarysse et al., 2016).
In this paper, we adopt a process-focused lens and an interpretive qualitative approach
(Denzin and Lincoln, 2005) to develop an inductive model (Strauss and Corbin, 1990) that
explores the role of accelerators in the development of a regional entrepreneurial ecosystem.
Because cognitive approaches have been found to be helpful in understanding entrepreneurial
ecosystems (Nambisan and Baron, 2013), we turn to dynamic socially-situated cognition
(Mitchell, Randolph-Seng and Mitchell, 2011; Smith and Semin, 2004) as a way of
understanding the cognitive underpinnings of the intermediation processes (Howells, 2006;
Kistruck et al., 2013), that accelerators can facilitate.
We thus address two primary research questions: (1) how do accelerators affect venture
success or failure? and (2) how do accelerators affect regional entrepreneurial ecosystems? Our
answers build on a model by Smith et al. (2009) that extends expert information processing
theory to inform the interrelationships between analogous constructs at multiple levels of
analysis (individual level and economy level) (Chan, 1998). Specifically, we embed accelerators
at the meso-level of analysis as a way of understanding their socially-situated role (Mitchell et
al., 2011; Smith and Semin, 2004) in ecosystem intermediation. This allows us to better
understand how accelerators act as a socially-situated cognitive bridge between the “individual”
and the individual’s “context” (see Autio et al., 2014).
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Through inductive research involving 54 interviews and a variety of published sources we
aim to make three contributions. First, we contribute to the emerging literature on accelerators by
elucidating “how” accelerators help develop ventures at the micro-level, increase commitment to
the regional entrepreneurial ecosystem at the meso-level, and help develop ecosystems at the
macro-level. Second, we contribute to the growing area of research that investigates the
underpinnings of entrepreneurial ecosystems by highlighting the role accelerators can play in
affecting performance outcomes related to venture validation (success or failure) as well as the
development of the regional entrepreneurial ecosystem. Third, we contribute to entrepreneurial
cognition research by offering a deeper understanding of the cognitive underpinnings of the
socially-situated ecosystem intermediation processes that support such performance outcomes.
THEORETICAL UNDERPINNINGS
Entrepreneurial ecosystems
As the earlier Saxenian (1994) quotation illustrates, although individuals and markets matter,
every “industrial community” contains complex social processes that also shape the outcomes of
micro-level entrepreneurial action. To capture this complexity, scholars have called for more
dynamic approaches to studying entrepreneurial processes (Phan et al., 2005; Smith et al., 2009;
Van De Ven, 1993). Research along these lines included the initial work of Moore (1993) on
business ecosystems, which in turn led to research on the importance of innovation ecosystems
(Autio and Thomas, 2014; Nambisan and Baron, 2013) and regional entrepreneurial ecosystems
(Ács, Autio and Szerb, 2014; Parthasarathy and Ranganathan, 2011). Mason and Brown (2014:
5) defined an entrepreneurial ecosystem as: “a set of interconnected entrepreneurial actors …
institutions … and entrepreneurial processes which formally and informally coalesce to connect,
mediate, and govern the performance within the local entrepreneurial environment.” In turn,
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entrepreneurial ecosystems support the emergence of new firms through “the incessant formation
of a multitude of specialized, diverse entities which feed off, support, and interact with one
another” (Bahrami and Evans, 1995: 63). Thus, ecosystem-based views of entrepreneurship
reflect a dynamic and socially complex aspect of action and interaction in the entrepreneurial
process.
Socially situated cognition and expertise
Another stream of research that emerged to address dynamic aspects of action focused on
entrepreneurial cognition, or “the knowledge structures that people use to make assessments,
judgments, or decisions involving opportunity evaluation, venture creation, and growth”
(Mitchell et al., 2002: 97). Representing a variety of “complementary” perspectives that “spring
from common roots” (Mitchell et al., 2007: 7), this research primarily includes: (1) the
heuristics-based approach (e.g., Busenitz and Barney, 1997; Katz, 1992), (2) the perception/
entrepreneurial alertness-based approach (e.g., Busenitz, 1996; Gaglio and Katz, 2001), (3) the
information-processing/ expertise-based approach (e.g., Baron and Henry, 2010; Mitchell and
Chesteen, 1995), and (4) the effectuation-based approach (e.g., Sarasvathy, 2001). In this paper,
we apply the information-processing/ expertise-based approach to explore how entrepreneurial
processes are shaped by their situated context (Ucbasaran, Westhead and Wright, 2001).
Specifically, we apply a process-focused entrepreneurial cognition lens that moves away from
“seemingly static representations of abstract, disembodied cognitive structures (e.g., biases,
heuristics, scripts, etc.)” toward a view of entrepreneurial cognition as embedded “within
specific social situations, with specific social actors” (Mitchell et al., 2011: 774-775).
The socially-situated theoretical model that we adopt links entrepreneurial expertise,
entrepreneurial commitment and new value creation through the commitment engagement
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process: “the process whereby cognition affects … commitment” (Smith et al., 2009: 822).
Similar to Smith et al., we view commitment as “a definable point in the value creation process”
that “impels . . . a course of action” (2009: 820-821) and does so in a way that persists over time
(Ghemawat, 1991: 14). Likewise, similar to Smith et al. (2009) we seek to understand how
entrepreneurial expertise can lead to entrepreneurial commitment, which can lead to new value
creation; but we do so primarily at the meso-level of analysis (House, Rousseau and Thomas-
Hunt, 1995 ). Specifically, we see entrepreneurial accelerators as playing a key intermediary role
in linking founders to their regional entrepreneurial ecosystems. This happens as accelerator
expertise is applied to building commitment (see Gioia and Manz, 1985) through a meso-level
commitment engagement intermediation process. This compositionally similar process1 (Chan,
1998) represents a type of “cognitive coordination” (Foss and Lorenzen, 2009: 1202), with
accelerators acting at the meso-level as socially-situated ecosystem intermediaries (see Gioia and
Manz, 1985) between founders at the micro-level and the regional entrepreneurial ecosystem at
the macro-level.
Ecosystem intermediaries
In essence, intermediation represents a process that connects individuals or organizations within
a specific context through knowledge and information (see Howells, 2006; McEvily and Zaheer,
1999). While socially-situated entrepreneurial cognition and the concept of intermediation are
not explicitly linked in prior research, intermediaries have historically fulfilled the role of
“important informal disseminators of knowledge” (Howells, 2006: 716). Thus, we see
entrepreneurial cognition research on expertise development (Baron and Henry, 2010; Mitchell
et al., 2000; Smith et al., 2009) as being especially compatible. In prior research, intermediation
1 “Composition models specify the functional relationships among phenomena … at different levels of analysis...
that reference essentially the same content but that are qualitatively different at different levels” (Chan, 1998: 234).
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has taken a variety of forms. For example, “middlemen” are important informal disseminators of
knowledge (Hill, 1967; Howells, 2006), “technology intermediaries” facilitate technology
transfer (Knockaert, Spithoven and Clarysse, 2014), “network intermediaries” assist in the
development of firm capabilities by providing access to expertise (McEvily and Zaheer, 1999),
“social intermediaries” enable individual actors in emerging markets to transact (Sutter, Kistruck
and Morris, 2014) and “institutional intermediaries” help address institutional failures in a
specific situation (Armanios et al., 2017; Dutt et al., 2016). In our study, we seek to understand
how accelerators act as institutional intermediaries in the developing regional entrepreneurial
ecosystem of Bangalore, India.
RESEARCH METHODS
Research setting
As historical background, Bangalore began to emerge as a hub of defence, aeronautics and space
research in the 1950s, and by the 1970s the State of Karnataka, of which Bangalore is the capital,
had become a leading center in the electronics industry in India (Parthasarathy and Ranganathan,
2011). Although initial science and technology investments in Bangalore were mainly
government-driven, increased autonomy for businesses and infrastructure support from the
federal and state governments (Jain and Sharma, 2013; Parthasarathy and Ranganathan, 2011)
soon paved the way for private industry participation. In 1983, Infosys, still a new company at
the time, relocated to Bangalore from Pune. During the same decade, a number of multi-national
corporations established a presence in Bangalore (e.g., Texas Instruments in 1985). Bangalore
continues to attract skilled workers from Karnataka and four surrounding states, which together
supply roughly 60% of India’s engineering graduates (Parthasarathy and Ranganathan, 2011).
This human capital advantage, combined with Bangalore’s climate, cosmopolitan culture, social
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capital networks, and the processes underlying knowledge spillovers (Parthasarathy and
Ranganathan, 2011; Saxenian, 2000; Taeube, 2004) make Bangalore the world’s second-fastest
growing entrepreneurial ecosystem (Herrmann et al., 2015).
However, while Bangalore has one of the youngest pools of entrepreneurs compared to other
ecosystems (Herrmann et al., 2015), this talent pool is still underdeveloped. Indeed, this is one of
the reasons for the popularity of the accelerator model in India. Morpheus, the first accelerator in
Bangalore, began in 2008—three years following the launch of Y Combinator in Silicon Valley
(Cohen, 2013b)—and closed at the end of 2014. At the end of Fall 2016, there were 14
accelerators in Bangalore, four of which were created from April through August 2016. Given
the newness of the accelerator phenomenon and the emergent nature of theory regarding both
accelerators specifically and entrepreneurial ecosystems more generally, we employ an
interpretive qualitative approach (Denzin and Lincoln, 2005), based on extant literature. In other
words, rather than aiming for “untethered ‘new’ theory” building (Suddaby, 2006: 635), we use
an exploratory, iterative process to offer an “elaboration of existing theory.”
Data collection
To gain a dynamic and socially complex understanding of regional entrepreneurial ecosystems,
we sought to involve a broad set of entrepreneurial actors in Bangalore. Thus, we purposively
selected informants, including accelerator managers, accelerator mentors, start-up founders
(accelerator graduates), entrepreneurship educators/ university representatives, and policy
representatives. We began with the six accelerators operating out of Bangalore as of June 2014.
Using information from the accelerators’ websites, we created a list of graduates of these six
Bangalore accelerators between December 2012 and June of 2014.
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Data collection began in October 2014. We contacted each accelerator with a request to
speak with an accelerator manager. Two informants (one with ties to two accelerators) provided
first-hand interview data for three of the six accelerators. We also contacted a variety of
accelerator graduates, aiming for diversity and information-rich examples to facilitate theory
building (Eisenhardt and Graebner, 2007). Specifically, we looked for examples of success/
failure in raising funds; early/ late stage start-ups; business-to-consumer/ business-to-business
focus; little/ extensive founder experience; generic/ niche focus of the accelerator; and
accelerator association with local/ multinational corporations. Of the 38 accelerator graduates we
contacted, a diverse set of 18 informants agreed to speak with us.
To ensure interview data captured the emergent nature of the Bangalore regional
entrepreneurial ecosystem (including both successful and failed ventures), we contacted five
more accelerators founded between June 2014 and March 2016. We talked with three accelerator
managers and four graduates. Further, we went back to speak with the founder of Morpheus and
with five2 additional informants from our earlier set of accelerators, where leadership had
subsequently changed. This resulted in data from four of the six original accelerators in
Bangalore as well as four of the newer accelerators.
We also approached 25 individuals who were more broadly involved in the entrepreneurial
ecosystem in Bangalore, including mentors, educators/ university representatives and policy
representatives. Twelve consented to speak with us (three mentors, five policy representatives,
four university/ entrepreneurial education experts). Further, at a conference related to
entrepreneurial education policy for the State of Karnataka, we conducted 10 short interviews
2 One of these graduates was part of a virtual accelerator and was not physically located in Bangalore.
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with other actors in the regional entrepreneurial ecosystem. Table 1 lists our informants and
Table 2 describes the specific start-ups represented.
[Insert Tables 1 and 2 About Here]
To begin, we based our semi-structured interview questions on prior research relating to the
components and purposes of accelerators (Cohen, 2013b). Specifically, we asked our first six
informants about their background, mentoring received, cohorts, educational seminars,
experiences with demo-day and other outcomes. The later semi-structured interviews were more
focused on some of the key themes that emerged in the initial interviews, including informant
background, status of ventures prior to joining the accelerator, experiences within the accelerator
itself, counterfactual questions relating to what could be changed and finally a set of eight
questions (akin to a Likert-type scale) about various accelerator design components.
The first author conducted all the interviews. The majority were conducted in person, and all
were conducted in English, the language most often used for business in Bangalore. We
interviewed 54 informants in total, conducting interviews until reaching saturation (Strauss and
Corbin, 1998) in terms of first-order informant categories (discussed in detail in the next
section). Following the interviews, we remained in contact with informants through social media
and email. Additionally, we identified and analysed 49 websites, 13 online video interviews of
actors within the ecosystem, 26 different online news sources and 301 pages of policy documents
and industry reports. The use of multiple data sources helped not only in developing a nuanced
and vivid understanding of the research setting, but also in triangulating data for enhanced
validity and reliability (Jain and Sharma, 2013).
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Data analysis
The initial interviews with accelerator managers and graduates provided us with a preliminary
understanding of the accelerator’s role (the what), especially as it relates to providing expertise
to founders and connecting them more broadly with the regional entrepreneurial ecosystem. The
later interviews with accelerator managers, graduates from accelerators and other actors in the
regional entrepreneurial ecosystem allowed us to better understand the process (how) elements
related to the role of accelerators as intermediaries in a regional entrepreneurial ecosystem.
We used NVivo software throughout the process to assist us in organizing and consolidating
the multiple first-order categories (Gioia, Corley and Hamilton, 2013). We also enlisted the help
of four independent research assistants, who were otherwise not involved in the study, to
individually come up with first-order categories from the data. These research assistants then met
with two of the three authors as part of validating the first-order categories. Additional first-order
categories continued to emerge as we continued to collect data. These were validated as two of
the authors evaluated the data separately and then met together. These first-order categories
reflect the voice of the informants in the data (see Gioia et al., 2013; Ko and Liu, 2015).
Two co-authors then considered how the first-order categories might be organized in terms of
second-order themes that were consistent with extant theory and could be understood in terms of
aggregate dimensions (Gioia et al., 2013). The resulting structure of first-order categories and
second-order themes, along with their corresponding aggregate dimensions, are depicted in
Figures 1 and 2.
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[Insert Figures 1 and 2 About Here]
FINDINGS AND CROSS-LEVEL, INTEGRATED MODEL
We adopt a process-focused lens to understand: (1) how do accelerators affect venture success
or failure? and (2) how do accelerators affect regional entrepreneurial ecosystems? The
emerging data structure (Figures 1 and 2) highlights four kinds of expertise that allow
accelerators to function as meso-level intermediaries between founders and the regional
entrepreneurial ecosystem: connection expertise, development expertise, coordination expertise,
and selection expertise. Specifically, accelerators with this expertise can engage the ecosystem
intermediation processes that best influence commitment to the regional entrepreneurial
ecosystem, venture validation (success or failure) and ecosystem additionality. These aggregate
dimensions form the foundation of our cross-level, integrated model, depicted in Figure 3. In the
following sections, we describe our findings that emerge from the interviews with the
informants. Additional quotations from informants can be found in Tables 3 and 4.
[Insert Figure 3 and Tables 3 and 4 About Here]
Accelerator connection expertise
Accelerator connection expertise involves accelerators’ capability to foster relationships between
founders and the regional entrepreneurial ecosystem. Establishing connections is typically
viewed as an essential aspect of what accelerators do. As is shown in Figure 1, two second-order
themes in our data underlie accelerators’ connection expertise: (1) frequency of interaction and
(2) intensity of interaction (Knockaert et al., 2014).
Frequency of interaction involves learning through connections made during periodic
reviews and a variety of formal and informal networking opportunities. Informants mentioned
seminars and networking events, mentoring sessions and parties. With respect to the connections
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accelerators seek to create, an informant noted, “There were lots of people in the start-up
ecosystem [with whom] we generally discuss our business and business ideas with, not in a very
official, deep mentor relationship, but almost [in] an informal chat. So, through that … always
sometime or the other there is some seed of an idea or something somebody else is doing which
ignites a spark in your brain” (Start-up Jayanagar, online learning). Frequent opportunities for
interaction thus enabled connections that built founders’ expertise.
Intensity of interaction refers to physical proximity and the unscheduled, unstructured
opportunities that allow accelerator members to share ideas and encouragement in person. Our
data highlight differences in intensity for accelerators run virtually compared to those requiring
founders’ physical presence:
I guess if I were in a normal office, I wouldn’t have done so much work … because
everybody is working … Parties are really important … We used to [solve] each other’s
problems … Whenever we’d get stuck we’d go to other start-ups and ask about that … and
also, every week there used to be some guy from the industry coming and giving a talk … If
it’s a physical accelerator and not a virtual accelerator, it always helps because we are
pushed to excellence … I think that being a part of accelerator, you get rid of [the Indian
culture of not sharing ideas] because everybody is sharing ideas. It’s OK to share because
you learn and grow together. (Start-up HSR Layout, business website promotions)
For each of our founders, intense interactions from sharing a physical space, increased
connections to the regional entrepreneurial ecosystem. We note that the extent to which these
connections are facilitated will partly depend on whether the accelerator is a niche or generic
accelerator. The difference between niche and generic is evident in the description of niche
accelerators as having “strong contacts” (Start-Up Ulsoor, ridesharing) and providing more
implementable advice” (Start-up Frazer Town, sports and fitness) relative to generic
accelerators.
Whether niche or generic, accelerators that foster frequent and intense interactions ultimately
connect the founders to the regional entrepreneurial ecosystem, thus broadening the nature of
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founders’ experiences and enabling them to further enhance their expertise (see Gavetti and
Levinthal, 2000). We therefore suggest:
Proposition 1: Accelerator connection expertise is a necessary mechanism for enhancing
founder expertise through linking founders to a regional entrepreneurial ecosystem.
Accelerator development expertise
Accelerators must also possess development expertise, or the capability to enable founders’
growth and improvement by providing education sessions and other learning opportunities (see
Gavetti and Levinthal, 2000). As is demonstrated in Figure 1, two second-order themes emerged
from the data related to accelerators’ development expertise: (1) formal education scripts and (2)
informal education scripts. Both represent important aspects of entrepreneurial education (Honig,
2004; Robinson and Sexton, 1994).
Relating to formal education scripts, an accelerator manager described formal elements of the
educational experience for entrepreneurs: “You can’t just randomly tell them [everything they
need to know]… so we have structure there. And that structure is an 18-week structure … first, a
customer development workshop is done, and then we go into a second workshop which is kind
of a technology workshop, and then it goes into a product workshop(Accelerator X). Feedback
from the entrepreneurs regarding these formal sessions was mixed. Some of the informants in
later stage start-ups (beyond three years from firm founding) felt ambivalent: the “seminars
around the basics of how to start a start-up … were the things that we already learned in [an]
MBA” but “there were certain things that we really, really liked and thought they were of value
(Start-up Agara, internet-based advertising). Other founder informants recognized that not every
session will benefit every founder because of founder team heterogeneity (see Vanaelst et al.,
2006), yet still expressed enthusiasm. One informant described:
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[The value of education sessions] depends on what stage you are in because sometimes you
know some of these things … or you have already been through that or maybe you are not
ready for it yet, so you are not quite open to it … I think most of the seminars were fairly high
quality based on the general discussions that I have had with my peers, the other start-ups.
So who ever was involved was able to take something out of it. (Start-up Garuda, life
sciences)
A majority of our founder informants mentioned the benefits of informal education scripts—
especially related to learning from cohorts and learning from others. One informant said that the
cohort “is one thing I am really happy to be talking about,” going on to say that because “we
were the youngest team in the cohort … we got to learn a lot from all these [senior] people. So
everybody helped us, more than we helped them … The peer learning was really good (Start-up
Domlur, data collection and aggregation). Although this informant was part of an early-stage
start-up, the positive sentiment surrounding cohorts was corroborated by informants from later-
stage start-ups as well. Informal education also occurred through the program elements that
encouraged founders to engage in market-focused learning. This informal learning was often
embedded in the program structure of the accelerator, as one mentor described:
We encourage you to go and meet actual customers in the market, not necessarily people
whom you already have on your board, but new ones, new prospects. So, go talk to them and
come back to us with the learnings … [In] the pitch sections … we let the entrepreneur learn
the art of pitching … to the ecosystem whether it is customers … investors and to the external
stakeholders … So by doing all this … then we have opened their eyes on to … what they
should do and how they should do it. (Accelerator X)
Our data suggest that although formal training in the “basics” of starting a venture are needed,
informal education scripts play an essential role in founders’ market-focused understanding of
how to grow their businesses.
Mentoring is another essential element of the informal education. Specifically, accelerator
managers seemed to recognize the potential limits of formal training and were working to better
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utilize informal interactions to help bridge founders’ expertise gaps. The importance of mentors
in this informal training is illustrated in the following:
I’ll give you … a real-life example … take three individuals [let’s call them Aarav, Diya and
Reyansh] … they are all very active with [our organization]. They all often sit together.
[Aarav] … His old boss which is [Diya] … and his new investor [Reyansh] … who’s an
[angel] investor into [Aarav’s company] and also a board member. And you ask [Aarav] and
say, “[Aarav], what do you attribute your success to?” And [Aarav’s] answer is: “Eighty
percent the informal know-how I got from [Diya] … and 20% is everything else.” (Regional-
level Policy Informant 3)
Specifically, accelerators’ development expertise, transmitted through both formal and informal
education scripts, seemed to enhance the effects of connection expertise on founder learning.
Thus:
Proposition 2a: Accelerator development expertise is a necessary mechanism for enhancing
founder expertise through providing founders an opportunity to gain new knowledge through
both formal and informal means.
Proposition 2b: Accelerator development expertise amplifies the benefits that can be gained
through application of accelerator connection expertise.
Accelerator coordination expertise
As described by informants in the previous section, founders tend to “align” to different
topics based on their perceived needs. That puts the difficult onus on the founders to know what
they do not know. Accelerator coordination expertise shifts the onus back to the accelerator.
This involves the accelerators’ capability to enable fit and alignment between founders’ interests
and mentor/ accelerator capabilities. As is depicted in Figure 1, coordination expertise comprises
two second-order themes: (1) cognitive proximity and (2) alignment. Both relate to
communication and understanding (Bird, 1988; Nooteboom, 2000). Cognitive proximity
(Nooteboom, 2000: 72) comes from a perceived fit between the mentor’s experience or
capabilities and the founders’ needs. One informant described the newness of mentoring in the
Bangalore entrepreneurial ecosystem as a challenge based in fit:
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People have just started mentoring start-ups, right? … So nobody has experience being
mentor … So for [the accelerator] it was an experiment finding people who can help … With
the diversity of start-ups that were there it’s difficult to find a mentor who had had prior
experience in your kind of business. But that is understandable being that that was their first
program, right? So now I think now they have gone to getting more people … who have got
prior experience in specific things. (Start-up Frazer Town, sports and fitness)
An accelerator manager highlighted mutual interest as a requirement of the mentoring
relationship: “If the start-ups are really interested [in the mentors], they get back … and it’s a
very hands-on mentoring that they seek” (Accelerator Z).
Other founder informants reported that many of the mentors they worked with lacked
experience or capabilities in the specific domain, and in many instances lacked recent (or even
first-hand) entrepreneurship experience. One informant suggested that if accelerators “could
have gotten other entrepreneurs just ahead of us … because they have just gone through it…they
have clarity and they remember … In 5-6 years, you forget all that stuff” (Start-up Frazer Town,
sports and fitness). Another informant compared the accelerator experience in Bangalore to an
accelerator experience elsewhere in the world. He mentioned that what he really liked in the
other accelerator was “structure in mentorship … you don’t get assigned mentors randomly … So
the accelerator first seeks to understand what are your areas of weaknesses” (Start-up HSR
Layout, business website promotion).
The second-order theme of alignment refers to the correspondence of founder goals and
priorities with mentor goals, regional priorities and accelerator goals. Such alignment is crucial
in start-ups (see Bird, 1988). One informant discussed the need to:
Consider the quality of mentors [and] … Have certain very clear ‘asks’ before you go [into
an accelerator] or at least formalize it in conjunction with the accelerator—the people who
are going to help you. I think it’s important to have that at the beginning of the program or
start of the journey. (Start-up Garuda, life sciences)
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Another informant explained that different accelerators have different value propositions and
capabilities. He suggested that the founders need to “look at what you hope to get out of [the
accelerator] and align yourself to the appropriate one” (Start-up Lavelle Road, mobile/ social
messaging).
But from the perspective of accelerator expertise, the primary onus for alignment falls on
accelerators, not on founders. As another founder described: “I think it is very important to have
a dialogue upfront as to what you are expecting and what you think is going to come out of it.
And there needs to be a good fit … In some cases it did happen quite well” (Start-up Ejipura,
online customer engagement). This dialogue is grounded in accelerator coordination expertise.
Without such expertise, the accelerators and founders can go through the motions of
development and connection, but founders may still not gain the expertise they need to grow
their ventures. By contrast, accelerators high in coordination expertise will optimally leverage
their existing expertise in development and connection. We therefore suggest:
Proposition 3a: Accelerator coordination expertise is a necessary mechanism for enhancing
founder expertise through ensuring that founders have access to the knowledge that is
specifically relevant and appropriate for them.
Proposition 3b: Accelerator coordination expertise amplifies the benefits that can be gained
through application of accelerator development expertise and accelerator connection
expertise.
Accelerator selection expertise
In our data, accelerator connection, development and coordination expertise were further
bolstered by accelerator selection expertise, which involves accelerators’ capability to select
individual mentors and founders who are sufficiently motivated and knowledgeable. While
accelerator coordination expertise focuses on effective match-making thorough assessment of
relative cognitive proximity and mutual alignment between mentor and the founder, accelerator
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selection expertise focuses on gauging independent levels of motivation and knowledge of
individual mentors and founders. Thus, as noted in Figure 1, four second-order themes emerged
around accelerators’ selection expertise: (1) mentors’ motivation, (2) mentors’ knowledge, (3)
founders’ motivation and (4) founders’ knowledge (McMullen and Shepherd, 2006).
Ensuring mentor motivation can be a major problem for accelerators. While most
accelerators boast a marquee list of mentors, founders often described negative experiences, as
this one did: “Unfortunately for me, I was assigned a mentor … [who] was a high profile guy
who would understand the whole thing [I was doing]. But he was a very busy person, so he got
me assigned to someone below him, who had no clue about [what I was doing]” (Start-up MG
Road, 3D imaging). Although the mentor had some of the necessary knowledge, he apparently
had neither time nor incentive to engage. Even managers of accelerators saw a need for better
assessing mentor motivation:
We also need to do a … better job. Because when you have a … well-known [accelerator] …
there is a tendency on the part of lot of people to come and associate with us as mentors.
What I would ideally like to see is that the mentors really follow up and make themselves
available, rather than just lend a name. We don’t want names, but we want people to actually
sit for that one hour. (Accelerator X)
One founder informant touched on this by describing an accelerator program in North America
he was familiar with, which paid mentors so that they would be financially obliged to invest
time. In Bangalore, mentors predominantly serve on a voluntary basis and are not compensated
monetarily.
Finding mentors with domain knowledge can also be a challenge—particularly in emerging
ecosystems. As previously noted, the accelerators in our sample did not always select mentors
with adequate expertise. One informant said his own firm had a good experience with their
mentor, but “for some of the other start-ups I felt that [the mentors] were not of much help to
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them … For B2C [business to consumer], as well I think [the mentors] don’t have that much
experience and expertise” (Start-up Banasvadi, mobile security). Indeed, informants frequently
noted that many mentors were corporate executives with no entrepreneurial experience, only
information technology experience, and no exposure to up-and-coming fields such as education,
healthcare, life sciences, or sports. Thus, the expertise of the accelerator in recruiting and
motivating mentors with appropriate entrepreneurship experience is critical.
In terms of founders, we saw in the data the importance of selecting founders who are
motivated to learn (McMullen and Shepherd, 2006)—and to act. Founders’ coachability was
mentioned by multiple informants (mostly accelerator managers and managers). For example,
the manager of an accelerator emphasized this as a major selection criterion: “[Ideal founders are
good at] accepting the thoughts of what we bring across and what our mentor ecosystem brings
across … The coachable aspect of the entrepreneur becomes very important … How coachable
is the entrepreneur? (Accelerator X). We also saw the need for founders to be willing to act. As
another informant described: “So in an accelerator you will get all the feedback, all the advice,
all the mentoring. But then you, as a leader, need to take [a] decision” (Accelerator Y).
Relating to the second-order theme of founder knowledge, we saw the importance of
selecting founders who have sufficient experience and knowledge around a potential business
solution. As an informant managing an accelerator described: Hundreds of people get
shortlisted … then we go to the actual criteria of, you know, figuring out how unique the solution
is from the Indian market perspective [and] how strong is the team” (Accelerator X). The
expertise required to select founders with the appropriate breadth of knowledge and experience,
related to a solution that has market potential, is essential.
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The existence of accelerator selection expertise thus provides a foundation for coordination
expertise, development expertise and connection expertise to result in the development of
founder expertise. We therefore suggest:
Proposition 4a: Accelerator selection expertise is a necessary mechanism for enhancing
founder expertise through ensuring that founders and mentors have the necessary motivation
and prior knowledge to act.
Proposition 4b: Accelerator selection expertise amplifies the benefits that can be gained
through application of accelerator coordination expertise, accelerator development expertise
and accelerator connection expertise.
Proposition 5: Accelerator selection expertise, accelerator coordination expertise,
accelerator development expertise and accelerator connection expertise combine as
necessary and sufficient conditions for enhancing founder expertise.
Accelerators as intermediaries
In emerging regional entrepreneurial ecosystems, institutional voids are prevalent and continue
to persist (see Armanios et al., 2017; Dutt et al., 2016). For example, in our sample in Bangalore,
founders and even mentors frequently lacked expertise. Moreover, we saw substantial variance in
accelerator expertise. Fortunately, we also saw how accelerator expertise enabled accelerators at
the meso-level to better fulfil an intermediary role at both the micro-level (i.e., developing the
venture), as well as at the macro-level (i.e., developing the regional entrepreneurial ecosystem).
In this way, accelerators meet Howells’s (2006: 716) description of intermediaries as “important
informal disseminators of knowledge” that can help address gaps in expertise or knowledge.
Building on a model of entrepreneurial expertise and commitment (Smith et al., 2009), we
conceptualize ecosystem intermediation as a socially-situated process whereby expertise affects
commitment and action in a regional entrepreneurial ecosystem. In the following sections, we
discuss our findings related to three intermediation processes and their outcomes (as depicted in
Figure 3).
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Ecosystem intermediation and commitment to the regional entrepreneurial ecosystem
The first ecosystem intermediation process we highlight is the commitment engagement
intermediation process (cf. Smith et al., 2009). This process builds commitment by transforming
the beliefs of individual actors associated with the accelerator in a way that enhances the shared
commitment to the regional entrepreneurial ecosystem. At its core, commitment to the regional
entrepreneurial ecosystem is dispersed and depends on the extent to which accelerator beliefs
and expertise are distributed across various actors in the ecosystem and in the broader
environment (see Mitchell et al., 2011). As Figure 2 highlights, this distributed element of
commitment to the regional entrepreneurial ecosystem is evident in two second-order themes that
emerged from the data: (1) situated accelerator understanding (Mitchell et al., 2011; Sarasvathy
et al., 2008) and (2) distributed accelerator expertise (Mitchell et al., 2011; Mitchell et al., 2000).
The commitment engagement intermediation process occurs as accelerator connection
expertise enables frequent and intense interactions that form the condensed networks for
accessing financial, human, and social capital (see proposition 1). These connections are further
strengthened through accelerator development expertise, which provides the appropriate formal
and informal learning that enables the founder to leverage these connections (see propositions
2a-b). The benefits from development are then amplified through accelerator coordination
expertise, wherein mentors and founders are matched appropriately to facilitate cognitive
proximity and alignment (see propositions 3a-b). And finally, all of this is fuelled by the
accelerator’s selection of founders and mentors who have appropriate prior knowledge and
motivation to take entrepreneurial action (see propositions 4a-b). We saw this commitment
building process in the following description from an informant:
Some of these vertical areas like healthcare and so on, what we have discovered is there
exists a depth of [domain] expertise. But those are people who have so far not interfaced
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with the entrepreneurial ecosystem. So that’s one set of connections we are in the process of
building. So for example people inside academic institutions or research labs or even large
corporations... these are people who have done original research who have decades of
experience in the space, but haven’t really interfaced with the entrepreneurial ecosystem. So
if you bring them in contact with the entrepreneurial ecosystem—that in itself is a huge value
add. So that depth of experience and expertise becomes available to entrepreneurs, in some
cases these folks get entrepreneurial ideas themselves. (Accelerator V)
This example demonstrates how accelerator expertise can be used to connect and align
people who are not currently inside the entrepreneurial ecosystem (e.g., people in research labs)
with those who are (e.g., mentors and investors). The process of “interfacing” with the regional
entrepreneurial ecosystem thus puts the accelerator in the role of ecosystem intermediary (cf.
Howells, 2006; Kistruck et al., 2013). What appears on the surface as merely “bringing [others]
in contact” is actually intermediation through a kind of “cognitive coordination” (see Foss and
Lorenzen, 2009: 1202) of beliefs and actions between the various actors in a way that builds
overall commitment to the regional entrepreneurial ecosystem.
In our data, we saw the second-order theme of situated accelerator understanding in the
accelerators’ acknowledgement that they need to adapt to the evolving conditions of the regional
entrepreneurial ecosystem. In one case, an accelerator stopped providing educational seminars
based on feedback from founders. In another case, an accelerator completely switched to a model
in which they designed and operated accelerators for other corporate partners.
The second-order theme of distributed accelerator expertise appeared in transformed beliefs
about sharing best practices and fostering collaboration amongst accelerators. For some
informants, sharing and collaboration represented a commitment to the regional entrepreneurial
ecosystem. One manager described how he did not see his accelerator as being in competition
with other accelerators, but instead saw an opportunity to work together:
It makes all the more sense for folks not to wear the hat of ‘compete’ but rather
‘collaborate’. Because there is no need for an accelerator to compete. I mean, whom are we
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competing against? There’s nobody. Right? … There is a lot of things that we can share, a
lot of best practices that can be shared … Because, there is a certain amount … of good
things that you bring to the table, there are certain things that we bring to the table.
(Accelerator X)
Another manager saw “a lot of collaboration [among accelerators]” where everybody is
interested in doing something together and “there are … many activities that you plan together
… many events, [and] conferences” (Accelerator Z). Through distributed beliefs, best practices,
and expertise, accelerators both manifest their own commitment to the ecosystem and strengthen
the commitment of other actors in the system. We therefore suggest:
Proposition 6: The commitment engagement intermediation process leverages accelerator
expertise to improve situated understanding and to share distributed expertise, so as to
increase overall commitment to the regional entrepreneurial ecosystem.
Ecosystem intermediation and venture validation (success or failure)
The second ecosystem intermediation process we highlight is the venture development
intermediation process. This process builds on accelerators’ expertise and their commitment to
the regional entrepreneurial ecosystem to help founders gain quick and relevant feedback as well
as access to financial, human, and social capital. Positive and/or negative feedback results in
venture validation (success or failure), which is evident in informants’ use of terms such as
having the “right people,” gaining “confidence,” learning through “experiments,” and choosing
to “fail fast or fail cheap.” One informant invoked the process by describing his need for
validation from the accelerator:
When I joined [the accelerator] … that was one of the most difficult times, right, because … I
was the only one doing it and I just moved to another city and suddenly your expenses started
going high … Because I didn't have a product ready, I didn't have a customer … so I was in a
phase … thinking am I doing things right, am I doing things wrong, what should I do? So, it
wasn't very clear on my thoughts also and confidence. (Start-up Frazer Town, sports and
fitness)
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Often a strong need for validation and clarity underlies founders’ expectations and objectives for
joining accelerators. Uncertainties that founders face include whether the founders have the right
idea, the right product, the right customer segment, the right geography, and the right team
members; and whether the founders should stay the course or pivot. The same informant
continued:
"We validated [a] few assumptions, which was good. Then we pivoted. We learned from that
and then we pivoted to a wider segment focussing on events, but more on bookings rather
than engagements on fixtures and schedules … Then we had another pivot after the
warehouse, now we’re focussed on bookings, but more on venues." (Start-up Frazer Town,
sports and fitness)
Later, based on accelerator feedback, this informant changed not only the focus but also the
name of his company.
Thus, through the venture development intermediation process, founders make ongoing,
critical improvements that allow their businesses to succeed. As demonstrated in Figure 2, two
second-order themes emerged from the data relating to venture validation (success or failure): (1)
entrepreneurial team development (Clarysse and Moray, 2004; Vanaelst et al., 2006) and (2)
opportunity development (Ardichvili, Cardozo and Ray, 2003; De Koning, 2003).
We saw the second-order theme of entrepreneurial team development in the founders’ efforts
to build a venture team. As one informant described:
When we joined [the accelerator], we already were in contact with few of the publishers in
[named country] … But we didn't have any contacts in [the] Indian market. And the main
reason to join [the] accelerator was that they have got huge contacts and networks and
connections. So they can help us reach out to them … It was a bit harder for us to reach out
to them directly, but they coming [in a partners matchup] and listening what we do … that
actually geared up our confidence … and made us reach out to them in a better way. (Start-
up Banasvadi, mobile security)
As another informant likewise noted, the venture development process assisted them in adding
the right people to the team: “Our first problem was to find some good technical person since
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[on] our core team nobody was from a software background, so we understand this is a problem
with our sector … We want people who can refer us to some good technology people … So, both
the cohort members as well as the core team at [the accelerator], referred us to many people”
(Start-up Domlur, data collection and aggregation). The challenge faced by this informant was a
gap in expertise that they sought to fill by adding people to the founding team (Clarysse and
Moray, 2004; Vanaelst et al., 2006).
Entrepreneurial team development can also occur in accelerators through deliberate practice
(Baron and Henry, 2010; Mitchell, 2005), for example, “through observation of the actions and
outcomes of others” (Baron and Henry, 2010: 57). As one informant described: “We had these
talks scheduled … we had different people coming up … some could be technical, some could
just be experienced with other successful start-ups … some could be HR related [seminars] and
team building [seminars]” (Start-up Neelasandra, online shopping).
We saw the second-order theme of opportunity development take shape as founders worked
to improve their core business model. In opportunity development, accelerators enable individual
founders to get quick feedback on their ventures from various mentors, investors, and potential
customers, as a way of experimenting with various hypotheses about their ventures. One founder
described how the accelerator pushed entrepreneurs to ask for feedback:
In the first couple of weeks … the goal is try to talk to as many customers as possible. B2C
[business to consumer] start-ups are encouraged to talk to 100 customers where as B2B
[business to business] companies are encouraged to talk to 25-30 customers. That sort of is
the general aspect of it … so that they had some kind of validation. (Start-up Garuda, life
sciences)
Opportunity development also occurs as various actors share with participants the lessons
from past successes and failure. An informant provided this example:
The seminars where people talked about the mistakes they made … because it’s always
important to know what mistakes he had done and how did he rectify them. That was more
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helpful than someone saying we have achieved ABCD … Because we had our own set of
targets, so whatever you have achieved is very different from what I want to achieve. What I
want to know is where did they fail so that I don’t repeat the same mistake. (Start-up HSR
Layout, business website promotions)
In focusing on developing the venture, accelerators help founders better understand how to
reach out [to] your customers, find out what their problems are, figure out … how do you
position your product” (Start-up Koramangala, device management and software services). As
the prior discussion and Table 4 highlight, accelerators can thus provide the tools needed to
expedite success or failure, while at the same time minimizing the costs of either. We therefore
suggest:
Proposition 7: The venture development intermediation process combines accelerator
expertise and commitment to the regional entrepreneurial ecosystem to help expedite venture
validation (success or failure).
Ecosystem intermediation and ecosystem additionality
The third ecosystem intermediation process we highlight is the ecosystem development
intermediation process. This process combines accelerator expertise with increased commitment
to the regional entrepreneurial ecosystem to transform the infrastructure (Venkataraman, 2004)
of that ecosystem. Transformation reflects ecosystem additionality, which is defined as the
ecosystem-level competence, expertise and networks that speed up venture validation processes
in a regional entrepreneurial ecosystem (cf. Autio, Kanninen and Gustafsson, 2008; Clarysse,
Wright and Mustar, 2009; Knockaert et al., 2014).
Ecosystem additionality is thus an ecosystem-level construct that is similar to (yet distinct
from) the firm-level concept of second-order additionality (Autio et al., 2008). We suggest that
ecosystem additionality results, in part, from engaging accelerator expertise and commitment to
the regional entrepreneurial ecosystem, leading to an ecosystem-level “learning effect” (Clarysse
et al., 2009: 1518). As Figure 2 highlights, two second-order themes emerged from the data
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relating to ecosystem additionality: (1) the tangible infrastructure of entrepreneurship (e.g.,
government policies, capital markets, university programs, etc.) (Venkataraman, 2004), and (2)
the intangible infrastructure of entrepreneurship (e.g., availability of role models, informal
opportunities for learning, etc.) (Venkataraman, 2004).
The tangible entrepreneurial infrastructure in Bangalore can be evaluated in terms of both
what exists and what is missing. From the perspective of what exists, we see the proliferation of
accelerators as promising; as noted, four new accelerators joined the ecosystem between April to
August 2016. From the perspective of what is missing, gaps in the Bangalore regional
entrepreneurial ecosystem remain in terms of developing early stage discoveries/ ideas into later-
stage start-ups. As a representative with the Ministry of Science and Technology said:
Some of those discoveries are so good and so compelling but are not ... ready for industry to
be taken up because of the early stage they are in ... even entrepreneurs will not take chance,
because their validation will not take one to two years, validation takes four-five years,
right? The proof of concept will come in four-five years, so… you cannot let those
discoveries go away and fade away... can we validate that in a lab environment and the
government can support it because of the very high risk nature that it stands. (Regional-level
Policy Informant 4)
Although the government provides some support, this support only represents the initial stages of
the tangible infrastructure. At some point, the private sector also needs to contribute. The gap
that exists in the tangible infrastructure to support the development of early stage discoveries/
ideas into later-stage start-ups, partly derives from the newness of the ecosystem. For example,
one accelerator manager explained that angel capital is “a very new concept” in Bangalore.
Enough people “have sufficient funds to invest” but for there to be a good market for angel
capital in Bangalore, these potential investors “have to look at the start-ups for the right reasons,
they have to have a risk appetite.” He went on to say: “I think that is the place where a lot of
maturity needs to come … So everyone in the ecosystem obviously needs to grow themselves, the
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funding aspect is something that needs a lot of attention” (Accelerator Y). Ecosystem
additionality is thus evident as government institutions and accelerators recognize their
complementarities and the need to collaborate in building this tangible infrastructure:
I would say with the government bodies, [it] is still coming up. The support that the private
players seek from the government bodies [are] still in a very initial building stage. Not really
very active. But yes, of course, even the government bodies have realized the value of the
ecosystem … They do actively approach us in certain things as well, but still it’s in a very
initial stage. (Accelerator Z)
Cooperation among accelerators, themselves, as driven by commitment to the regional
entrepreneurial ecosystem, also creates ecosystem additionality. This tangible aspect of the
ecosystem development process occurs, as the Accelerator Z informant described, through the
development of “a common vision … which is to accelerate growth, which is to foster innovation
… [and] to enhance the quality and the effectiveness of the start-ups (Accelerator X).
In our data, we saw the second-order theme of intangible infrastructure in the need for
collaborative relationships among the various actors in the ecosystem. For example, this
informant wanted stronger connections with business schools:
It's like [a specific Indian educational institution], huge resource, completely disconnected
with their entrepreneur ecosystem in India. That's not how MIT is, that is not how Stanford
is, but that's what it is [in India]. So [Indian business schools] have become completely
disconnected with the … entrepreneur, [there’s] some pretense activity, but that amounts to
nothing. I am sorry to be so critical. (Regional-level Policy Informant 3)
The desire for more collaboration among the government, universities, research institutions and
accelerators came through strongly in our data. An accelerator manager expressed a need for the
government to more actively partner in creating the intangible infrastructure:
I think accelerators being a private initiative, can only make it to a certain level … to take it
from there to the national scale … something big had to come in and the government of
India has attempted to do that … “Make in India” [and] "Start-Up India” [initiatives to
encourage manufacturing or entrepreneurship] … are both, kind of, at a very macro-level …
trying to encourage the trend and from a policy level, provide support for it. So I think it's a
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very positive sign, it basically amplifies the signal even more for start-ups and it takes it to a
different level … there have [also] been nice changes in the taxation system. (Accelerator T)
The importance of connection also occurs in terms of understanding the specific roles that
angel investors and venture capitalists should play. That is, while there exists a need for markets
for risk capital generally (as noted), it is equally important to develop stakeholders’
understanding of these investor roles—another element of the intangible infrastructure. Our
findings at the meso- and micro-levels emphasize the importance of role models, especially as it
relates to the need to have alignment and cognitive proximity between founders and mentors. At
the macro-level, an increasing number of accelerator graduates possess knowledge that can be
modeled in the ecosystem to guide investors and founders.
While ecosystem development remains a work in progress for Bangalore accelerators, it is
nonetheless clear that the accelerators viewed the development process as part of their broader
mandate: “For us, internally our metrics are all about what kind of impact we have made in the
ecosystem … will we be able to cultivate and drive good citizenship by getting good solutions to
meet the [needs of the] local ecosystem (Accelerator X). This impact is manifest as ecosystem
additionality. We therefore suggest:
Proposition 8: The ecosystem development intermediation process combines accelerator
expertise and commitment to the regional entrepreneurial ecosystem to result in increased
ecosystem additionality.
One interesting finding relates to the founders whose ventures “failed.” While we
acknowledge the emotional and cognitive effects of failure (Shepherd, 2003), we repeatedly saw
that failed ventures contributed to ecosystem additionality. At the time of our interviews, three
out of the 22 informants had shut down their ventures after graduating from an accelerator, four
others had changed their name and identity of their venture, and two additional informants had
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seen their ventures acquired.3 The founders of the three “failed” ventures were all now working
for other start-ups in senior executive roles and were valued for the expertise they had built while
working on their “failed” venture. As one founder described,
[The start-up that I now work for] … they allow me to be very entrepreneurial … a lot of the
[other] managers … they come from different backgrounds … many of them are B-school
graduates … but I think what I have that sort of differentiates me from them is that I have this
experience … so I know that if my gut says something then I should just go and implement it
and be up for failures. So, we’ve done like a lot of experiments … a lot of these experiments
have given me zero sort of results but quite a few have been very successful. I think my [prior
venture] made me a lot more courageous. (Start-up Whitefield, mobility and transportation)
Similarly, the founder of Accelerator T explained how a failed venture that is supported by the
experience in an accelerator can be helpful to the regional entrepreneurial ecosystem:
[Anyone] who goes through one or two years of [experiencing entrepreneurship] becomes
mature and expanded in his knowledge and can be an asset … because then they go back and
work for other start-ups. One of the things you see is that many start-ups … have tried to hire
big-big people from big-big companies and … it’s really bombed. Most start-ups really
prefer to hire founders of start-ups who tried but things didn’t work out. You know, a guy
who has built a start-up can be a great CTO … there is a lot of good coming from
accelerators because they are creating a very good pool of human resources … some of [the
accelerator graduates] may go on to build companies, but many of them will become a part
of that start-up industry, adding value in different ways … because after founders, the biggest
problem is to find good co-founders or good people.
Without discounting the importance of venture validation success, we emphasize that venture
validation failure also provides a benefit to the ecosystem. This benefit accrues through micro-
level learning, an intermediate outcome that is reflected in (and adds to) ecosystem additionality
at the macro-level (see Autio et al., 2008: 59; Knott and Posen, 2005). We therefore suggest:
Proposition 9: Accelerated failure, as a consequence of accelerator expertise and
commitment to the regional entrepreneurial ecosystem, contributes to ecosystem
additionality, which in turn supports further entrepreneurial activity.
3 However even amongst these two seemingly “successful” exits there was a nuanced difference. One of them was a
“satisfactory” sale for a disclosed/ publicized $ 15 million USD to a global multinational company, whereas the
other was perceived as a “distress” sale for an undisclosed amount.
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DISCUSSION
In this study, we built on Smith and colleagues’ (2009) model of entrepreneurial cognition to
investigate how accelerators affect (1) venture success or failure and (2) the regional
entrepreneurial ecosystem now emerging in Bangalore. Placing accelerators at the meso-level of
analysis allowed us to explore their intermediary role in these development processes. Interviews
with 54 ecosystem actors, along with a variety of published sources, informed our iterative,
qualitative research method.
Our findings depict how accelerators act as meso-level intermediaries through a combination
of connection, development, coordination, and selection expertise. Further, the cross-level,
integrated model and propositions that emerged from extant theory and informant data provide a
more nuanced understanding of ecosystem intermediation processes. Specifically, we describe
the processes that enable accelerators to enhance expertise, commitment to the regional
entrepreneurial ecosystem, venture validation (success or failure) and ecosystem additionality.
We found that accelerators in Bangalore do more than assist firms and founders; they also
play a critical role in developing the regional entrepreneurial ecosystem. By enhancing
stakeholder cooperation and founder knowledge, accelerators create ecosystem additionality
even when the specific firms they sponsor are unsuccessful. We thus contribute to theory on the
processes that support emerging regional entrepreneurial ecosystems.
Implications for research
We believe our paper offers three primary contributions. First, we add to the emerging literature
on accelerators, a relatively new development in entrepreneurship. As noted previously, research
on accelerators has primarily contributed to understanding the various components and purposes
of accelerators (the what elements). Our findings related to accelerator expertise begin to unpack
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processual elements (the how). To the predominant discussions of connection and development,
we add the dimensions of coordination and selection. Further, while prior work on
entrepreneurial expertise has focused on expertise at the individual level (Mitchell et al., 2000;
Reuber and Fischer, 1994; Seawright, Mitchell and Smith, 2008), the model that we propose
embeds accelerator expertise at the meso-level of analysis. Specifically, we suggest that while
each type of accelerator expertise is individually necessary at the meso-level, each type alone is
not sufficient to influence accelerator performance outcomes of venture validation (success or
failure) at the micro-level, or ecosystem additionality at the macro-level. In doing so, we
highlight how accelerator coordination expertise and selection expertise amplify the effects of
accelerator connection expertise and development expertise.
Our conceptualizations of accelerator expertise build on research that suggests cognitive
coordination (Nooteboom, 2000) as a way to resolve problems related to relational risk. As Foss
and Lorenzen described: “a (some would say the) problem of economics is that of coordination”
(2009: 1203, emphasis in original). In an accelerator context, coordination expertise and
selection expertise begin to resolve this problem. For example, we theorize that accelerator
coordination expertise establishes the cognitive proximity between founders and mentors that
allows development expertise and connection expertise to work effectively. Meanwhile, selection
expertise helps to ensure both founders and mentors possess the basic motivation and knowledge
needed to enhance founder expertise and contribute to venture and ecosystem development.
Second, we add to theory related to entrepreneurial ecosystems by highlighting the dual role
accelerators can play in developing both ventures and ecosystems. We describe a venture
development intermediation process that supports (1) entrepreneurial team development and (2)
opportunity development, to result in (3) venture validation (success or failure). On the other
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hand we observe that accelerators’ expertise-building (Hallen et al., 2014) is not limited to the
individual-level or firm-level. Rather, we see accelerators engaging in an ecosystem
development intermediation process that achieves additionality by combining tangible and
intangible infrastructure elements.
Third, we deepen understanding of the cognitive underpinnings of the socially-situated
ecosystem intermediation processes. Our findings move beyond static representations of
cognitive constructs to more dynamic portrayals (Mitchell et al., 2011) by demonstrating the
importance of intermediation processes that are socially situated in nature and that engage with
accelerator expertise to result in ecosystem additionality. In line with prior research on learning
from failure (Cope, 2011; Knott and Posen, 2005), we find that accelerators can speed up failure
to a nonetheless positive end: the founders of “failed” ventures can more quickly contribute their
expertise in other areas of the entrepreneurial ecosystem.
While we acknowledge the distinctions between accelerators and incubators (Cohen, 2013b;
Pauwels et al., 2016), we note prior research on incubator intermediation has also been based on
interactive, bridging processes (Amezcua et al., 2013; Etzkowitz, 2002). We see commonalities
between the accelerator expertise that we propose and the relational connections (Baum and
Oliver, 1991), interactive processes (Etzkowitz, 2002) and normative alignment (Zimmerman
and Zeitz, 2002) that occurs in incubators. However, we also find that accelerator expertise is
more focused on providing access to expertise, and less focused on issues related to legitimacy,
as discussed in the context of incubators by Amezcua et al. (2013). Likewise, we saw limited
evidence related to buffering (i.e., “maintaining a protective environment” [Amezcua et al.,
2013: 1632]) in an accelerator context. Additional research is needed to understand where and
how accelerators are similar to and distinct from incubators as intermediaries in an ecosystem.
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Future research should also seek to understand how incubators, as compared to accelerators, also
may contribute to ecosystem additionality.
Implications for practice
From a practice perspective, our research underscores the value of a highly interactive mode of
knowledge transfer. According to our informants, the frequency and intensity of interactions—
both with peers and mentors—help develop expertise. Thus, designers of entrepreneurial
learning programs should place appropriate emphasis on informal modes of learning, especially
in emerging contexts, where there are fewer role models and fewer curated interactions. Further,
accelerators must be able to select appropriate mentors and founders, and should pair them based
on cognitive proximity. In terms of identifying gaps, while the question “What is the founder’s
domain experience?” is important, the question, “What is the mentor’s domain experience?” is
equally important. Motivation, for both mentors and founders, matters as well.
More broadly, our findings suggest that accelerators need not be judged solely on the success
of the participating firms. Some of our informants expressed a more negative perspective of
accelerators. But that negative perspective predominantly looks at the role accelerators play in
developing individual ventures. It misses the role that accelerators play in developing regional
entrepreneurial ecosystems and contributing to ecosystem additionality. Indeed, as already noted,
by speeding the failure of some firms, accelerators help develop the ecosystem. In this sense, our
results suggest that government policy makers should judge accelerators based on their expertise;
namely, their expertise in building connections, developing founders, coordinating mentorship,
and selecting participants (both founders and mentors). These evaluation standards should
benefit both individual founders and the broader entrepreneurial ecosystem.
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Limitations and future directions
Although our qualitative method provides rich data and helps us elaborate on existing theory
(Suddaby, 2006), we acknowledge that our study is nonetheless limited. For example, our
findings come from a single region: Bangalore, India. Compared to developing contexts like
Mexico or Pakistan, Bangalore has a solid information and communications technology
infrastructure and a strong business to business focus. We understand that every regional
entrepreneurial ecosystem has its own idiosyncrasies, and generalizing from one ecosystem to
another, need be done cautiously. Yet, as Pratt (2008: 496) argued, some forms of
generalizability are particularly accessible through a qualitative approach:
Even though a fundamental drawback of most qualitative research is its lack of statistical
generalizability, other forms of generalizability for qualitative research have been proposed.
Yin (2003), for example, argues that case studies rely on analytical generalizability where
data is generalized to a theory, not to a sample. Ecological validity argues that a theory must
capture key contextual aspects of a theory for it to be relevant (Lee, 1999). And naturalistic
generalization (Stake, 2000) argues that one can create a sense of external validity by
recognizing how one case is similar to another. To illustrate, one can recognize an oak as a
tree after seeing a maple tree.
In this sense, although our findings cannot be extrapolated to the population of entrepreneurial
ecosystems generally, or even regional entrepreneurial ecosystems in developing countries
specifically, our paper does capture these three other forms of generalizability.
In terms of analytic generalizability, we “provide evidence that supports (but does not
definitively prove)” (Firestone, 1993: 17) theories of socially-situated entrepreneurial cognition.
Ecological validity is high in our study as a result of data collected directly from a wide variety
of context-specific actors, including experts on accelerators (founder participants, managers,
mentors, etc.) and ecosystems (educators/ university representatives, investors, policy
representatives, etc.). In our presentation of results, we enable naturalistic generalization (Stake,
1978: 6) by providing sufficient detail; that is, readers may consider our findings in light of their
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own context-rich knowledge—such as their experiences with other ecosystem intermediaries that
rely on expertise to address institutional voids (Mian, Corona and Doutriaux, 2010).
So, although we cannot (statistically) generalize our findings to these contexts, we do have
evidence of a set of phenomena in one context that can be evaluated for similarity with other
contexts. For example, a regional economy transitioning from a large-scale, specialized
manufacturing base (e.g., parts of the Northeast and Midwestern United States) to one that is
more entrepreneurial, might seem unlike Bangalore. However, decision makers might find some
important similarities (e.g., a scarcity of mentors with niche subject matter expertise and
experience in entrepreneurship).
Another consideration is our specific theoretical lens (Mitchell et al., 2011; Smith et al.,
2009). Other lenses that likewise capture the importance of context—such as complexity theory,
economic geography, institutional theory, or network theory—might also be applicable.
Although these lenses are distinct from that used herein, through our use of socially situated
cognition, we have nonetheless worked to also capture contextual aspects in our theorizing.
Likewise, other factors may serve as starting points for accelerator expertise, such as legitimacy,
social capital and financial capital.
To address the above gaps, we see opportunities for future research. Scholars could use
various approaches to gauge accelerator expertise, capture ecosystem intermediation processes,
and quantify the measurable outputs of venture validation (success or failure). Proxies for
performance might include first customer, first pivot, profitability, and so on. In a similar vein,
ecosystem additionality might be measured by the number of accelerator graduates working on
other teams, serving as mentors, or actively investing capital in the ecosystem. New scales could
capture the aggregate theoretical dimensions that emerged from our analysis—connection,
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development, coordination, and selection expertise—as well as commitment to the regional
ecosystem, venture validation (success or failure) and ecosystem additionality. To best account
for the cross-level and dynamic nature of the phenomenon being studied, we would recommend
a series of longitudinal research studies, comparative case analyses and historical approaches.
CONCLUSION
In sum, we build upon a socially-situated model of entrepreneurial cognition (Smith et al., 2009)
to describe the process (how) elements of accelerators in Bangalore, India. By studying what
worked well and what did not in this developing regional entrepreneurial ecosystem, we
document what accelerator expertise looks like and how it can affect commitment to the regional
entrepreneurial ecosystem, venture validation (success or failure) and ecosystem additionality.
We note that accelerators in Bangalore are in many ways start-ups themselves, facing the same
challenges that other start-ups face. But these accelerators also act at the meso-level to build the
regional entrepreneurial ecosystem. Our findings suggest that as these accelerators continue to
build their own expertise, and continue to engage in ecosystem intermediation processes, they
will more fully benefit from the macro-level expertise that emerges as the ecosystem itself,
continues to develop.
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ACKNOWLEDGEMENTS
The authors would like to thank Alan Meyer, Eric Morse, Lawrence Plummer, Dominic Lim,
Mike Wright and three anonymous reviewers for their gracious and helpful comments.
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TABLES AND FIGURES
Table 1. Bangalore entrepreneurial ecosystem
Launch Year – Accelerators operating in Bangalore between January 2008 and August 2016 (Focus of the Accelerator)
1. Early 2008 - Morpheus (no specific industry focus, exited in 2014)
2. End 2012 - Microsoft Ventures (Focus on technology)
3. Early 2013 – Kyron (Focus on fin tech, education, media & retail)
4. 2014 - Target (run by Kyron mgmt./ Focus on retail)
5. 2014 – Pitney Bowes (based out of Noida/ Focus on mobile & data
analytics, e-commerce, data integration and management)
6. 2014 - GSF (Focus on technology)
7. 2015 – T-Labs (Founded 2011, moved to Bangalore 2015/ Focus on
technology, internet and mobile)
8. 2015 – Axilor Ventures (Focus on e-commerce, enterprise and
healthcare)
9. 2015 – Numa (No specific industry focus)
10. Early 2016 - WRI India (Focus on addressing urban
transportation challenges)
11. Early 2016 - Bosch (Focus on auto tech, big data analytics)
12. April 2016 – Lowe’s (run by Kyron management/ Focus on retail
innovation
13. April 2016 - Oracle Cloud (Focus on technology)
14. June 2016 - Axis Bank (Focus on fin tech)
15. August 2016- Brigade Group (Focus on real estate, hospitality,
retail and education)
Ecosystem informants (54 interviews) –
22 Founders (Accelerator Graduates – See Table 2 for details)
10 Accelerator Program Managers (from six accelerators)
12 Mentors, University representatives and Policy (Government) representatives
10 Entrepreneurial Education Conference participants (educators and government-policy representatives)
Table 2. Description of informant firms
Start-up
Informant Business Type (Scale of
Operations - Global or
Local)
Industry/Domain Focus Start-up
Stage* Stage of
Product/
Solution
Team Size
(at time of joining
Accelerator)
Agara B2B/ Products (Local) Internet-based
advertising Very early Prototype 2
Banasvadi
B2B/ Services (Global –
Asia focus) Mobile security Very early Prototype 2
Cox Town B2B/ Products (Global) Digital content
management Very early Beta 3
Domlur B2B/ Products (Local) Data collection and
aggregation Very early Idea 3
Ejipura B2B/ Products (Global) Online customer
engagement Very early Beta 4
Frazer Town B2C/ Products (Global) Sports and fitness Very early Idea 2
Garuda B2B/ Products (Global) Life Sciences Late Live 6
HSR Layout B2B/ Products (Global) Business website
promotion Early Beta 9
Indiranagar B2C/ Products (Local) Ridesharing Very early Beta 2
Jayanagar B2C/ Products-services
hybrid (Global) Online learning Very early Beta 6
Koramangala B2B/ Products (Global) Device management and
software services Late Live 22
Lavelle Road B2B/ Products (Global) Mobile/ social messaging Late Live 10
MG Road B2B/ Products (Local) 3D imaging Intermediate Live 2
Neelasandra B2B/ Service (Global) Online shopping Intermediate Live 15
Cubbon Park B2B/ Products (Global) Big data analytics Very early Idea 2
Peenya B2B/ Products (Global) Social data intelligence Intermediate Live 3
Hoodi B2B/ Products (Global) Big data analytics Early Live 17
RT Nagar B2B/ Products (Global) Social commerce Early Live 12
Shivajinagar B2B-B2C Hybrid/
Services (Local) Healthcare Intermediate Beta 4
Ulsoor B2C/ Hybrid Product-
services (Local) Ridesharing Early Beta 3
Whitefield B2C/ Services (Local) Mobility and
transportation Early Live 2
Yelahanka B2B-B2C Hybrid/
Product-services (Global) Survey analytics/ market
research Early Prototype 1
* Very Early Stage (< 6 months), Early Stage (6 months - 1 year), Intermediate Stage (1 to 3 years), Late Stage (more than 3 years)
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Table 3. Accelerator expertise: Representative quotes
Aggregate
dimensions Second-
order
themes
First-order
categories Representative quotes
Accelerator
Connection
Expertise
Frequency
of
Interaction
(see
Knockaert
et al., 2014)
Milestone reviews
Networking events
“Every week …there was a scheduled half-an-hour discussion with them… we used
to discuss what we have worked around and what we are planning to do next week.
And it was really helpful because at times …they told us that you can reach out to
this person and they connected us. And then they followed up like how exactly…
how far have you went” (Start-up Banasvadi)
“But you know [being part of a virtual accelerator] more frequent and more in person
interaction would help us…”(Start-up Ulsoor)
“Start-ups need to network. And I know of no place [in India] other than Bangalore
which has almost every day two events connected to start-ups and on weekends as
many as five events connected to start-ups” (Policy Informant 2)
Intensity of
Interaction
(see
Knockaert
et al., 2014)
Virtual versus
physical accelerator
Niche versus
generic accelerator
“We already had a team and handful of customers and we were based out of Pune
[while accelerator was in Bangalore]…we did not relocate….we didn’t go through
the entire agenda…interaction was limited [with cohort members]” (Start-up Ejipura)
“I wish we were in a Subject Matter Expertise [non-generic] accelerator, right? Just
creating a pool of mentors doesn’t make sense. Now if you look at a verticalized
[niche] accelerator they would have verticalized [niche] experts also” (Start-up HSR
Layout)
“..person was so busy…didn’t help us. Gyan [platitudes] and no follow up. Having
him as a mentor was good but experience wasn’t consistent…” (Start-up RT Nagar)
“For example, if Uber is coming out with an accelerator [ride-sharing], ya it will help
me…[comparing with existing generic accelerators]” (Start-up Indiranagar)
Accelerator
Development
Expertise
Formal
Education
Scripts
(see Honig,
2004;
Robinson
and Sexton,
1994)
Seminars-based
learning “We had a kind of orientation wherein we were taken through the basics of …starting
a start-up…basics of finance, basics of marketing, basics of branding” (Start-up
Agara)
“Being a single founder, I had my hands.. like full... I think, initially when we started
we focussed on few things which weren't required …at that stage where it doesn’t
matter, like…. numbers, I had no clue, right? We made three-year costing and
revenues…it was all in the air” (Start-up Frazer Town)
Informal
Education
Scripts
(see Honig,
2004;
Robinson
and Sexton,
1994)
Cohorts-based
learning
Contacts-based
learning
Mentor-based
learning
“It’s a very informal process. I think that's the mistake many of the start-ups do,
thinking that it is gonna be a structured process. It's not.” (Start-up Koramangala)
“[Each week] one person from each start-up used to come and then tell everyone how
[does the] week looked like for them, is it good/ bad… what's the experience for
them… so it was kind of interesting to understand what’s happening in a start-up
which is completely different from you…” (Start-up Cox Town)
“…there’s a revolving door of people going in and out, from one to the other...either
as employees or founders and more recently, investors” (Policy Informant 2)
“There was a structured process, of course. But then, it did not prevent us from
accessing the mentors on a more as need basis as well. So, we did a combination of
both” (Start-up Lavelle Road)
Accelerator
Coordination
Expertise
Cognitive
Proximity
(see
Nooteboom,
2000)
Fit between
founder domain
needs and mentor
domain experience
“With the diversity of start-ups that were there, it’s difficult to find a mentor who had
had prior experience in your kind of business. Because, our business is also new…it
is very hard to find people who’ve got experience in [our domain]” (Start-up Frazer
Town)
“…there were hardly any people in the accelerator who understood B2C or
education. So, most of the feedback or suggestions we got were very generic and
sometimes not even applicable to our business because, the nature of business is so
different” (Start-up Jayanagar)
Alignment
(see Bird,
1988)
Founder/accelerator
goals match
“There is no financial contribution from [our accelerator] ..a lot of things we need to
do require some capital…so, waiting for six months for raising capital and then
suddenly these things would not make sense….” (Start-up Ulsoor)
“I think start-ups should understand whether they are ready for an accelerator or not. I
think that’s the most important thing that a start-up should figure out …if they are
building a product maybe it’s not the right time…” (Start-up Cox Town)
“[Differentiating between government priority on small and medium businesses and
accelerator focus] The emphasis through accelerators and otherwise has been more…
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Founder/regional
priorities match
on the disruptive startups right now, they are sexier, right.... and it has been less on
the SMB [small and medium businesses] startups.” (Policy Informant 3)
Accelerator
Selection
Expertise
Mentor
Motivation
Assessment
Scripts
(see
McMullen
and
Shepherd,
2006)
Mentor having
incentives to
engage
Mentor having
available time
“One of the best mentor program in the entire world…[referring to a Canadian
accelerator] …there is a structure in mentoring…they sit with you and what are your
areas of weaknesses…. let’s say you need help in HR. Then they connect to one HR
person and the mentor gets paid for it. He is financially obliged, so he actually comes
and gives you some time. He was paid by the accelerator and I don’t mind paying if
there is ROI.” (Start-up HSR Layout)
“Not a dedicated mentor… they had a full plate….one guy round robined amongst
us…disappointing” (Start-up Cubbon Park)
“Mentors were for namesake… very inaccessible” (Start-up Peenya)
“The business mentor, I actually didn’t meet at all. He was a very busy person,
travelling, and…. so we just did phone calls” (Start-up Jayanagar)
Mentor
Knowledge
Assessment
Scripts
(see
McMullen
and
Shepherd,
2006)
Mentor having
domain experience
Mentor having
prior start-up
experience
“Unfortunately, we didn't find a mentor in time …very specifically because, there
[are] not many [our niche industry] focused start-ups or companies in India.” (Start-
up Garuda)
“Mentor was very shallow… they had no idea of the product of any of the cohort. I
wish my mentor had spent time understanding what I am doing” (Start-up Cubbon
Park)
“Their mentor's list is mainly people who are working in [X] in some or the other
field. And when it comes to B2C, they don't have much experience …they are mainly
focused on enterprise…” (Start-up Banasvadi)
Founder
Motivation
Assessment
Scripts
(see
McMullen
and
Shepherd,
2006)
Founder(s) being
coachable
Founder(s) having
willingness to act
“The number one attribute in my opinion is coachability… the ability to change your
mindset and course of action based on inputs that you get” (Accelerator V)
“Need to have some commitment or passion [for] the idea. Display a reasonable
amount of energy because it is going to be a long, painful, frustrating journey”
(Educator 2)
“The first thing is obviously a demonstration of the passion for the particular
venture… how keen are they? How passionate are they?... Then comes their ability to
demonstrate, or rather have a demonstrated ability of resilience….of being able to
deal with crisis, things of that nature. Sort of in high pressure environments the ability
to cope with it and execute” (Mentor 3)
“It’s on every individual company to make maximum use of their mentors. It's how
much you engage with them” (Start-up Koramangala)
Founder
Knowledge
Assessment
Scripts
(see
McMullen
and
Shepherd,
2006)
Founder(s) having
industry experience
Founder(s) having
a good/ unique
solution
“If you’ve been a software engineer all your life, and were starting something in
diagnostics, then… you know it was unlikely you had any advantages” (Educator 2)
“..what is their background and competence, and their capability to execute ..then
comes obviously their educational and work experiences..” (Mentor 3)
“...is this a good idea? Secondly, can it be a business? If it is a business, is this the
team to take it to market” (Accelerator V)
“They needed to do something that was truly innovative…second is, it had to make
some sort of an impact…thirdly, it had to be an implementable idea” (Educator 2)
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Table 4. Ecosystem intermediation outcomes: Representative quotes
Aggregate
Dimensions Second-order
themes First-order
categories Representative Quotes
Commitment
to Ecosystem Situated
Accelerator
Understanding
(see Mitchell et
al., 2011;
Sarasvathy et al.,
2008)
New/ innovative
models of
accelerators
Shifts in
accelerator
location
and focus
“So the first decision I made is shut down the accelerator…so, we are [now] in the
business of designing and operating corporate acceleration programs for large
multinationals” (Accelerator Y)
“We’re doing a residential one now [at that juncture this was a virtual accelerator]. A
lot of this is understanding …[what] works for different set of entrepreneurs as well”
(Accelerator U)
“…[start-up firms] are at different levels of readiness… their competencies are
different… some are more mature…it is kind of impossible to put them altogether in
one program and …one single cohort and give them the same kind of mentoring… the
benefits are, it’s like diluted” (Accelerator Y)
“one of the small experiment that we are running, is a program called [ABC] – it’s a
directed innovation challenge…the primary objective is to increase the number of
experiments… this time we have selected [a particular disease]” (Accelerator V in an
online interview)
Distributed
Accelerator
Expertise
(see Mitchell et
al., 2011;
Mitchell et al.,
2000)
Organized
conferences for
collaboration
Cross-pollination
of practices
Experts
volunteering
time
“Today… we are also hosting an incubator and an accelerator meet, for all the
incubators/ accelerators around the country to actually come here and get to work
together more to create a much larger impact on the ecosystem” – Microsoft Ventures
ThinkNext Conference Summer, June 2016 (Source: YouTube)
"But being in that environment we know that we are not only persons facing that
environment, all of us are facing the similar problems whether it is a discussion on say,
which is a best known platform to post our applications and getting those feedbacks
from people who had already used saying these are the advantages and these are the
disadvantages. Always there is some person to whom you can talk on the varied level
of subjects." (Start-up Domlur)
"So, what these preparation sessions did was to give us feedback about, what are
people perceiving our pitches, what are points of confusion. So, that was great
because, not just the people who ran the accelerator but your mock presentations were
attended by people from cohort as well. We got very rich feedback about, what's
wrong with our pitch and that we don't even know and we could fix it." (Start-up
Jayanagar)
“There are mentors and there are mentors… and very few of them are willing to roll
up their sleeves and help the start-up. So, we make sure whoever is one of our
mentors, somebody who has the domain, somebody who has the time, inclination and
most importantly who is a believer in the ecosystem and wants to contribute”
(Accelerator Y)
Venture
Validation
(Success or
Failure)
Entrepreneurial
Team
Development
(see Clarysse and
Moray, 2004;
Vanaelst et al.,
2006)
Possessing the
right
connections
Having
right people
on team
Possessing
relevant
knowledge
“It’s the networking, it’s the connects. You get connected to the right people, you get
connected to the right customers, right mentoring… that’s something we are looking
at.” – (Start-up Neelasandra)
“We wanted a little more local expertise…we wanted to get some connects and mentor
connects for the network primarily, which is why we were here.” – (Start-up
Koramangala)
“..for my developers who joined me that was a big deal for them [referring to being
part of this accelerator]. It also helped in giving moral boost to my employees. So that
always helped in attracting and retaining talent.” - (Start-Up HSR Layout)
“I think it was interesting to see how different people were in slightly different
stages… no one was exactly the same yet there are some common underlying themes
in terms of struggle to hire people, [etc.]” – (Start-up Garuda)
“Although it was a lot of learning through sessions and stuff….you don’t get time to
actually build a business… we also did work on things which weren’t required at that
stage….working on numbers and stuff which wasn’t, I think required at that stage. It
just wasted a lot of time.” – (Start-Up Frazer Town)
“We were exposed to the tools …for making our start-up fail fast or fail cheap.” –
(Start-up Agara)
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Opportunity
Development
(see Ardichvili et
al., 2003; De
Koning, 2003).
Emphasis on
quick feedback
Focus on fast
product/
market
validation
Sharing about
successes and
failures
“That was the time when we used to read the user sentiments, launch something
immediately, see whether the user is using and how is he using… we learnt a lot in
those days” – Start-up Agara
“What we were hoping to gain [from our accelerator]…how do we sustainably scale?...
we really needed expert guidance on how do we streamline our operations… we were
also trying to experiment with various business models” – (Start-up Whitefield)
“Essentially [our] accelerator program is designed to help the start-up answer three
questions…how do you know you are building something people want? In what form
are they willing to consume it? How do you know they are willing to pay” –
(Accelerator V)
“..we encourage them to meet actual customers in the market. Not necessarily people
whom you already have in the board but the new ones…[next]…technology
workshop…then the product workshop... about how you manage your product…and
what areas of product do you build. Do you solve the entire problems that are there in
the ecosystem of your product or do you go surgical?” – (Accelerator X)
“The end of the program is like, you have to have a clear picture of what you are
doing, why you are doing and for whom are you doing it? And that's when we saw
most of the pivots happening.” – (Start-up Cox Town)
“That was a wonderful experience…being among other entrepreneurs, understanding
their problems, see how they are going ...some of the failures that you face…people
are often facing similar problems…getting those feedback” – (Start-up Domlur)
Ecosystem
Additionality Tangible
infrastructure
of
entrepreneurship
(see
Venkataraman,
2004)
Additional
investments by
existing actors
Additional
accelerators being
founded
Entrepreneurship-
focused
government
policy
"See, I think, first of all, this government for the first time has articulated that
entrepreneurship is an important part of economic growth, which has never before
been articulated [referring to the Govt of India Start-up India Policy]… While it is not
entirely satisfactory, what it has done is that it has introduced the word start-up in the
government lexicon... as we know, once something is added onto the government
lexicon it is almost impossible to have it removed, so that's a big plus...” (Mentor 3)
“Brigade Group Launches India’s First Accelerator for Real Estate Start-ups” –
CNBC-TV18 (27th Aug 2016)
“Technology has revolutionized daily commutes… WRI India Sustainable cities
launched the New Mobility Accelerator 2016…[for] early stage shared mobility
businesses … in partnership with Center for Innovation Incubation & Entrepreneurship
and supported by Shell Foundation & Hewlett Foundation” – WRI India blog post
“The State would invite the private sector including globally and nationally well-
known accelerators and incubators to set up world class incubation centers and
accelerators or expand existing facility /operations on PPP [Public Private Partnership]
basis” - Karnataka Start-up Policy 2015-2020 (Bangalore is capital of the State of
Karnataka)
“Prime Minister Narendra Modi announced Action Plan for encouraging Start-Ups.
Plan [includes]…funding support through fund-of-funds with corpus of Rs. 10,000
crores [Rs. 100 billion]...No tax on profit, inspection for three years…encouragement
to incubation centres…” – Start-Up India, Stand-Up India Policy (January 2016)
“… a common start-up portal and hotline, which could provide information
on…incubators/ accelerators/ co-working space” - Karnataka Start-up Policy 2015-
2020 (Bangalore is capital of the State of Karnataka)
Intangible
infrastructure
of
entrepreneurship
(see
Venkataraman,
2004)
Niche/ specialist
mentors available
Network of
accelerator
graduates
“The reason us joining [niche accelerator] was not money and all but primarily we
were into the transportation space and we had strong contacts [through the accelerator]
with local governing bodies... that would have been a big plus for us.” (Start-up
Ulsoor)
“If any start-up wants to join an accelerator, they should first look at alumni start-ups
because they help start-ups a lot…. the other reason we should look at alumni is
accelerator has itself worked them, so they know a bit of that field and they can further
work with you and get you into.” (Start-Up Banasvadi)
“When you have 60-64 people alumni, the beauty is that you find all varieties of
people.. So the amount of mentoring that these guys have, these people have now seen
success. So replicating their path may be a good idea for some of the start-ups or may
be learning from mistakes what the other guy did. And we strongly encourage alumni
also to sit in our accelerator as much as possible….at any point of time if you go and
visit our accelerator, at least 5-10 % of people who are present will be alumnus who
have come down to use our office space for something or who have come to meet the
other start-up or to help the other guy.” (Accelerator X)
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Accepted Article
Figure 1. Data structure: Accelerator expertise
Figure 2. Data structure: Ecosystem intermediation outcomes
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Accepted Article
Figure 3. Cross-level, integrative model: The role of accelerators in the development of a regional entrepreneurial ecosystem
This article is protected by copyright. All rights reserved.
... Although the growth of EEs in non-central regions and emerging economies has been increasing in the past two decades, little is known about how they operate in these environments [41,42]. These new emerging regions assume an increasingly relevant position and demand more attention to their gaps [43][44][45], going through a transition to an economy based on knowledge, entrepreneurship, and innovation [46][47][48]. ...
... Commitment engagements in emerging EEs can be reflected through investor risk sharing, mentor volunteer time, and updating business models focusing on continued innovation [47,53]. Among the gaps, the authors pointed out several restrictions of different natures: institutional regulatory frameworks, market settings, access to financing, establishment and dissemination of knowledge and innovation, formation of entrepreneurial capacities and cultures, lack of effective interaction between educational and research institutions, and entrepreneurs and the fear of failure [54,55]. ...
... Others bring the amplified attraction of capital that would directly benefit the region's tax base [78,79]. Likewise, gentrification and the increase in the cost of living were identified as possibilities for results that, depending on territorial aspects, can be considered positive or negative [47,80,85]. ...
Article
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Entrepreneurial ecosystems remain under-theorised and conceptually fragmented, making it challenging to comprehend their disposition and performance in the business process. Accordingly, in this research, we explored how knowledge sharing flows through entrepreneurial ecosystems to make analyses and trials to assess new ventures' creation, continuity, and development opportunities. We carried out a systematic literature review on the Web of Science database. The analysis was carried out in two stages: (i) content analysis using NVivo software and (ii) statistical processing and clustering with the support of VOSviewer and Bibliometrix software. Moreover, we reviewed entrepreneurial literature and proposed conceptual model mapping relations through all main actors and knowledge flow in ecosystems. Our findings suggest the knowledge path in the near field sharing mechanisms resulting in a new conception of traditional structures and relations used to judge and decide how to assess opportunities for new ventures' opening, maintenance, and growth. This study contributes to entrepreneurial literature, demonstrating knowledge sharing flow through entrepreneurial ecosystems, considering an embracing, dynamic, and multilevel approach. Furthermore, it highlights political and social contributions to include new emergent perspectives: resource scarcity and structural and institutional gaps. This representation is the first knowledge management model applied to different economies and areas, respecting their singularities.
... Primarily, the accelerator is involved in temporal scaling, or "accelerating the performance speeds" of a process (Lehrer, Banerjee, & Wang, 2017, p. 152). This is reflected in a number of studies including a temporal element (e.g. , except there are still calls for more longitudinal research (Crișan et al., 2021; Goswami, Mitchell, & Bhagavatula, 2018). Few studies also consider the spatial and product scales of an accelerator. ...
... First, much of the current research does not delve into outcomes or long-term results of participation; instead, the focus tends to be on outputs, program end results, or after immediate results (Crișan et al., 2021). Potential proxies for measuring success or failure have been suggested as avenues for future research with longitudinal research recommended, taking into account the empirical setting and actors involved (Goswami et al., 2018;Mian et al., 2016). Second, to move beyond the predominance of positive accelerator effects, there are calls for research into the viewpoints of the actors involved in accelerator programs (Crișan et al., 2021). ...
... As we noted in Figures 5 and 6, only several a couple companies pursued their best game due to implied limited commerciality. Our final time scale was 12 months, responding to calls for longitudinal research (Goswami et al., 2018). Whereas other studies have used funding as a proxy for success (Buffart et al., 2020;Hallen et al., 2020), we concentrated on released games since this was the goal set out by the RPI (see also Barbero et al., 2012). ...
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Full-text available
Objective of the study: We seek to understand two aspects of a business accelerator: first, how an accelerator influences early product development, and second, how an accelerator impacts participants during and after acceleration. Methodology/approach: We conducted an ethnography of a rapid prototyping program in video game development. Methods included 810 hours of participant observation, 58 interviews, and hundreds of analyzed material artifacts. Originality/Relevance: We add insight into the impact and outcomes of an accelerator program across multiple scales: spatial, temporal, and product. Our study is one of the first to examine a formal video game development accelerator. Main Results: Accelerator participants created 42 prototype games, two companies received additional funding, but no games were released within one year of the program. Product scales changed over time from expectations, to prototypes, to final games. The spatial-temporal scale of the accelerator was open to interpretation. Participants and observers held two main spatial-temporal perspectives (present-local and future-global) that changed over a one year time period. Theoretical/methodological contributions: First, we conceptualize an accelerator as a dual competitive place where participants and observers engage in dueling and evolving spatial-temporal perspectives over time. Second, we develop the concept of an accelerated digital product scale to explain the process of evolvement from an accelerator product to a potential final product. Social/Management contributions: We conclude the impact of an accelerator is more complex than the structure or the output. The accelerator may rapidly generate ideas or prototypes, but this does not guarantee a quicker final product release. Resumo Objetivo do estudo: Buscamos entender dois aspectos de um acelerador de negócios: primeiro, como um acelerador influencia o desenvolvimento inicial do produto e, segundo, como um acelerador impacta os participantes durante e após a aceleração. Relevância/originalidade: Adicionamos insights sobre o impacto e os resultados de um programa de aceleração em várias escalas: espacial, temporal e de produto. Nosso estudo é um dos primeiros a examinar um acelerador formal de desenvolvimento de videogames. Metodologia/abordagem: Realizamos uma etnografia de um programa de prototipagem rápida no desenvolvimento de videogames. Os métodos incluíram 810 horas de observação participante, 58 entrevistas e centenas de artefatos materiais analisados. Principais resultados: Os participantes do Accelerator criaram 42 protótipos de jogos, duas empresas receberam financiamento adicional, mas nenhum jogo foi lançado dentro de um ano do programa. As escalas de produtos mudaram ao longo do tempo de expectativas para protótipos e jogos finais. A escala espaço-temporal do acelerador estava aberta à interpretação. Participantes e observadores tinham duas perspectivas espaço-temporais principais (presente-local e futuro-global) que mudaram ao longo do período de um ano. Contribuições teóricas/metodológicas: Primeiro, conceituamos um acelerador como um lugar competitivo duplo onde participantes e observadores se envolvem em duelos e perspectivas espaço-temporais em evolução ao longo do tempo. Em segundo lugar, desenvolvemos o conceito de uma escala de produto digital acelerada para explicar o processo de passar de um produto acelerador para um produto final potencial. Contribuições sociais/para a gestão: Concluímos que o impacto de um acelerador é mais complexo do que a estrutura ou a saída. O acelerador pode gerar ideias ou protótipos rapidamente, mas isso não garante uma liberação mais rápida do produto final. Palavras-chave: Aceleradora. Indústria de videogames. Etnografia. Incubadoras. Indústrias criativas. Resumen Objetivo del studio: Buscamos comprender dos aspectos de un acelerador de negocios: primero, cómo un acelerador influye en el desarrollo temprano del producto, y segundo, cómo un acelerador impacta a los participantes durante y después de la aceleración. Originalidad/Relevancia: Agregamos información sobre el impacto y los resultados de un programa acelerador en múltiples escalas: espacial, temporal y de producto. Nuestro estudio es uno de los primeros en examinar un acelerador formal de desarrollo de videojuegos. Metodología/enfoque: Realizamos una etnografía de un programa de creación rápida de prototipos en el desarrollo de videojuegos. Los métodos incluyeron 810 horas de observación participante, 58 entrevistas y cientos de artefactos materiales analizados. Principales resultados: Los participantes de Accelerator crearon 42 prototipos de juegos, dos empresas recibieron financiamiento adicional, pero no se lanzaron juegos dentro del año del programa. Las escalas de los productos cambiaron con el tiempo, desde las expectativas hasta los prototipos y los juegos finales. La escala espacio-temporal del acelerador estaba abierta a interpretación. Los participantes y observadores tenían dos perspectivas espacio-temporales principales (presente-local y futuro-global) que cambiaron durante el período de un año. Aportes teóricos/metodológicos: Primero, conceptualizamos un acelerador como un lugar competitivo dual donde los participantes y los observadores se involucran en duelos y perspectivas espacio-temporales en evolución a lo largo del tiempo. En segundo lugar, desarrollamos el concepto de una escala acelerada de productos digitales para explicar el proceso de pasar de un producto acelerador a un producto final potencial. Contribuciones sociales/gestión: Concluimos que el impacto de un acelerador es más complejo que la estructura o la salida. El acelerador puede generar rápidamente ideas o prototipos, pero esto no garantiza un lanzamiento más rápido del producto final. Palabras clave: Aceleradora. Industria de los videojuegos. Etnografía. Incubadoras. Industrias creativas.
... Research studying entrepreneurial ecosystems in Silicon Valley, Bangalore, London and other regions finds that how entrepreneurs interact with entrepreneurial ecosystems, comprised of investors, mentors, support organizations (e.g. incubators, accelerators) and other actors who enable entrepreneurship, influence entrepreneurs' ability to acquire social, material and cultural resources which, in turn, influences the likelihood of venture growth and success (Goswami et al., 2018;Spigel, 2017;Stam and Van de Ven, 2021). Although ecosystems research has begun to examine how entrepreneurs build businesses focused on AI technologies in ecosystems (Hannigan et al., 2021;Cetindamar et al., 2020), there is no theory to explain how entrepreneurs' use of AI influences their interactions with entrepreneurial ecosystems. ...
... Entrepreneurial ecosystems research has generally focused on the impact of non-technology ecosystem elements, such as support organizations (e.g. small business development centres) (Goswami et al., 2018), culture (Donaldson, 2021) and networks (Neumeyer et al., 2019). However, the technologies that entrepreneurs implement in their ventures can have community ramifications. ...
Article
Purpose Entrepreneurs are increasingly relying on artificial intelligence (AI) to assist in creating and scaling new ventures. Research on entrepreneurs’ use of AI algorithms (machine learning, natural language processing, artificial neural networks) has focused on the intra-organizational implications of AI. The purpose of this paper is to explore how entrepreneurs’ adoption of AI influences their inter- and meta-organizational relationships. Design/methodology/approach To address the limited understanding of the consequences of AI for communities of entrepreneurs, this paper develops a theory to explain how AI algorithms influence the micro (entrepreneur) and macro (system) dynamics of entrepreneurial ecosystems. Findings The theory’s main insight is that substituting AI for entrepreneurial ecosystem interactions influences not only entrepreneurs’ pursuit of opportunities but also the coordination of their local entrepreneurial ecosystems. Originality/value The theory contributes by drawing attention to the inter-organizational implications of AI, explaining how the decision to substitute AI for human interactions is a micro-foundation of ecosystems, and motivating a research agenda at the intersection of AI and entrepreneurial ecosystems.
... However, many times, unawareness of the government programs among Indian female entrepreneurs deprives them of the utility of these benefits (Shukla et al., 2022). Goswami et al. (2018) identifies how accelerators or intermediaries in Bangalore further help connect the beneficiary entrepreneurs with the larger entrepreneurship ecosystem. These initiatives are critical in women's entrepreneurship: a recent study (IANS, 2021) shows that despite the various government policies and initiatives available, only 11 % of female entrepreneurs were aware of them. ...
Article
Entrepreneurial ecosystems have become a popular concept within research and practitioner contexts. Yet, while both literature streams have produced relevant eco-factors, no clear empirical evidence has emerged on their impact. This study addresses the following question: in impoverished areas, to what extent does the business ecosystem reduce gender differences in entrepreneurial success (controlling ownership and business longevity)? Our framework distinguishes three levels-cultural, social, and material-in the four major regions of the Indian ecosystem. Our results show that family support is most important in reducing the gender gap in the success of entrepreneurs. We establish the importance of social network support. We find no evidence that capital funding influences the gender gap in entrepreneurial success. Last, our study suggests that the more female entrepreneurs are exposed to local markets at the beginning of their enterprise, the more entrepreneurially successful they are than male entrepreneurs. Implications are discussed.
... Findings consistently suggest that accelerators help startups achieve milestones earlier (Clayton et al., 2018;Yu, 2020). Scholars also measure outcomes at the ecosystem level, highlighting how accelerators improve the entrepreneurial capacity of ecosystems Hochberg, 2014, 2019;Goswami et al., 2018;Xing et al., 2018). More recent studies try to understand the mechanisms by which accelerators support startups (Brown et al., 2019;Lyons and Zhang, 2018;Stevenson et al., 2020). ...
Article
Although the literature on accelerators, an important and newer model of entrepreneurial support, considers their performance and the definition of the form, little is known about how accelerators populate in a single ecosystem over time. We find accelerators are established by different types of entities such as non-profit organizations, local governments, universities, and even foreign government agencies with different goals. Based on a novel dataset of all 107 accelerator programs that ever operated in New York City, we propose a new way of categorizing accelerators by their founding attributes. We confirm that the emergence of accelerators in New York City started with the entry of non-profit accelerators for the purpose of local economic development. For-profit actors followed. Accelerators began from the periphery of the city’s geographic boundaries, but over time became concentrated in Manhattan. We also observe a shift toward sector specialization. Our contributions are to examine the development of one entrepreneurial support organization over time in one ecosystem, present a method to categorize accelerators based on their sub-niches, and to provide evidence of a catalyzing role of local government in fostering ecosystem emergence.
... [52] As shown in Figure 7, the nodes with purple colour represent the "traditional" topics (i.e., prior to 2010) in start-up success literature e.g., Entrepreneurialism, [81] high tech, [82] growth. [83] Meanwhile, the nodes with yellow colour represent the "recent" topics (i.e., 2015 onward) in start-up success literature e.g., Entrepreneurial ecosystem, [84][85] Start-up performance, [86] Open innovation; [87] and the nodes with green colour represent the topics first appeared between 2010 and 2015. ...
Article
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Despite being received increasing attention from academic scholars, there have yet any review study on the topic of start-up success. This work fulfills this research gap by investigating 1554 start-up success documents collected from Scopus dataset between 1981 and 2019. Using bibliometric analysis, we reveal that the topic of start-up success only receives more attention from academic scholars since 2011 onwards. Regarding geographical distribution, the US, Germany, and the UK are the three countries contributing the highest number of start-up success related documents. Besides, it’s revealed that 305 (or 19.6%) start-up success documents were published in the top 20 journals. The co-author analysis found that the research groups of start-up success are still small and dispersed and there was a lack of continuity in the research. The science mapping identified six main topics of start-up success, including: (1) Business in General, (2) Start-up Ecosystem, (iii) Academic Start-up, (iv) Drivers of Start-up Success, (v) Resources for start-up, and (vi) Start-up Model. The study’s findings provide implications for stakeholders, including academic scholars, policymakers, start-up owners, entrepreneurs, and practitioners.
... For example, Hochberg (2016: 40) find that "the arrival of an accelerator is associated with an annual increase of 104% in the number of seed and early-stage VC deals and an increase of 289% in the log total dollar amount of seed and early-stage funding provided in the region." Goswami et al. (2018) similarly find that accelerators can act as a bridge to the entrepreneurial ecosystem and help build local capacity, and this coalescing of resources is especially important for the legitimacy of social impact initiatives (Thompson et al., 2018). By validating SIAs as a vehicle for social and economic change, we believe our findings should encourage governments and foundations that seek to affect societal change to invest in them as a valuable part of the local entrepreneurial ecosystem. ...
Article
Full-text available
Given the legitimacy challenges faced by entrepreneurs, gaining access to the resources necessary to create viable new ventures is often difficult. Accordingly, scholars advocate that entrepreneurs align with high-status partners to convey that they are an accepted part of the sociocultural and organizational landscape. Although startup accelerators have been argued to play this supportive role for high-tech, high-growth ventures, it remains unclear whether they are effective at serving the needs of ventures pursuing social missions alongside business structures, or for-profit social ventures (FPSVs). To explore this issue, we examine whether social impact accelerators (SIAs), accelerators specifically designed to support FPSVs, help such ventures make the transition from mere ideas to viable organizations, a process known as emergence. To determine a causal relationship, we employ a quasi-experimental design and adopt propensity score matching with the nearest neighbor matching algorithm to study 7185 startups that applied to 383 accelerators worldwide from 2013 to 2019. By matching accepted startups to a control group of rejected startups, we find that SIAs, on average, facilitate new venture emergence, with accelerated FPSVs raising more external financing, earning more revenues, and hiring more full-time employees than their unaccelerated counterparts. These results hold when controlling for selection bias, thereby providing robust evidence for a causal relationship between acceleration and startup emergence. However, a subsequent subgroup analysis reveals that this causal effect is contingent across a breadth of “who,” “when,” and “where” contexts, highlighting the idiosyncratic differences that different startups face in the acceleration process.
... investors, venture capitalists) play a salient role in the genesis and expansion of entrepreneurial ecosystems (Autio et al., 2017, Autio and Levie, 2017, Goswami et al., 2018 by investing in tech start-ups, university spin-outs, academic entrepreneurs, and collaborative research. ...
Thesis
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Over the past two decades, there has been a significant growth in the popularity of the concept of ecosystem in the research and practice associated with management of technology and innovation. Managers in spatially bounded ecosystems (e.g., knowledge, innovation, and entrepreneurial ecosystems) seek opportunities to explore and exploit technical knowledge. Yet, ambiguities and challenges in discovering opportunities (e.g., lack of resources, cognitive and policy constraints) constrain the process, leading to loss of latent opportunities, which, in turn, culminate in financial and reputational damages. The scholarly research has investigated this problem by employing an exploratory approach and suggested practical solutions (e.g., open innovation practices) to attenuate the effects of those challenges within specific contexts (with respect to region and domain). However, little attention has been paid to the potential of analytical methods for systematically improving opportunity identification processes in ecosystems. The present PhD with publications dissertation, comprising four scholarly journal articles (the forth manuscript to be submitted soon), adopted an analytical approach (with ecosystem as unit of analysis), culminating in a methodological framework for systematically identifying opportunities in spatially bounded ecosystems (knowledge, entrepreneurial, innovation). The proposed framework utilizes data from scientific publications, patents, and domain-specific expert views as inputs, employs techniques from data science (particularly scientometrics, patent statistics and text mining techniques), and generates valuable insights and methodological approaches for all actors in these ecosystems as output. The current dissertation demonstrates an exemplary application of the proposed framework in the context of Nordic renewable energy ecosystem. This research has significant implications for practice, management, and policy by proposing a framework that assists with strategic planning (e.g., collaboration, investment, productivity monitoring), saving resources (e.g., time, budget), policy promulgation (supportive and regulatory policy instruments), and potentially stimulation of entrepreneurial activities (e.g., productization and servitization). Moreover, the present thesis contributes to the methods commonly employed to analyze ecosystems by combining extant and novel methods in scientometrics, patent statistics, and text analytics. This study extends the concept of ecosystem by synthesizing the literature related to value creation and capture in ecosystems and developing new constructs relating to ecosystems.
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Hub-based entrepreneurial ecosystems (HEEs) have become an important venue for entrepreneurship. This study examines how ecosystem-specific resources and capabilities are orchestrated by ecosystem actors (i.e., hub firms and ecosystem entrepreneurs) to support the development of new ventures in the context of HEEs. Using an explorative single case study approach, we uncover nine distinctive resource orchestration subprocesses that are grouped into three aggregate processes that help sustain enduring entrepreneurship in the HEE context. Our findings extend and complement the literature on entrepreneurship and ecosystems by developing a new resource orchestration model and by illustrating how resource orchestration in an HEE facilitates the synergies across ecosystem ventures as well as the synergies between hub firms and ecosystem entrepreneurs in coexploring and coexploiting new opportunities.
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What explains differences in firms’ abilities to acquire competitive capabilities? In this paper we propose that a firm’s embeddedness in a network of ties is an important source of variation in the acquisition of competitive capabilities. We argue that firms in geographical clusters that maintain networks rich in bridging ties and sustain ties to regional institutions are well‐positioned to access new information, ideas, and opportunities. Hypotheses based on these ideas were tested on a stratified random sample of 227 job shop manufacturers located in the Midwest United States. Data were gathered using a mailed questionnaire. Results from structural equation modeling broadly support the embeddedness hypotheses and suggest a number of insights about the link between firms’ networks and the acquisition of competitive capabilities. Copyright © 1999 John Wiley & Sons, Ltd.
Conference Paper
Since Indian independence in 1947, Bangalore has been envisioned as a center for science and technology. This paper will show that while science and technology, especially information and communication technologies (ICTs), has persisted as the lietmotif in these visions, the handmaiden has shifted from the public sector enterprise to internationally mobile capital. This paper will trace the trajectory of this shift and Bangalore’s emergence from an autarkic economy to its integration into production networks and, subsequently, into innovation networks of the global informational economy. To this end, the paper will describe the technological changes and an increasingly liberal policy environment that have facilitated the emergence of a regional innovation system in Bangalore. A critical aspect of this regional innovation system is the institutional means to provide skills and infrastructure. Responding to the regional innovation system, there has evolved a historically specific organization of production in the ICT industry, with local and international linkages for production and innovation. More recently, addressing the “bottom of the pyramid”, is providing firms with new opportunities and resources for innovation to address national and international markets. The paper discusses the implications of the Bangalore region for our understanding of global innovation networks.
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The success of an innovating firm often depends on the efforts of other innovators in its environment. How do the challenges faced by external innovators affect the focal firm's outcomes? To address this question we first characterize the external environment according to the structure of interdependence. We follow the flow of inputs and outputs in the ecosystem to distinguish between upstream components that are bundled by the focal firm, and downstream complements that are bundled by the firm's customers. We argue that the effect of external innovation challenges depends not only on their magnitude, but also on their location in the ecosystem relative to the focal firm - whereas greater innovation challenges in components enhances the benefits that accrue to technology leaders, greater innovation challenges in complements erodes these benefits. We further argue that the effectiveness of vertical integration as a strategy to manage ecosystem interdependence increases over the course of the technology life cycle. We explore these arguments in the context of the global semiconductor lithography industry from its emergence in 1962 to 2005 across nine distinct technology generations. We find strong support for our arguments.