Innovation and Entrepreneurship

Edward J. Malecki, The Ohio State UniversityBen Spigel, University of Edinburgh Business School

Abstract: We follow Schumpeter in attributing to entrepreneurs the spark to bring new combinations to market by combining knowledge, perceived opportunity, and other resources to form new firms. A link between innovation and entrepreneurship was first seen in new firms exploiting new technologies in high-technology regions. This context set the tone for research, which we explore in this paper. We identify five topics: entrepreneurship in high-tech contexts, spinoffs from university research, science parks (or research parks), the local/regional ecosystem or innovation system, and flows of knowledge within social and professional networks. Underlying these five attributes of high-tech innovation are cultural outlooks and orientations. Without an understanding of how culture influences entrepreneurial and innovative activities, it is difficult to study their relationship with the cultural contexts in which they take place. Building on a nexus-based view of innovation and entrepreneurship, we argue that culture is best understood as a process through which actors interpret the world around them and which can either encourage or discourage entrepreneurial and innovative activity. Keywords: Economic development, Innovation, Policy and Practice

Introduction

The connection between innovation and entrepreneurship originated with Schumpeter’s

(1934) emphasis on new combinations – new goods, new methods or processes, new markets,

or the new organization of an industry – introduced by entrepreneurs. “New combinations

are, as a rule, embodied, as it were, in new firms” (Schumpeter 1934: 66). As Landström et

al. (2012: 1155) observe, “Schumpeter’s idea was … that economic growth resulted not from

capital accumulation, but from innovations or ‘new combinations’ that create a

disequilibrium on the market.” Despite the common origins of research on both innovation

and entrepreneurship in the work of Schumpeter, they have “evolved over time as two largely

separate research fields” and remain “surprisingly disconnected from the neighbouring field

of innovation studies” (Landström et al. (2012: 1171-1172).

The definition of entrepreneurship has evolved over time (Braunerhjelm 2011; Hébert and

Link 2006). Drucker (1985) combines innovation and entrepreneurship and stresses that

entrepreneurs must be innovative, which requires systematic search and analysis of

innovative opportunities. A key aspect of new firms is that entrepreneurs have more to learn

from their local environment and actors within it than do large firms (Zahra et al. 2006).

In entrepreneurial capitalism, small, innovative firms play a significant role (Baumol et al.

2007). Such firms are the “fruit flies” of innovation, contributing to its heterogeneity (de Jong

and Marsili 2006). There are several types of innovative entrepreneurship, including new

New technologyTechnology-based Based firms Firms (NTBFs), spinoff firms, and high-

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growth startups (Stam and Nooteboom 2011). NTBFs are acquirers, synthesizers and

introducers of new technology, and they contribute to the local or regional economy (Fontes

and Coombs 2001). Academic spinoffs are typically in research and development (R&D)-

intensive high technology, associated with new fields and emerging sectors (Lawton Smith

and Bagchi-Sen 2012).

Generally speaking, the stylized facts of innovation leave little space for entrepreneurs.

Exceptions are found in the literature on nursery cities (Duranton and Puga 2001) and cluster

formation (Bresnahan and Gambardella 2004). While The the conventional wisdom and

standard models focus on cities as the locus of innovation,; innovation occurs in small and

isolated places as well (Shearmur 2012). Recent research highlights how knowledge sparks

innovation and how it lubricates entrepreneurship (Bae and Koo 2009; Braunerhjelm et al.

2010; Iammarino and McCann 2006; Qian et al. 2013).

We review the literature on entrepreneurship and innovation in regions, highlighting dynamic

processes and supporting institutions (Stam and Nooteboom 2011). We stress that this paper

is not about the topic of spillovers and agglomeration (Feldman and Avnimelech 2011;

Feldman and Kogler 2010; van Oort and Bosma 2013). As Shearmur (2012: 2352) suggests,

“innovation dynamics do not necessarily occur in agglomerations (although of course they

can occur there).”

We identify five core topics in this paper. First, much early research on entrepreneurship

focused on high-tech contexts (for example, biotech and ICT). Second, the phenomenon of

firms spinning out of university research put a spotlight on academic and basic research as

the starting point of innovative entrepreneurship. Third, science parks (research parks in the

USA) were identified as particularly fertile locations for high-tech entrepreneurs. Fourth, the

local or regional ecosystem or innovation system has been identified as a nexus of social and

economic links and support for entrepreneurship. Fifth, flows of knowledge within social and

professional networks allow diffusion of knowledge to new places. Underlying these topics

are the regional and organizational cultures that influence the willingness of actors to engage

with the risks of the entrepreneurship process.

The high-technology context

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Empirical observation of the link between innovation and entrepreneurship largely grew out

of the experience in California’s Silicon Valley and Route 128 outside Boston beginning in

the 1960s, and set the tone for understanding the links between high-tech innovation and

entrepreneurship. By the mid-1980s, it was well-established that places where high-

technology, R&D-intensive firms were active and abundant generated spinoffs and grew into

(what would later be called) clusters (Cooper 1986; Cooper and Folta 2000; Malecki 2011).

Silicon Valley was not the product only of entrepreneurs; large multilocational firms also

were attracted to the region and its universities and clusters of firms, and they continue to be

a lure (Adams 2011; Poon et al. 2006). Globalization of R&D has spread the potential for

high technology to new places (Malecki 2010). Large firms, together with entrepreneurs, co-

create regional high-tech clusters (Smilor et al. 2007). A vibrant global competition for high-

tech success continues (Anttiroiko 2004; Castells and Hall 1994).

Technology clusters differ significantly from other industrial clusters in that they are tied

more to the early stages of industry life cycles, and resources at the regional level support

growth and innovation (St. John and Pouder 2006). Therefore, what is considered “high tech”

changes over time, encompassing innovative sectors that present new opportunities. The

principal activity of technology-based sectors is research, and their main input as well as

output is knowledge. For firms, locating near sources of knowledge (such as universities and

research centers) and clustering in specialized labor markets maximizes opportunities for

collective learning and exploitation of entrepreneurial opportunities (Audretsch et al. 2006).

We may be able to identify tendencies such as those above but, as Iammarino and McCann

(2006) point out, diversity and heterogeneity continue to operate, so that we are unable to

predict with accuracy where innovative clusters will emerge.

Therefore, high technology is typically defined as innovative, and measured by through

inputs of expenditure on R&D and employment of scientists, engineers, and technicians

(Hecker 2005). Schoales (2006) expands the concept of newness to include all industries in

which product life cycles are very short, thereby embracing several service sectors including

advertising, design, fashion, finance, and others. Stoneman (2010) likewise includes products

of the ‘creative industries’, encompassing culture, media, and the arts, as examples of soft

innovation, which places emphasis on aesthetic rather than technological characteristics.

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Finally, knowledgeKnowledge-intensive Intensive business Business services Services

(KIBS) are a “hidden engine” of high technology (Probert et al. 2013).

For several decades, we have come to consider high-tech industries and regions as innovative

and entrepreneurial. By studying innovative entrepreneurship not only in prominent high-tech

regions, but also in other locales, we have learned that innovation and entrepreneurship are

found in many, though by no means all, places.

University spinoffs

Universities are frequently among the “incubator organizations” that are thethat act as the

foundation of innovative entrepreneurial regions (Mayer 2007). Spinoffs in the Boston area

were largely from MIT, rather than Harvard or the other higher education institutions in the

Boston area (Roberts 1991). Similarly, Silicon Valley evolved both from corporate spinoffs

and from entrepreneurial activity related to Stanford University. These two models are

difficult for other regions to imitate, since the numbers of spinoff firms from top research

institutions are not possible to match in other settings (Degroof and Roberts, 2004). Shane

(2004) summarizes the findings for the USA, updated by Grimaldi et al. (2011).

Both the US and European experiences have created an expectation regarding the regional

role of a university: to contribute to the regional economy through spinoffs of new firms

based on innovative technologies that flowflowing from university research (Lerner 2005;

Wright et al. (2007). Etzkowitz (1983) has documented the role of entrepreneurial scientists

and entrepreneurial universities in American academic science. His picture of entrepreneurial

researchers and science parks has had broad influence, which has grown further with the

development of the “triple helix” model (Etzkowitz and Leydesdorff, 2000). Universities are

not monolithic; within each, four sets of actors – individuals, research groups, departments,

and the university as an organization – compete for resources, prestige, and recognition

within universities (Deiaco et al. 2012; Etzkowitz 2003). For academic entrepreneurs, a

decision to start a firm is rooted within the values of an academic career (Franzoni and

Lissoni 2009).

Through spinoffs – and profiting from spinoffs – universities have broadened the scope of

their activities beyond teaching and research. The “entrepreneurial university” model

includes patenting, commercialization, and technology transfer as a “third stream” of revenue

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and/or as a way to engage with the local communitycontribute to the local economy (Clark

1998). European universities are “learning to compete” and becoming multidimensional in

their entrepreneurialism and other aspects of the “knowledge business” (McKelvey and

Holmén 2009). The allure of profit has been especially strong in biomedical fields (Åstebro

and Bazzasian (2011). Rothaermel et al. (2007) and Siegel (2011) review the burgeoning

literature on academic entrepreneurship and university technology transfer.

European countries have attempted to imitate the favorable conditions found for spin-off

formation in US high-tech regions (Mustar et al. 2008; Wright et al. 2007). The variability

among national academic cultures is overwhelmed by the “imitation effect” that has “led to a

convergence of policies toward the same goal: to foster a larger number of academic spin-

offs.” Imitation also leads nearly all imitators to target biomedical and nanotechnology fields.

Such policies, however, have not imitated faculty mobility, university autonomy, and

generous support of basic research found in the US (Franzoni and Lissoni 2009; Howells et

al. 2012).

Spinoffs started by professors, researchers and other university employees are are relatively

easily easy to tracktracked when professors, researchers, and other university employees are

the entrepreneurs. However, former students (including alumni) also start firms, utilizing

knowledge and contacts that originated at a university. Many spinoffs are by graduates

(Åstebro et al. 2012), but such firms are not readily identified in available data sets (see also

Bathelt et al. 2011). Thus, recent research, reviewed by Grimaldi et al. (2011), Mustar et al.

(2006), and Pirney et al. (2003), scans moves beyond university faculty and research staff to

identify a broader cadre of university-related entrepreneurs. Broad surveys of alumni have

been conducted by MIT (Hsu et al. 2007; Roberts and Easley 2011) and Stanford (Eesley and

Miller 2012). However, A a focus on graduates or alumni will missmisses entrepreneurs who

drop out (e.g., Michael Dell and Bill Gates) as well as those who benefit indirectly from the

university environment.

The principal challenge of understanding university startups is that far more knowledge

transfer occurs than is imagined in the linear technology transfer model. Research “spills

over” and informal transfer of knowledge takes place continually as research is conducted

and as student entrepreneurship is encouraged in other ways that are underestimated and

understudied (Grimaldi et al. 2011; Nelson 2012). Many spinoffs are “spontaneous” rather

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than planned, growing out of informal activities in the “grey zone” where tacit knowledge is

shared and transfused into society (Bathelt et al. 2010; Nilsson et al. 2010; Rappert et al

1999). Many university-related start-ups arise from “decentralized idea development” that

may have originated in a classroom or lab or from social ties that are informal and related to

the university only indirectly. Such tacit knowledge is basically unknown to and

uncontrollable by a university, yet it may well represent the majority of knowledge

transferred (Karnani 2013). Knowledge-related collaboration by academic researchers with

non-academic organizations, whether patentable or not, is innovative (Perkmann et al. 2013).

Universities produce many outputs, including new knowledge and human capital. They

transfer existing know-how and produce technological innovation. They also provide regional

leadership, co-producing the regional knowledge infrastructure. Together, the mechanisms by

which university R&D activity stimulates economic development are both broader and more

diverse than spinoffs, patenting, and licensing activity (Benneworth and Charles 2005;

Goldstein 2009; Lendel 2010).

As the discussion above suggests, research on academic spinoffs has been empirically rich

but “mainly atheoretical” (Autio 2000: 332). Spinoffs are part of the culture of

entrepreneurial universities, but they can hardly be planned and they vary greatly in nature.

Academic culture is not necessarily at odds with entrepreneurship. Scientific productivity

enhances entrepreneurial activity rather than substituting for it (Franzoni and Lissoni 2009;

Van Looy et al. 2010). In developing a spinoff strategy, a university should focus on

developing a critical mass of world class research in a few areas in which they can attract

industrial partners (Siegel et al. 2007). The exceptional university culture also builds an

institutional structure of incentives, such as profit shared among the university, departments,

and inventors. However, a research-intensive institutional culture can discourage technology

transfer or commercialization activities if they are seen as distracting from basic research and

publication.

Entrepreneurs penetrate the “knowledge filter” between research and economic use (Carlsson

et al. 2009). They are able to do so when an entrepreneur has the ability “to understand new

knowledge, recognize its value, and subsequently commercialize it by creating a firm” (Qian

and Acs 2013: 191). This ability, which Qian and Acs call entrepreneurial absorptive

capacity, involves two dimensions: scientific knowledge as well as market or business

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knowledge. A pool of academic researchers and their new firms adds to the regional

knowledge base for further innovative entrepreneurship.

University spinoffs are innovative, applying cutting-edge research to new purposes. They

also are an unusual type of entrepreneurship, because academic entrepreneurship is counter to

long-standing scholarly models (Martin 2012). New skills must be acquired, and new

networks formed, to assemble a new spinoff firm and for it to succeed (Clarysse et al. 2005;

Vohora et al. 2004). Without question, university spinoffs combine innovation and

entrepreneurship and are the archetypes of new combinations.

Science parks and research parks

The Silicon Valley experience also highlighted the Stanford Research Park (Stanford

Industrial Park until the 1970s) as a site for the emergence and growth of firms. As the first

university-owned industrial park, it has inspired imitators since the 1970s (Anttiroiko 2004;

Miller and Coté 1987). Because of the diverse nature of science parks and the firms that

locate in them, they serve several functions and appeal to different types of firms at once

(Johannisson et al. 1994). Consequently, much recent research has focused on creating

typologies to understand this diversity (Mustar et al. 2007; Nicolau and Birley 2003; Pirnay

et al. 2003). In general, science parks of research-oriented universities, and parks that are

older are nearer to the main university campus, are more likely to contain university spinoff

companies (Link and Scott 2005).

Many science parks also have an incubator function, but investigations into the survival and

performance of tenant firms have been investigated unevenly and incompleteely (Bergek and

Norrman 2008; Phan et al. 2005). Because of their diversity, typologies also have been

constructed to understand the roles and relative success of incubators (Bergek and Norrman

2008). As science park occupants – many of them university technology-based spinoffs – go

through various growth stages, different incubator services are needed in each stage (Chan

and Lau 2005; van Geenhuizen and Soetanto 2009).

Science parks not only incubate new firms but also attract established companies. For large

firms, science parks allow collaborative links to be established with a recognized academic

‘center of excellence’ and to take advantage of an agglomeration of skilled researchers and

new graduates. Proximity to a center of excellence may attract large firms, but does not

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necessarily indicate any linkage or interaction with the local universities – or with one

another (Johannisson et al. 1994).

According to Macdonald and Deng (2004: 3), “what little evidence there is does not conclude

that science parks offer the optimum location for high technology firms. Indeed, it would

seem that the science park offers little advantage at all”. The most imitated regions were the

product of serendipity rather than of planning – but grounded in the benefits of agglomeration

economies, externalities, networking, and clustering, with most information flow taking place

informally. Despite their rather poor proof of success, science parks have remained extremely

popular as a policy tools (van Geenhuizen and Soetanto 2008).

Overall, science parks continue to be an attractive policy for universities and other regional

players. Because they are property-based, the temptation is always present to keep them filled

– with large tenants as well as small, with technology lifestyle businesses as well as high-

growth potential start-ups (Harrison and Leicht 2010). Not surprisingly, they have difficulty

to fulfill the needs of this diverse mix of firms to have positive impact, and to enhance the

reputation of the university sponsor (Chan and Lau 2005). Much depends on what is being

evaluated. Studies of science parks have focused on firms (numbers of spinoff and other

firms, innovativeness, survival, growth), the science park itself (employment, networking),

and the regional economy (numbers and types of firms, employment) (Van Geenhuizen and

Soetanto 2008). The variety of purposes and functions of science parks remains problematic.

Perhaps, as van Geenhuizen and Soetanto (2008: 106) suggest, we “need to investigate more

thoroughly why Science Parks exist in the first place.”

Regional/local ecosystems and innovation systems

Urban areas offer favorable conditions as incubators for innovative entrepreneurship, as a

result of their economies of density and the opportunities created by cities as nuclei of

broader networks, both local and global (Nijkamp 2003). Much research has aimed to

understand just what is present in the most innovative regions. Once the conditions are

known, can they be created, grown, or transferred to other places?

The synergy necessary for a self-sustaining area is found in an active local or regional

‘entrepreneurial ecosystem’ (Bahrami and Evans 1995). Silicon Valley’s innovative

ecosystem represents an the archetypical ‘entrepreneurial Entrepreneurial regional Regional

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innovation Innovation system’ System (ERIS) (Cooke 2004). The environments found in and

around Boston (USA), Cambridge (UK) and Southern California are atypical, and can be

argued to act as “regional incubators” (Clarysse et al. 2005: 213). More broadly, such habitats

and ecosystems are ‘regional Regional innovation Innovation systems’ Systems (RISs). RISs

are, at the regional scale, the institutional characteristics that influence innovation at a scale

smaller than the Nnational innovation Innovation system System (NIS) (Asheim and Gertler

2005; Cooke 2004). Generally, entrepreneurship increases with the level of economic

development, in an S-shaped manner (Acs and Szerb 2009). The NIS and national policies

affect strongly the nature of university entrepreneurialism and constrain regional policy

(Uyarra and Flanagan 2010).

“There is no such thing as an innovation system without entrepreneurs. Entrepreneurs are

essential for a well functioning innovation system” (Hekkert et al. 2007: 421). Indeed,

entrepreneurial activities, together with knowledge development, knowledge diffusion

through networks, and market formation, are among the key functions of innovations. Recent

research has moved beyond a focus on individuals to emphasize the systemic nature of

entrepreneurship, whether within national and regional innovation systems (Qian et al. 2013;

Radosevic and Yoruk 2013) or as a national system of entrepreneurship (Szerb et al. 2013).

Knowledge-intensive entrepreneurship is a systemic feature of innovation systems, and new

knowledge, innovation, and entrepreneurship are inseparable elements of a dynamic

innovation system (Radosevic and Yoruk 2013: 1015). A RIS must have strength not only in

innovation, but also the capacity to generate and attract entrepreneurship and talent (Cooke

2007).

RISs can be seen to embrace other concepts at the subnational scale, including clusters,

territorial production complexes, productive systems, territorial systems, milieus, and local

systems (Asheim et al. 2011; Moulaert and Sekia 2005). A RIS also must be linked to

knowledge and innovation sources in other regions. These “pipelines” serve as conduits for

an interregional spatial innovation system (SIS) (Bathelt et al. 2004; Oinas and Malecki

2002). However, the SIS structure the structure of spatial innovation systems differs among

high-tech industries. Biotechnology is characterized by an economic geography that is less

concentrated (and more dispersed among global biotech centers) than that of semiconductors

(Kenney and Patton 2005).

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Julien (2007) depicts the entrepreneurial milieu and identifies information and networks as

necessary conditions, and innovation as a sufficient condition, for entrepreneurship. These

attributes of innovative milieus are soft and invisible, and therefore are hard to create,

maintain, and change – and to measure. Policies and investments in education and training,

R&D, technology transfer, and marketing do not automatically ‘produce’ innovations or new

firms.

A key ingredient in ERISs is venture capital, facilitating serial start-ups (Cooke 2007; Florida

and Kenney 1988). Venture capitalists contribute more than money to entrepreneurs; they

also provide advice and guidance and links to other networks (de Clerq et al. 2006; Manigart

and Sapienza 2000; Zider 1998). Other intermediaries, such as attorneys, lawyers, and

consultants, also provide key knowledge and act as gatekeepers for entrepreneurs (Cooke

2008; Howells 2006). Finally, information, advice, and encouragement from experienced

entrepreneurs adds social capital to an entrepreneur’s own human capital (Mosey and Wright

2007).

The location of venture investors and their investments remains stubbornly concentrated in

only a few regions (Mason and Pierrakis 2013; Kenney 2011). It is difficult to create a venture

capital industry where none has existed. The emergence of a VC industry requires both a pool

of entrepreneurs and venture capitalists – and suitable capital markets for exit. Venture

capital firms based in locales that are venture capital centers outperform those elsewhere,

regardless of the stage of the investment (Chen et al. 2010), and this benefits local firms

(Zhang 2007). Such a VC system, with startups and venture capital co-evolving, can emerge

in different ways (Avnimelech et al. 2010; Kenney 2011). However, agglomeration forces

strongly affect venture capital and consequently it is very difficult to disperse to other places.

Experience in and personal links to Silicon Valley might be one route (Saxenian 2006), but

more than imitation is involved.

A key role of universities is to create and enhance the territorial regional knowledge pool

(Benneworth and Charles 2005). This is an indirect contribution to the regional economy, and

involves a densification of the techno-economic network (Fontes and Coombs 2001), which

makes the RIS more “munificent” (Dubini 1989; Malecki 2009). Uyarra (2010) outlines

several key roles of universities which affect innovation and entrepreneurship. Universities

are “knowledge factories” and “boundary-spanning institutional nodes” that are “relational,”

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“entrepreneurial” and “developmental” within their regions. Goddard (2011) distinguishes

among three levels of university activities: first, those that are less complex, and tend to be

transactional and timebound with clear outcomes; second, those that are more complex,

whose outcomes are longer term and less tangible; and third, highly complex activities with

potential for transformational change in regions. Power and Malmberg (2008) are skeptical

about the degree to which universities actually contribute to regional development or more

broadly to regional innovation systems, other than by attaining global excellence in research,

innovation, and value creation.

RISs evolve for many reasons, and the concept of a RIS has also evolved (Cooke 2008).

Among the few constants in the dynamic is that high-tech regions have advantages that are

able to adapt to new conditions. “The most radical form of change is brought about by the

emergence and growth of industries based on new technological and organizational

trajectories such as knowledge-intensive and high-technology industries” and these often

grow from earlier successful high-tech sectors, even if different from the new ones (Tödtling

and Trippl 2013).

Knowledge flows within networks

Entrepreneurs exist in networks – social and personal as well as business- and innovation-

oriented (Johannisson et al. 1994). A network mix – both weak ties and strong ties, both local

and nonlocal networks, and both internal and external networks within the regional

environment – is needed to provide social ties, knowledge, technology, marketing, and

reputation for entrepreneurial success (Lechner and Dowling 2003). Networking among firms

promotes innovation in both medium-technology and high-tech clusters as well as those that

are high-tech (Cappellin and Wink 2009). Dense networks of relations and multifaceted links

between university faculty and non-academic actors are also common (Martinelli et al. 2008).

In network-intensive regions, knowledge is shared and a more favorable entrepreneurial

climate results (Malecki 1997). For high-tech firms, localized linkages are a source of

innovation (Lawton Smith 2008).

While policies to spark innovation and/or entrepreneurship are common (Hart 2003;

Lundström and Stevenson 2005), they are only partially able to influence knowledge flows.

Among the most useful knowledge is that generated by close interaction during which

knowledge remains tacit, but which may be measurable later in co-authored articles and

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patents. High levels of tacit knowledge exchange are likely only when close links exist

between academic scientists and researchers in firms (including recent spinoffs) (Zucker et al.

2007). Other unintended, informal knowledge spillovers – from universities, within firms,

and between firms – are largely ignored (Howells 2002). Networks to identify and attract

human resources are often more important for start-ups than financial networks, and are a key

element in successful policies (Clarysse and Bruneel 2007). Overall, networks are diverse,

complex, and dynamic, changing as the needs of firms change (Steiner 2011).

Although we have not stressed the point thus far, knowledge is extremely complex, far

beyond the dichotomy between tacit and codified knowledge (Howells 2012). Howells et al.

(2012) find that informal and formal knowledge links are equally significant in influencing

innovation outcomes in firms, reinforcing one another in a complex manner.

Cultural outlooks and orientations

[Ben]Innovative entrepreneurship is not a disembodied economic activity. While an

entrepreneur may be aa “heroic economic superman” (Schumpeter, 1934: 85) who disrupts

existing value chains through novel innovation, this is not done in isolation. Rather,

entrepreneurs are deeply embedded in networks of social and cultural outlooks and beliefs.

Researchers have long argued that the social character of a place, industry, or organization

has a profound influence on innovation and entrepreneurship processes (see Saxenian, 1994;

Schoenberger, 1997; Feldman, 2001; O’Shey et al., 2005). This realization has, in turn, led to

an interest amongst policymakers on how to foster a particular kind of culture within a region

or organization that supports risk taking, cooperation, and entrepreneurship (e.g. Acs et al.,

2008; Bercovitz and Feldman 2008). The goal of such efforts is the creation of a community

that encourages the free exchange of knowledge and support, with the expectation that this

contributes to innovative entrepreneurship and therefore higher levels of of economic growth.

While the importance of culture is well understood, its complex and ephemeral nature has

made it difficult to study its role in the entrepreneurship process. Many authors fail to define

how they use culture or use only individual attributes of a person, such as nationality or

ethnicity, to identify their ‘culture’ (see Wilkinson, 1996 and Raghuram and Strange, 2001

for critiques of such studies). The lack of attention to defining culture is problematic but not

surprising: culture is a difficult word to define, with meanings ranging from the agricultural

to the artistic. The result is that research on culture within the entrepreneurship and

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innovation literature tends to either rely on over-simplified notions of culture by assuming a

homogeneous national culture, or produces descriptive accounts of cultural attributes with

few generalizable findings.

The major focus within the entrepreneurship literature is how cultural attributes influence

decisions relating to starting, financing, and growing a new firm. This began with very broad

based investigations into differences in entrepreneurial rates and performance between

nations (Shane, 1992; Tan, 20002; Morris and Schindehutte 2005). Such research frequently

draws on the work of Greet Hofstede (2001), who identifies five core cultural attributes:

power distance, uncertainty avoidance, individualism/collectivism, masculinity/femininity

and long term/short term orientation. Hofstede provided scores for each of these attributes for

over seventy countries, allowing researchers to investigate relationships between variations in

national cultural attributes and aggregate levels of innovation and entrepreneurship. Several

articles have identified low levels ofof uncertainty avoidance (the desire to avoid risk and

uncertainty) and high levels of individualism (focus on individual over collective needs) as

important for encouraging innovation-based entrepreneurship (e.g. Shane, 1993; Lee and

Peterson, 2000). However, critics have questioned the usefulness of Hofstede’s methods for

cross-cultural research, pointing out that it ignores variation in cultural outlooks within

nations (McSweeney, 2002) and relegatesrelegates culture to a deterministic variable

(Baskerville, 2003).

In light of these criticisms, there has been a renewed interest in interpretive approaches to

understanding the relationship between culture and innovative entrepreneurship. These

studies employ qualitative, ethnographic, or historical analysis to identify salient cultural

attributes within a region, organization, or industry and show how these encourage or

discourage innovative entrepreneurial practices. Works such as Saxenian’s (1994) Regional

Advantage or Schoenberger’s (1997) The Cultural Crisis of the Firm were instrumental in

demonstrating not only the existence of cultures that are beneficial or detrimental to

innovation, but also revealing the causal relations between these outlooks and innovative

activities. However, because these methods are focused on individual case studies, they

provide few generalizable findings that are useful in other contexts. This contributes to the

movement of policies that were effective in one context to other regions, often leading to the

failure of policies that fail to connect with their new cultural environment.

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Organizational and regional cultures have become important tools in the study of academic

entrepreneurship and university spinoffs (Jenson et al., 2003; Bathelt et al., 2011). The

culture of a university, often seeded by the university’s founders, plays a role in the creation

of formal policies and informal beliefs within the university that promote successful spinoff

and technology transfer activities, or conversely that discourage non-research activities like

patenting and commercialization (Colyvas, 2007; Bramwell and Wolfe, 2008). It is difficult

for top-down policies by university administrators to promote the formation of spinoffs

because they clash with preexisting informal cultural outlooks that dismiss entrepreneurship

as a violation of academic norms (Bathelt and Spigel, 2011). This points to the role of culture

as a social system underlying more formal programs such as tenure, promotion, and hiring:

universities such as the Stanford or MIT, which have had an industry-oriented culture since

their founding, have had greater success in seeding innovative startups than other universities

whose culture is focused on basic science. Failed attempts by other universities to foster a so-

called ‘entrepreneurial cultures’ illustrate the difficulty of overcoming cultural inertia within

large organizations with diffuse power structures.

Similarly, there has been a bourgeoning interest in qualitative studies of entrepreneurial

cultures. This is part of a larger movement within entrepreneurship studies to highlight the

discursive and social aspects of entrepreneurship (Dodd, 2002; Steyaert and Katz, 2004). As

Licht and Siegel (2006: 516) argue: “culture bears a profound impact on all facets of

entrepreneurship in society.” The development of these perspectives in management science

has been mirrored by other allied disciplines such as economic geography, where a growing

body of work has investigated the origins and influence of regional cultures on

entrepreneurship. Feldman’s (2001; Feldman et al., 2005) work on Washington D.C and

James’ (2005) work on Salt Lake City examine the development of local cultural norms

towards entrepreneurship and how this has influenced networks of entrepreneurs, advisors,

and investors. Evidence suggests that these entrepreneurial cultures develop over time in

response to both long-term economic and demographic developments as well as through

short-term shocks like the loss of a major employer.

The examination of culture has been a principal feature of recent research into entrepreneurial

ecosystems. Entrepreneurial ecosystems are combinations of public programs, innovation-

producing universities, support networks of advisors, and availability of venture and angel

investment within a region that create the conditions for successful entrepreneurship- led

14

economic growth and innovation (Kenney and Patton, 2005; Malecki, 2009; Harrison and

Leitch, 2010). As with innovation ecosystems, entrepreneurial ecosystems provide a context

in which new ideas constantly circulate through local networks, providing opportunities for

nascent entrepreneurs and where successful firm founders act as both role models and

investors for fast-growing ‘gazelle’ startups. All of these elements, in turn, depend on

existence of an underlying culture — or as Malecki (1997:82) terms it, “entrepreneurial

climate,” that normalizes the high risk, long hours, and absence of immediate rewards that

characterize innovative entrepreneurship.

While the importance of culture in entrepreneurial ecosystems is well accepted (Nijkamp,

2003; Julien, 2007), the processes through which cultural outlooks catalyze and reproduce

ecosystems are unclear. Entrepreneurs are to some extent culturally embedded in their home

region, meaning that they internalize the collective understandings and social ‘scripts’ within

the community (Zukin and DiMaggio, 1990). A supportive entrepreneurial culture might then

normalize certain activities such as knowledge sharing and cooperation amongst knowledge

workers, mentoring relationships between entrepreneurs, or a tendency for angel investors

and successful businesspeople to actively network with startup founders. Similarly, a non-

entrepreneurial culture might normalize actions detrimental to entrepreneurship like risk

aversion (James, 2005; Malecki, 2009). However, while embeddedness provides some clues

to how culture contributes to entrepreneurial ecosystems, it does not explain how these

cultures initially develop within a region or how they change over time (James, 2007).

Further work is necessary to reveal the connections between cultural outlooks and innovative

and entrepreneurial activities with regions and organizations.

Innovative entrepreneurship depends on more than the presence of financial and knowledge

endowments: it also requires a supportive set of cultural outlooks to normalize the risks it

entails. While researchers have long acknowledged the importance of culture to innovation

and entrepreneurship, our understanding of how such culture develop within regions or

organizations and actually influences the actions of entrepreneurs remains underdeveloped.

As policy makers and corporate leaders embrace entrepreneurship as a key factor in

economic growth, the importance of regional and organizational cultures will grow even

further.

Conclusions

15

Building innovative, entrepreneurial regions remains an imperfect art. Entrepreneurs and

innovations can arise in any industry and from universities and other institutions. Much of

what we know is based on a few success stories and on case studies. Less is known about

regions that fail to create innovation-led economies or those which passively wait for

innovative entrepreneurs to appear. The presence of individual ingredients, such as research

universities, large innovative firms, or science parks, does not guarantee success.

Nearly all regions aspire to high-tech success, targeting biotech and nanotech; few will

succeed in the short term, but many will improve their development capacity and …future

innovative potential.

While creative destruction as a consequence of discontinuous technological change is a

central theme in the literature on innovation and technology, incumbent firms are also able to

evolve a “creative accumulation” in response (Bergek et al. 2013).

Both innovation and entrepreneurship are complex processes, and policy options are many

and varied. The creation of new research campuses in Abu Dhabi and New York City suggest

a continued appetite for multi-billion dollar state investments in research and development.

At the same time, policy makers also are turning towards fostering existing regional assets to

encourage innovative entrepreneurship, through the cultivation of stronger networks linking

researchers, entrepreneurs, and investors or small scale incubators and accelerators for new

technology-based firms or university spinoffs.

However, innovation policy does not exist in a vacuum. Policies that fail to account for the

cultural outlooks they exist in are to likely flounder. Instead, policy makers must craft new

programs taking into account the local cultural outlooks, for instance considering their

tolerance for the risks of leaving stable employment to lead a startup. At the same time,

policymakers must keep in mind that culture is not static: the presence of successful,

innovative entrepreneurs can spur others to follow in their footsteps while a period of

economic decline can lead to a retrenchment where the risks of innovation and

entrepreneurship seem increasingly untenable.

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