Electronic copy available at: http://ssrn.com/abstract=2375052

!

!

1!

Entrepreneurial!Ideation!and!Organizational!Performance:!Imprinting!Effects!

!

!

!

Charles!E.!Eesley!

Assistant!Professor!

Stanford!University!

Department!of!Management!Science!&!Engineering!

cee@stanford.edu!

740H236H4653!

!

David!H.!Hsu!

Richard!A.!Sapp!Associate!Professor!of!Management!

Wharton!School,!University!of!Pennsylvania!

!

Edward!B.!Roberts!

David!Sarnoff!Professor!of!Management!of!Technology!

MIT!Sloan!School!of!Management!

!Abstract!

How!does!the!relationship!between!the!organizational!context!for!venture!idea!formation!

and! venture! performance! depend! on! the! venture’s! founding! team! and! business!

environment?! Using! data! from! a! survey! of! 2,067! firms,! we! show! that! venture! ideas!

emerging! from!research! lab!contexts!are! imprinted! in!a!way!that! is!better!aligned!with!a!

cooperative!commercialization!environment.!Ideas!from!industry!contexts!are!aligned!with!

a! competitive! commercialization! environment.!We! contribute! to! prior! work! by! showing!

that!imprinting can come both from how a venture idea interacts with the business environment and how those ideas interact with the type of founder.! Keywords: imprinting, business environment, ideation, venture performance

Electronic copy available at: http://ssrn.com/abstract=2375052

!

!

2!

Introduction

While initial venture knowledge is most frequently associated with top management

teams (TMTs), another mechanism linking initial knowledge with outcomes is

through imprinting from the organizational context of venture ideation. Prior theory has

examined how characteristics of the entrepreneur and (separately) how the broader population-

level environment at founding leave imprints on the firm (Stinchcombe, 1965; Hannan, Burton,

Baron, 1996; Boeker, 1988). This imprinting then helps to shape and determine subsequent

strategic behaviors and outcomes (Hannan, Burton, and Baron, 1996, Burton, Sørensen, and

Beckman, 2002). For instance, organizational blueprints present at founding for how to manage

employment relations predict subsequent organizational decisions (Baron, Burton, and Hannan,

1999a; 1999b). We examine the degree to which technical and research-based knowledge is

present in the organizational context at venture inception. In contrast to prior work, we show

how imprinting from the organizational context interacts with characteristics of the founders

resulting in performance differences depending on the type of commercialization environment.

We follow the definition of imprinting offered by Marquis and Tilcsik (2013): a process

whereby, during a brief period of susceptibility, a focal entity develops characteristics that reflect

prominent features of the environment, and these characteristics continue to persist despite

significant environmental changes in subsequent periods (p. 8). We can further dissect this

definition into three components which distinguish it from related concepts: 1) short periods of

transition in which the focal entity has a high sensitivity to external influences; 2) a process

where elements of the environment during the sensitive period become embedded in the focal

entity; and 3) persistence of the imprint in spite of any subsequent changes in the environment.

!

!

3!

The idea that founders imprint the new organization alongside forces affecting the

industry-wide business environment to produce long-term effects on the organization is

widespread in the literature. This finding has been explored in a variety of domains, including

management and organizational structure (Beckman and Burton, 2008) and corporate strategy

(Boeker, 1988; 1989). Enduring effects arise as a result of institutionalization and/or efficiency

born out of policies, processes, knowledge and culture present at the founding of the firm

(Stinchcombe, 1965). Thus, organizations develop along different trajectories from one another

not only because of on-going adaptation, but also due to the lasting effects of differences in their

conditions at founding. Prior work has focused on imprinting from the population-level

environment (i.e., population density, resource munificence) or on imprinting from the

backgrounds of the founders themselves. In focusing on the long-lasting effects of imprinting,

prior research leaves gaps in our understanding of how and when imprinting influences

performance. First, we lack an understanding of imprinting from the organizational context

where the initial idea for the venture emerged and whether this form of imprinting interacts with

imprinting from the founders. Second, previous work rarely looks at whether different types of

imprinting are important in different industry environments.

We address these shortcomings by exploring contingencies between the type of

imprinting resulting from the initial organizational environment where the startup idea emerged

and the industry competitive environment. Furthermore, we examine how this important, but

understudied source of imprinting interacts with the industry environment and founder

characteristics to shape venture performance.

The main contribution of this paper is to show that the organizational context where the

venture emerged (specifically, the degree of technical and non-technical knowledge present in

!

!

4!

the venture ideation stage) shapes the strategy of the venture by selecting certain ideas and

influencing how the founders conceive of and build their competitive edge. Imprinting from the

organization in which venture ideation occurs produces different performance results depending

on the characteristics of the industry environment. There is a match required between the

organizational environment where the venture idea originated and the industry environment

(whether competitive or cooperative commercialization characterizes venture competitive

dynamics). Overall, we argue that imprinting can occur both from how a venture idea interacts

with the immediate environment and through the interaction with the type of founder.

Theory and Hypotheses

Imprinting from the Organizational Context on Venture Ideas

The myriad ways and settings in which individuals create or discover entrepreneurial

opportunities make for fascinating stories. Yet, they may also play an important imprinting role,

influencing the venture’s development and performance outcomes. Previous literature separately

examines imprinting and entrepreneurial opportunity discovery (for an exception, see Hsu and

Lim, forthcoming). The contribution of this paper is to further build theory connecting the two.

We respond to a gap in the literature by developing the construct of imprinting from the

organizational context of ideation. We first review the literature on imprinting, followed by a

discussion of its influence on entrepreneurial ideation.

The idea that founders imprint the new organization along with the industry-wide

business environment to produce long-term effects on the organization is widespread in the

literature (e.g., Beckman and Burton, 2008; Boeker, 1988; 1989). Enduring effects arise as a

result of institutionalization and/or efficiency born out of policies, processes, knowledge and

culture present at the founding of the firm (Stinchcombe, 1965).

!

!

5!

Stinchcombe (1965) argued for the importance of the external environment in shaping

initial firm structures and their persistence over time. An important, unique aspect of the

imprinting concept is that the focal entity is influenced during limited time intervals in which the

entity is more sensitive to influence by environmental conditions. We can organize the literature

into three different sources of imprinting, including economic and technological conditions,

institutional factors, and individuals (Johnson, 2007; Carroll and Hannan, 1989).

Imprinting from Individuals

The individual imprinting stream has been the most influential in the entrepreneurship

literature (e.g., Burton and Beckman, 2007; Baron, Burton, and Hannan, 1999a). Imprinting from

institutions and economic conditions has been studied more broadly in other streams of literature.

Yet, the most common finding is that organizations are imprinted by their founders (Kimberly

and Bouchikhi, 1995; Johnson, 2007: 97). The founders transmit elements of the founding

environment and their own mental models onto the firm. The choices founders make to

incorporate certain elements and not others into the firm result in long-lasting heterogeneity

across organizations (Hannan, Burton, and Baron, 1996). Scholars have examined the sustained

influence of early career experiences (Azoulay, Liu, and Stuart, 2011) and the transfer of career

imprinting across organizations (McEvily et al., 2012). Founders influence the employment

model of the firm (Baron et al., 1999), the internal gender hierarchy (Phillips, 2005), the

importance of specific functions within the organization (Boeker, 1989), and the likelihood of

raising venture capital (Burton, Sørensen, and Beckman, 2002).

Prior work has used the concept of imprinting at multiple levels of analysis, yet has

analyzed each level separately (e.g., Marquis, 2003; Johnson, 2007; Burton and Beckman, 2007).

The aspects of the economic and technological conditions that imprint firms include economic

!

!

6!

systems and prevailing social arrangements (e.g., Boeker, 1988; Carroll and Hannan, 2004: 446).

At the level of institutional factors (Eesley, Yang, and Liu, 2013), imprinting occurs on the

industry and geographic community (Marquis and Battilana, 2009) and strategic choices

(Johnson, 2007; Marquis and Huang, 2010). Despite this vast literature, a recent review shows

that relatively little to no previous work examines imprinting from the organizational level

(Marquis and Tilcsik, 2013).

Imprinting from the Organization

A missing level is imprinting from the organization. This level is most relevant for new

ventures since we know that many ventures are spinoffs or the founders came up with the initial

idea while working (or receiving education) while in another organization. Burton and

colleagues (2002) as well as Boeker (1989) raise the possibility of the transfer of imprints from

the organization to its employees and then from those individuals to the firms that they found.

However, prior work has not been able to disentangle this mechanism of imprint transfer from an

alternative mechanism of imprinting directly from the organization in which the new venture

idea emerged. Our paper is among the first to fill this gap. Similar to organizational building

blocks, ventures (when at the idea stage) are born within other organizations. Thus, we would

expect that an immediate imprinting influence stems from new ventures’ organization context.

In establishing the imprinting concept and its widespread utility, the literature focuses

less on differences between the origins of imprinted characteristics and their current usefulness.

Instead of a single source of imprinting, we view organizations as being composed of multiple

layers of imprints from the environment during multiple sensitive periods. Marquis and Tilcsik

(2013) note this gap, stating: “we are far from even a nascent theory” of how multiple sources of

imprints may modify each one’s influence on the organization.

!

!

7!

Organizational Context for Entrepreneurial Ideation

Recent literature points to the idea that imprinting is not entirely out of the control of

founders, but rather it can be shaped and may even begin much earlier in the process of forming

a new firm than traditional literature had assumed (Johnson, 2007; Hsu and Lim, forthcoming).

Yet, imprinting from sources other than the founder characteristics or the industry-wide business

environment at the time has rarely been explored, limiting our understanding of how individuals

might be able to shape the imprinting process.

The choice to found that the founder(s) make at the beginning of every new venture

depends upon an entrepreneurial conjecture that may or may not turn out to be correct once

resources are put towards executing on it. Previous literature mainly focuses on the role of

experience. More recent work has shown that entrepreneurial theorizing and imagination also

play a role alongside experience (Felin and Zenger, 2009; Baron and Ensley 2006, Gruber et al.

2008).

The organizational environment where the initial idea was conceived imprints ventures.

For example, if the idea for the venture was born in a research lab, there are certain types of

discussions, initial knowledge and a structure to the social interactions that occur in this type of

organizational context. To contribute to the literature on imprinting in entrepreneurial firms, we

draw on recent insights on the social and cognitive processes during the earliest venture ideation

stages. Cornelissen and Clark (2010) describe how creating novel ventures utilizes both

inductive analogical and metaphorical reasoning. Entrepreneurs must construct meaning,

comprehend an opportunity and justify it to others. This process does not occur in a vacuum, but

rather there is often an organizational context and social processes that inform and guide it.

Entrepreneurial Ideation and Venture Formation

!

!

8!

The analogies and metaphors that are chosen to generate or recognize the initial idea and

to justify and communicate it to others are likely to be shaped by the organizational context that

the founder or cofounders are working within. These analogies help both to reduce uncertainty as

well as to build legitimacy when communicating the idea to others. Most literature assumes that

in the later stages of venture development, reliance on inductive, analogical reasoning that was

characteristic of the ideation stage declines and is replaced by more calculated, deductive

reasoning. In contrast, we argue that the context shaping the ideation and theorizing process at

the venture’s earliest stage influences the venture’s development and performance outcomes.

In the example of generating a new venture idea while in a research lab context, the

analogies and metaphors as well as the initial knowledge that can be drawn upon are not

limitless. More likely, they are constrained by and draw from the set of analogies and metaphors

in use in research lab discussions. How novel the technology is and how well it performs along

technical dimensions relative to other technologies are common discussions and salient aspects

to be considered in this setting. The basis of evaluating ideas and for promotion is more likely to

be a focus on technical novelty than on other aspects. Other possible sets of knowledge,

analogies and metaphors, such as those that are more likely to be discussed in marketing

departments or boardroom contexts are less likely to be used in a research lab context.

During the ideation stage of a venture, a potential entrepreneur faces uncertainty and

pressures for legitimacy in justifying the choice to start a new firm. Selecting ideas and

emphasizing features and aspects of the idea that achieve fit with the social environment and

isomorphism with accepted organizational settings is one way potential founders address this

uncertainty and generate legitimacy (DiMaggio and Powell, 1983; Hannan and Freeman, 1977).

In the social environment and organizational context of venture ideation, ideas get scrutinized

!

!

9!

and tested against prevailing assumptions about customer needs, feasible technologies and

market opportunities. At the subsequent stage of beginning to organize and mobilize resources,

there is further scrutiny as entrepreneurs struggle to gather financial and human capital. Due to

these social processes, the new venture that emerges is bound to reflect the social structure and

imprint of the organizational context of ideation.

The earliest stages of venture formation are when entrepreneurs theorize about new

opportunities (Felin and Zenger, 2009). Three mechanisms are central: 1) experiential and

observational fragments, 2) imagination of possibilities, and 3) reasoning and justification. They

also highlight the social mechanisms in the creation of entrepreneurial beliefs or ideas. While

experience and perception are important inputs for the origins of entrepreneurial beliefs and

ideas, theorizing beyond experience requires social interaction. Using fragmented experiences,

groups of individuals imagine possibilities and select the more promising ones (Sutton and

Hargadon, 1996). The experiences that are most likely to occur as inputs into this imagining

process are those from the organization where the venture idea originated. The process of

entrepreneurial theorizing and ideation is described as a trial and error process that allows a way

to imagine new markets, products and services (Felin and Zenger, 2009).

Connecting Organizational Imprinting and Ideation

The venture ideation and theorizing process is not only an individual-level one, and need

not occur only among cofounders. In the process of deciding whether to even pursue the idea or

to recruit cofounders, individuals are likely to discuss and solicit feedback from colleagues in

their immediate social and organizational context. Such conversations are likely to help in

refining and selecting the idea to pursue, as well as provide justification to the founders

themselves and early employees or investors. Those who do elect to join the nascent venture are

!

!

10!

likely to be those who will likely share a similar vision of the initial idea and opportunity. The

organizational context surrounding the origins of the venture idea will shape what aspects of the

idea are initially developed and the tactics used to create the organization and craft the strategy.

If the venture idea originated in a research lab, then the experiences that feed into the

social process are likely to be technical in nature and based on insights into science and

engineering. In the lab setting, ideas are evaluated most frequently on the basis of technical

performance and novelty relative to existing technologies. In the process of social interaction in

brainstorming and justifying the idea, the basis of the idea is likely to be seen as technical

advantages primarily. Therefore, ventures where the idea was born in a research lab setting are

screened for innovative, technical quality and adopt routines that institutionalize an orientation

towards competition based on innovation. Business and competitive aspects of the venture, such

as cost, marketing strategies, market segmentation or competition are less likely to be

emphasized or will be marginalized as part of the initial discussion. Hsu and Lim (forthcoming)

connect entrepreneurial ideation with ongoing organizational processes of innovation. They

show that there are heterogeneous imprinting effects according to the degree to which the

ideation process for a venture included brokering knowledge from a different technical domain.

In this paper, we shed light on the role of imprinting from the organizational context

during the entrepreneurial opportunity recognition and ideation stage. A long literature

demonstrates how organizational search in R&D tends to be localized (e.g., Katila and Ahuja,

2002). Search is often constrained by the organization’s own historical experience, as well as

routines and procedures meant to foster efficiency (Henderson and Clark, 1990; Helfat, 1994).

The Role of Commercialization Environments

!

!

11!

The influence of a firm’s environment has long been of interest to organizations and

strategy theorists (Selznick, 1949; Stinchcombe, 1965). Prior work explores the strategic

implications of social movement organizations (Eesley and Lenox, 2006) and high velocity

industry environments (Eisenhardt, 1989). The focus of this paper is on contributing to research

on imprinting by utilizing insights from the stream of literature on how technical dimensions of

the industry influence organizations (Woodward, 1965).

In industries with certain technical dimensions, firms opt to partner and cooperate with

industry incumbents rather than compete with them in the product market (e.g., Teece, 1986;

Tripsas, 1997). Specific, technical dimensions of industry environments, such as the

effectiveness of patent protection and the importance of complementary assets, shape

competitive dynamics between ventures and incumbent firms (Woodward, 1965; Tripsas, 1997).

These aspects of the industry shape the likelihood that a venture will pursue a competitive versus

cooperative strategy with incumbents (Gans and Stern, 2003).

This literature allows for a theoretically-based way to categorize industry environments

and competitive dynamics. An example is in the biotechnology industry where partnering with

incumbents (pharmaceutical firms) is common. Consistent with prior literature, we label this type

of industry environment as cooperative, with incumbents (Gans, Hsu, and Stern, 2002; Eesley,

Hsu, and Roberts, forthcoming). In other industries, entrepreneurial firms compete with

incumbent firms. We follow prior literature in labeling these industries as competitive.

The cooperative environment favors ventures that partner with industry incumbents, such

as often occurs in chemicals, telecommunications and biotechnology. When patent protection is

effective and technologies are difficult to copy or invent around, contracting with a partner is

easier due to reduced fears of expropriation. The second requirement is that complementary

!

!

12!

assets owned by incumbents are difficult for new ventures to replicate and necessary for

commercialization (Rothaermel, 2001; Tripsas, 1997). The need for complementary assets

incentivizes ventures to partner for commercialization. In cooperative commercialization

environments, ventures tend to compete with one another in developing innovative technologies

and then partner with incumbents for commercialization.

Cooperative Environments and Ventures Emerging from Research Contexts

Previous literature on spin-offs from academic labs emphasized either the human capital

that academic faculty provide to firms (Zucker, Darby and Brewster, 1998) or on the

determinants of technology transfer (Rothaermel et al. 2007). Prior work focusing on the human

capital aspect of academic spin-offs emphasizes the role of tacit knowledge (Agrawal and

Henderson 2002) or information signaling about the quality of the science and engineering

(Audretsch and Stephan, 1996).

Recent work examines the importance of social capital and networks shared with

ventures spinning out from research labs (Murray, 2004). Yet this prior work does not examine

how the social and organizational environment of the lab is likely to influence the formulation of

venture ideas. This setting will imprint ventures with an orientation towards the pursuit of ideas

that are based on technological innovation to the exclusion of other criteria.

Technical knowledge and novel, high-performance technologies are relatively more

important for ventures in cooperative environments because competition is between

entrepreneurial firms to supply innovations to incumbents. In the cooperative environment,

ventures can rely on their incumbent firm partner’s capabilities in sales, marketing, operations

and customer relationships. The result is that knowledge related to these areas may be of lesser

importance when formulating the initial idea for the venture. In this industry environment,

!

!

13!

entrepreneurs do not need to bear the entire cost of developing complementary assets since they

have the option to license their innovations to established firms. The ability to outsource the

downstream functions such as sales and marketing pushes the basis of competition towards

innovation. Venture ideas that have originated and been imprinted in the organizational context

of the research lab will result in better performance in a cooperative commercialization

environment. Such ventures have an orientation towards technology and have been imprinted

with advantages in the technical knowledge present initially. Ventures that are imprinted in other

types of organizational contexts, such as in an industry or business context may have less and

older technical knowledge and less of an orientation towards competition based on technological

innovation. Thus, we expect that in a cooperative industry environment, imprinting from a

research-oriented organizational context will result in improved performance.

H1: Ventures originating in a research context and operating in a cooperative industry environment will be associated with better performance outcomes.

!

Industries like software and consumer products where ventures compete directly in the

product market against incumbents are known as competitive commercialization environments

(e.g., Katila, Rosenberger, and Eisenhardt, 2008; Tripsas, 1997). Such industries are defined by

having technology that is difficult to exclude other firms from copying (e.g., patent protection is

less effective) and existing complementary assets are less important for commercialization.

The implication of these differences in the technical aspects of the industry environment

is that a different type of imprinting is needed from the organizational context where the venture

idea is born. In a competitive environment, ventures are compelled to compete in the product

market against incumbent firms. This means that they need to be more aware of the competitive

landscape of the industry. In addition, to compete effectively in the market, ventures must make

their own investments in building complementary assets, such as sales, marketing,

!

!

14!

manufacturing, and distribution. Ventures that originate in a corporate or industry organizational

context are likely to be oriented towards competition in the market. The metaphors that are

drawn upon are likely to come from experiences in the industry in prior product launches,

marketing campaigns or competition with other firms in the market. To the extent that technical

knowledge is included in ideation, it is likely to be more applied rather than cutting-edge

research-based knowledge. Such settings are more likely to have more initial non-technical

(business and management-based) knowledge and analogies relative to ventures that originated

in a research lab setting. This initial imprinting with non-technical knowledge gives them an

advantage in building these business aspects of the firm and allows the venture to compete more

effectively in the market. In addition, since it is difficult to exclude others from copying

technology in this environment, technical knowledge and imprinting with an innovation

orientation cannot be relied upon solely as it offers less of an advantage. For ventures where the

idea was imprinted in the research lab setting, it is more likely that they are imprinted in a way

that orients their attention away from these non-technical aspects of the firm. In an industry

organizational context, the presence of initial knowledge related to the business environment will

help to select startup ideas that are more commercially viable in the market and focus the

founders on business, rather than technical aspects of competition.

H2: Ventures originating in an industry context and operating in a competitive industry environment will be associated with better performance outcomes.

Interaction of the Organizational Context with Individual Characteristics

As Marquis and Tilcsik (2013) point out, an underexplored area is how organizations

experience imprinting from multiple sources and during multiple sensitive periods over time.

Besides the stage of ideation, a second sensitive period, which may overlap with the ideation

stage, but often comes later, is the stage when cofounders join. Imprinting from the

!

!

15!

organizational context where the venture idea originated also interacts with imprinting from the

characteristics of the founders (Boeker, 1988). One way to manage the influence of imprinting is

by having individuals on the founding team whose experience and skills complement or counter-

balance the imprinting effects. An experienced entrepreneur is likely to bring performance-

enhancing prior startup experience and routines to the venture. Due to their knowledge of the

startup and commercialization process, the imprinting from experienced entrepreneurs may be

particularly beneficial when combined with imprinting from a research lab, where the non-

technical aspects of entrepreneurship are not a central focus.

Prior literature shows that compared with novice entrepreneurs, those with more founding

experience have a greater likelihood of creating successful subsequent ventures (Eesley and

Roberts, 2012). The effect appears to be particularly strong for entrepreneurs who had prior

success experience (Gompers et al., 2010). Also leading to their performance advantages,

experienced founders raise capital from higher quality and higher status investors and they raise

it more quickly (Hsu, 2007; Hallen and Eisenhardt, 2012). However, Eesley and Roberts (2013)

find that entrepreneurial experience is more valuable in some situations than others.

Entrepreneurs develop a more complete understanding of the various non-technical tasks

involved in founding a firm, such as gathering financial resources, identifying a business model,

hiring key executives, or crafting a marketing strategy. Experience in entrepreneurship aids in

product development, internationalization (Bingham and Eisenhardt, 2011), and in identifying

entrepreneurial opportunities (Baron and Ensley, 2006).

Novice entrepreneurs, who have only large firm experience are less likely to have

experience in identifying better entrepreneurial opportunities and in executing on them (Delmar

and Shane, 2006). Experienced entrepreneurs are likely to be able to quickly reuse routines from

!

!

16!

prior ventures, especially if they were successful in the prior venture. Prior learning allows

entrepreneurs to draw on analogies from past ventures (Gavetti, Levinthal, and Rivkin, 2005) and

imprint their subsequent ventures more effectively by choosing better opportunities and

establishing effective procedures early on. This allows them to develop advantages in creating

viable business models, raising funding, establishing strategic processes and the related non-

technical tasks involved in creating a new organization.

As discussed above, when the entrepreneurial ideation and theorizing occurred in the

context of a research laboratory, technical dimensions of the venture are likely to overshadow

considerations of the other non-technical and business aspects. The drawback of technical

knowledge present at founding is a lack of knowledge regarding the process and realities of

successful startup commercialization. Experienced entrepreneurs, particularly those with prior

success experiences bring complementary experiences, routines and capabilities to ventures

arising out of the research lab context. Experienced entrepreneurs who have taken a previous

startup from founding to a successful liquidity event have seen the path to success and are in a

better position to choose and imprint the next venture relative to those whose ventures ended

earlier in the process. Imprinting that comes out of the theorizing, ideation and screening

provided by experienced, successful entrepreneurs in the non-technical aspects of the firm makes

up for the weaknesses that may be inherent in venture ideas that emerge from research labs.

H3: Ventures originating in a research context will be associated with better performance outcomes when a founder has prior success experience.

Besides founders with success experience, the entrepreneur may also involve academic

scientists in founding the venture. This decision may be expected to interact with the effects of

imprinting from the organizational context of venture ideation. When academic scientists and

faculty members are involved the founding a venture, they imprint it with a unique source of

!

!

17!

human and social capital. While they lack the commercial expertise of experienced

entrepreneurs, faculty have also been found to contribute to the performance of entrepreneurial

firms (Murray, 2004). They imprint the firm with routines and processes as well as tacit

knowledge that give the firm advantages in R&D over non-faculty founded firms.

Older literature emphasized the firm attributes resulting from firm-scientist relationships

and especially human capital that academic faculty bring to firms (e.g., Zucker, Darby and

Brewster, 1998). More recent literature has shed light on the important social capital held by

academic scientists and faculty that they share with new ventures, allowing the firm to build its

technical and scientific network (Murray, 2004). Faculty involvement in startups ranges from

limited consulting, to research collaboration, through to faculty as founders. When faculty are

involved, at times it is to commercialize their own research and other times it can be to

contribute to an idea that emerged in a company or elsewhere.

An academic’s human capital (technical knowledge) aids in both the transfer of tacit

knowledge and as a signal. When knowledge is tacit, it is difficult for it to move among

organizations (Agrawal and Henderson, 2002), making it more important to have the direct

involvement of the faculty member. Having a faculty member affiliated as a cofounder sends a

signal about the quality of the science and engineering (Audretsch and Stephan, 1996).

Murray (2004) demonstrates that in addition to their human capital, faculty founders also

contribute their social capital and networks to the venture. First, the venture gains access to the

faculty founder’s local laboratory network for recruiting and for scientific/technical advisors.

Second, the venture benefits from the wider, cosmopolitan network of coauthors and colleagues.

This broader network aids the venture in understanding other technologies being developed.

!

!

18!

The presence of a faculty member in the founding imprints a venture through the

faculty’s human and social capital as well as signaling effects. The (tacit) knowledge present

helps in screening and formulating the entrepreneurial idea. The social networks provide early

advisors and technical employees who further solidify the imprinting towards a technical and

innovation-led orientation. Signaling both to investors and other partners that a given idea is a

high quality technical one aids in the fundraising and recruiting necessary to pursue R&D.

While venture ideas born in an industry context have the advantage of an orientation

towards non-technical and competitive issues, they suffer from corresponding disadvantages.

The drawback of the industry context is that knowledge is more applied and there is less

imprinting towards innovation and subsequent R&D. These drawbacks can be overcome if there

is involvement of a faculty member in the founding of the firm. The type of imprinting that

comes through a faculty founder is complementary to these disadvantages and advantages that

venture ideation in an industry/business environment generates.

H4: Ventures originating in an industry context will be associated with better performance when a faculty member plays a role in the founding. !Data and Measures !

We use a sample of 2,067 ventures founded between 1931 and 2003 to test our

hypotheses. The sample was generated from a 2001 survey administered to all 105,928 alumni

from the Massachusetts Institute of Technology (MIT) (Hsu, Roberts and Eesley, 2007). This

methodology creates a set of ventures that is sampled from a well-defined population of

comparable individuals across multiple industries (Hsu, Roberts and Eesley, 2007). Industries

covered include aerospace, architecture, biomedical, chemicals, consumer products, consulting,

electronics, energy, finance, law, machine tools, publishing, software, telecommunications, other

services, as well as other manufacturing. The dataset is unique in being less affected by concerns

!

!

19!

of survivorship bias1 (relative to surveys of ventures currently in existence), and in providing

detailed information on founders, the organizational context surrounding venture ideation as well

as firm performance information. Alumni surveys increase the response rate and trust in the

survey for respondents due to the alumni university connection. Since all alumni were surveyed,

we have polled all individuals from this population who could have founded a firm. The

utilization of alumni surveys, particularly for entrepreneurship research has increased over time

due to these advantages (Dobrev and Barnett, 2005; Hsu, Roberts, and Eesley, 2007).

A total of 43,668 responses to the 2001 survey equates to a 41.2 percent response rate.

Among the founders, there was a 25.6 percent response rate (2,111 out of 7,798 founders) to the

more detailed survey in 2003. Removing duplicate cases where multiple cofounders reported on

the same firm results in a total sample of 2,067 firms. Since we have data on the entire alumni

population, we can compare demographic and educational characteristics with the survey

sample. Differences in means tests of observed characteristics of the responders and non-

responders of both the 2001 and 2003 surveys detect little difference between the groups.2

Complementary data sources through 2006 were matched with the data from Compustat

(for public companies), the United States Patent and Trademark Office (USPTO), and Dun and

Bradstreet (for private companies). The scope of coverage and detailed data on both the source of

the idea, the founding team and on performance are key features of this dataset. All living MIT

alumni graduating between 1930 and 2001 were included in the survey.

Dependent Variables

!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!1 Respondents also reported on firms that later failed as well (41 percent of the firms failed), so the data include failed founding attempts. 2 In only a few instances do the differences between the sub-samples vary by three percentage points or more. For the 2001 survey, only the variables male, European citizen, and Middle Eastern citizen meet these criteria.

!

!

20!

Consistent with much of the literature, initial public offering (IPO) or acquisition

liquidity events are our measure of entrepreneurial success. We define a venture as having a

favorable exit if it had an IPO, or in the case of acquisition, the acquisition meets either of two

criteria: the acquired firm had been founded more than five years prior to the acquisition and had

positive (greater than zero) revenues or if the acquired firm made money for the investors (the

valuation was higher than the capital raised). The measure is meant to create a higher bar than

prior literature by eliminating acquisitions where the firm was not generating positive cash flow,

would otherwise have gone out of business and was acquired at a low valuation (Arora and

Nandkumar, 2011). We confirmed the accuracy of self-reported acquisition and IPO events with

the Compustat and SDC Platinum databases.

We also tested the results for robustness by using an alternative performance measure,

exits, which equals 1 if the firm experienced any type of acquisition or IPO and 0 if not (as of

2003). The results are also robust to using the number of employees (logged to account for skew)

as the dependent variable. The youngest firms would not have had sufficient time to have an IPO

or acquisition so we restricted the analysis to firms founded in 1998 and earlier, giving the firms

at least five years of operating time.

Independent Variables Organizational context for the venture idea. We measure idea from research lab if the

self-reported source of the idea for the venture was in a research laboratory setting. Respondents

were asked to answer from a list of possible sources, “What was the source of the idea for the

product or service leading to the founding of the company? (Please answer even if the idea came

from one of your co-founders and not from you.).” The variable idea from research lab is equal

to 1 if the respondent indicated the venture idea arose from one of the following: doing outside-

!

!

21!

funded research at the University, graduate thesis, research conference, in class, undergraduate

research opportunity, reading the literature, discussions with scientists and engineers, or other

research. Respondents could also indicate whether the research was done at MIT or at another

university, however the source need not be a university lab as respondents working in a company

could indicate that the idea came from attending a research conference. The variable is defined as

zero if other sources were indicated and as missing if the respondent did not fill out any response

to this question. We measure idea from industry using the same survey question except we define

the variable as equal to 1 if the respondent indicated that the source of the idea was while

“working in industry”. The omitted category is ideas that came from discussions with social

acquaintances, with other students, or from working in the military.

We measure prior successful experience in entrepreneurship by entrepreneurs who had a

previous entrepreneurial liquidity event. Prior exit is equal to 1 if the entrepreneur had a previous

startup that was acquired or experienced an IPO.

Commercialization environment. We follow the prior literature in defining two different

types of commercialization environments based on complementary asset importance and

intellectual property protection (Gans and Stern, 2003). Complementary assets have been defined

as capabilities or assets that aid in the commercialization of new products and services (Teece,

1986).3 Such assets can be organizational competencies, including sales and service expertise,

manufacturing capabilities, or brand recognition. Strong intellectual property rights (IPR)

increase the value of innovations by reducing their potential expropriation by others, such as by

copying (e.g. Arora, Fosfuri, and Gambardella, 2001). Innovators can use several methods to

protect their innovations including trade secrets or formal intellectual property rights such as

!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!3 Rosenbloom and Christensen (1994) describe a similar idea using the term “value network” to describe the system of producers and markets serving “the ultimate user of the products or services to which a given innovation contributes.”

!

!

22!

patents or copyrights. The strength of patent protection varies by industry (Cohen et al., 2000)

and when it is stronger, startups have less fear of forming alliances or partnerships to

commercialize (Katila, et al., 2008).

We define a competitive commercialization environment by two simultaneous

dimensions. First, the patent channel of appropriability is relatively weak. Second, incumbents’

existing complementary assets are largely disrupted or unimportant. The result of these two

factors is that the cost of entry is relatively low and startups fear bargaining with incumbents out

of the fear of expropriation. A cooperative commercialization environment is defined in the

opposite way. When patent protection is effective and the value of incumbents’ complementary

assets is retained, startup innovators feel more comfortable bargaining with incumbents at the

same time that the relative cost of replicating the incumbent’s complementary assets (the value

of which persists) is high.

Our measures for the effectiveness of patent protection and the importance of

complementary assets in a firm’s industry come from matching industry sectors to the Carnegie

Mellon R&D survey (Cohen, et al., 2000). We average the importance of complementary

manufacturing and sales or services (then take the natural log to account for the skewed

distribution) to create the measure of industry complementary asset importance. Electronics,

telecommunications, machinery, chemicals and materials, biotechnology, medical devices and

consumer products scored highly on this measure while software, finance and services scored

low).4 To create the measure of patent strength, we created an average of the importance of

!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!4 Not all MIT alumni firms fit into the industries in the CMU data (restaurants, dry cleaners, etc. are fairly rare). However, there are a number of services firms, such as consulting, law, accounting, and so on. These were grouped into an “other services” category. The results are robust to excluding these firms. Patents are very unlikely to be effective in the case of services firms; similarly, specialized complementary assets are likely unimportant. Thus, both of these measures are likely to be low. We therefore used the lowest values from the CMU survey for this category, which places them on similar footing as the printing and publishing industries, for example.

!

!

23!

patents for protecting products and processes (and took the natural log to adjust for the skewed

distribution). Sectors high in patent strength were energy, aerospace, electric utilities, machinery,

materials, medical devices and biotechnology (scoring low were services, software and finance).

We use the median values of these measures (importance of complementary assets and the

effectiveness of patent protection) to define the firms that are in a cooperative commercialization

environment where complementary assets are important and patents are effective (594 firms) and

a competitive commercialization environment where the opposite holds (patents are weak and

complementary assets are less important, 885 firms).5 Firms in other industry sectors (the high

and low combinations) were also included. The remaining firms in the sample were missing

industry information and our final regressions include 554 and 581 firms in the competitive and

cooperative environments respectively, due to missing values on other control variables.

Competitive edge. Survey respondents also indicated their primary source of competitive

advantage in answering the question, “What factors are critical in giving your company a

continuing competitive edge?” We coded the binary variable technology edge equal to 1 if

respondents indicated innovation/new technology and zero otherwise. We coded the variable

brand edge as equal to 1 if respondents indicated market image/brand recognition or dominant

market position. The variable finance edge is equal to 1 if the respondent indicated access to

capital as giving a competitive edge.

Control variables. We control for other factors influencing venture performance.

Team characteristics. Prior work finds that the founding team composition also influences

venture performance depending on the type of commercialization environment (Eesley, Hsu, and

Roberts, 2013). Functionally diverse teams tend to perform better in a competitive environment,

!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!5 Grouping industries based on their complementary assets and patent protection dimensions is a method grounded in the prior literature, and allows future researchers to classify new industries based on these characteristics.

!

!

24!

while technically focused teams perform better in a cooperative environment. Thus, we control

for these characteristics of team composition. We measure diverse teams by the different

functional roles on the founding team with the variable diverse team. The survey asked

respondents for the role at founding for each cofounder. A diverse team is coded as a count of

the number of functional roles on the founding team. These roles were coded according to

whether they were technology roles (CTO, Chief Scientist, etc.), finance, sales and marketing, or

other. The number of roles ranges from 1 to 4. Beckman and Burton (2008) also use the count of

the number of functional roles on the founding team. We created the variable technically focused

team as a measure of how technology-focused the founding team is. This is a dichotomous

variable equal to 1 if the founding team was composed of individuals who all had a role at

founding focused on technology development (as opposed to roles including marketing, sales,

finance, management, etc.).

Prior literature shows that firm performance is related to industry factors, so we use a set

of industry dummies as controls for the industry segment (such as biotech, software, and

electronics). Survey respondents chose the industry category that fit their firm. We also include a

set of founding year fixed effects to control for the macroeconomic conditions at founding.

Entrepreneurial performance is also related to the founder’s level of education (Roberts,

1991). We control for education level with master’s degree and doctorate degree controls. While

having a founder with a doctorate degree might be an indication of a technology-focused team,

not all doctorates in the sample are in technical fields. Furthermore, general and industry-specific

experience may increase entrepreneurial performance (Klepper and Simons, 2000). Relatedly,

older, more experienced top management team members are found to aid venture performance

(Eisenhardt, 1989). We therefore include founder age, which is the entrepreneur’s age the year

!

!

25!

the firm was founded.

Finally, team and firm-level effects that may influence venture performance are

controlled. Larger founding teams have been shown to have higher performance (Roberts, 1991)

so we control for founding team size (in addition to the respondent). We control for the age of the

startup, as measured by firm age in years, since older firms tend to have higher revenues.

External investors are associated with better venture performance (Hellmann and Puri, 2002;

Hsu, 2007), and so we control for these effects with dummy variables for venture capital (VC)

and angel investors (high net-worth individuals). Used VC is equal to 1 if the individual raised

funds from venture capital firms and used angel is equal to 1 if funds came from angel investors.

Analysis and Results

-------------------------------------------------------- Insert Table 1 about here

-------------------------------------------------------- Table 1 provides descriptive statistics and a pair-wise correlation table.6 Table 2 reports

the results of the probit regressions predicting favorable exits. Table 2, model 2-1 shows results

for the controls only. Model 2-2 shows that idea from research is negative and insignificant and

cooperative environment is negative and significant (p<0.05). Hypothesis 1 was that ventures

originating in a research context and operating in a cooperative industry environment would be

associated with better performance outcomes (relative to either alone). The interaction term

between idea from research and cooperative environment is positive and significant (p<0.05),

supporting H1. Taken together, the results show that the economic magnitude of the interaction !!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!6 A majority (64 percent) of the firms have no founder in a technical role. Of the firms with no technical cofounders, 67 percent of them are solo founders. Of these, most are in service industries (law, consulting, management). We examined the types of degrees earned by those who indicated that they did not have a technical role on the founding team and found 61.5 percent had engineering degrees, 15.5 percent had science degrees, 13.9 percent had management degrees, 4.8 percent had humanities and social sciences degrees and 4.3 percent had architecture degrees. Some of these individuals had been inventors and worked in technical roles in the past, but may have moved into management roles (29 percent indicated that in their prior work experience, they had created patented inventions).

!

!

26!

effect is a net 6.3 percent (average marginal effect) higher likelihood of a favorable exit. Further

supporting the hypothesis, model 2-3 shows that the coefficient on the competitive environment

variable is positive and significant (p<0.001) and the coefficient on idea from industry is

positive, but insignificant. The coefficient on the interaction term between these two is negative

and significant, indicating that ideas from research perform more poorly in the competitive

environment.

Hypothesis 2 was that ventures originating in an industry context and operating in a

competitive industry environment would be associated with better performance outcomes. Model

2-4 tests the hypothesis by interacting idea from industry with competitive environment and we

find insignificant coefficients on the main effects and a positive and significant interaction effect

(p<0.001), supporting the hypothesis. Taken together, the results show that the economic

magnitude of the interaction effect is a net 13.9 percent (average marginal effect) higher

likelihood of a favorable exit. Model 2-5 interacts idea from industry with cooperative

environment and we find insignificant main effects and the interaction term goes in the right

direction, but the estimate is non-significant. Figure 3 (a and b) shows the interaction effect

between idea from industry and competitive environment. The figure shows that the effect is

positive and significant.

Since we have interaction effects in non-linear models, we graph the interaction effect

since the marginal effect depends on the levels of other variables (Norton, Ai and Wang, 2004).

The corrected interaction effects remain significant and continue to support the hypotheses for

most observations. We highlight some examples where the results shed additional light on our

findings. Figure 1 (a and b) shows the interaction effect between idea from research and

cooperative environment. The effect is strongest at the mid-point in the likelihood of a favorable

!

!

27!

exit and the effect is statistically significant, particularly for the observations where the

likelihood of a favorable exit is higher than 0.4. The interaction between idea from research and

prior exit shows a similar inverse-U graph in the strength of the effect (Figure 2a) and here

nearly all of the observations are statistically significant in the effect (Figure 2b).

HHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHH!

Insert Table 2 and Figures 1 & 2 about here HHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHH!

Hypothesis 3 was that ventures originating in a research context will be associated with

better performance outcomes when a founder has prior success experience. Model 2-6 finds

support for the hypothesis with a positive and significant (p<0.001) coefficient on the interaction

term between idea from research and prior exit. The main effect of prior exit is positive yet non-

significant. Hypothesis 4 was that ventures originating in an industry context will be associated

with better performance when a faculty member plays a role in the founding. Model 2-7 finds

support for the hypothesis in a positive and significant (p<0.001) coefficient on the interaction

term between idea from industry and faculty role. Both main effects are non-significant.

Additional Analysis, Robustness and Limitations

The survey data also allow us to test the link in our hypotheses from the organizational

context of venture ideation to the type of strategy the venture focuses on. In hypothesis 1, we

theorize that the organizational context of the research lab focuses venture ideation on ideas

where the strategy is focused on a competitive edge via technological innovation. To further test

the mechanism that the organizational context of ideation influences and imprints the strategic

and competitive orientation of the venture, we regressed the source of the venture idea on the

source of competitive edge. Table 3 shows the results of probit regressions predicting the

likelihood that the entrepreneur indicated that technological innovation was the basis of the

!

!

28!

competitive edge (Model 3-1) or indicated that marketing was the basis of the competitive edge

(Model 3-2). Consistent with the hypothesis, we find that if the idea for the venture originated in

a research lab, there is a significantly greater likelihood (p<0.001) that the respondent indicated

that pursuing a strategy focused on technological innovation resulted in the competitive edge.

Consistent with the idea behind hypothesis 2, the results show that if the venture idea originated

in a firm, then there is a significantly greater likelihood (p<0.05) that the respondent indicated

that the competitive edge resulted from marketing-related factors. We interpret these results as

further evidence of the link from imprinting as a result of the organizational context of venture

ideation and the strategy pursued by the firm.

Endogeneity

Next, we examine the extent to which our results may be driven by the possibility of co-

determination of the context for venture ideation, founding team composition and strategy or

business environment. If founders are first choosing a commercialization environment and

strategy, then going to a particular organizational context to generate venture ideas, this presents

a challenge to our hypotheses that the organizational context imprints the venture. Consistent

with our ideas, however, existing work suggests that ideation and team formation may precede

the formulation of strategy (Beckman, 2006: 742; Burton, Sorenson, and Beckman, 2002). Prior

work also provides evidence that the beginning stages of venture and team formation are often

influenced by social convenience rather than strategic considerations (Ruef et al., 2003: 754).

However, team and idea formation might be an endogenous process alongside choices of

commercialization environment and strategy. The example of a sophisticated founder who

already has in mind a strategic orientation and industry commercialization environment, then

knows from experience to search for venture ideas in research lab contexts, for instance, would

!

!

29!

cast doubt on an imprinting theory from the ideation context yet would be consistent with our

empirical results. We use an instrumental variables approach as a robustness check. In addition

to shedding light on the mechanism, the results in Table 3 provide us with suggestions for

possible instrumental variables. In Table 4, we use an instrumental variables (IV) approach with

an IV probit estimation procedure. We find results consistent with our main results.

To conduct our IV analysis, we ran the first-stage as a probit regression on the potentially

endogenous variables, idea from research lab and idea from industry. We constructed the

instruments team from research, brand edge, and finance edge (used for idea from research lab)

and brand edge, finance edge, and team from research (used for idea from industry) where these

variables indicate the primary source of the competitive advantage and of the founding team.

These instruments are used separately in the regressions and are significantly correlated with the

organizational context of the idea, but should not be correlated with the error term through

omitted variables. The instruments satisfy the exclusion restriction because the source of the

founding teammates and the perceived source of competitive advantage should not have a direct

impact on the likelihood of a favorable exit (venture execution rather than strict venture genesis

is more likely to determine ultimate enterprise outcomes). We then assessed the instrument’s

relevance. Using an F-test where the first stage model is compared to a model without the

instrument, we find that the F-statistic is greater than the recommended values, suggesting that

the instruments are not weak.7 The results in Table 4 are consistent with our main results in

Table 2, providing greater confidence in our findings.

Discussion and Conclusion

!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!7 We also assess the instruments’ exogeneity using the over-identification J-test and the test fails to reject the null that the instrument is valid. This test assesses whether the bundle of instruments is exogenous assuming that a least one of the instruments is exogenous. The additional instruments allow us to perform the J-test for over-identification to test the exclusion restriction.

!

!

30!

Initial venture imprinting and knowledge is often in the prior literature associated with

the top management team. For example, an influential line of research examines how

characteristics of the broader population-level environment at founding or of the entrepreneur’s

background imprint the firm (Hannan and Carroll, 1992; Boeker, 1988). Yet, the imprinting

impact of organizational context during venture ideation has largely been neglected. This paper

contributes to this literature by demonstrating another mechanism linking initial knowledge and

imprinting with outcomes. We show organization-level imprinting from the degree to which

technical and research-based knowledge versus non-technical knowledge is present at the

inception of the venture idea shapes organizational performance. Furthermore, we contribute to

the literature on imprinting by connecting the type of imprinting to an important, yet overlooked

match with the industry commercialization environment in producing venture performance

outcomes.

When in a cooperative industry environment, imprinting from a research context results

in a higher likelihood of a successful exit and in a competitive environment it is imprinting from

a business context that is favored. This paper responds to recent calls in the literature for more

work on 1) interactions of multiple sources of imprinting, and 2) moderating influences on the

role of imprinting (Certo et al., 2006; Hambrick, 2007). We do so by showing that the

characteristics of high performing founders are contingent on the imprinting from the

organizational environment.

One way to manage the influence of imprinting is by having individuals on the founding

team whose experience and skills complement or counter-balance the imprinting effects. An

experienced entrepreneur is likely to bring performance-enhancing prior startup experience and

routines to the venture. Due to their knowledge of the startup and commercialization process, the

!

!

31!

imprinting from experienced entrepreneurs may be particularly beneficial when combined with

imprinting from a research lab, where the non-technical aspects of entrepreneurship are not a

central focus.

Interpretation One alternative explanation is that the differences in the estimates are not about

imprinting but rather an indication that different types of opportunities are being pursued in the

research lab setting and in industry. It could be that the ventures originating from research ideas

are simply more innovative and innovation matters more in the cooperative environment. We

point out this potential argument to demonstrate that it is not fundamentally different from ours.

Ideas born in a research lab context are likely to be (and stay) more innovative due to the initial

knowledge and screening process that this type of organizational context provides. It is precisely

because different types of ideas and opportunities are necessary in different commercialization

environments that the type of imprinting during venture idea formation matters.

Another alternative is that the results could be driven by the founding team composition

that arises in these organizational contexts rather than about knowledge imprinting from the

context. To address this concern we control for the effects of founding team composition,

particularly the dimensions that have previously been shown to matter in competitive vs.

cooperative environments (Eesley et al., 2013).

One implication of our results regards the nature of managerial agency in imprinting.

Rather than imprinting as a force devoid of agency, our results suggest that founders may be able

to choose industries and cofounders so that they take advantage of the strengths (and avoid the

weaknesses) from the organizational context that imprinted their venture. Instead of a single

early period of imprinting, it appears there are at least two – when the idea is being formed and

!

!

32!

when cofounders are being chosen. In addition, founders have an opportunity to match the type

of imprinting that occurred during these time periods with the commercialization environment.

However, this agency is temporally constrained (to the period when cofounders are chosen and

assumes that the founder has flexibility in the type of commercialization environment or industry

in which to commercialize her idea or technology).

Our results also contribute to the debate between lifecycle and imprinting models. The

lifecycle models argue that over time, top managers with appropriate skills can be added to the

growing venture (e.g., Greiner, 1972). Such models would argue that a fit between the initial

conditions and the venture’s industry environment is unnecessary since ventures can add

professionals over time (Hellmann and Puri, 2000; Keck, 1997). Imprinting models argue, in

contrast, that the conditions at founding have a long-lasting influence on the venture (Beckman

and Burton, 2008; Burton and Beckman, 2007). The contribution of our results to this literature

is in demonstrating that both the founding team and the organizational context for

entrepreneurial ideation must be aligned with the industry environment and type of competition

to generate venture performance. These sources of imprinting may place limits on the extent of

effectiveness in adding TMT members over the life cycle of the venture. For instance, if a

venture that originated in a research context could simply add TMT members later if competing

in a competitive industry environment, then we would not expect to see the significant effects of

the initial organizational context or of faculty founders on performance that we find.

Despite the continued interest by strategy and organization theorists on the firm’s

business environment (e.g., Porter, 1991), relatively little prior work links the firm’s

commercialization environment to the type of imprinting from the organizational context where

the entrepreneurial idea emerged. Whereas prior literature shows that entry strategies are

!

!

33!

contingent on the business environment (Teece, 1986; Gans et al., 2002), our results show that

the commercialization environment is an overlooked contingency in the link between imprinting

and organizational performance. Early work on contingency theory relates features of the

business environment such as turbulence or stability to organizational design decisions (Burns

and Stalker, 1961). However, these decisions did not include the organizational context of

venture ideation or founding team composition. As a result, our results contribute to the literature

by showing how the knowledge and imprinting from the organizational context where the idea

for the startup emerged influences performance and is moderated by alignment with both the

founding team composition and the industry commercialization environment.

Limitations and future research. Consistent with the commercialization environment

literature, we have conceptualized our analysis statically. However, one limitation of this

approach and question for future research is whether a more dynamic model of changes in

venture ideation, founding team additions and choice of industry environment would yield

different predictions. We have also not been able to explicitly examine the costs of search for

more ideal cofounders (such as those with prior entrepreneurial experience or a faculty

cofounder). Another open question is whether other resource providers such as investors, early

employees, or advisors might bring similar, complementary skills and information to ventures

that originated in research or industry contexts.

These and other future research directions would be interesting, however, the results here

improve our understanding of the sources of imprinting (particularly those that are more under

the potential control of founders). Furthermore, they aid existing literature in shedding light on

when the context for venture ideation might need to be aligned with the founding team

composition and business environment. Our main contribution is in demonstrating how the

!

!

34!

organizational context where the venture idea was born shapes the strategic options available to

the venture, and results in different performance depending on the business environment. In

conclusion, we find that imprinting occurs both through the organizational context of venture

ideation and through interaction with founder characteristics. Important contingencies exist

between the type of imprinting and the industry commercialization environment.

References Agrawal A, Henderson, R. 2002. Putting Patents in Context: Exploring Knowledge Transfer

from MIT. Management Science 48(1): 44-60. Arora A, Fosfuri A, Gambardella A. 2001. Markets for Technology: The Economics of

Innovation and Corporate Strategy. MIT Press: Cambridge, MA. Arora A, Nandkumar A. 2011. Cash-out or flame-out! Opportunity cost and entrepreneurial

strategy: theory, and evidence from the information security industry. Management Science 57(10): 1844–1860.

Audretsch DB, Stephan P. 1996. Company-scientist locational links: the case of biotechnology, American Economic Review 86(4): 641-652.

Azoulay P, Liu CC, Stuart TE. 2011. Social Influence Given (Partially) Deliberate Matching: Career Imprints in the Creation of Academic Entrepreneurs, Working Paper, Harvard University, Cambridge.

Baron RA, Ensley MD. 2006. Opportunity recognition as the detection of meaningful patterns: Evidence from comparisons of novice and experienced entrepreneurs. Management Science 52: 1331-1344.

Baron JN, Burton MD, Hannan MT. 1999a. Engineering bureaucracy: the genesis of formal policies, positions, and structures in high-technology firms. Journal of Law, Economics, and Organization 15(1): 1-41.

Baron JN, Hannan MT, Burton MD. 1999b. Building the Iron Cage: Determinants of Managerial Intensity in the Early Years of Organizations. American Sociological Review, 64:527-547.

Beckman C, Burton MD. 2008. Founding the Future: The Evolution of Top Management Teams from Founding to IPO. Organization Science, 19(1):3-24.

Beckman CM. 2006. The influence of founding team prior company affiliations on firm behavior. Academy of Management Journal 49: 741-758.

Beckman CM, Burton MD, O'Reilly C. 2007. Early teams: The impact of team demography on VC financing and going public. Journal of Business Venturing 22: 147-173.

Bingham CB, Eisenhardt KM. 2011. Rational Heuristics: the 'simple rules' that strategists learn from process experience. Strategic Management Journal 32(13), 1437-1464.

Boeker W. 1988. Organizational Origins: Entrepreneurial and Environmental Imprinting at the Time of Founding. In G.R. Carroll (Eds.), Ecological Models of Organizations (pp. 33–52). Ballinger, Cambridge MA,

Boeker W. 1989. Strategic change: The effects of founding and history. Academy of Management Journal 489-515.

!

!

35!

Burns T, Stalker GM. 1961. The Management of Innovation. Tavistock: London, UK. Burton DM, Sørensen JB, Beckman CM. 2002. Coming From Good Stock: Career Histories and

New Venture Formation. Research in the Sociology of Organizations 19: 229-262. Burton MD, Beckman CM. 2007. Leaving a legacy: Position imprints and successor turnover in

young firms. American Sociological Review 72(2): 239. Carroll GR, Delacroix J. 1982. Organizational mortality in the newspaper industries of Argentina

and Ireland: An ecological approach. Administrative Science Quarterly 27(2): 169-198. Carroll GR, Hannan MT. 1989. Density Dependence in the Evolution of Populations of

Newspaper Organizations. American Sociological Review 54(4): 524-541. Certo ST, Lester RH, Dalton CM, Dalton DR. 2006. Top management teams, strategy and

financial performance: a meta-analytic examination. Journal of Management Studies 43(4): 813–839.

Cohen W, Nelson R, Walsh J. 2000. Protecting their intellectual assets: appropriability conditions and why U.S. manufacturing firms patent (or not). Working paper W7552, National Bureau of Economic Research (NBER), Cambridge, MA.

Cornelissen JP, Clarke JS. 2010. Imagining and rationalizing opportunities: Inductive reasoning, and the creation and justification of new ventures. Academy of Management Review 35 (4), 539-557.

Delmar F, Shane S. 2006. Does experience matter? The effect of founding team experience on the survival and sales of newly founded ventures. Strategic Organization 4(3): 215-247.

DiMaggio PJ, Powell WW. 1983. The Iron Cage Revisited: Institutional Isomorphism and Collective Rationality in Organizational Fields. American Sociological Review 48: 147-160.

Dobrev SD, Barnett WP. (2005). Organizational roles and transition to entrepreneurship. Academy of Management Journal 48(3): 433-449.

Eisenhardt K. 1989. Making fast strategic decisions in high-velocity environments. Academy of Management Journal 82: 929-964.

Eesley CE, Lenox M. 2006. Firm Responses to Secondary Stakeholder Action. Strategic Management Journal 27(8): 765-781.

Eesley C, Roberts EB. 2012. Are you experienced or are you talented?: When does innate talent versus experience explain entrepreneurial performance? Strategic Entrepreneurship Journal 6(3): 207-219.

Eesley CE, Hsu DH, Roberts EB. 2013. The contingent effects of top management teams on venture performance: Aligning founding team composition with innovation strategy and commercialization environment. Strategic Management Journal doi: 10.1002/smj.2183

Felin T, Zenger TR. 2009. Entrepreneurs as Theorists: On the Origins of Collective Beliefs and Novel Strategies. Strategic Entrepreneurship Journal 3: 127-146.

Fuller AW, Thursby MC. 2008. Chapter 8 Technology commercialization: Cooperative versus competitive strategies, in Gary D. Libecap, Marie C. Thursby (ed.) Technological Innovation: Generating Economic Results (Advances in the Study of Entrepreneurship, Innovation & Economic Growth, Volume 18), Emerald Group Publishing Limited; 227-250

Gans JS, Hsu DH, Stern S. 2002. When does start-up innovation spur the gale of creative destruction? The Rand Journal of Economics 33(4): 571-586.

Gans JS, Stern S. 2003. The product market and the market for "ideas": Commercialization strategies for technology entrepreneurs. Research Policy 32(2): 333-350.

!

!

36!

Gavetti G, Levinthal DA, Rivkin JW. 2005. Strategy making in novel and complex worlds: The power of analogy. Strategic Management Journal 26: 691–712.

Gompers P, Lerner J, Scharfstein D. 2005. Entrepreneurial spawning: public corporations and the genesis of new ventures, 1986 to 1999. Journal of Finance 60(2): 517–614.

Greiner LE. 1972. Evolution and revolution as organizations grow. Harvard Business Review, 50(4): 37-46.

Gruber M, MacMillan IC, Thompson JD. 2008. Look before you leap: Market opportunity identification in emerging technology firms. Management Science 54(9): 1652-1665.

Hallen B, Eisenhardt K. 2012. Catalyzing Strategies and Efficient Tie Formation: How Entrepreneurial Firms Obtain Investment Ties. Academy of Management Journal 55(1): 35–70.

Hambrick DC. 2007. Upper echelons theory: an update. Academy of Management Review 32(2): 334–343.

Hannan MT, Burton MD, Baron JN. 1996. Inertia and Change in the Early Years: Employment Relations in Young, High Technology Firms. Industrial and Corporate Change 5(2): 503-536.

Hannan MT, Carroll GR. 1992. Dynamics of Organizational Populations: Density, Competition, and Legitimation. New York: Oxford University Press.

Hannan MT, Freeman J. 1977. The Population Ecology of Organizations. American Journal of Sociology 82(5): 929-964.

Helfat C. 1994. Evolutionary trajectories in petroleum firm R&D. Management Science 40(12): 1720–1747.

Hellmann T, Puri M. 2002. Venture capital and the professionalization of start-up firms: empirical evidence. Journal of Finance 57(1): 169-197.

Hellmann T, Puri M. 2000. The Interaction between Product Market and Financing Strategy: The Role of Venture Capital. Review of Financial Studies 13(4): 959-984.

Henderson RM, Clark KB (1990) Architectural innovation: The reconfiguration of existing product technologies and the failure of established firms. Administrative Science Quarterly 35:9–30.

Hsu DH. 2004. What do entrepreneurs pay for venture capital affiliation? Journal of Finance 59:1805-1844.

Hsu DH. 2006. Venture capitalists and cooperative start-up commercialization strategy, Management Science 52: 204-219.

Hsu DH. 2007. Experienced entrepreneurial founders, organizational capital, and venture capital funding. Research Policy 36: 722-741.

Hsu DH, Lim K. 2013. Knowledge Brokering and Organizational Innovation: Founder Imprinting Effects. Organization Science, forthcoming.

Hsu DH, Roberts EB, Eesley CE. 2007. Entrepreneurs from technology-based universities: Evidence from MIT. Research Policy 36: 768-788.

Ingram P, Baum J. 1997. Opportunity and constraint: organizations' learning from the operating and competitive experience of industries. Strategic Management Journal 18(S1): 75-98.

Johnson V. 2007. What Is Organizational Imprinting? Cultural Entrepreneurship in the Founding of the Paris Opera. American Journal of Sociology 113(1): 97-127

Katila R, Ahuja G. 2002. Something old, something new: a longitudinal study of search behavior and new product introduction. Academy of Management Journal 45(6): 1183–1194.

!

!

37!

Katila R, Chen E. 2009. Effects of search timing on product innovation: The value of not being in sync. Administrative Science Quarterly 53: 593-625.

Katila R, Rosenberger J, Eisenhardt KM. 2008. Swimming with sharks: Technology ventures, defense mechanisms, and corporate relationships. Administrative Science Quarterly 53: 295-332.

Keck SL. 1997. Top management team structure: Differential effects by environmental context. Organization Science 8(2): 143-156.

Kimberly JR, Bouchikhi H. 1995. The Dynamics of Organizational Development and Change: How the Past Shapes the Present and Constrains the Future. Organization Science 6(1): 9-18.

Klepper S, Simons KL. 2000. Dominance by birthright: entry of prior radio producers and competitive ramifications in the U.S. television receiver industry. Strategic Management Journal 21(10/11): 997–1016.

Lerner J, Malmendier U. 2011. With a little help from my (random) friends: Success and failure in post-business school entrepreneurship. NBER Working Papers 16918, National Bureau of Economic Research, Inc.

Lerner J, Merges RP. 1998. The control of technology alliances: An empirical analysis of the biotechnology industry. Journal of Industrial Economics 46(2): 125-156.

Marquis C. 2003. The Pressure of the Past: Network Imprinting in Intercorporate Communities. Administrative Science Quarterly 48: 655-689.

Marquis C, Battilana J. 2009. Acting Globally but Thinking Locally? The Influence of Local Communities on Organizations. Research in Organizational Behavior 29: 283-302.

Marquis C, Tilcsik A. 2013. Imprinting: Toward A Multilevel Theory. Academy of Management Annals 7: 193-243.

McEvily B, Jaffee J, Tortoriello, M. 2012. Not All Bridging Ties Are Equal: Network Imprinting and Firm Growth in the Nashville Legal Industry, 1933–1978. Organization Science 23(2): 547-563.

Murray F. 2004. The role of academic inventors in entrepreneurial firms: sharing the laboratory life. Research Policy 33(4), 643–659.

Phillips DJ. 2005. Organizational Genealogies and the Persistence of Gender Inequality: The Case of Silicon Valley Law Firms. Administrative Science Quarterly 50(3): 440-472.

Porter ME. 1991. Towards a dynamic theory of strategy. Strategic Management Journal 12: 95–117.

Roberts EB. 1991. Entrepreneurs in High Technology: Lessons from MIT and Beyond. Oxford University Press: New York.

Rosenbloom RS, Christensen CM. 1994. Technological discontinuities, organizational capabilities, and strategic commitments. Industrial and Corporate Change, 3(3): 654–668.

Rothaermel FT, Agung SD, Jian L. 2007. University entrepreneurship: a taxonomy of the literature. Industrial and Corporate Change 16(4): 691–792.

Rothaermel FT. 2001. Incumbent’s Advantage Through Exploiting Complementary Assets Via Interfirm Cooperation. Strategic Management Journal, 22: 687–699.

Ruef M, Aldrich H, Carter N. 2003. The structure of founding teams: homophily, strong ties, and isolation among U.S. entrepreneurs. American Sociological Review 68(2): 195–222.

Selznick P. 1949. TVA and the grass roots. Berkley, CA: University of California Press. Stinchcombe AL. 1965. Social Structure and Organizations. In J. G. March (Ed.), Handbook of

Organizations: 142-193. Chicago: Rand McNally & Co.

!

!

38!

Sutton RI, Hargadon A. 1996. Brainstorming groups in context: effectiveness in a product design firm. Administrative Science Quarterly 41: 685–718.

Teece DJ. 1986. Profiting from technological innovation: implications for integration, collaboration, licensing and public policy. Research Policy 15: 285–305.

Tripsas M. 1997. Surviving radical technological change through dynamic capability: Evidence from the typesetter industry. Industrial and Corporate Change 6(2): 341-377.

Woodward, J. 1965. Industrial Organization: Theory and Practice. Oxford University Press, Oxford.

Zucker LG, Darby MR, Brewer MB. 1998. Intellectual human capital and the birth of U.S. biotechnology enterprises. American Economics Review 88(1) 290–306.

!

!

39!

Table 1: Variables, Descriptive Statistics, and Correlations!

Obs Mean SD Min Max 1 2 3 4 5 6 7 8 9 10

1 Favorable exit 2133 0.305 0.461 0 1 1.00

2 Cooperative 1297 0.458 0.498 0 1 0.17 1.00

3 Competitive 1297 0.542 0.498 0 1 -0.17 -1.00 1.00

4 Idea from research lab 1388 0.199 0.399 0 1 0.00 0.07 -0.07 1.00

5 Idea from industry 1387 0.560 0.497 0 1 0.03 -0.01 0.01 -0.41 1.00

6 Team from industry 929 0.537 0.499 0 1 0.07 0.08 -0.08 -0.22 0.33 1.00

7 Team from research 929 0.243 0.429 0 1 -0.08 0.03 -0.03 0.40 -0.31 -0.50 1.00

8 Team from family 929 0.074 0.262 0 1 -0.14 -0.13 0.13 -0.03 -0.02 -0.16 -0.01 1.00

9 Master’s degree 2133 0.387 0.487 0 1 0.04 0.03 -0.03 0.12 -0.02 -0.10 0.10 0.00 1.00

10 PhD degree 2133 0.155 0.362 0 1 0.03 -0.06 0.06 0.12 -0.11 -0.10 0.12 0.01 -0.03

11 Founder age 1653 38.15 10.32 17 83 -0.10 -0.01 0.01 -0.11 0.07 0.14 -0.22 0.00 -0.05

12 Firm age 1702 17.03 10.61 0 74 0.25 0.13 -0.13 0.03 0.03 0.08 -0.05 -0.01 -0.04

13 VC funded 1630 0.450 0.498 0 1 0.24 0.21 -0.21 0.14 -0.06 0.00 0.12 -0.11 0.05

14 Angel funded 1536 0.117 0.321 0 1 -0.01 0.10 -0.10 0.02 -0.12 0.01 0.14 -0.01 -0.06

15 Team size 1915 1.208 1.338 0 4 0.27 0.09 -0.09 0.11 -0.06 0.03 0.09 -0.01 0.03

16 Technically focused team 1766 0.162 0.369 0 1 0.14 0.06 -0.06 0.05 -0.02 -0.07 0.07 -0.11 0.01

17 Functional diversity 1766 1.261 0.521 1 4 0.13 0.07 -0.07 0.07 0.00 0.04 0.05 0.05 0.01

18 Technology edge 2133 0.218 0.413 0 1 -0.16 0.00 0.00 -0.02 0.05 0.05 -0.04 0.03 -0.06

19 Brand edge 2133 0.159 0.366 0 1 -0.17 -0.05 0.05 -0.03 0.07 -0.03 -0.05 0.04 0.01

20 Finance edge 2133 0.111 0.314 0 1 -0.12 0.06 -0.06 0.02 -0.02 -0.10 0.06 0.14 -0.04

21 Prior exit 2133 0.112 0.316 0 1 0.17 0.04 -0.04 0.011 0.051 0.041 -0.107 0.074 -

0.017

10 11 12 13 14 15 16 17 18 19 20

10 PhD degree 2133 0.155 0.362 0 1 1.00

11 Founder age 1653 38.15 10.32 17 83 0.02 1.00

12 Firm age 1702 17.03 10.61 0 74 -0.05 -0.09 1.00

13 VC funded 1630 0.450 0.498 0 1 -0.01 -0.13 -0.16 1.00

14 Angel funded 1536 0.117 0.321 0 1 0.01 -0.07 -0.15 0.18 1.00

15 Team size 1915 1.208 1.338 0 4 0.01 -0.13 0.03 0.25 0.17 1.00

16 Technically focused team 1766 0.162 0.369 0 1 0.00 -0.03 -0.01 0.12 0.01 0.20 1.00

17 Functional diversity 1766 1.261 0.521 1 4 -0.02 -0.08 0.07 0.14 0.12 0.56 -0.19 1.00

18 Technology edge 2133 0.218 0.413 0 1 0.02 -0.01 -0.01 -0.14 0.07 0.05 0.08 0.01 1.00

19 Brand edge 2133 0.159 0.366 0 1 0.00 0.05 -0.03 -0.14 -0.01 0.06 0.05 0.03 0.60 1.00

20 Finance edge 2133 0.111 0.314 0 1 -0.05 -0.01 -0.05 0.02 0.12 0.06 0.05 0.04 0.44 0.42

21 Prior exit 2133 0.112 0.316 0 1 0.02 0.17 -0.01 0.15 0.01 0.11 0.10 -0.05 -0.06 -0.04 -0.00

!

!

40!

Table 2: Probits of favorable exit for varied organizational contexts for venture ideation.

Industry and founding year fixed effects are included in the regressions but the coefficients are unreported . Robust,!twoHtailed!standard!errors!in!parentheses.!***!p<0.001,!**!p<0.01,!*!p<0.05!!

VARIABLES (2-1) (2-2) (2-3) (2-4) (2-5) (2-6) (2-7) Idea research*coop 0.970* (0.424) Idea research*comp -0.758* (0.378) Idea industry*coop -0.141 (0.151) Idea industry*comp 0.548*** (0.177) Idea research*prior exit 2.163*** (0.452) Idea industry*faculty role 1.268*** (0.374) Faculty role -0.252 (0.430) Prior exit 0.188 (0.151) Idea from research lab -0.418 0.366 0.055 0.100 -0.318** 0.049 (0.248) (0.329) (0.231) (0.220) (0.147) (0.213) Idea from industry 0.174 0.155 -0.085 0.264 0.056 0.123 (0.121) (0.124) (0.135) (0.150) (0.118) (0.122) Competitive env. -0.791 0.356*** -0.142 (0.519) (0.126) (0.181) Cooperative env. -0.935 -1.177* -0.900 (0.541) (0.559) (0.557) Func. diversity count -0.297*** -0.285*** -0.282*** -0.298*** -0.301*** -0.089 -0.299*** (0.091) (0.095) (0.096) (0.091) (0.094) (0.091) (0.100) Tech. focused team 0.002 -0.034 -0.052 -0.045 -0.014 0.044 (0.069) (0.231) (0.231) (0.240) (0.240) (0.235) (0.117) (0.249) Met via industry 0.068 0.083 0.065 0.027 0.041 -0.058 0.014 (0.198) (0.233) (0.228) (0.205) (0.209) (0.107) (0.186) Met via family -0.190 -0.202 -0.242 -0.218 -0.199 -0.837*** -0.245 (0.202) (0.172) (0.192) (0.212) (0.190) (0.243) (0.199) Master’s degree 0.077 0.080 0.077 0.078 0.081 0.027 0.084 (0.181) (0.172) (0.156) (0.166) (0.183) (0.099) (0.160) Doctorate degree -0.264 -0.185 -0.148 -0.179 -0.232 0.029 -0.226 (0.248) (0.224) (0.235) (0.226) (0.241) (0.133) (0.275) Founder age 0.008 0.007 0.006 0.007 0.007 0.000 0.007 (0.009) (0.009) (0.008) (0.008) (0.009) (0.005) (0.008) Firm age 0.033* 0.031 0.029 0.031 0.032* 0.039*** 0.031* (0.015) (0.016) (0.017) (0.017) (0.015) (0.005) (0.018) VC funded 0.318*** 0.376*** 0.377*** 0.353*** 0.353*** 0.430*** 0.348*** (0.053) (0.055) (0.054) (0.054) (0.067) (0.103) (0.066) Angel funded -0.072 0.041 -0.012 -0.049 0.004 -0.293** -0.055 (0.164) (0.170) (0.147) (0.170) (0.170) (0.145) (0.131) Founding team size 0.143 0.139 0.139 0.141 0.143 0.118** 0.136 (0.137) (0.135) (0.135) (0.133) (0.130) (0.048) (0.133) Constant -0.964 -1.193 -2.047*** -1.782*** -1.093 -1.070*** -1.756*** (0.743) (0.820) (0.617) (0.561) (0.784) (0.273) -0.564 Observations 763 763 763 763 763 763 763 Pseudo R-squared e(r2_a) e(r2_a) e(r2_a) e(r2_a) e(r2_a) 0.151 0.260

!

!

41!

Figure 1: Interaction effect between idea from research and cooperative environment on the probability of a favorable exit.

!

Figure 1a Figure 1b Corrected effect is plotted using the Norton, Wang and Ai (2004) Stata command. These figures show that the interaction effect is positive (and is statistically significant for most of the range of the dependent variable). !

!

Figure 2: Interaction effect between idea from research and prior exit on the probability of a favorable exit.

!Figure!2a! ! ! ! ! ! Figure!2b!

Corrected effect is plotted using the Norton, Wang and Ai (2004) Stata command. These figures show that the interaction effect is positive (and is statistically significant for most of the range of the dependent variable). !

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

0

.1

.2

.3

.4

Inte

ract

ion

Effe

ct (p

erce

ntag

e po

ints

)

0 .2 .4 .6 .8 1Predicted Probability that y = 1

Correct interaction effect Incorrect marginal effect

Interaction Effects after Probit

®

!

!

42!

!

!

!

Figure 3: Interaction effect between idea from industry and competitive environment on the probability of a favorable exit.

!

Figure!3a! ! ! ! ! Figure!3b!

Corrected effect is plotted using the Norton, Wang and Ai (2004) Stata command. These figures show that the interaction effect is positive (and is statistically significant for most of the range of the dependent variable).!!

Figure 4: Interaction effect between idea from industry and faculty role on the probability of a favorable exit.

!

Figure 4a Figure 4b Corrected effect is plotted using the Norton, Wang and Ai (2004) Stata command. These figures show that the interaction effect is positive (and is statistically significant for most of the range of the dependent variable). !

!

!

! !

.1

.2

.3

.4

.5

Inte

ract

ion

Effe

ct (p

erce

ntag

e po

ints

)

0 .2 .4 .6 .8 1Predicted Probability that y = 1

Correct interaction effect Incorrect marginal effect

Interaction Effects after Probit

®

−5

0

5

10

z−st

atis

tic

0 .2 .4 .6 .8 1Predicted Probability that y = 1

z−statistics of Interaction Effects after Probit

®

!

!

43!

Table!3:!Probit!regressions!predicting!factors!stated!by!founder!in!giving!the!firm!a!competitive!edge!(marketing!vs.!

technology!factors)!

Pr(technology edge) Pr(brand edge)

(3-1) (3-2) Idea from research lab 0.595*** 0.001 (0.220) (0.196) Idea from industry 0.293 0.333* (0.184) -0.164 Tech. focused team 0.429* 0.172 (0.179) (0.160) Func. diversity count -0.040 0.027 (0.141) (0.130) Met via family -0.017 0.157 (0.290) (0.292) Master’s degree -0.361* 0.393*** (0.144) (0.133) Doctorate degree 0.302 0.228 (0.182) (0.175) Founder age -0.0206*** -0.006 (0.007) (0.006) Firm age 1.040*** 0.551*** (0.109) (0.164) VC funded -0.335** -0.185 (0.159) (0.151) Angel funded -0.058 -0.215 (0.216) (0.194) Founding team size -0.100 0.020 (0.075) (0.067) Team via industry 0.214 -0.048 (0.178) (0.140) Team via research lab -0.275 -0.311 (0.230) (0.222) Constant -5.820*** -4.299*** (0.882) (1.178) Observations 672 649 Pseudo-R2 0.404 0.305

Industry and founding year fixed effects are included in the regressions but the coefficients are unreported. Robust,!twoHtailed!standard!errors!in!parentheses.!***!p<0.001,!**!p<0.01,!*!p<0.05!!

!

!

44!

Table!4!Instrumental!variables!(IV)!analysis!

Pr(Exit) Pr(Exit) (4-1) (4-2) Idea research*coop 1.712* (0.801) Idea industry*comp 2.457*** (0.649) Idea from research lab -1.020 (0.880) Idea from industry -2.335*** (0.756) Competitive env. -0.639* (0.284) Cooperative env. -0.720*** (0.271) Func. diversity count -0.038 0.006 (0.128) (0.107) Tech. focused team 0.277 0.269* (0.151) (0.137) Met via industry 0.108 0.433* (0.137) (0.182) Met via family 0.429 0.460 (0.283) (0.244) Master’s degree 0.038 -0.033 (0.136) (0.114) Doctorate degree -0.035 -0.082 (0.225) (0.149) Founder age 0.012 0.013* (0.007) (0.005) Firm age 0.020 0.0326 (0.023) (0.018) VC funded 0.260 0.049 (0.157) (0.143) Angel funded -0.352 -0.654*** (0.201) (0.178) Founding team size 0.095 0.085 (0.063) (0.058) Constant -1.481*** -1.008 (0.446) (0.576) Observations 658 675 Log-likelihood -319.611 -404.623

Industry and founding year fixed effects are included in the regressions but the coefficients are unreported. TwoHtailed!standard!errors!in!parentheses.!***!p<0.001,!**!p<0.01,!*!p<0.05!We!instrument!the! idea!from!research!lab!variable!with!the!variables!team!from!research,!technology!edge,!and!finance!edge,!and!all!R2!statistics!are!relatively!high,!indicating!there!is!not!a!weak!instrument!problem.!The!F!statistic!is!18.332,!which!exceeds!the!critical!value! for!a!weak! instrument.!We! instrument! the! idea!from!industry!variable!with! the!variables:!brand!edge,!finance!edge,! and! team!from!research!(inversely!correlated).!Again,!all!the!R2!statistics!are!relatively!high,!so!they!do!not!imply!a!weakHinstrument!problem.!In!addition,!the!F!statistic!is!7.350,!indicating!there!is!not!evidence!of!a!weak!instrument!problem.!!

!