Intellectual property protection and the formation of entrepreneurial growth aspirations

Copyright © 2010 Strategic Management Society

Strategic Entrepreneurship JournalStrat. Entrepreneurship J., 4: 234–251 (2010)

Published online in Wiley Online Library (wileyonlinelibrary.com). DOI: 10.1002/sej.93

INTELLECTUAL PROPERTY PROTECTION AND THE FORMATION OF ENTREPRENEURIAL GROWTH ASPIRATIONS

ERKKO AUTIO1* and ZOLTAN ACS2

1Imperial College Business School, London, U.K.2George Mason University, School of Public Policy, Fairfax, Virginia, U.S.A.

Applying real options logic, we build and test a multilevel model that explicates the infl uence of a country’s intellectual property protection regime on the effect of an individual’s human and fi nancial capital on entrepreneurial growth aspirations. The results suggest that the strength of the intellectual property regime moderates negatively the relationship between an individual’s education and entrepreneurial growth aspirations; and it moderates positively the relationship between an individual’s household income and growth aspirations. Intellectual property protection, thereby, encourages specialization amongst differently qualifi ed entre-preneurs. Our fi ndings support claims that strategic entrepreneurial behaviors cannot be fully understood without giving attention to the context in which those behaviors are observed. Copyright © 2010 Strategic Management Society.

INTRODUCTION

Although growth has always been a central theme in entrepreneurship research, the determinants of growth aspirations remain relatively unexplored (Davidsson and Wiklund, 2000). Yet, entrepreneurial growth seldom occurs without the fi rm seeking it. Obtaining organizational growth is diffi cult and risky and requires a substantial investment of resources, time, and effort. Because the rewards of growth are so dif-fi cult to achieve, the majority of new start-up fi rms do not even seek growth (Autio, 2007; Delmar, Davidsson, and Gartner, 2003). A central topic for entrepreneurship research, then, is the factors that propel some individuals and not others to allocate effort to growth-seeking entrepreneurial ventures.

In spite of extensive evidence pointing to the importance of high-growth fi rms for economic

development (Acs, 2008), there is little research on the determinants of entrepreneurial growth aspira-tions in young fi rms. This is an important gap, given the multitude of studies that point to the important role of entrepreneurial entry for job creation (Henrekson and Johansson, forthcoming). As already observed by Penrose (1959) and elaborated on in the context of entrepreneurial fi rms by Davidsson (1991), the growth of entrepreneurial fi rms results from the combination of three factors: (1) the quality of opportunities available for the fi rm; (2) the moti-vation of the decision makers of the fi rm to pursue those opportunities; and (3) their ability to do so successfully. Whereas the entrepreneurship litera-ture has largely focused on opportunity quality and the ability to pursue opportunities, the third factor—growth motivation—has received considerably less attention (Wiklund and Davidsson, 2003). In this article, we focus on infl uences on growth motiva-tion, operationalized here as growth aspirations.

Three broad explanations have been offered for the formation of entrepreneurial growth aspirations by individuals. The psychological approach emphasizes the presence of innate growth motivations, often

Keywords: strategic entrepreneurship; intellectual property protection; growth aspirations; multilevel analysis*Correspondence to: Erkko Autio, Imperial College Business School, Exhibition Road, London SW7 2AZ, U.K. E-mail: [email protected]

Intellectual Property Protection and Entrepreneurial Growth Aspirations 235

Copyright © 2010 Strategic Management Society Strat. Entrepreneurship J., 4: 234–251 (2010) DOI: 10.1002/sej

operationalized in the entrepreneurship literature under the rubric of entrepreneurial orientations (e.g., Lumpkin et al., 1996; Wiklund and Shepherd, 2005). The socio-logical approach emphasizes the importance of prevail-ing social norms that operate through the pressure to conform (e.g., Haveman, 1993; Krueger, Reilly, and Carsrud, 2000). Relatively less common, the economic approach emphasizes the importance of rational, utility-maximizing considerations of risks and expected returns as the main drivers of the choice between stra-tegic alternatives (e.g., Campbell, 1992; Douglas and Shepherd, 2000; Eckhardt and Shane, 2003; Eisenhauer, 1995; Fiegenbaum and Thomas, 1988; Kirzner, 1997; Lazear, 2005). In this article, we subscribe to the third approach and apply real options logic to consider the entrepreneur’s choice of whether or not to allocate effort to the pursuit of growth in a new entrepreneurial venture (Dixit, 1989; O’Brien et al., 2003). While all explanations have merit, the real options theory pro-vides a coherent framework against which to consider individuals’ resource allocation decisions. In our model, growth aspiration is infl uenced by opportunity costs and trade-offs associated with partially irrevers-ible resource allocations: the more valuable the resources allocated into the venture, the higher its growth aspirations will be. This is because valuable resources require higher returns and the venture does not have to match only the value of the resource, but also the cost of external uncertainty (e.g., Amit, Muller, and Cockburn, 1995; O’Brien et al., 2003). Trade-offs are infl uenced by institutional conditions, which regu-late opportunity costs through their effect on external uncertainty (Crifo and Sami, 2008).

Our starting point is that the decision to allocate one’s human and fi nancial capital into a growth-oriented new venture can be modelled as a rational decision made by individuals who seek to maximize the utility of these resources (Bowen and DeClercq, 2008; Douglas and Shepherd, 2000, 2002; Michelacci, 2003). The trade-offs associated with resource alloca-tion decisions are infl uenced by the strength of the country’s intellectual property rights (IPR) protection regime, which infl uences the distribution of profi ts on innovation between innovators, users, producers, and competitors (Arora, Fosfuri, and Gambardella, 2001; Foss and Foss, 2008; Schendel and Hitt, 2007; Teece, 1998). We argue that a country’s IPR protection regime will have a differential effect on how a given individual’s education and household income infl u-ence the decision to allocate effort into a growth-oriented entrepreneurial venture, because of the way technical appropriability impacts trade-offs associ-

ated with the semireversible allocation of human and fi nancial capital to alternative, often mutually exclu-sive uses.

We test our theoretical model using data collected by the Global Entrepreneurship Monitor GEM (Reynolds, Bosma, and Autio, 2005). We combined eight years of GEM data from 65 countries, thereby creating a dataset of more than 900,000 person-to-person interviews. This dataset was complemented with country-level data. This design enabled us to consider the effect of country-level institutional con-ditions on individual-level entrepreneurial behaviors, thereby contributing toward a more generalized understanding of how individuals make strategic choices in different contexts. By applying a multilevel research design to examine determinants of entrepre-neurial growth aspirations, our study responds to numerous calls for multilevel approaches to the study of entrepreneurship (Busenitz et al., 2003; Phan, 2004; Schendel and Hitt, 2007). Most studies of entre-preneurial growth motivations have employed single-country data, where variation in institutional conditions is typically zero (Davidsson and Wiklund, 2001). By looking at growth aspirations of early-stage entrepreneurs, we also move beyond post hoc designs typically used in studies of entrepreneurial growth and shed light on growth aspirations and motivations that ultimately drive strategic entrepreneurship.

The next section of this article develops hypotheses regarding the effect of an individual’s education and household income on the individual’s entrepreneurial growth aspirations. Section three discusses the vari-ables and methods, and section four presents our fi nd-ings. The fi ndings show that the strength of an IPR protection regime moderates the extent to which indi-viduals aspire to exploit their human and fi nancial capital through entrepreneurial ventures: it moderates negatively the relationship between an individual’s education and entrepreneurial growth aspirations, and it moderates positively the relationship between an individual’s household income and entrepreneurial growth aspirations. This, we argue, is because of how IPR protection regulates the exploitation of the inno-vator’s own human intellectual capital versus that of others. The conclusions are in the fi nal section.

INFLUENCES ON ENTREPRENEURIAL GROWTH ASPIRATIONS

Entrepreneurial entry and growth aspiration result from individual-level decisions, whereby

236 E. Autio and Z. Acs


individuals seek returns to their human and fi nancial capital (Douglas and Shepherd, 2000; Shane and Venkataraman, 2000). When exploiting their human and fi nancial capital to advance valued goals, entre-preneurs face important economic trade-offs (Åstbro and Bernhardt, 2005; Bruderl, Preisendorfer, and Ziegler, 1992). First, the individual needs to decide whether a growth-oriented entrepreneurial venture provides a better conduit than regular employment for the realization of valued goals (Cassar, 2006). Second, the individual needs to decide how much effort and resources he/she should invest into growing the venture (Douglas and Shepherd, 2002). Such trade-offs are not easy to strike, as returns to resource allocations are uncertain, and it is usually not possible to effectively pursue two occupations simultaneously on a full-time basis (Sparrowe et al., 2001). To manage this uncertainty, most entrepre-neurial ventures tend to be started as part-time efforts, and entrepreneurs consider how to allocate their effort between the new venture and alternative sources of income (Autio, 2007).

A particularly important infl uence on effort allo-cation decisions has to do with technical appropri-ability conditions—the IPR protection regime—and how it impacts the ability of inventors and investors to protect their own human and intellectual capital and exploit that of others (Feldman et al., 2002; Schendel and Hitt, 2007). We argue that technical appropriability conditions will infl uence the alterna-tives available to high-income and well-educated individuals differently. Our theoretical model is illustrated in Figure 1.

Our theoretical model is based on several prem-ises. First, we consider the individual to be more or less rational when making resource allocation deci-sions, and to consider the opportunity costs and

potential returns associated with those decisions. Second, we consider an individual’s human capital (as expressed in education) and fi nancial capital (as expressed in household income) to constitute valu-able resources that carry nontrivial opportunity costs, both immediately before and after the entry decision. Third, we expect that opportunity costs are infl uenced by the strength of the country’s IPR pro-tection regime. In the next section, we explain our general theoretical logic and lay out the direct hypotheses concerning the effect of education and household income on entrepreneurial growth aspirations.

Entrepreneurial decisions in a utility-maximizing perspective

Dixit (1989) proposed that uncertainty infl uences the likelihood of investment when it entails sunk cost and when the investor has discretion over the timing of investment—conditions characteristic of the decision to allocate resources to entrepreneurship (O’Brien et al., 2003). Yet, in the entrepreneurship literature, there have been few studies to consider the decision to allocate effort into entrepreneurship as a rational, utility-maximizing decision (Douglas and Shepherd, 2000). Campbell (1992) proposed an economic decision theory of entrepreneurial acts, modeling entry into entrepreneurship as a career choice between entrepreneurship and wage labor and proposing a net present value (NPV) model to highlight entrepreneurial decision heuristics. Eisenhauer (1995) presented another NPV model and showed that roughly 95 percent of the variance in self-employment rates in the U.S. from 1959 to 1991 was explained by economic utility derived from self-employment versus wage labor. Building

Education

Household income

Entrepreneurial growth aspiration

IPR protection

Individual-level effects

Country-level effects

(+)

(+)(-)

(+)

Figure 1. Theoretical model of the study



on these works, Douglas and Shepherd (2000) pre-sented an entrepreneurial utility-maximizing model which included not only NPV calculations, but also individual preferences with regard to attitudes to risk, work effort, and independence. These studies show that rational calculations play an important role in entrepreneurial decisions.

A complementary approach to NPV-based utility maximizing calculations is provided by real options theory (Dixit, 1989; O’Brien et al., 2003). Because it considers allocation of effort into entrepreneurship as a partially irreversible resource commitment (with consequent sunk costs) made by utility-maximizing individuals who value fl exibility, the real options logic should provide particularly good guidance to the understanding of entrepreneurial behaviors (Kogut and Kulatilaka, 2001). As a real options framework does not rely on assumptions regarding individuals’ risk preferences (as NPV models do), it also provides a more parsimonious approach to understanding entrepreneurial resource allocation decisions (O’Brien et al., 2003). Therefore, we draw on real options logic to explain the effect of an individual’s education and household income on entrepreneurial growth aspirations, as well as the moderating effect of the IPR protection regime on these.

Real options are present in irreversible and risky investments where the individual has a possibility to infl uence the timing of the investment (Jacobs, 2007). Under uncertainty, the possibility to defer investment becomes a real option that has value for the entrepreneur (Kogut and Kulatilaka, 2001). This is characteristic of a situation in which an individual has discretion to decide whether or not to invest his/her education and household income into an entre-preneurial growth fi rm. Such resource and effort allocation decisions are heavily infl uenced by oppor-tunity costs relative to wage-earning positions (Campbell, 1992; Djankov, McLiesh, and Ramalho, 2006; Evans and Jovanovic, 1989). When the returns to this investment are uncertain, individuals will defer allocation of effort into entrepreneurship until such time that they believe entrepreneurship will offer superior compensation for the risks taken (O’Brien et al., 2003). An individual considering risks and returns will have several options available, including the option to defer allocation of effort and the option to abandon the pursuit, as well as the option to regulate the amount of effort invested in the pursuit of growth through the venture (McGrath, 1997). Although the value of these options will

depend on the quality of the individual’s human and fi nancial capital, the option value of deferring an action will increase as a function of external uncer-tainty (Crifo and Sami, 2008). Because IPR protec-tion has major infl uence on external uncertainty, it will infl uence how these two forms of capital are associated with an individual’s aspiration to grow an entrepreneurial venture.

Previous applications of real options theory on entrepreneurial behaviors have focused on either entry into or exit from entrepreneurship (McGrath, 1999; O’Brien et al., 2003). In this article, we extend this thinking to post-entry situations, recognizing that most entrepreneurial ventures are started on a part-time basis with the founder still holding another source of income (Autio, 2007). Thus, entry into entrepreneurship is a gradual process in which many crucial resource allocation decisions are made after the entry has already occurred (Reynolds, 2007). However, we also recognize that some of the perti-nent mechanisms operate through the selection of individuals into entrepreneurship, because of the enduring character of initial resource allocations. In the following section, we draw on real options logic to elaborate specifi c hypotheses.

Education, household income, and growth aspirations

From a utility-maximizing perspective, the decision to pursue an entrepreneurial venture is a resource allocation decision taken in the presence of oppor-tunity costs, as the individual needs to weigh poten-tial returns achieved through the entrepreneurial venture against returns obtainable through alterna-tive occupations (McGrath, 1999; O’Brien et al., 2003). Education is a valuable, inalienable resource (Davidsson and Honig, 2003; Shrader and Siegel, 2007; Wright et al., 2007): acquiring it demands time and money. Education increases an individual’s value in the job market, such that the individual’s job market value is roughly commensurate with the time and effort invested in education (Dunn and Holtz-Eakin, 2000; Jacobs, 2007). Because individ-uals can typically pursue only one full-time occupa-tion at a time, the opportunity cost of occupational choice increases with the level of education.

These characteristics of education suggest two reasons (from a utility-maximizing perspective) why an individual’s education should be positively asso-ciated with entrepreneurial growth aspirations (Jacobs, 2007). First, individuals aware of the job



market value of their education will require that the potential returns offered by a given entrepreneurial opportunity measure up to the job market value of their education (O’Brien et al., 2003). Second, once an entrepreneurial venture has been launched, the entrepreneur would work hard to offset the education-related opportunity cost of this occupa-tional choice (Jacobs, 2007). Thus, ex ante, a well-educated individual would demand higher returns from an entrepreneurial opportunity before choosing to pursue an entrepreneurial venture. This reinforces a positive association between an individual’s edu-cation and entrepreneurial growth aspirations. Post-entry, well-educated individuals would be pushed by opportunity costs to seek higher returns from their entrepreneurial ventures, again reinforcing a posi-tive association between an individual’s education and entrepreneurial growth aspirations. Put another way, post-entry entrepreneurs with greater invest-ment in education seek to justify their choice of start-up by realizing higher growth than others who have less invested in education.

The opportunity costs associated with allocation of human capital to entrepreneurship drive individu-als to demand higher-quality opportunities and increase their willingness to strenuously pursue those opportunities. As is widely recognized in the entrepreneurship literature, education enhances the ability of individuals to successfully pursue entre-preneurial opportunities (Shane and Venkataraman, 2000). Education enhances the individual’s cogni-tive ability to manage organizational growth, thereby enabling individuals to manage complexities involved with rapid organizational growth (Shane and Venkataraman, 2000). Through the process of obtaining formal education, individuals also acquire valuable social capital and contacts that can be lever-aged to mobilize resources for the pursuit of entre-preneurial growth opportunities (Gerber and Cheung, 2008; Stevens, Armstrong, and Arum, 2008). These aspects contribute to a higher growth self-effi cacy, which translates into higher growth aspirations. Summarizing, we hypothesize:

Hypothesis 1 (H1): An individual’s level of educa-tion will be positively associated with aspiration to grow the venture.

From a utility-maximizing perspective, an indi-vidual’s household income infl uences entrepreneurial growth aspirations in three ways. First, similar to education, household income increases perceived

opportunity costs by increasing an individual’s income expectations (e.g., McGrath, 1999; Smith and Powell, 1990). Similarly to highly educated individu-als, individuals from high-income households would place greater ex ante demands for the quality of entre-preneurial opportunities when choosing between alternative occupational pursuits. Reinforcing this mechanism, high-income households would also provide fertile environments for accessing high-quality opportunities, because the social connectivity associated with fi nancial wealth would enable indi-viduals from high-income households to see more entrepreneurial growth opportunities (Dunn and Holtz-Eakin, 2000). Second, high household income creates higher income expectations. Once the decision to start a new venture has been taken, individuals from high-income households would be more moti-vated to work hard to ensure that income. From a real options perspective, working hard to ensure success reduces downside risk, thereby increasing the value of early action (McGrath, 1997). Third, high-income households are better endowed with fi nancial resources. The option to tap venture capital to access resources is usually available for only the most prom-ising ventures (Wright et al., 2006). Financial capital inputs enhance the entrepreneur’s ability to acquire other resources—such as human and intellectual capital—necessary to pursue entrepreneurial growth (Evans and Jovanovic, 1989). Greater ability to acquire resources from resource markets should translate into faster growth expectations. Summarizing, we predict:

Hypothesis 2 (H2): An individual’s household income will be positively associated with aspira-tion to grow the venture.

Intellectual property protection and individual growth aspirations

Earlier, we argued that opportunity costs associated with high education and high household income would prompt individuals to look for higher-quality entrepreneurial opportunities prior to entry, to be more motivated to grow their ventures post-entry, and to be better equipped to succeed in this pursuit, once started. Next, we propose that these opportu-nity costs are infl uenced by the strength of a given country’s intellectual property protection regime. This effect occurs because of the way well-function-ing markets for technology—more broadly, markets for knowledge (Arora et al., 2001)—infl uence the



choices available for individuals who are making strategic resource allocation decisions concerning their alienable human capital, on the one hand, and inalienable human capital, on the other.

Education contributes to two distinct forms of human intellectual capital: inalienable and alienable (Moen, 2005). The individual’s cognitive ability and skills are inalienable: they are embedded in indi-viduals and, therefore, are naturally excludable and appropriable (Zucker, Darby, and Torero, 2002). The products of this ability and skills—i.e., the intel-lectual property produced by individuals—are alien-able: they can be separated from individuals and traded in the marketplace, e.g., by selling, licensing, trademarking, copyrighting, or franchising. Because one form of human intellectual capital (i.e., cogni-tive ability) is naturally excludable and appropriable whereas the other form is not (i.e., IP produced), these two forms are infl uenced differently by the country’s IPR protection regime.

Entrepreneurs who possess intellectual prop-erty—in the form of patentable technologies, copy-righted creative outputs such as new designs, or perhaps in the form of trademarked service concepts and consumer goods—have two options when con-sidering how to take advantage of their intellectual property (Teece, 1986). First, they may seek to produce and sell the good or service through their own fi rm. Second, they may use the market for knowledge to sell, license, or franchise their intel-lectual property for exploitation by someone else. When a country’s IPR protection regime is weak, its markets for knowledge will be defi cient (Arora et al., 2001). In such a situation, individuals cannot easily take advantage of the market for knowledge to sell, license, copyright, trademark, or franchise their intellectual property for exploitation by someone else. This concerns well-educated indi-viduals in particular, as the likelihood of the produc-tion of distinctive intellectual property increases as a function of an individual’s formal education. In weak IP regimes, the protections against misappro-priation are weak, which forces individuals who possess intellectual property to invest in production facilities and other complementary assets to take advantage of their creative outputs. The need to do so quickly is exacerbated by fear of misappropria-tion, lest competitors copy the innovative aspects of the new venture’s offering. Thus, in weak IPR regimes, well-educated individuals are pushed to grow their ventures organically in order to generate the required returns to their education.

In addition to pushing well-educated individuals to grow their ventures, weak IPR regimes may also inhibit less-educated individuals from growing their ventures. Weak IPR protection adds to external uncertainty affecting the venture, in the form of mis-appropriation threat. Formal education leads to skills that may be useful across a wide range of occupa-tions (Crifo and Sami, 2008). Well-educated indi-viduals who are forced to abandon their ventures may thus fi nd it easier than less-educated individuals to use their entrepreneurial experience in alternative employment (Lazear, 2005; Michelacci, 2003). In contrast, former entrepreneurs with little formal edu-cation may fi nd it diffi cult to fi nd an alternative occupation where the entrepreneurial experience is valued (O’Brien et al., 2003). This implies that the sunk cost of human capital is higher for less-educated individuals. This asymmetry in downside risks makes less-educated individuals more sensitive to external uncertainty and, thus, less willing to allo-cate substantial effort into growing the new venture.

In strong IPR protection regimes, these mecha-nisms work to opposite direction. For highly edu-cated individuals, a strong IPR regime will increase the value of the option to defer allocation of effort into the venture, as they are more likely than less educated individuals to possess tradeable intellec-tual property. Although uncertainty concerning mis-appropriation may be reduced with a strong IPR regime, other sources of external uncertainty remain. In this situation, a strong IPR regime will increase the discretion available to well educated individuals to defer their investment into growing the venture until external sources of uncertainty are reduced (Dixit, 1989). At the same time, individuals with alienable human capital may have alternative avenues for taking advantage of their intellectual property, as strong IPR protection regimes promote the functioning of markets for knowledge—for patents, copyrights, designs, and trademarks. In addition to growing their venture organically—a risky up-front investment with uncertain returns—such individuals may choose to leverage the market for technology by, e.g., licensing, franchising, or selling their intellectual property without fear of misappropriation (Shane, 2001).

Finally, strong IPR protection regimes also facili-tate industrial specialization (Jacobides, Knudsen, and Augier, 2006). A well-functioning IPR protec-tion regime fosters the creation of complex indus-trial value chains, where some fi rms specialize in knowledge creation and others may specialize in



manufacturing. This specialization creates niches where knowledge-intensive ventures may manage risk by specializing in knowledge production without investing in production facilities. Such specializa-tion represents, in effect, another valuable option for highly educated individuals to defer investment in organic growth, thereby mitigating both internal and external uncertainty.

In summary, well-functioning markets of technol-ogy associated with strong IPR protection regimes infl uence educated individuals’ resource allocation decisions by infl uencing the trade-offs associated with entrepreneurs’ decisions to exploit their human capital. Because the alienable and inalienable forms of human intellectual capital are infl uenced differ-ently by the country’s IPR protection regime, the relationship between education and growth aspira-tion will grow weaker in strong IPR protection regimes. This is not because educated individuals will be disincentivized to grow their ventures when the IPR protection regime is strong, but rather, because high human capital individuals will have more alternatives available for taking advantage of their human intellectual capital. Summarizing, we hypothesize:

Hypothesis 3 (H3): IPR regime moderates the positive relationship between education and growth aspirations such that the stronger the IPR regime, the weaker this relationship.

The same technical appropriability considerations suggest different moderating infl uences for the rela-tionship between household income and entrepre-neurial growth aspirations. Again, this is because of the way the national IPR protection regime facili-tates the functioning of markets for knowledge (Arora et al., 2001; Shane, 2002). When the markets for technology operate well (i.e., when the intellec-tual property protection regime is strong), individu-als from high-income households can use their fi nancial resources to buy the intellectual inputs (i.e., the IP) required to grow their ventures. Thus, in addition to exploiting their own human capital, high-income individuals can use their fi nancial resources to exploit the intellectual property produced by others. When the market for technology operates well, opportunities to pursue entrepreneurial growth ventures will increase for wealthy individuals because they will be better able to acquire the intel-lectual capital required to grow the venture. On the other hand, under conditions of weak IPR protec-

tion, the possibilities of high-income individuals doing so will be diminished. Summarizing, IPR pro-tection should have a positive moderating infl uence on the relationship between an individual’s house-hold income and growth aspiration. This is because of how a functioning market for technology has dif-ferent effects on individuals seeking to exploit their own human capital, on the one hand, and on indi-viduals seeking to exploit the intellectual capital produced by others, on the other. We, therefore, hypothesize:

Hypothesis 4 (H4): IPR regime moderates the positive relationship between personal wealth and growth aspirations such that the stronger the IPR regime, the stronger this relationship.

VARIABLES AND METHOD

To test the above hypotheses, we combined nine years of adult population survey data from the Global Entrepreneurship Monitor (GEM) survey to form an initial database of more than 902,000 inter-views in 53 countries with adult individuals from 18 to 64 years old (Reynolds et al., 2005). This data is summarized in Table 1. We combined GEM data with country-level data on IPR protection taken from the Index of Economic Freedom (IEF) dataset.

GEM identifi es three types of entrepreneurs: nascent, new (or early stage), and established. New entrepreneurs are owner-managers of entrepreneur-ial fi rms that have been in existence for less than 42 months. Because our analysis focused on the strate-gic decision to allocate one’s human and fi nancial resources in the presence of trade-offs, as well as on early motivations to grow the venture, we limit our analysis to new entrepreneurs. The career trade-offs faced by new entrepreneurs remain real, because the majority of them still have a job (Autio, 2007). In total, the GEM 2000 to 2008 dataset contained 33,279 new entrepreneurs.

Variables

The dependent variable measures the entrepreneur-ial growth aspirations of identifi ed new entrepre-neurs. Each individual was asked to estimate their expected number of employees within fi ve years’ time. Because our theory centers on trade-offs and opportunity costs associated with initial allocations of effort to new ventures, we argue that growth



aspirations provide a better test of our theory than realized growth. Our focus is on initial resource allo-cations to entrepreneurship by individuals. Growth aspiration refl ects a best guess, under uncertainty, regarding both expected and required success of the new ventures. Although our measure does not refl ect actual growth, and most guesses are likely to be optimistic, our measure provides a good refl ection of considerations driving strategic resource alloca-tions to entrepreneurship, as well as a good match with the conditions in which the real options logic is applicable.

The weighted average of expected employees was 11.18. A natural logarithm of expected jobs was

used after removing and resetting extreme cases. We also controlled for the number of current jobs within the venture.

The predictor variables in our analysis were educa-tion (primary, secondary, postsecondary, and gradu-ate experience1), household income (three tiers in national distribution—lowest, middle, and highest third2), and IPR protection from the Index of Economic Freedom database (index scale from 10 to a high of 100). As measured by the Index of Economic Freedom, the IPR protection variable combines various aspects

Table 1. Countries in the sample, adult-population prevalence of nascent and new entrepreneurs (unweighted)

Country Obs % nascent or new entreps

Country Obs % nascent or new entreps

Angola 1,491 23.9% Jordan 1,989 19.2%Argentina 15,578 13.6% Kazakhstan 2,000 9.2%Australia 10,230 10.2% Latvia 7,933 5.5%Austria 4,191 4.2% Macedonia 1,746 13.5%Belgium 22,352 3.3% Malaysia 2,005 11.5%Bolivia 1,879 30.0% Mexico 9,118 11.7%Bosnia & Herzegovina 1,586 8.8% Netherlands 20,197 5.1%Brazil 19,837 13.3% New Zealand 7,572 14.8%Canada 6,660 8.3% Norway 14,175 7.8%Chile 15,315 13.0% Peru 7,560 33.0%China (PR) 10,835 14.3% Philippines 2,000 21.3%Colombia 6,082 22.4% Poland 5,396 7.3%Croatia 12,778 7.7% Portugal 4,981 7.0%Czech Republic 1,628 7.4% Puerto Rico 1,830 2.7%Denmark 24,934 5.5% Romania 3,406 3.3%Dominican Republic 4,094 17.5% Russia 7,288 3.2%Ecuador 5,860 22.7% Serbia 3,580 7.2%Egypt 2,603 13.3% Singapore 19,212 5.6%Finland 24,538 5.1% Slovenia 17,116 4.5%France 14,089 4.1% South Africa 21,298 6.7%Germany 44,865 6.0% South Korea 7,530 13.4%Greece 11,970 7.0% Spain 134,888 6.4%Hong Kong 6,599 4.8% Sweden 36,805 3.6%Hungary 15,701 5.9% Switzerland 11,040 6.1%Iceland 13,417 11.2% Taiwan 1,977 4.4%India 12,368 12.1% Thailand 6,985 17.2%Indonesia 1,998 19.3% Turkey 7,217 5.4%Iran 3,119 9.2% Uganda 2,957 29.7%Ireland 15,327 7.4% UAE 2,857 6.9%Israel 10,875 5.9% United Kingdom 113,604 5.2%Italy 17,726 4.7% Uruguay 4,897 11.5%Jamaica 7,992 18.5% USA 27,168 10.8%Japan 15,689 2.8%

Total 902,533 7.8%

1 Coded as 1, 2, 3, and 4, respectively.2 Coded as 1, 2, and 3, respectively.



of the degree to which private property is protected in a given country, intellectual property rights are respected, and citizens are protected against extrale-gal seizure of property.

As individual-level control variables, we used the age of the individual in years; mean centered and squared term of age; and gender (1 = male, 2 = female). In addition, we controlled for the individu-al’s fear of failure, measured with the statement: ‘Fear of failure would prevent me from starting a new business’ (1 = yes). This statement provided an inverse proxy of self-effi cacy.

At the country level, we controlled the country’s GDP per capita (in thousands of U.S. dollars), the mean centered squared term of it so as to capture any curvilinear effects, as well as GDP change during the previous year, population size (in mil-lions), and population growth (Levie and Autio, 2008). We also controlled for transition economies (former centrally planned economies), because of their idiosyncratic economic history. Finally, we controlled for industry structure by using GEM’s index for established entrepreneurs (adult popula-tion prevalence rate of owner-managers in ventures more than 3.5 years old).

An individual’s entrepreneurial growth aspiration can be observed for only those individuals who fi rst self-select into entrepreneurship. Therefore, the dis-tribution of growth aspiration is left truncated, and it can be infl uenced by some of the same factors that infl uence the self-selection of individuals into entre-preneurship (Heckman, 1979). Therefore, we per-formed the analysis in two stages. In the fi rst stage, we performed a probit equation to predict the self-selection of individuals into entrepreneurship (Kyriazidou, 1997; Wooldridge, 1995). The residu-als from the selection equation were then used to compute an inverse Mill’s ratio, which was included as a control in the eventual regression equation pre-dicting growth aspiration.

Method

Our dataset was cross-sectional panel data, grouped by country and year. Thus, we had hierarchical and clustered data in which the assumption of independ-ence of observations was violated (Hofmann, Griffi n, and Gavin, 2000). Therefore, we used a generalized least squares (GLS) procedure with a random effects specifi cation to analyze the data (Rabe-Hesketh and Skrondal, 2005; Raudenbush, 1988). This specifi ca-tion allows regression coeffi cients and intercepts to

vary across countries, and it also enables more accu-rate tests of cross-level moderation effects (Martin et al., 2007). The regression model took the follow-ing form (Snijders and Bosker, 2004: 68–75):

GROASP

IPR GDPCAP

GDPCAP SQ POP

POPG

j j

j

=

+

+ +

+ +

γ

γ γ

γ γ

γ

00

01 02

03 04

05

_

RRO GDPCHG

TRANSITION HHINC

EDUC IPR E

i j

ij j

+ ++ +

+ ∗

γγ γ

γ γ

06

07 10

20 11 DDUC

IPR HHINC AGE

AGE SQ SEX

FE

ij

j ij ij

ij ij

+

∗ + +

+ +

γ γ

γ γ

γ

21 30

40 50

60

_

AARFAIL NOWJOB

INVMILLS U U x R

ij ij

ij j j i j ij

+ +

+ + +

⎛

⎝

⎜⎜⎜⎜⎜⎜

γ

γ70

80 0 1

⎜⎜⎜⎜⎜⎜⎜⎜⎜

⎞

⎠

⎟⎟⎟⎟⎟⎟⎟⎟⎟⎟⎟⎟⎟⎟

=∑j

n

1

where γ00 = intercept, γn0 = main effect coeffi cients of individual-level predictors, γ01 = main effect coef-fi cient of country-level predictor (IPR), γ02 to γ07 = main effect coeffi cients of country-level controls, γn0 = main effect coeffi cients of individual-level con-trols, and γn1 = main effect coeffi cients of cross-level interaction terms. The combination (U0j + U1jxij + Rij) represents the random part of the equation, where U0j and U1j are country-level residuals, Rij represents individual-level residuals, and xij represent individ-ual-level direct effects. The interaction terms were formed using standardized forms (grand means) of the interaction components to test the moderation effects (Hofmann, 1997; Hofmann and Gavin, 1998).

Our objective to examine cross-level moderating effects implied a four-step testing strategy (Hofmann et al., 2000). First, we verifi ed that we had meaning-ful between-group variance in the data. Second, we tested a random coeffi cient regression model to determine whether signifi cant variance resided in intercepts and slopes across year-country groups. This was a signifi cant precondition for testing Hypotheses 3–4. Third, we tested an intercepts-as-outcomes model to see if country-level appropriabil-ity conditions were statistically signifi cantly associated with the dependent variable. Fourth, we tested a slopes-as-outcomes model as a direct test of cross-level moderation effects. As a confi rmatory step, we performed a median split analysis by split-ting the data into weak IPR and strong IPR country groups on the basis of their index values of national-level IPR protection.



RESULTS

Tables 1 and 2 show sample descriptives and Table 3 shows the correlation matrix. A precondition for running a hierarchical linear model is that signifi cant between-group variance exists for the dependent variable (Bliese, 2000; Hofmann, 1997; Hofmann et al., 2000). We, therefore, performed an ANOVA with individual-level growth aspiration as the dependent variable and country group membership as the predictor. This test indicated signifi cant between-group variance within the data, with χ2(147) = 2 223.80 (p < 0.000). The intraclass correlation indicated that 9.7 percent of the total variance within the data resided between groups (95% confi dence interval: 8.1–11.3%). This is within the normal range (5–20%) that can be expected of grouped data

of this nature (Bliese, 2000). The ICC size suggests that the country-level variance was both nontrivial and highly signifi cant.

Next, we tested a random coeffi cient GLS model, using only level-1 variables as predictors. The analysis showed signifi cant variance in intercepts across year-country groups (τ00 = 0.054; χ2(8) = 2 745.54 (p < 0.000)). Also, the LR test indicated highly signifi cant between-group variance in slopes. Combined, these observations strongly supported the preconditions for testing Hypotheses 3–4. The tests also showed strong support for Hypotheses 1 and 2, with both education and household income strongly associated with entre-preneurial growth aspirations (Table 4).

Hypotheses 3–4 were tested using a slopes-as-outcomes model (Table 4, third column). The reduction of the log-restricted likelihood ratio is

Table 2. Sample descriptives (unweighted)

Individual-level variable Obs Mean Std. dev. Min Max

Expected jobs in fi ve years’ time 33,279 9.54 63.26 0 4,000Current jobs 33,279 8.26 119.77 0 8,500Age of respondent 902,533 40.48 12.90 18 64Gender (male = 1, female = 2) 902,350 1.53 0.50 1 2Fear of failure (1 = yes) 691,617 0.36 0.48 0 1Education index (4 = highest) 856,071 2.21 1.06 1 4Household income tier (3 = highest) 690,699 1.90 0.80 1 3

Country-level variable Obs Mean Std. dev. Min Max

IPR protection index (100 = highest) 897,123 72.75 20.42 10 90GDP per capita (1000 s of US$) 900,703 25,356.06 10,726.25 764.51 55,452.14Population size, millions 900,703 77.42 192.39 0.288 1,321.052Population growth, % 900,703 0.8% 0.0074 −1.5% 6.1%GDP change, % 900,703 3.6% 2.40 −10.9% 16.0%Established business owner-managers, %

of adult-age population901,775 6.3% 0.03 0.8% 21.5%

Table 3. Correlation matrix (grand correlations)

1 2 3 4 5 6 7 8

1 Age2 Age squared 0.03083 Gender (m = 1, f = 2) 0.0260 −0.02604 Education level −0.0789 −0.1018 −0.01245 Household income −0.0243 −0.0981 −0.0870 0.23536 Fear of failure −0.0028 −0.0353 0.0664 −0.0428 −0.05447 GDP per capita 0.0845 −0.0082 0.0084 0.1531 −0.0076 0.01568 GDP per cap squared −0.0133 0.0019 0.0070 0.0078 −0.0012 −0.0190 0.39609 IPR protection index 0.1057 −0.0177 0.0161 0.1215 0.0149 −0.0016 0.5266 −0.0261



statistically highly signifi cant (p < 0.001) over the model without interaction terms (second column). The moderation effect of IPR protection on educa-tion is negative and statistically signifi cant (p < 0.01), indicating that when the intellectual property protection was stronger, education was a weaker predictor of entrepreneurial growth aspirations. H3, therefore, received support in our data. We also observed a positive moderation effect of IPR on the household income-growth aspiration relationship (p < 0.01). When the IPR protection regime was

strong, household income was a stronger predictor of entrepreneurial growth aspirations. Therefore, H4 was supported.

We also observed several interesting effects for both country- and individual-level control variables. First, the inverse Mill’s ratio was shown as a statisti-cally signifi cant infl uence in all models, confi rming the importance of controlling for self-selection. Second, a country’s GDP per capita had a positive curvilinear association with individual-level growth aspirations. This pattern may be driven by the high

Table 4. Effects on entrepreneurial growth aspirations

Expected jobs in fi ve years (log) Coef. P > z Coef. P > z Coef. P > z

Selection controlInverse Mill’s ratio −1.16857*** −0.36871*** −0.33587***

Country-level controlsGDP per capita (ppp) 0.00002*** 0.00001*** 0.00001***GDP per capita (squared) −8.34E-10*** −4.16E-10* −3.78E-10*Population, millions −0.000087 −0.000096 −0.000090Population growth 10.5789*** 12.2363*** 11.6730***GDP change 0.0335*** 0.0371*** 0.0362***Established entrepreneurs rate −4.5337*** −2.6812*** −2.5371***Transition country dummy (1 = yes) 0.2402*** 0.0663 0.0595IPR protection index −0.0018 −0.0096

Individual-level controlsAge 0.00079 −0.00374*** −0.00375***Age (squared) −0.00004 −0.00008 −0.00010+Gender (m = 1, f = 2) −0.03715+ −0.20693*** −0.20960***Current jobs 0.00042*** 0.00042*** 0.00042***Fear of failure −0.12113*** −0.10976*** −0.10650***

Individual-level predictorsEducation (H1:+) 0.07112*** 0.06112***Household income (H2:+) 0.13254*** 0.12248***

Cross-level interactionsIPR * education (H3:−) −0.02413**IPR * household income (H4:+) 0.02980**_cons 3.1254 2.0455 1.9913LR test prob > chi2 0 0 0Number of obs 25,141 25,062 25,062Number of groups 272 270 270Obs per group: min 3 3 3avg 92.4 92.8 92.8max 970 970 970Prob > chi2 0.000 0.000 0.000Log restricted-likelihood −39,214.41 −39,001.63 −38,975.75

Note: ***p < 0.001; **p < 0.01; *p < 0.05; +p < 0.1.Two-tailed signifi cances, hypothesis tests one-tailed.Mixed-effects REML regression, GLS coeffi cients.



incidence of necessity-driven entrepreneurship in low-income economies, an emphasis on industrial scale-up in middle-income economies, and increas-ing specialization in high-income economies (Bosma et al., 2009). Third, population growth and GDP growth were positively associated with entrepre-neurial growth aspirations, probably indicating the effect of market growth on expected returns to entre-preneurship. The adult population prevalence of established entrepreneurs was negatively associated with entrepreneurial growth aspirations, perhaps refl ecting the effect of industry structure on entre-preneurial opportunities. Finally, transition economy dummy was positively associated with entrepreneur-ial growth aspirations when education, household income, and IPR protection were not present in the equation. This may indicate idiosyncratic conditions that are particularly infl uential on education effects in those economies, the populations of transition economies being generally well educated. Because of this, we reran all our analyses in a country sample that excluded transition economies. The fi ndings were not affected by this exclusion.

Finally, we performed a median split and per-formed separate regressions for strong IPR and weak IPR countries. These tests are shown in Table 5 and graphically illustrated in Figures 2 and 3. Consistent with the interaction effect, the regression coeffi cient for the education variable decreased from the value

of 0.111 in weak IPR countries to 0.05 in strong IPR countries. Thus, the effect of education on growth aspiration grew weaker as a function of the strength of a country’s IPR protection regime, but it remained positive and statistically signifi cant throughout. Also, the effect of household income on growth aspiration increased from the value of 0.122 in weak IPR countries to 0.160 in strong IPR countries. These patterns are consistent with the cross-level moderation analysis shown in Table 4. As such, the moderating effect appears particularly strong for education, as the value of the average GLS coeffi -cient more than doubled when moving from strong IPR to weak IPR countries. For household income, the effect of national-level IPR protection regime was smaller at 24 percent.

DISCUSSION AND CONCLUSIONS

One of the pertinent questions in the emerging agenda of strategic entrepreneurship research con-cerns the susceptibility of strategic entrepreneurial behaviors to institutional and cultural infl uences (Schendel and Hitt, 2007). The protection of intel-lectual property rights constitutes a particularly important institutional infl uence, because it directly infl uences the leakage of opportunities through imitation and, thus, the effi ciency with which the

Table 5. Regressions in strong- and weak-IPR countries

Expected jobs in fi ve years (log) Strong IPR regimes Weak IPR regimes coef.

Inverse Mill’s ratio −0.2849*** −0.4608***GDP per capita (ppp) 2.56E-07 9.88E-06*GDP per capita (squared) 3.20E-11 −5.05E-10+Population, millions 0.0002 −0.000038Population growth 13.7340*** 12.6423***GDP change 0.0219*** 0.0421***Established entrepreneurs rate −2.6009*** −2.8413***Transition country dummy (1 = yes) −0.2419*** 0.0910+Age −0.0056*** −0.0008Age (squared) 2.41E-05 −0.0001Gender (male = 1, female = 2) −0.2273*** −0.1691***Current jobs 0.0003*** 0.0013***Fear of failure −0.1251*** −0.1307***Education (H1:+) 0.0497*** 0.1112***Household income (H2:+) 0.1601*** 0.1216***Cons 1.8951 1.5940

Note: ***p < 0.001; **p < 0.01; *p < 0.05; +p < 0.1.Two-tailed signifi cances.



6.5

7.5

8.5

9.5

10.5

4321

Strong IPR regime

Weak IPR regime

7.5

8.5

9.5

10.5

321

Strong IPR regimeWeak IPR regime

Figure 2. Effect of education on growth aspirations in strong and weak IPR regimes

Figure 3. Effect of household income on growth aspirations in strong and weak IPR regimes

creation of competitive advantage can be combined with the pursuit of opportunity (Hitt et al., 2001). As Schendel and Hitt (2007) observed, nations differ in terms of their regimes of intellectual property pro-tection and, therefore, the sharing of profi ts amongst innovators, developers, users, and consumers. Thus, the protection of intellectual property is likely to have a direct infl uence on the allocation of effort into growth-oriented entrepreneurial ventures that seek

to combine opportunity pursuit with the creation of competitive advantage. In this article, our objective was to advance the understanding of how the protec-tion of intellectual property infl uences the allocation of effort into growth-oriented new ventures by individuals.

While this is one of the fi rst studies to demonstrate the effect of country-level infl uences on individual-level growth aspirations, country-level moderation



effects were weaker than the direct effect of individ-ual-level direct predictors of entrepreneurial growth aspirations. This can be seen by comparing the log likelihoods in Table 4: the biggest change was pro-duced by the introduction of an individual’s educa-tion and household income. The change produced by the introduction of cross-level interactions, while still signifi cant, was smaller. This pattern shows that, although contextual infl uences cannot be ignored, the individual remains the central agent in entrepre-neurial endeavors. This, as such, is consistent with the emphasis of the entrepreneurship research tradi-tion. Of individual-level characteristics, household income and gender clearly exhibited the strongest infl uences on entrepreneurial growth aspirations. The direct effect of education, while highly signifi -cant, was slightly less strong. The signifi cant infl u-ence of household income on growth aspirations may indicate that entrepreneurial growth opportuni-ties may be, to some extent, socially stratifi ed. Household income is an important determinant of one’s social class. High-income households may have better social connections and, therefore, they may get to see better growth opportunities. Another possible mechanism may concern resource acquisi-tion. It may be that high-income households are simply better able to act on the opportunities they see by mobilizing their household wealth for the pursuit of entrepreneurial growth. A high household income may also create an expectation for a certain lifestyle, the pursuit of which could then be refl ected on entrepreneurial growth aspirations.

Our study makes several contributions. Our model highlights the importance of initial resource alloca-tions and associated considerations in determining the strategic orientation of new entrepreneurial ven-tures. In contrast to macroeconomic perspectives in entrepreneurship research (e.g., Kirzner, 1997), our study shows that real options considerations matter: individuals do not react automatically to opportuni-ties, but rather they act with foresight and with giving due consideration to the likely outcomes of their actions. Furthermore, rather than reacting to isomorphic pressures (Aldrich and Fiol, 1994), our model portrays entrepreneurs as performing rational calculations in relation to objectively observable conditions, such as external uncertainty and expected payoffs. In addition to highlighting the rational fore-sight of entrepreneurs, our research also highlights the effect of initial resources on the strategic orienta-tions of new fi rms. This is an important considera-tion, given the tendency of early strategic orientations

to become imprinted in organizations over time (Hannan and Freeman, 1984; Sapienza et al., 2006). Our research shows that not only does the availabil-ity of external resources affect how entrepreneurial fi rms behave (Baker and Nelson, 2005), but also that the nature of initial resources committed to the new venture exercise a formative infl uence on how the fi rm will exploit them.

In this study, we applied real options logic to understand how differently qualifi ed individuals react to opportunities in different contexts. By so doing, we extended applications of real options logic to entrepreneurship research in general, and we also moved beyond traditional focus on entrepreneurial entries and exits (Crifo and Sami, 2008; McGrath, 1999; O’Brien et al., 2003). Our study shows that considerations of resource allocation trade-offs are not limited to pre-entry situations alone. The same trade-offs that infl uence an individual’s decision to enter or not continue to infl uence his/her behaviors in post-entry situations. It may well be that the most pertinent infl uences on new venture growth actually operate in post-entry situations where a new fi rm has already been created. This is a tantalizing possibility that should be considered further in economic analy-ses of new venture entries, exits, and growth.

As we argued earlier, the real options theory offers a parsimonious and salient perspective to understanding individual-level considerations that regulate allocation of effort to entrepreneurship. This logic does not have to rely on assumptions regarding individuals’ risk preferences or lifestyle choices. Our study shows that real options logic can be fruitfully applied to large, multi-country and multi-industry datasets to predict and demonstrate response patterns to contextual infl uences. So doing, our study contributes to the utility-maximizing per-spective to understanding entrepreneurial behaviors, a perspective that has not, thus far, been accorded the attention we think it deserves in entrepreneurship research (Douglas and Shepherd, 2000; Eisenhauer, 1995; O’Brien et al., 2003). Although the psychol-ogy of the entrepreneur undoubtedly matters, we take heart in having been able to demonstrate, using highly heterogeneous samples, contextual infl uences on individual entrepreneurial behaviors. In fact, although the effects may seem small, we think that it speaks for the salience of the effects that they have been demonstrated using representative, random samples of adult population individuals in 53 coun-tries. It is diffi cult to imagine a more heterogeneous sample for entrepreneurship research. As shown by



Figures 2 and 3, the patterns observed in the data are nontrivial, as the difference in the growth aspirations of well-educated individuals between weak and strong IPR regimes is nearly 30 percent. We should be able to observe much stronger differences when looking at individual sectors.

From a methodological perspective, our fi ndings support the often cited need for multilevel research designs to address the complexities on context-dependent entrepreneurial behaviors (Busenitz et al., 2003; Davidsson and Wiklund, 2001; Hitt et al., 2007). In addition to providing a way to reintroduce context into the study of important phenomena, mul-tilevel designs also provide a mechanism for cross-pollination among specialized subfi elds addressing different levels of research in the fi eld of manage-ment (Hitt et al., 2007). As Phan (2004: 620) observed: ‘One cannot fully understand, for example, opportunity recognition as an emergence phe-nomenon, without being sensitive to its higher contexts—culture, institutional arrangements, and political-economic exigencies.’ Study designs limited to a single level imply often unreasonable assumptions regarding, in particular, the homogene-ity of individual-level behaviors, as well as the inde-pendence of entrepreneurial decisions from the higher-level contexts in which those decisions are made (Klein, Dansereau, and Hall, 1994). This may give rise to erroneous empirical inferences, espe-cially in situations where higher-order contingencies moderate the effect of individual-level characteris-tics on individual-level behaviors (House, Rousseau, and Thomashunt et al., 1995; Klein and Kozlowski, 2000). Therefore, we suggest that future research on strategic entrepreneurial behaviors could be well advised to pay greater attention to the context within which those behaviors are observed.

This study is not without limitations. First, our measure of growth aspiration was based on expected employment within fi ve years. While better suited for the study of factors driving initial resource allo-cations into strategic entrepreneurship, most aspira-tions are likely to turn out optimistic. However, in our theoretical framework, data on eventual growth is not even necessary, as our interest is on factors that trigger resource allocations into strategic entre-preneurship. Second, we tested the effect of only one country-level moderating effect on strategic entre-preneurial behaviors—the strength of the national IPR regime. While IPR protection has been recog-nized as a central infl uence on strategic entrepre-neurship, other country-level infl uences such as the

national governance regime (e.g., rule of law, pre-dictability of regulations, regulations imposed upon fi rms), national culture, and national fi scal regime also exist. These should be explored in future research. Third, our theoretical framework has emphasized the rational aspects of the decision to allocate resources into strategic entrepreneurship. While we think this is a justifi ed decision given our focus on how IPR impacts the distribution of profi ts among different stakeholders, it is well known that entrepreneurs are also motivated by many other forces that have less to do with economic rationality. Finally, our theoretical framework has evoked both selection effects and behavioral effects for the cross-level moderation infl uence of IPR protection on the education (household income)-growth aspiration relationship. The dataset available for our analysis was cross-sectional panel data, which prevented us from providing a strict test between the two effects. Distinguishing between selection effects and behav-ioral effects has important consequences for policy, and future research should seek to address this important question.

CONCLUSION

In conclusion, our study has demonstrated that an individual’s context constitutes an important regula-tor of individual-level entrepreneurial behaviors by infl uencing the trade-offs associated with resource allocation decisions. Even though individual-level predictors are important, intellectual property pro-tection exercises an important moderating infl uence on the effect of an individual’s household income and education on growth aspirations. Thus far, entre-preneurship theory has been mostly preoccupied with one external infl uence on entrepreneurial behaviors—the distribution of knowledge regarding means and ends in socioeconomic systems (Companys and McMullen, 2007; Kirzner, 1997; Peter, 2008; Shane and Venkataraman, 2000). Our study has shown that individuals may not react simi-larly to opportunities in all contexts, but rather their reactions may be conditioned by the institutional context within which the individuals fi nd them-selves. In our model, the primary effect of context operated through its asymmetric effect on downside risks and upside returns for less- and more-educated individuals, as well as on upside returns of low- and high-household income individuals. Because of such effects, opportunity quality is not the sole infl uence



on the allocation of entrepreneurial effort by indi-viduals. Not only may differently qualifi ed individu-als react differently to the same opportunities, but similarly qualifi ed individuals may also react differ-ently to the same opportunity in different contexts. This aspect is often ignored in entrepreneurship research. We have shown that intellectual property protection encourages specialization among differ-ently qualifi ed individuals, thereby providing for greater entrepreneurial dynamism. We hope that our study will inspire further investigations into individual- and country-level determinants of strategic entrepreneurship.

ACKNOWLEDGEMENTS

The fi rst author acknowledges the support of EPSRC and QinetiQ to this research. We would like to thank seminar participants at the Babson Entrepreneurship Research Conference in Madrid, Spain, and the GEM Research Conference in Washington, D.C. We also thank Paola Criscuolo, Gerard George, Jonathan Levie, Paul D. Reynolds, David B. Audretsch, Karl Wennberg, and Matthew Cleevely for their comments. Finally, we thank the three anonymous referees for their insights that sig-nifi cantly infl uenced the formation of this article.

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Intellectual property protection and the formation of entrepreneurial growth aspirations

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