استعداد کارآفرینی و عملکرد سرمایه گذاری: یک تحقیق فراتحلیلی از شرکت های کوچک و متوسط

As the broad link between small and medium-sized firm activity and key policy goals such as employment or economic growth has become generally accepted, the conversation has focused on a more nuanced understanding of the entrepreneurial engines of economic activity. A significant body of research looking at antecedents to venture performance has identified that entrepreneurial talent variables account for meaningful differences in venture performance and that significant heterogeneity exists across performance measures. These are important issues for institutions and policy makers seeking to achieve specific economic goals (e.g., survival or growth of ventures, employment or revenue). Using meta-analysis, we integrate this work to view connections between aspects of entrepreneurial talent and different performance outcomes. Our investigation includes 50,045 firms (K of 183 studies) and summarizes 1002 observations of small and medium-sized firms. Analysis of these data yields an unexpectedly weak connection between education and performance. Furthermore, growth, scale (number of employees) and sales outcomes are significantly related to planning skills, while profit and other financial and qualitative measures are strongly connected with the network surrounding the firm founders. Moreover, we observe that entrepreneurial talent is more relevant in developing economies.

According to the Organisation for Economic Co-operation and Development (OECD) (2006), small and medium-sized enterprises (SMEs) represent over 95% of all businesses and account for 60–70% of all new jobs created in OECD member countries. Coming out of the recent recession, startups have historically provided a dominant engine of durable new job creation (see e.g., Stangler, 2009) and economic growth (see e.g., Foster, 2010). This emphasizes why SMEs are considered to be an economy's backbone in terms of employment as well as innovation (OECD, 2006). As institutions and policy makers have devoted effort and investment to the development of firms at the diminutive end of the spectrum (see e.g., Audretsch et al., 2009), so have academics devoted research attention to the connection with economic growth (e.g., Audretsch et al., 2007, Carree and Thurik, 2010, Naudé, 2011 and Schumpeter, 1976). Prior work motivates this paper, as scholars in the area clearly identify the supply and allocation of entrepreneurial talent in an economy as being central to its vitality (Baumol, 1990 and Baumol, 2010). Moreover, prior work suggests meaningful variance within the dependent level of firm performance outcomes (e.g., Chaganti and Schneer, 1994, Venkatraman and Ramanujam, 1985, Venkatraman and Ramanujam, 1986 and Zou et al., 2010). We expand on this analysis of entrepreneurship by bringing together empirical data on variance in the nature of entrepreneurial talent with variance in outcomes of the enterprises entrepreneurs lead (SMEs). From a policy perspective, a better understanding of which element of entrepreneurial talent is associated with which venture performance dimension is of utmost importance in the efficient deployment of scarce resources. If the connections were well understood, funds could be targeted to foster entrepreneurial talent aspects that have the highest impact on desired venture performance outcomes, since different outcome constructs (such as survival, growth, employment and profit) might not evenly relate to each other (see e.g., investigation of entrepreneurship and different outcomes on a macro-economic level by Nyström, 2008). Moreover, prior work suggests that cultural and economic context (Baumol, 1968) influence the availability and deployment of entrepreneurial talent (Zhang et al., 2010). Hence understanding the impact of these contextual factors on the entrepreneurial talent–SME performance relationship can also be beneficial for policy makers around the globe. Significant academic effort has generated an enormous cache of data that investigates how a variety of antecedent variables relates to different venture performance outcomes. We aggregate these data using meta-analysis. This systematic, evidence-based approach (Hunter and Schmidt, 2004, Lipsey and Wilson, 2001 and Rosenberg and Donald, 1995) seeks to identify elements of entrepreneurial talent that economic policy can influence to foster entrepreneurship and inform the macro-economic understanding of the entrepreneurship phenomenon (van Praag and Versloot, 2008). But while Baumol views the components of entrepreneurial talent as a black box of unaccounted variance (Baumol and Blinder, 2010), our meta-analysis aims to enhance understanding by piecing apart different aspects of entrepreneurial talent to determine their connection with different performance outcomes. Thus, our meta-analysis responds to the old saw about an economist being someone who worries about proving that “something that works in practice works in theory” (Baumol et al., 2007, p. 125) with an inductive approach to identifying policy implications around SME performance. Systematic reviews of previous research are important (e.g., Macpherson and Holt, 2007) and meta-analysis is of specific relevance to policy makers as a basis for addressing a key issue highlighted by Frese et al. (2012, p. 42): “There are, of course, public policies for fostering entrepreneurship in most countries but there is up to this point, relatively little evidence-based public policy.” While other science fields like medicine rely heavily on meta-analytic techniques to aggregate empirical results (Hunter and Schmidt, 2004), this powerful approach has only recently caught the attention of management researchers (Brinckmann et al., 2010, Dalton et al., 2003, Kirca et al., 2011, Read et al., 2009, Rosenbusch et al., 2011, Shea-Van Fossen et al., 2006, Song et al., 2008 and Unger et al., 2011). A number of previous meta-analyses in the management and entrepreneurship literature analyze the effect size of one specific antecedent derived from theory against performance (e.g., Unger et al. (2011) investigate the relationship between human capital and firm performance). But to the best of our knowledge, there is no integrated work of relevance to policy makers that seeks to bring together a variety of independent variables associated with entrepreneurial talent while at the same time unpacking the broad construct of performance. Our analysis organizes and summarizes these data so that different SME performance outcomes relevant to policy makers can be meaningfully examined against different entrepreneurial talent aspects that can be influenced by policy makers. Furthermore, we investigate the moderating effects of economic development and cultural attitude toward uncertainty on the entrepreneurial talent–SME performance relationship. This investigation reveals useful insights for policy makers seeking to influence the entrepreneurial landscape, as well as researchers seeking to understand the role of entrepreneurial talent in SME performance. Our unique view into the diverse dependent variables associated with SME performance begins to expose the various levers associated with firm scale (in number of employees) and sales versus financial performance (such as profit or aggregated financial measures) versus qualitative outcomes (such as survival or perceived success). While these categories reflect SME performance at a certain point in time, we also separate out performance specific to growth in order to contribute insights related to dynamic outcomes such as increase in employment or revenues. One of the results especially pertinent to policy economists and policy makers is that we clearly show that investment in human capital in the form of education – a fundamental input for many models of economic growth (e.g., Becker and Wößmann, 2009) – has a weak connection with SME performance, particularly in advanced economies. Therefore, from a policy perspective, we find limited justification for investing in general education as a route to economic growth via entrepreneurship. In contrast to education, we find that human capital derived from the network that surrounds the firm's founders has the most robust connection with profit, other financial measures and non-financial venture outcomes ranging from venture survival to perceived success. Furthermore, we find that activities focused on planning have a strong connection with firm scale, sales and growth. Our enquiry follows five main steps. First, we identify two categories of constructs (entrepreneurial talent and venture performance) from the academic literature. Second, we amass studies from 1990 to 2010 including correlates of different performance measures and entrepreneurial talent aspects, and third, we examine it using meta-analysis. Fourth, after analyzing the main effects, we investigate the moderating effects of economic context and cultural attitude toward uncertainty. We close with conclusions for policy makers looking to achieve certain goals and academics interested in the nature of performance and entrepreneurial talent.

While the quantitative results are presented in Table 3, Fig. 2 displays the main effects in a clustered bar chart to provide a graphical illustration summarizing the main findings of our work. The richness and breadth of these data offer many potential avenues for discussion and conclusions, but we focus our attention on five elements in particular.6.1. Moderating effects of economic development and uncertainty avoidance Our moderator analyses revealed that entrepreneurial talent is more strongly connected with performance in developing economies than in advanced economies. As this finding may encourage policy makers in developing countries to consider ways of enhancing the relevant entrepreneurial talents of individuals, we explore related research and possible underlying explanations. Carayannis and von Zedtwitz (2005) build on a similar premise, assuming that startup incubators are more valuable in less developed economies since their functionalities of bridging knowledge or increasing the access to different resources can have more impact than in already developed countries. The resource-based view offers insight into why this may be, starting with the assumption that entrepreneurial talent is unevenly distributed across individuals entering entrepreneurship (Barney, 1991). Compounding that effect, individual entrepreneurial talent is likely to vary more in developing than in advanced economies, owing to a higher and more consistent education level across developed economy populations (e.g., Lerner et al., 1997). Furthermore, in developing economies, more individuals may enter entrepreneurship out of necessity, a situation that changes with economic development (Kelley et al., 2012 and Venkataraman, 2004), adding to the heterogeneity of active entrepreneurial talent. As our results support these arguments of previous researchers, further efforts to unpack the mechanisms and causality underlying the relationship between entrepreneurial talent and performance in developing economies should be encouraged. Our finding that entrepreneurial talent is connected with performance in uncertainty-avoiding cultures adds to the literature in important ways. Previous research has focused on entrepreneurial entry, and at the macro and micro levels generally connects low uncertainty avoidance and entrepreneurial entry (Hayton et al., 2002), though results and explanations are equivocal (Wennekers et al., 2007). Similarly, at the individual level, previous research shows that across countries, entrepreneurs exhibit lower uncertainty avoidance than non-entrepreneurs (McGrath et al., 1992), and that investigations focusing on entrepreneurial cognition propose lower uncertainty avoidance is positively connected with entrepreneurial cognition (Busenitz and Lau, 1996). Work investigating uncertainty avoidance and performance outcomes has not paralleled that investigating entrepreneurial entry, and the contingent influence of cultural elements on entrepreneurial outcomes has been identified as an under-explored area (George and Zahra, 2002). As we establish the connection between uncertainty avoidance and performance in our data, we offer a speculation regarding the self-selection effects that might be at play, as a means of encouraging future research. It could be that in high uncertainty-avoiding cultures, individuals who are quite sure they have what it takes to be successful in building and managing a venture are ready to choose entrepreneurship with its inherent uncertainty over a secure and more predictable employment. This could contrast with cultures that present a lower level of uncertainty avoidance where individuals of all levels of entrepreneurial talent might just “try” entrepreneurship, with less reflection on whether they have the necessary talents to make their business successful. As these considerations are purely hypothetical, we call out for further research to explore the underlying mechanisms of how cultural context affects the entrepreneurial talent–performance relationship. 6.2. Different outcomes are connected with different entrepreneurial talent aspects Different firm performance outcomes are not necessarily correlated with each other (e.g., Chaganti and Schneer, 1994, Venkatraman and Ramanujam, 1985, Venkatraman and Ramanujam, 1986 and Zou et al., 2010) and theory often does not provide us with indications on how talent mechanisms differ with regard to various venture performance outcomes (e.g., human capital theory). In this paper, we are able to provide a contribution to theory by synthesizing a large volume of empirical work. Growth and firm size measures (scale in number of employees and sales) are predominantly tied to talents connected with planning – at least for SMEs of a certain size. However, in addition to planning, team size also presents a strong association with scale and sales, supporting the notion that greater management capacity better enables the kind of coordination that is necessary as firms get bigger (Penrose, 1959). Profit offers a stable connection with the entrepreneurial talent variable of network and to a lesser extent with experience and skills. In our analysis, the connection between planning and profit is not as robust as the connection between network and profit or experience and profit, as the various robustness tests showed a decrease in the significance level with regard to planning. If SMEs are considered an important vehicle in generating economic surplus, this finding suggests the importance of support for public policies that increase the stock of strong entrepreneurial networks and entrepreneurial experience in an economy. Venture profit is not only important for tax revenues but also for individuals considering entry into entrepreneurship according to rent-seeking theory (Baumol, 1990) and selfish motivation (Weitzel et al., 2010). This implies a case for policy interventions that invest in building or deepening the stock of entrepreneurial networks and entrepreneurial experience in a region or country, beyond promoting startups. This notion is consistent with literature on economic growth that highlights the contribution of different knowledge stocks to growth (Romer, 1990). Furthermore, we find that network has the highest correlation with the “other financials” performance category. This implies that some aspects of SME performance, ranging from financial alliance performance to initial public offering (IPO) and return on equity (ROE) may likely require a broader and more diverse cast of characters than the founders alone. We also observe the importance of clearly specifying the dependent variable. The connection between entrepreneurial talent and agglomerated performance measures such as “other financials” differs substantially from more narrow measures such as sales. For the qualitative performance category, network emerges as the entrepreneurial talent with the strongest connection. Our finding regarding qualitative measures and overall the finding that network is connected most strongly with three of the investigated performance outcomes are also in line with contemporary network research, which broadly shows positive network performance effects in the entrepreneurial context (Hoang and Antoncic, 2003). From a theoretical point of view, the four mechanisms of social networks in an inter-organizational context identified by Zaheer et al. (2010) provide an explanation as to why network has the strongest relationships with half of the tested performance outcomes. First, according to Zaheer et al.’s (2010) review, social networks are often considered a valuable resource offering access to additional (economic and non-economic) resources from which venture performance can benefit (e.g., Bourdieu, 1986, Nahapiet and Ghoshal, 1998 and Portes, 1998). Second, according to Zaheer et al. (2010), they are also a means of generating trusting relationships, which add to performance by reducing transaction costs (e.g., Wu and Leung, 2005). A third mechanism described by Zaheer et al. (2010) refers to inter-organizational networks being a source of power and control that are able to reduce or increase resource dependencies of a focal firm (Pfeffer and Salancik, 1978). The fourth mechanism identified by Zaheer et al. (2010) refers to the signaling effect that can arise from partnering with a high-status company (see e.g., Stuart et al., 1999). These findings related to network and venture performance imply that policy makers need to simplify and encourage networking for (potential) founders. For example, by increasing and institutionalizing mentorship programs in universities or governmental institutions in which an experienced founder acts as a mentor and provides advice on a regular basis to new or potential firm founders, founder networks could be enhanced and hence lead to better venture performance on various dimensions. Overall, two contributions are generated by our analysis. First, with these data, we are able to do more than demonstrate a differential correlation between outcome variables – we are able to show that entrepreneurial talent inputs associated with growth and firm size (scale in number of employees and sales) are different from those associated with performance outcomes such as profit, IPO and survival. This should further encourage researchers and policy makers to specify performance measures of interest, theorize more specifically with regard to specific dependent variables, and combine multiple performance measures with care. As enticing as it might be to combine performance variables, unpacking the objective function for both the founder and the policy maker will encourage more surgical, focused interventions that are more likely to generate the intended results. Second, we show that entrepreneurial talent is associated with growth, scale and sales, but to a lesser extent with financial performance outcomes such as profit. With these findings, we are able to add specificity to Penrose's (1959) theory of the growth of the firm, which argues that a key limitation to enabling organizational growth is the capability of the management team. Meanwhile, the entrepreneurial talent of the entrepreneur or the entrepreneurial team appears to be less important for profitability. This finding is consistent with the broader view of entrepreneurs creating artifacts, which are of value especially to themselves (Benz and Frey, 2008). To this point, we have indications that across the population, entrepreneurs work more hours (Ajayi-Obe and Parker, 2005) and make less money than their employed peers (Hamilton, 2000), while at the same time extracting a number of side-benefits (Carter, 2011). Given that we find substantial variance across the different investigated performance outcomes, we suspect that there will be even greater variance against an even broader slate of dependent variables such as satisfaction, happiness, social progress, financial freedom and making a difference in the world. These variables have begun to be (somewhat grudgingly) accepted in economic circles, largely as a result of political adoption in some European countries (Blanchflower and Oswald, 2011 and Stiglitz et al., 2010). So, as much as traditional economists might consider these objective functions irrational or subjective, there are indications that these variables may compose much of what the founder of a small firm is working to accomplish (e.g., Benz and Frey, 2008 and Blanchflower et al., 2001). We believe that a clearer understanding of these variables will facilitate a more fruitful relationship between venture founders and policy makers in shaping outcomes. 6.3. Contingency in planning and performance From a theoretical point of view, the positive relationship between planning and performance can be argued both from the perspectives of having the artifact (a plan) and from the learning that is derived from the process (Brews and Hunt, 1999, Brinckmann et al., 2010 and Delmar and Shane, 2003). Expanding this debate, prior research has indicated that planning leads to better venture performance (Delmar and Shane, 2003), a finding reinforced by a recent meta-analysis (Brinckmann et al., 2010). At the same time, other researchers questioned the immediate impact of business planning on performance, with work showing the planning to performance relationship to be largely superficial (Honig and Karlsson, 2004, Kirsch et al., 2009 and Powell, 1992). Another view suggests that planning is to some extent endogenous to cognitive ability and human capital (Frese et al., 2007), where planning leads to improved performance, but talented entrepreneurs would also be more likely to plan. Overall, our data suggests support of the planning school, as the effect size of planning to performance overall is higher than any of our other talent variables (effect size = 0.171; p < 0.001). However, two important caveats accompany this result. First, the difference to the next highest talent variable – network (effect size = 0.135, p < 0.001) – is not statistically significant (t-value = 0.889; two-tailed p = 0.374). Moreover, the average breadth of the 95% confidence intervals around the main effect between performance and planning is 0.134, nearly the size of the effect itself (0.171), and more than 30% larger than the next highest average confidence interval (team size = 0.090). This indicates meaningful endogeneity in the relationship between planning and performance, perhaps suggesting the presence of contextual moderators. Second, our results highlight the importance of specification of the dependent variable, as we find planning primarily associated with growth, scale and sales measures and to a substantially lesser extent with profitability and other financial measures. Moreover, as we see in a post hoc analysis (Section 5.3), this only applies to SMEs that have achieved a certain size. The contingencies associated in planning are also illustrated when our results are viewed with those of Brinckmann et al. (2010). Neither their bivariate moderation analysis nor their meta-regression indicated significant differences between the performance impact of having a plan and the planning process. We also coded studies according to whether they measure having a plan or planning (excluding studies where the construct was ambiguous). With our data we do find a significant difference (Q = 5.384; p = 0.020) with regard to the impact on overall performance of planning process (effect size = 0.183, p = 0.000) versus having a plan (effect size = 0.066, p = 0.011). We assume the differences are attributed to the study inclusion criteria of both meta-analyses, but more importantly, we suspect that these findings might be more attributable to a lack of precision in the underlying studies. One issue lies in the difficulty of distinguishing between idiosyncratic planning and process from having a plan. There is a big difference between an entrepreneur who writes a plan once at the beginning of the venture, files it away and only takes it out for discussions with financial investors, and an entrepreneur who has a plan, uses it as a strategic and operational tool and revises it on a constant basis. Hence, it is not surprising that studies investigating only the bare existence of a plan might fail to capture a large part of the variance around planning. There may also be an issue of measurement within underlying studies at play. Our review of the articles in our dataset that contained planning constructs revealed a meaningful difference. Of the 183 studies, 26% included independent variables measured as dichotomous (representing 36% of the firm population). But of the studies specific to planning, 42% of the firm population represented operationalized business planning as a dichotomous variable. This difference led us to not perform the correction for dichotomous variables (Hunter and Schmidt, 2004), as the correction would have unevenly biased our analyses toward studies measuring planning.7 It also leads us to the question of why planning should be measured as a dichotomous variable at all (the degree to which a plan is developed and/or employed feels important in understanding planning). Our conclusion on this topic is that consumers of academic research demand that scholars investigating planning address a number of key issues with rigorous empirical research prior to making their own plans based on academic investigations of business planning. These include (but are not limited to): (a) (How) is the business plan actually used in a small enterprise? (b) Are business planning and adaptation alternatives or orthogonal? (c) What is the causality between planning and scale? (d) Do experienced founders use business plans differentially from novices? (e) Is business planning in firms primarily a vestigial outcome of education? (f) When is a business plan a liability? We hope that until some clarity can be offered on these and other questions around business planning, policy makers and researchers alike will critically reflect on the application of planning in their specific venture context. 6.4. Re-educate education to foster entrepreneurial performance Some of our key findings relate to education. Education is distinctive in that it presents the lowest effect size against two of our measured dependent variables (education with sales: effect size = 0.011, p = 0.694, education with profit: effect size = −0.011, p = 0.739) and presents the lowest relationship with all performance measures aggregated of any of our talent variables in direct effects (effect size = 0.060, p < 0.001). This finding is also reflected in the meta-regression (see Table 6), indicating that after controlling for different performance outcomes, every talent variable analyzed in the models demonstrates a significantly stronger relationship to performance than education since education is the excluded variable in the regression models. This persistently weak connection between education and performance may be unexpected because according to the education–growth nexus, it is plausible that societies with more educated populations have more skilled labor forces and should grow faster ( Baumol et al., 2007), though Baumol et al. (2007) caution that for economic growth, education is not a sufficient but a necessary condition. One explanation for our finding could lie in the general empirical measurement of education, i.e., the number of years spent in an educational context. Rather, output (i.e., the quantity and quality) of what individuals actually accumulate as knowledge (see e.g., Unger et al., 2011) might provide a more accurate measure relating to economic growth. Further research needs to disentangle the education–growth nexus to provide additional policy implications to foster entrepreneurial talent. Conversely, it is possible to argue that education in general today is not meant to help people start and run small firms. And although we looked at education in general, taking Baumol's view, this result would be expected to remain substantially the same if we investigated only specific entrepreneurial education. Baumol stated that it may not be feasible to teach entrepreneurial talent in class (Baumol and Blinder, 2010) – at least not in the kind of educational settings that past classrooms have provided. To this, we strongly encourage the debate on why and suggest moving to how. Clearly, not every curriculum needs to promote entrepreneurship but – broadly speaking – education needs to provide people with the tools for what they want to do in the world. As evidenced by the amount of venture creation activity, one of the things that people want to do in the world is create firms to help themselves fulfill their goals, whatever these may be. The debate we seek to encourage is how education might be reshaped so that it provides a more positive connection to at least some of the objective and subjective functions entrepreneurs pursue when starting and running firms. Policy debates highlight the role of formal educational institutions in developing and socializing individuals ( Heckman, 2000), but education might also fulfill a more prominent role in fostering the development of firms. At present, early entrepreneurship education is presumed to occur largely in families. However, skill formation is a dynamic process in which early learning provides foundations for later development ( Heckman, 2000) and firms provide a strong source of skill development via on-the-job experience. Therefore, we suggest that there may be unrealized synergies between early (formal) education about entrepreneurship and later experiential skill acquisition in firms. Extant research and analyses summarized by Heckman (2000) point in general to underinvestment in the very young despite the benefits of learning synergies and much longer payoff horizons that such investments yield. We therefore encourage further research that takes a holistic view of the connections between entrepreneurship-promoting skill formation across the institutions of family, formal education and firms. 6.5. Theoretical conclusions for researchers For researchers, we raise three theoretical issues arising from our results: 6.5.1. Theory for predicting the relationships affecting performance Our results underline the importance of a fine-grained analysis of distinct performance outcomes. However, current theoretical research offers little basis for predicting or understanding the relative magnitude of the relationships between the various components of entrepreneurial talent and different indicators of performance (Unger et al., 2011). Therefore, a challenge – and opportunity – now exists for researchers to craft a cohesive and persuasive theory that predicts specific talent variables’ differential impact on certain measures of performance. 6.5.2. Conceptualizing talent mixes and profiles The findings of our study lend support to notions of the multidimensionality of entrepreneurial talent (Federici et al., 2008). This leads us to suggest that future research should develop theory about entrepreneurial talent that recognizes the complexity of talents, including interactions between different aspects of talent. The notion we prefer here is that of talent mixes, resulting in an overall talent profile. There is no necessary one-to-one mapping of talents to an overall profile; dissimilar talents may yield similar overall profiles. Some prior research has highlighted one aspect of talent mixes: the performance impact of generalists (“jack-of-all-trades,” balanced portfolio of talents) versus specialists (Hartog et al., 2010 and Lazear, 2005). Furthermore, work by Weitzel et al. (2010) has already begun to explore the possible impact of specific talents (creativity and business talent) on selfishness versus altruism, thus highlighting the importance of distinguishing between different talent mixes when considering the impact on an entrepreneur's goals and performance. 6.5.3. Incorporating venture profiles into talent research Lastly, there is an important modeling issue in the literature on entrepreneurial talent that needs to be addressed by researchers, which is that the talent–performance link is incomplete. Explicit in the economic research on entrepreneurial talent is the notion that persons can be (self) identified or revealed as entrepreneurs (Ferrante, 2005) and that these talents can be directed by appropriate economic policy into more or less productive avenues (Acemoglu, 1995, Baumol, 1990 and Murphy et al., 1991). Based on our findings, we argue that one paradox of profiling people in entrepreneur versus non-entrepreneurs is that care has to be taken to go far enough in profiling. Dividing a population of students (for example) into those with entrepreneurial potential and those without it fails to incorporate the issue of what kinds of ventures might work well for individuals with different talent profiles, contingent on their choice to start a venture. Instead of asking whether an individual has the “right stuff” to become an entrepreneur, the next stage of talent research must ask and answer the question, “What kind of venture would be good for a person to start, given their particular constellation of talents?” In other words, future research should develop models of the talent–performance relationship that incorporate a mediating role for the venture profile, whereby the venture is construed as a design task that incorporates the individual's talents, values and aspirations. Researchers may then be able to recommend how venture design can be leveraged to appreciate a person's talents, whatever they may be.