Explaining entrepreneurial behavior: dispositional personality traits, growth of personal entrepreneurial resources, and business idea generation.
Article Type:
Scientists (Behavior)
Obschonka, Martin
Silbereisen, Rainer K.
Schmitt-Rodermund, Eva
Pub Date:
Name: Career Development Quarterly Publisher: National Career Development Association Audience: Trade Format: Magazine/Journal Subject: Business; Human resources and labor relations Copyright: COPYRIGHT 2012 National Career Development Association ISSN: 0889-4019
Date: June, 2012 Source Volume: 60 Source Issue: 2
Computer Subject: Company growth
Product Code: 8520110 Scientists NAICS Code: 54171 Research and Development in the Physical, Engineering, and Life Sciences
Geographic Scope: Germany; New York Geographic Code: 4EUGE Germany; 1U2NY New York

Accession Number:
Full Text:
Applying a life-span approach of human development and using the example of science-based business idea generation, the authors used structural equation modeling to test a mediation model for predicting entrepreneurial behavior in a sample of German scientists (2 measurement Occasions; Time 1, N = 488). It was found that recalled early entrepreneurial competence in adolescence predicted business idea generation. This link was mediated by entrepreneurial human and social capital. Moreover, an entrepreneurial Big Five profile was associated with early entrepreneurial competence and predicted entrepreneurial human and social capital. Results underscore the relevance of the long-neglected developmental approach to entrepreneurship.

Keywords: entrepreneurship, opportunity recognition, personality, Big Five, competence growth in adolescence

Across the globe, the world of work is changing rapidly. Economic, social, and technological changes bring new demands but also opportunities for individuals' careers (Silbereisen & Chen, 2010). One way to proactively cope with those demands and to utilize the new possibilities is through entrepreneurship, that is, starting one's own business. Indeed, Hisrich, Langan-Fox, and Grant (2007) reported that entrepreneurship is a worldwide phenomenon that is on the rise (see also Mahbubani, 2008).

The core of entrepreneurship represents the innovative business) idea, defined by Grandi and Grimaldi (2005,. p. 826) as "the complex of products/services, knowledge, competencies, market, and technologies that are necessary to run a business" (see also Ardichvili, Cardozo, & Ray, 2003). Shane and Venkataraman (2000) defined the field of entrepreneurship research as the study of "how, by whom, and with what effects opportunities to create future goods and services are discovered, evaluated, and exploited" (p. 218). As Audretsch (2007) emphasized, not only is the success of a new venture rooted in the quality, newness, and potential of its business idea, but the success of whole entrepreneurial societies depends on the generation (and exploitation) of innovative business ideas.

Why do some individuals engage in the development of a business idea whereas others do not? To understand entrepreneurial behavior, entrepreneurship research traditionally focused on personality traits (Rauch & Frese, 2007). In contrast, vocational development in the context of entrepreneurship is an understudied field of research, and previous studies have neglected to explore the process through which personality traits could channel a person's vocational development toward entrepreneurship. This process may start early in life given that vocational development is considered to begin in childhood (Hartung, Pollen., & Vondracek, 2005). Likewise, modern personality psychology emphasizes the relevance of a life-span approach when studying the effect of personality traits. For example, McAdams and Pals (2006) assumed that personality is expressed as an evolving pattern of dispositional traits, characteristic adaptations (e.g., competencies), and personal life narratives. Indeed, Schmitt-Rodermund (2007) and Zhang and Arvey (2009) found adults' entrepreneurship to be linked with the interplay between personality traits and characteristic adaptations (e.g., age-appropriate entrepreneurial competence in adolescence) from early developmental stages forward.

In the present study, we examined adults' engagement in business idea generation from a life-span perspective. Targeting the evolving pattern of dispositional personality traits and characteristic adaptations across adolescence and adulthood, we developed and tested a path model using the example of science-based business idea generation by researchers. We chose this approach because, in today's knowledge-based economies, competitive advantage comes in large part from innovations. Audretsch (2007) stressed the fundamental role of innovative entrepreneurship, that is, the entrepreneurial exploitation of new knowledge generated in research institutions, for job creation and macroeconomic growth (see also Grandi & Grimaldi, 2005). However, given the tacit character of new research knowledge, it often requires scientists' active involvement in marketing their own research (Shane, 2004). Taken together, investigating researchers' business idea generation targets both a prototypical example of innovative entrepreneurship and an important feature (marketing academia's research) of what Audretsch (2007) called the entrepreneurial society.


Consistent with general trait approaches of career choice (Holland, 1997), McClelland (1961) suggested almost 40 years ago that personality traits explain the engagement in entrepreneurship. This view received broad empirical support with respect to both specific traits (e.g., need for achievement or risk taking) and broad traits such as the Big Five (Rauch & Frese, 2007). (The Big Five personality traits--extraversion, openness, conscientiousness, agreeableness, and neuroticism--are widely recognized as the leading universal, cross-culturally valid, minimal model of personality.) Whereas entrepreneurship studies usually investigated relationships between a person's single traits and entrepreneurship, Schmitt-Rodermund (2004, 2007) suggested looking at the trait structure within the person. She showed that a Big Five profile characterized as high in extraversion, conscientiousness, and openness and low in agreeableness and neuroticism relates to entrepreneurship. In the present study, such an entrepreneurial Big Five profile was thus expected to predict business idea generation (Hypothesis 1).

With respect to the question of how dispositional traits affect entrepreneurial activity, Schmitt-Rodermund (2004, 2007) further suggested considering early entrepreneurial competence in adolescence (early leadership as well as inventive and commercial activities). She argued that an entrepreneurial trait profile may channel individuals into an entrepreneurial career because of the stimulation of such early competencies. Empirical support for this notion comes from prospective life-span research (Schmitt-Rodermund, 2007) as well as from retrospective life-span studies (Obschonka, Silbereisen, & Schmitt-Rodermund, 2010; Schmitt-Rodermund, 2004). We thus expected that early entrepreneurial competence in adolescence would predict business idea generation in adulthood (Hypothesis 2) and that an entrepreneurial Big Five profile is associated with early entrepreneurial competence (Hypothesis 3). With regard to the measurement of both these constructs, it is important to note that we assessed participants' Big Five structure as current data in adulthood and early entrepreneurial competence as retrospective data. Although Caspi, Roberts, and Shiner (2005) showed that dispositional traits are relatively stable over time, we did not model a directed path from the trait profile to early competence but left this as a covariation.

Besides the role of financial capital, modern. entrepreneurship research emphasizes the importance of a person's human and social capital for his or her engagement in entrepreneurial activity (Davidsson & Honig, 2003; Kim & Aldrich, 2005). Davidsson (2006) argued that human and social capital are among the most important proximal predictors of entrepreneurial activity. Entrepreneurial human capital refers, for instance, to a person's business skills or entrepreneurial experience, whereas entrepreneurial social capital describes the provision of entrepreneurial resources by social networks. Such human and social capital in adulthood, in turn, may be the result of both growth in competence (Masten, Desjardins, McCormick, Kuo, & Long, 2010; Spencer & Spencer, 1993) and the expression of personality traits (Baum & Locke, 2004). Accordingly, we expected entrepreneurial human and social capital in adulthood to mediate both the link between personality and business idea generation (Hypothesis 4) and the link between early entrepreneurial competence in adolescence and business idea generation (Hypothesis 5).


The present study is part of the collaborative interdisciplinary research project called the Thuringian Founder Study (Thuringer Grunder Studie), which examines innovative entrepreneurship in the Federal State of Thuringia, Germany, from the perspective of economics and developmental psychology. This project applies a process perspective by studying the different stages of the business-founding process separately. In doing so, the project members conducted (a) a potential entrepreneurs survey, (b) a nascent founders survey (persons who were currently founding a new business), and (c) a founders survey (examination of business performance within the first 3 business years of a newly founded venture). In this article, we present data from the potential entrepreneurs survey. Here, scientists were surveyed via an online questionnaire on two measurement occasions. On the first measurement occasion in June 2008 (Time 1 [T1]), data on personality as well as human and social capital were collected as concurrent data. In addition, we assessed early entrepreneurial competence in adolescence retrospectively. Finally, the second measurement occasion in December 2009 (Time 2 [T2]) targeted the behavior of business idea generation between T1 and T2.


The database drew from a list of Internet homepages of all research institutions (e.g., universities, Max Planck Institutes, or Fraunhofer Institutes) in the German Federal State of Thuringia, which has a legacy of academic entrepreneurship (e.g., the founding of the optical lens manufactory Carl Zeiss in the city of Jena). All available e-mail addresses of scientists working there were collected (4,638 entries), and then a random subsample of 2,319 e-mail addresses was selected for the survey. At T1, 554 participants sent back completed online questionnaires (response rate of 23.9%; reminder e-mails were used). Because this study focused on scientists' marketing of their own research, we excluded participants who reported that they do not conduct any research., so that the final T1 sample consisted of 488 scientists.

On average, these participants were 38.6 years old (SD = 11.16, range = 23-68) and male (69.7%). About two thirds (66.3%) worked in a university, 26.0% worked in a nonuniversity research institution, and 9.8% worked in a university of applied science (Fachhochschule). More than two thirds (72.0%) were research associates, 17.6% were professors or university lecturers, and 10.4% reported another field of activity, for example, project-related specialists. With regard to the type of engagement in research, 54.1% described their work as applied science and 45.9% as basic science. The majority (52.6%) worked in the field of natural science; 29.7% worked in engineering; and 17.7% worked in economics, law, or social science. Official statistics on scientists in Germany (Statistisches Bundesamt, 2008) suggest that this survey sample is representative in terms of age, gender, and academic rank.


The questionnaire for the potential entrepreneurs survey comprised items on scientists' work situation and their individual characteristics (e.g., sociodemographics, personality traits, and entrepreneurial attitudes, experiences, networks, and intentions). We pilot tested and optimized this questionnaire and the data collection procedure by conducting an online survey of an independent sample of 133 scientists employed in universities and nonuniversity research institutions (e.g., Max Planck Institutes) in the Federal State of Saxony, Germany. Among these respondents were researchers of different occupational status (e.g., professors) and from different scientific disciplines (e.g., physics and engineering). The most important change we made according to respondents' feedback was to shorten the questionnaire (many respondents complained about the length of the questionnaire). Given that a central focus of the Thuringian Founder Study was on personality and adolescent competence, we decided not to change or shorten the complex and well-established measures we had chosen for these two constructs (with a total number of 68 items) but to consider possible one-item measures (instead of complex scales) when assessing other constructs (e.g., scientists' current entrepreneurial human and social capital).

Entrepreneurial personality profile. Using a well-validated German Big Five questionnaire by Ostendorf (1990), we asked participants to describe their personality in general by means of 45 bipolar items (nine items for each of the following five traits) with answer categories ranging from 0 to 5: agreeableness (e.g., "good-natured vs. cranky"; M = 3.20, Si) = 0.50, a = .73); conscientiousness (e.g., "lazy vs. diligent"; M = 3.37, SD = 0.61, a = .81); extraversion (e.g., "uncommunicative vs. talkative"; M = 2.88, SD = 0.69, a = .78); neuroticism (e.g., "vulnerable vs. robust"; M = 1.71, SD = 0.65, a = .85); and openness (e.g., "conventional vs. inventive"; M = 3.17, SD = 0.60, a = .73). Applying Schmitt-Rodermund's (2004, 2007) reference type of an entrepreneurial personality profile (the highest possible score in extraversion, conscientiousness, and openness and the lowest possible score in agreeableness and neuroticism), we then calculated an index for an individual's match with this reference type. Each person's squared differences between the reference values and the personal values on each of the five scales were first calculated. For example, for a person with the score 3 in neuroticism, the squared difference was 9 (because the reference value was 0). Then the five squared differences were summed for each person, and the algebraic sign of this sum was reversed (e.g., a value of 5 became 5), resulting in the final variable entrepreneurial personality profile with a mean of 24.53 (SD = 7.31).

Early entrepreneurial competencies in adolescence. Drawing from measures of adolescent competence in past entrepreneurship studies (Schmitt-Rodermund, 2004, 2007), we assessed early inventions, leadership, and early commercial activities to capture age - appropriate entrepreneurial competencies in adolescence. Because these data were collected retrospectively, we used the mnemonic technique of memory anchors. Before the sets of items on early behaviors were stated, we asked participants to "Think back to the time when you were 14 or 15 years old. This was probably the time when you were in the eighth or ninth grade and your 'Jugendweihe' or confirmation took place" (ceremonies in which 14-year-olds are given adult social status in Germany). Early leadership in adolescence was measured by means of a checklist consisting of six dichotomous items that asked for leadership roles at age 14 or 15 in class (e.g., class spokesman), in school (e.g., school magazine), in a club (e.g., treasurer), in a youth organization (e.g., scout), in a sports team (e.g., team captain), and other important responsibilities in leisure time (e.g., band leader), for example, "Did you have important responsibilities in your classroom (e.g., class spokesperson)?" (0 = no, 1 = yes). The number of positive answers was summed into an index of leadership experience (M = 1.42, SD = 1.32). Early inventive behavior in adolescence was measured with a 14-item scale that targeted inventive behavior during out-of-school leisure time at age 14 or 15. Each item focused on a specific domain of leisure activities (i.e., music, writing, painting, technical constructions, repair work, woodwork, cooking, handicrafts, gardening, magic, chemical experiments, new games, decorative work, building something), for example, "How often did you construct new technical things (e.g., metal construction kit, soldering, wiring)?"; Likert scale (1 = never, 5 = very often), M = 2.28, SD = 0.59, a = .73. Early commercial activities in adolescence was measured by a three-item scale on age-related selling activities during leisure time (i.e., trading things with friends, thinking about things that could sell well, selling things) at age 14 or 15, for example, "How often did you sell things (e.g., to friends)?"; Likert scale (1 = never, 5 = very often), M = 1.82, SD = 0.77, a = .68.

Entrepreneurial human capital. Human capital comprises a person's knowledge, experiences, and skills. In the context of entrepreneurship, one of the most widely studied and well-established human capital indicators is entrepreneurial experience (Davidsson & Honig, 2003). This variable has proved its relevance in the prediction of entrepreneurial behavior in numerous studies. Moreover, it is argued that prior entrepreneurial exposure also promotes other aspects of a person's entrepreneurial human capital (e.g., skills and knowledge) through learning processes. We thus assessed human capital by focusing on prior experience, using the item, "I have already gained considerable experience with the development of business ideas"; Likert scale (1 = not at all correct, 5 = totally correct), M = 1.76, SD = 1.04.

Entrepreneurial social capital. As with human capital, a person's social capital can be assessed along different dimensions. For example, one can differentiate between weak ties (e.g., acquaintances) and strong ties (e.g., family members). We decided to focus on weak ties because this type of network is particularly relevant for successful entrepreneurship (Davidsson & Honig, 2003). We used the item, "I have many business contacts/contacts with research partners in industry"; Likert scale (1 = no. 5 = vest M = 2.32, SD = 1.20.

Business idea generation. At T2 (December 2009), we were able to collect follow-up data from 200 of the 488 T1 participants. Here, we asked respondents whether they had pursued entrepreneurship since T1, using the item, "Since the last survey in June 2008, did you participate in the development of a business idea to commercialize your research?" (no: n = 154; yes, alone: n = 4; yes, together with others: n = 42). Against the backdrop of the global financial and economic crises that emerged between T1 and T2, we also asked the 154 respondents who did not engage in the development of a business idea whether they had to postpone an intended engagement because of external conditions (no: n = 125; yes: n = 29). These two items from T2 were then combined into the variable business idea generation (0 = no behavior shown and no postponement, 1 = no behavior shown, but behavior was intended and had to be postponed, 2 = behavior was shown, either alone or together with others; M = 0.61, SD = 0.84). Such an index of entrepreneurial behavior thus takes into account both the relevance of entrepreneurial intentions for entrepreneurial behavior (Krueger, Reilly, & Carsrud, 2000) and contextual barriers preventing individuals from actually engaging in intended entrepreneurial behavior (Shane, 2004).

Control variables. Following Davidsson and Honig (2003), we controlled our analyses for age and gender (0 = male, 1 = female).


To test the hypotheses, we utilized structural equation modeling using AMOS 7.0 (Arbuckle, 2006). Note that there was substantial attrition (59.0%) from T1 to T2. With regard to the T1 variables, participants who answered the follow-up questionnaire were younger on average than those who did not, t(458) = 2.42, p < .05. In view of this attrition, we conducted our analyses using the full information maximum likelihood method (which is implemented in AMOS; Arbuckle, 2006). This is the recommended strategy to deal with such missing data, even when the attrition rate is as high as in the present study (see Lovden, Ghisletta, & Lindenberger, 2005). Because the full information maximum likelihood method tests the hypothesized model on the basis of all available data points in the data set (without excluding participants), our model testing refers to the full sample (N = 488). Moreover, such a maximum likelihood method is rather robust when testing structural equation models with an ordinal dependent variable (as was the case in our analysis). For example, Muthen and Kaplan (1985) argued that "normal theory estimators [such as maximum likelihood estimators] perform quite well even with ordered categorical and moderately skewed/kurtotic variables, at least when the sample size is not small" (p. 187). According to Kline (2005), our sample size (N= 488) can be considered as relatively large.

In Table 1 we present the zero-order correlations between the variables. Although in the expected direction, the correlation between personality and business idea generation did not reach significance., and this was also the case after controlling for age and gender and using the full information maximum likelihood method via AMOS.

In a first step of the analysis, we tested direct effects of an entrepreneurial personality profile and early entrepreneurial competence (assessed as a latent construct) on business idea creation (see Figure 1). We controlled all effects for age and gender. For the model to achieve an acceptable fit, we included correlations between age on the one side and error terms associated with two indicators of early competence (i.e., inventions and leadership) on the other side. The final model then fit the data well, [x.sup.2] (6) = 4.55, p = .603, comparative fit index (CFI) = 1.000, root mean square error of approximation (RMSEA) = .000. Whereas Hypothesis 1 was not supported (an entrepreneurial personality profile had no effect on business idea creation), Hypothesis 2 was supported, because early entrepreneurial competence positively predicted entrepreneurial behavior. Finally, the personality profile and early competence correlated positively, supporting Hypothesis 3. In terms of effect size ([R.sup.2]), the model accounted for 13% of variance in business idea generation, which can be considered a medium effect suggestive of practical relevance (Cohen, 1988).

In a second step, we introduced entrepreneurial human and social capital as mediators into the model to test Hypotheses 4 and 5. Again, all effects were controlled for age and gender, and correlations between age and two error terms were included (as explained earlier). This model, illustrated in Figure 1, achieved an acceptable fit, [x.sup.2] (10) = 11.88, p= .293, CFI = .996, RMSEA = .020. In line with our expectations, both an entrepreneurial personality profile and early entrepreneurial competence positively predicted human and social capital, and human and social capital in turn positively predicted business idea generation. The explained variances (10) were 23% for human capital, 22% for social capital, and 21% for business idea generation, which, according to Cohen (1988), indicate large effects suggestive of significant practical relevance. Although an entrepreneurial personality profile had the expected indirect effect via human and social capital, Hypothesis 4, regarding a mediation effect of human and social capital between personality and business idea generation, was however not supported owing to the insignificant direct effect of personality (MacKinnon, Fairchild, & Fritz, 2007).

Finally, following Holmbeck (1997), we used a chi-square comparison test as a strict test for Hypothesis 5 (mediation effect between early competence and business idea generation). We tested the model shown in Figure 1 against another model in which the path from early competence to business idea generation was set to zero. As a result, the two models did not differ significantly in their fit, [DELTA] [x.sup.2] (1) = 2.45, p = .12, which confirmed that the effect of early competence on business idea generation was indeed mediated by human and social capital. Thus, Hypothesis 5 was supported. Note that all results from model testing in this study were robust when considering curvilinear instead of linear age effects (using a quadratic term).


Utilizing both retrospective and prospective data, we examined the pattern of personality traits and characteristic adaptations across adolescence and adulthood to understand adults' engagement in innovative entrepreneurship. With respect to entrepreneurial behavior, we focused on science-based business idea generation, thereby referring to economically valuable innovations (Audretsch, 2007; Shane, 2004).


Against the backdrop of research on personality psychology (McAdams & Pals, 2006) as well as on vocational development in general (Hartung et al., 2005) and in the specific context of entrepreneurship (Schmitt-Rodermund, 2007; Zhang & Arvey, 2009), our overall expectation was that personality traits channel a person's vocational development toward entrepreneurship from early developmental stages on. Following Schmitt-Rodermund (2004, 2007), we investigated an entrepreneurial Big Five profile. Although the results on adolescent competence are retrospective in nature, our two empirical path models (see Figure 1) together indicate that an entrepreneurial Big Five profile has an indirect effect on entrepreneurial activity via growth of personal entrepreneurial resources across adolescence and adulthood. Thus, our results are much in line with our overall expectations.

The only assumption in our study that was not supported reters to Hypotheses 1 and 4: An entrepreneurial Big Five profile was not significantly associated with entrepreneurial behavior (see Table 1 and Figure 1). This may be due to the relatively short time frame (1.5 years) between the two measurement occasions within which entrepreneurial activity may have occurred. For example, Schmitt-Rodermund (2007) examined a much longer career period (23 years) and found a significant link between such a Big Five profile and entrepreneurial activity.

As expected, early entrepreneurial competence in adolescence directly predicted entrepreneurial behavior (Hypothesis 2; see Figure 1), which underscores the relevance of adolescent competence for adults' entrepreneurship. Moreover, consistent with past entrepreneurship studies on adolescent samples (Schmitt-Rodermund, 2004) and adult samples (Baum & Locke, 2004; Obschonka et al., 2010), the Big Five profile appeared to be associated with personal entrepreneurial resources in adolescence (early entrepreneurial competence; Hypothesis 3) and in adulthood (entrepreneurial human and social capital; Hypothesis 4). Finally, consistent with more general research on work competence growth across the life span (see Masten et al., 2010), early entrepreneurial competence in adolescence appeared to be associated with entrepreneurial human and social capital in adulthood (Hypothesis 5), independent of the trait profile. Thus, early competence begets subsequent competence here, and, in line with personality theory and related findings (McAdams & Pals, 2006; Roberts, Caspi, & Moffitt, 2003), dispositional personality traits may stimulate early entrepreneurial competence, which then, according to our mediation results (Hypothesis 5), exerts its effect on subsequent entrepreneurial activity in adulthood via adult work resources relevant for entrepreneurship.

The effect sizes ([R.sup.2]) in our analyses, which ranged from medium to large, compare well with the effects detected in related prior research (Schmitt-Rodermund, 2004, 2007) and are suggestive of substantial practical relevance. We see at least two major implications of our study. The first refers to early entrepreneurship education, which has become a hot topic among today's policy makers aiming to better prepare adolescents for a future world of work that increasingly requires entrepreneurial thinking and acting (World Economic Forum, 2009). Together with past findings on contextual stimulation of early entrepreneurial competence (Schmitt-Rodermund, 2004, 2007), our results increase our confidence concerning the usefulness of early educational measures that target early competencies, such as adolescent leadership, creativity, and commercial activities. These measures may particularly focus on adolescents who score low in an entrepreneurial Big Five profile, as a growing body of studies indicates that they are somewhat disadvantaged in the growth of personal entrepreneurial resources across adolescence and adulthood.

The second major implication refers to the field of career counseling. Here, our results indicate that advice for or against an entrepreneurial career choice may take into account both the developmental aspect of competence growth and the individual Big Five profile. For example, adolescents who are interested in becoming entrepreneurs, but who lack early entrepreneurial competence and/or an entrepreneurial Big Five profile, may be advised either to engage in specific training that promotes relevant early competencies or to change their career planning. In turn, adolescents who exhibit the early competencies and/or an entrepreneurial Big Five profile, and who seek help in making adaptive career choices, could be encouraged to take entrepreneurship into account. The same advice may also apply in career counseling for adults. Note that Schmitt-Rodermund (2004) also found that those who become an entrepreneur and who exhibit early competence growth and/or an entrepreneurial Big Five profile are better prepared to be successful entrepreneurs.

This study has several limitations. It is clear that memories of early characteristics are subject to recall bias. We thus focused on clearly definable information regarding adolescent behavior (rather than requesting evaluations) and used memory anchors (cognitive landmarks) to facilitate recall (Belli, 1998). Moreover, Conway, Wang, Hanyu, and Hague (2005) showed that adolescence is a life phase that is in general well represented in the adult mind. Even more important, our retrospective results are much in line with Schmitt-Rodermund's (2007) findings from a comparable prospective longitudinal study covering almost the complete lives of its participants. Another limitation is that all information collected stemmed from a single source. Finally, because of length constraints in the questionnaire, human and social capitals were only assessed with one-item measures.

We conclude that future entrepreneurship research should continue to illuminate the nexus between personality, human development, and entrepreneurial behavior. Although existing results on this topic look promising so far (Obschonka et al., 2010; Schmitt-Rodermund, 2004, 2007; Zhang & Arvey, 2009), more life-span research, preferably using prospective longitudinal study designs, is strongly needed.


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Martin Obschonka, Rainer K. Silbereisen, and Eva Schmitt-Rodermund, Department of Developmental Psychology, Friedrich-Schiller-University Jena, Jena, Germany. The authors gratefully acknowledge financial support by the Thuringian Ministry of Education (ThUringer Kultusministerium) and the Hans-Bockler-Stiftung for the research project "Success and Failure of Innovative Start-Ups: A Process-Oriented Analysis of Economic and Psychological Determinants" (principal investigators: Uwe Cantner, Rainer K. Silbereisen Eva Schmitt-Rodermund, and Gabriele Beibst). Correspondence concerning this article should he addressed to Martin Obschonka, Department of Developmental Psychology, Friedrich-Schiller-University Jena, Am Steiger 3/1, D-07743 Jena, Germany (e-mail: martin.obschonka@uni-jena.de).
TABLE 1 Zero-Order Correlations Between the Variables

Variable   1       2      3      4      5     6     7     8     9


1. Age T1        -

2. Gender     -.25      -
T1a            ***


3. EPP T1      .02    .14      -

4. ELA T1      .23    .01    .17      -
               ***           ***

5. EIB T1      .15   -.02    .20    .19     -
                **           ***    ***

6. ECA T1     -.06   -.05    .21    .13   .38     -
                             ***     **   ***

7. EHC T1      .21   -.09    .25  .11 *   .22   .26     -
               ***           ***          ***   ***

8. ESC T1      .28   -.09    .23    .13   .25   .19   .48     -
               ***           ***     **   ***   ***   ***

9. BIG T2      .09   -.21    .08    .09   .22   .15   .41   .36  -
                       **                  **     *   ***   ***
             (.05)  (-.16  (.10)  (.06)  (.24  (.14  (.39  (.35  -
                       *)                ***)    *)  ***)  ***)

Note. T1 = Time 1; T2 = Time 2. Correlations between variables
from T1 refer to N = 488. Correlations between BIG and all other
variables refer to the T2 sample (N = 200) when values are not
in parentheses. In contrast, values in parentheses represent
correlations estimated using the full information maximum
likelihood method via AMOS. This method estimates coefficients
using all information of the observed data in the data set. The
values in parentheses thus refer to N= 488. EPP = entrepreneurial
personality profile; ELA = early leadership in adolescence;
EIB = early inventive behavior in adolescence; ECA = early
commercial activities in adolescence; EHC = entrepreneurial human
capital; ESC = entrepreneurial social capital; BIG = business
idea generation.

(a.) Female.

* p< .05. ** p< .01. *** p< -001.
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