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
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
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
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
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,
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).
[FIGURE 1 OMITTED]
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
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
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.
Arbuckle, J. L. (2006). Amos 7.0 user's guide. Chicago, IL:
Ardichvili, A., Cardozo, R., & Ray, S. (2003). A theory of
entrepreneurial opportunity identification and development. Journal of
Business Venturing, 18, 105-123.
Audretsch, D. B. (2007). The entrepreneurial society. New York, NY:
Oxford University Press.
Baum, K. J., & Locke, E. A. (2004). The relationship of
entrepreneurial traits, skill, and motivation to subsequent venture
growth. Journal of Applied Psychology, 89, 587-598.
Belli, R. F. (1998). The structure of autobiographical memory and
the event history calendar: Potential improvements in the quality of
retrospective reports in surveys. Memory, 6, 383-406.
Caspi, A., Roberts, B. W., & Shiner, R. L. (2005). Personality
development: Stability and change. Annual Review of Psychology, 56,
Cohen, J, (1988), Statistical power analysis for the behavioral
sciences. Mahwah, NJ: Er1baum.
Conway, M. A., Wang, Q., Hanyu, K., & Hague, S. (2005). A
cross-cultural variation of autobiographical memory: On the universality
and cultural variation of the reminiscence bump. Journal of
Cross-Cultural Psychology, 36, 739-749.
Davidsson, P. (2006). Nascent entrepreneurship: Empirical studies
and developments. Foundations and Trends in Entrepreneurship, 2, 1-76.
Davidsson, P., & Honig, B. (2003). The role of social and human
capital among nascent entrepreneurs. Journal of Business Venturing, 18,
Grandi, A., & Grimaldi, R. (2005). Academic's
organizational characteristics and the generation of successful business
ideas. Journal of Business Venturing, 20, 821-845.
Hartung, P. J., Porfeli, E. J., & Vondracek, F. W. (2005).
Child vocational development: A review and reconsideration. Journal of
Vocational Behavior, 66, 385-419.
Hisrich, R., Langan-Fox, J., & Grant, S. (2007).
Entrepreneurship research and practice: A call to action for psychology.
American Psychologist, 62, 575-589.
Holland, J. L. (1997). Making vocational choices. A theory of
vocational personalities and work environments. Odessa, FL:
Psychological Assessment Resources.
Holmbeck, G. M. (1997). Toward terminological, conceptual, and
statistical clarity in the study of mediators and moderators: Examples
from the child-clinical and pediatric psychology literature. Journal of
Consulting and Clinical Psychology, 64, 599-610.
Kim, P. H., & Aldrich, H. E. (2005). Social capital and
entrepreneurship. Foundations and Trends in Entrepreneurship, 1, 55-104.
Kline, R, 13. (2005). Principles and practice of structural
equation modeling. New York, NY: Guilford Press.
Krueger, N. F., Reilly, M. D., & Carsrud, A. L. (2000).
Competing models of entrepreneurial intentions. Journal of Business
Venturing, 15, 411-132.
Lovden, M., Ghisletta, R, & Lindenberger, U. (2005). Social
participation attenuates decline in perceptual speed in old and very old
age. Psychology and Aging, 20, 423-434.
MacKinnon, D. P., Fairchild, A. J., & Fritz, M. S. (2007).
Mediation analysis. Annual Review of Psychology, 58, 593-614.
Mahbubani, K. (2008). The new Asian hemisphere. New York, NY:
Masten, A. S., Desjardins, C. II, McCormick, C. M., Kuo, S. I.,
& Long, J. D. (2010). The significance of childhood competence and
problems for adult success in work: A developmental cascade analysis.
Development and Psychopathology, 22, 679-694.
McAdams, D. P., & Pals, J. L. (2006). A new Big Five:
Fundamental principles for an integrative science of personality.
American Psychologist, 61, 204-217.
McClelland, D. (1961). The achieving society. Princeton, NJ: Van
Muthen, B., & Kaplan D. (1985). A comparison of some
methodologies for the factor analysis of non-normal Liken variables.
British Journal of. Mathematical and Statistical Psychology, 38,
Obschonka, M., Silbereisen, R. K., & Schmitt-Rodermund, E.
(2010). Entrepreneurial intention as developmental outcome. Journal of
Vocational Behavior, 77, 63-72.
Ostendorf, E. (1990). Sprache and Personlichkeitsstruktur: Zur
Validitat des Funf-Faktoren-Modell der Personlichkeit (Language and
personality structure: Toward the validation of the five-factor model of
personality]. Regensburg, Germany: S. Roeder Verlag.
Rauch, A., & Frew, M. (2007). Let's put the person back
into entrepreneurship research: A meta-analysis on the relationship
between business owners' personality traits, business creation, and
success. European Journal of Work and Organizational Psychology, 16,
Roberts, B. W., Caspi, A., & Moffitt, T. E. (2003). Work
experience and personality development in young adulthood. Journal of
Personality and Social Psychology, 84, 582-593.
Schmitt-Roderinund, E. (2004). Pathways to successful
entrepreneurship: Parenting, personality, entrepreneurial competence,
and interests. Journal of Vocational Behavior, 65, 498-518.
Schmitt-Rodermund, E. (2007). The long way to entrepreneurship:
Personality, parenting, early interests, and competencies as precursors
for entrepreneurial activity among the Termites." In R. K.
Silbereisen & R. M. Lerner (Eds.), Approaches to positive youth
development (pp. 205-224). London, England: Sage.
Shane, S. A. (2004). Academic entrepreneurship. Cheltenham,
England: Edward Elgar.
Shane, S., & Venkataraman, S. (2000). The promise of
entrepreneurship as a field of research. Academy of Management Review,
Silbcrciscn, R. K., & Chen, X. (2010). Human development and
social change: Concept and results. London, England: Sage.
Spencer, L. M., & Spencer, S. M. (1993). Competence at work.
New York, NY: Wiley.
Statistisches Bundesamt. (2008). Bildung und Kultur: Personal an
Hochschulen [Education and culture: Personnel at universities].
Wiesbaden, Germany: Author.
World Economic Forum. (2009). Educating the next wave of
entrepreneurs: Unlocking entrepreneurial capabilities to meet the global
challenges of the 21st century. Geneva, Switzerland: Author.
Zhang, Z., & Arvey, R. D. (2009). Rule breaking in adolescence
and entrepreneurial status: An empirical investigation. Journal of
Business Venturing, 24, 436-447.
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:
TABLE 1 Zero-Order Correlations Between the Variables
Variable 1 2 3 4 5 6 7 8 9
1. Age T1 -
2. Gender -.25 -
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
* p< .05. ** p< .01. *** p< -001.