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Explanation related to a biosocial model of entrepreneurship the combined effects of nurture and nature.
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A biosocial model of entrepreneurship: The
combined effects of nurture and nature
ARTICLE in JOURNAL OF ORGANIZATIONAL BEHAVIOR · MAY 2007
Impact Factor: 3.85 · DOI: 10.1002/job.432
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A biosocial model of entrepreneurship: the
combined effects of nurture and nature
RODERICK E. WHITE
1
*
, STEWART THORNHILL
1
AND ELIZABETH HAMPSON
2
1
Richard Ivey School of Business, The University of Western Ontario, London, Ontario, Canada
2
Department of Psychology, The University of Western Ontario, London, Ontario, Canada
Summary Why do people get involved in the creation of new ventures? Prior research suggests
entrepreneurial behavior has multiple causes. Nurture explanations; often couched in terms
of sociological theories like social learning have been popular. Aspects of nascent entrepre-
neurs’ social contexts, notably their family business background, have been associated with
newventure creation. But nature also appears to play a role. Other research has linked heritable
biological factors, including testosterone, with the career choice to launch a new venture. This
study presents theory and evidence linking the combination of both sociological and biological
factors with new venture creation: a biosocial model of entrepreneurship. Empirical results
indicate new venture creation is more likely among those individuals having a higher
testosterone level in combination with a family business background. Copyright # 2007
John Wiley & Sons, Ltd.
It has been known for some time that individuals raised in a family business environment are more
likely to express a preference for, and be involved in a new venture start-up (Collins & Moore, 1970;
Ronstadt, 1983). Early socialization or social learning theory is typically posited as the explanation for
this relationship (Scherer, Adams, Carley, & Wiebe, 1989). Like most of the social sciences this view
assumes, often implicitly, that the human mind is a blank slate written upon by our parents, our schools
and our culture (Pinker, 2002). Nurture dominates over nature. Recently this assumption has been
challenged; most directly by evolutionary psychologists (Barkow, Cosmides, & Tooby, 1992; Buss,
1999). This line of thinking contends that nature matters when we are attempting to understand human
behavior. Management researchers are just beginning to consider how evolutionary forces may affect
business related behaviors (Colarelli, 2003; Lawrence & Nohria, 2002; Nicholson, 1997, 2000;
Nicholson & White, 2006). With regard to entrepreneurship, research has shown that the likelihood of
engaging in new venture creation is explained, at least in part, by an heritable biological trait,
speci?cally testosterone (T) level (White, Thornhill, & Hampson, 2006).
Journal of Organizational Behavior
J. Organiz. Behav. 28, 451–466 (2007)
Published online 5 January 2007 in Wiley InterScience
(www.interscience.wiley.com) DOI: 10.1002/job.432
* Correspondence to: Roderick E. White, Richard Ivey School of Business, The University of Western Ontario, London, Ontario,
N6A 3K7, Canada. E-mail: [email protected]
Copyright # 2007 John Wiley & Sons, Ltd.
Received 12 December 2005
Revised 23 June 2006
Accepted 19 October 2006
The biological explanation argues for a nature effect; the social learning rationale for a nurture effect.
Historically these domains have been largely separate, but convergence appears to be occurring
(Massey, 2002). While these two research paradigms have rarely intersected it is not an either/or
choice. Biosocial research brings together and combines biological and sociological explanations for
behavior. Our research adopts this biosocial perspective and ?nds an entrepreneurial behavior, new
venture creation, is in?uenced by the combination of nature and nurture; a biosocial model of
entrepreneurship.
Nature, Nurture, and Entrepreneurship
Most of the research exploring why some people choose to become entrepreneurs and others do not has
examined individual differences in psychological variables (Rauch & Frese, 2000) like risk propensity
(Stewart & Roth, 2001), need for achievement (McClelland, 1961; Miner, 2000), locus of control
(Mueller & Thomas, 2000; Robinson, Stimpson, Huefnor, & Hunt, 1991) and self-ef?cacy (Krueger &
Dickson, 1994; Scherer et al., 1989). The origins for these differences, whether nurture or nature, are
rarely explored.
Nurture effects
At least since McClelland’s study of Asian entrepreneurs the importance of social forces in molding
entrepreneurial aspirations, speci?cally the need for achievement, has been recognized (McClelland,
1961). Social forces include the general legitimacy accorded by the society to an entrepreneurial career,
peer expectations, the availability of mentors and role models but most importantly the impact of
family. Prior research has found that individuals with entrepreneurial role models are more likely to
engage in entrepreneurial activity (Carsrud, Olm, &Eddy, 1987). Family members feature prominently
as entrepreneurial role models (Cooper & Dunkelberg, 1987; Ronstadt, 1984). Brockhaus and Horwitz
(1986: 43) noted that as role models ‘family members, particularly the mother and father are considered
key.’ In their review of the literature Matthews and Moser observed that ‘. . . the most salient factor for
entry into an entrepreneurial career remains the parental role model (1996: 30). While social contextual
factors beyond the family can affect the manifestation of entrepreneurial behavior (Carsrud & Johnson,
1989), we know empirically that individuals raised in a family business environment are more likely to
be involved in new venture start-up (Krueger, 1993; Matthews & Moser, 1996; Scherer, Adam, &
Wieke, 1989). The explanations advanced for this relationship mostly have to do with social and
learning processes: role modeling, imitation, basic values or utilities for certain kinds of behaviors
passed from parent to child.
Of course, the effect of family context upon entrepreneurship is more complex and complicated than
learning and adoption of extrinsic values and preferences. Entrepreneurship is deeply embedded in the
family context (Aldrich & Cliff, 2003). We know family members can be a source of support: both
moral and ?nancial for aspiring entrepreneurs (Aldrich & Zimmer, 1986; Steier & Greenwood, 2000).
Families with members having entrepreneurial or small business experience may be a more credible
and willing source of support than families without this background.
Research has found that becoming an entrepreneur is associated with an array of contextual factors
(Bloodgood, Sapienza, &Carsrud, 1995). Family is one of the most important factors. Aldrich and Cliff
conclude, ‘mounting empirical evidence suggests that families play an important role in the venture
Copyright # 2007 John Wiley & Sons, Ltd. J. Organiz. Behav. 28, 451–466 (2007)
DOI: 10.1002/job
452 R. E. WHITE ET AL.
process and thus deserve greater consideration in the entrepreneurship literature’ (2003: 577). It is
apparent from the existing research that family context is one of the social factors having a signi?cant
relationship with entrepreneurship. Unsurprisingly the available empirical evidence indicates
individuals from nurturing family contexts, rich in entrepreneurial role models and supportive of
new venture creation, are more likely to identify and initiate new ventures.
The nature effect
There is comparatively little evidence for an association between biological factors and
entrepreneurship. However, the absence of evidence does not prove the absence of a relationship.
Until recently no one has looked for such associations. More generally, associations between careers
and biological factors have been found.
Studies of twins show that genetic similarity and differences explain a lot about vocational interests
and career choice (Arvey et al., 1989; Moloney, Bouchard, & Segal, 1991). By studying identical and
fraternal twins researchers have been able to identify the genetic component of certain attitudes, values,
and interests and to lesser extent behavioral outcomes (Loehlin, 1992). Identical twins share the same
genes; fraternal twins like all siblings of the same parents share on average 50 per cent of their genes.
Thus by studying twins it is possible to associate genetic similarity with a host of psychological
characteristics and behaviors. Of particular interest to this study is the twin research that has examined
things like vocational interest, job satisfaction, work values, job switching, and career choices (Arvey
& Bouchard, 1994). Genetic similarities explain 40 per cent to 50 per cent of the variance in vocational
interests (Lykken, Bouchard, McGue, & Tellegen,1993; Moloney et al., 1991), 40 per cent of work
values (Keller, Bouchard, Arvey, Segal, & Dawis, 1992), 36 per cent of the variance in job switching
(McCall, Cavanaugh, Arvey, &Taubman, 1997), 30 per cent of job satisfaction (Arvey et al., 1989) and
48 per cent of the tendency to become self-employed (Nicolaou, Shane, Hunkin, Cherkas, & Spector,
2006). There is anecdotal evidence to suggest that genetic similarity may lead to similar careers
(Segal, 1999) and more systematic evidence that it explains the general type of occupation (complexity,
motor skill and physical demands; Arvey et al., 1989).While twin studies can point to a genetic
basis for behavioral differences this research does not indicate what biological mechanisms are
implicated. Speci?c endocrinal differences have been related to general occupation categories
(Dabbs, 1992; Dabbs & Morris, 1990); and more speci?c career choices (Dabbs, 2000; Dabbs,
Alford, & Fielden, 1998; Dabbs, de La Rue, & Williams, 1990a; Fannin, & Dabbs, 2003). White et al.
(2006) explored the relationship between a biological variable and entrepreneurship. They found a
heritable biological factor; T level was positively associated with the increased likelihood of an
entrepreneurial experience. This effect was partially mediated by a psychological variable (risk-taking
propensity): testosterone affected risk-taking, which in turn affected the likelihood of an
entrepreneurial experience.
Initiating a new venture amounts to a career choice and there is substantial evidence associating
biology with careers and vocational interests. The exact physiological and psychological mechanisms
linking genetic and endocrinal attributes to career predispositions are as yet undiscovered. There are
fears that a better understanding of these relationships will somehow validate biological determinism.
These fears are unfounded. Our biology affects but does not fully determine complex intentional
actions. The decision to start a new venture is not a re?ex reaction to a single stimulus. Higher order
cognitive functions are involved in this behavior. However, our nature, our evolved psychology
predisposes an individual to think and act in particular ways. But those endogenous predispositions are
affected by a host of exogenous factors, not the least of which is the individual’s family context.
Copyright # 2007 John Wiley & Sons, Ltd. J. Organiz. Behav. 28, 451–466 (2007)
DOI: 10.1002/job
A BIOSOCIAL MODEL OF ENTREPRENEURSHIP 453
A Biosocial Theory of Behavior
As Ellis (1993): xiii) explains, a biosocial perspective simply assumes ‘both biological and social
environmental factors are important for explaining variations in human behavior.’ Biosocial theorizing
is not newto the social sciences. Indeed, there is a society devoted to bringing together researchers from
the biological and social sciences (Human Behavior and Evolution Society). However to our
knowledge, no prior empirical research has employed this perspective to explore a business related
behavior.
Put simply most biosocial theory argues that nature predisposes and nurture disposes. Our biology
provides certain behavioral predispositions or propensities but socialization and other learning
processes develop and channel these predispositions. Humans have been a social species for millions of
years. Evolution has both helped to mold, and taken advantage of our social nature and our ability to
learn. Language, that most social of behaviors, provides an example of a biosocial phenomenon.
Chomsky (1986) demonstrated that humans are born with an innate ability, or predisposition to acquire
language. Basic grammatical structures come naturally to us (Pinker, 1994). But actual language is
acquired through social interactions between infants and adults, principally family members. Infants
deprived of these social interactions will not develop sophisticated language, even though they are
biologically inclined to do so. Nature and nurture interact in rich and complex ways.
In much the same way that humans have specialized cognitive mechanisms facilitating the
acquisition of language, it is believed our species has other evolved cognitive abilities. The facility to
detect cheaters may be another. There is a strong evolutionary argument for why a social species needs
to be able to detect cheaters: individuals who take advantage of social relationships but do not
reciprocate (Axelrod & Hamilton, 1981; Trivers, 1971). Research has shown that humans have an
innate cognitive ability to solve cheater detection problems (Cosmides, 1989; Cosmides & Tooby,
1992; Cummins, 1996). But Cummins (1999) has demonstrated that this ability is conditioned by social
rank: persons of higher social rank are more likely to detect cheaters than individuals of lower rank.
This ?nding illustrates the activation of an endogenous evolved ability, cheater detection, conditioned
by the exogenous social circumstances—another type of biosocial interaction.
The biological predispositions to acquire language and detect cheaters are believed to be human
universals. Yet there are many biological traits that differ within the species. And these differences can
interact with social processes in interesting ways. Biosocial studies, especially those using biological
traits that differ within the population are not commonplace. One such study demonstrated how
hormone experiences (testosterone) ‘facilitate or dampen the effects of socialization and environment
on gendered behavior’ (Udry, 2000: 443). Speci?c behaviors were associated with hormonal history
and subsequent socialization experiences. Exposure to testosterone signi?cantly moderated the effect
of socialization experiences upon certain types of behavior. Strong interactions were evident. Other
types of biosocial interactions have been observed. Schultheiss, Campbell, and McClelland (1999)
have shown that in particular behavioral settings (i.e., competitions) individual motivations, which are
in part learned, affect the level of testosterone. There is a rich two-way relationship between
testosterone and socialization with behavior.
A biosocial study of the relationship between adolescents and their parents is directly relevant to our
research. Booth et al. (2003) found that the quality of the parent–child relationship mediated the effect
of testosterone upon certain behaviors. Speci?cally, when the parent–adolescent male child
relationship was of low quality and testosterone was high, there was more evidence of (antisocial)
risk-taking, behaviors like skipping class and shoplifting. The propensity for testosterone to directly
increase risk-taking (or be less fearful) has been observed in other studies (Boissy & Bouissou, 1994;
Dabbs et al., 1990b). But Booth et al. (2003) demonstrated an interactive association between a familial
Copyright # 2007 John Wiley & Sons, Ltd. J. Organiz. Behav. 28, 451–466 (2007)
DOI: 10.1002/job
454 R. E. WHITE ET AL.
variable (parent–child relationship) in conjunction with a biological variable (testosterone level) upon a
behavior (risk-taking). Our study takes a similar approach with a signi?cant difference, as explained
below.
Booth, Johnson, Granger, Crouter, and McHale (2003) only studied the impact of testosterone and
parent–child relationship quality upon anti-social risk-taking behaviors. But some evolutionary
theorists have suggested this is one end of a continuum of behaviors (Ellis, 2004; Mof?t & Walsh,
2003). Just as characteristics of familial relationships can channel risk-taking toward anti-social
behaviors it is plausible that other characteristics of the family can channel this propensity toward
prosocial risk-taking behaviors, like new venture creation. Being raised in a family where other family
members, most notably the mother or father have started and run their own business would help to
direct any innate predispositions toward similar kinds of endeavors.
A biosocial theory of entrepreneurship
Any biosocial theory requires a biological component and a social component, which together
explain behavior. Our behavior of interest is entrepreneurship; speci?cally new venture creation.
Arguably new venture creation requires the taking of risk. Certain biological characteristics,
particularly testosterone, have been theoretically and empirically linked to risk-taking (Mazur &
Booth, 1998a). T levels affect not only obvious physiological characteristics (e.g., muscle
development) but also more subtle psychological processes. T can affect our psychology by
in?uencing brain structure during early development. The circulating level of testosterone can also
affect ongoing neural processes by directly or indirectly activating receptors present in the adult
brain. The effect of Tupon speci?c neural mechanisms and how this in?uences behavior is only just
being explored. However, at a more general level, T is one of the most studied of the endocrine
hormones (Dabbs and James, 2000; Mazur & Booth, 1998a; Mazur & Booth, 1998b).
Social factors, notably family business background, have also been associated with the propensity to
start a new venture. This study extends the prior research relating risk-taking behavior, family
background and testosterone to the prosocial risk taking behavior of starting a new venture. Generally,
we believe individuals with higher testosterone are predisposed toward risky behavior and family
background channels this propensity in a particular direction. When a high testosterone individual’s
family background includes the starting and/or running of a business the two factors, one sociological
the other biological interact to explain the likelihood of that individual being involved in the creation of
a new venture—a biosocial theory of entrepreneurship.
The general proposition consistent with this biosocial model of entrepreneurship is: New venture
creation is more likely to be exhibited by those individuals with a higher basal T level and a family
business background. Each effect is posited to separately and jointly in?uence the likelihood of
entrepreneurial behavior. Stated more formally the sequence of hypotheses is:
H1: Individuals with a family business background are more likely to be involved with the creation
of a new venture.
H2: Individuals with higher testosterone levels are more likely to be involved with new venture
creation.
H3: An individual’s family business background and testosterone level have separate and
independent effects upon the likelihood of involvement with new venture creation (i.e., they have
independent explanatory power).
Copyright # 2007 John Wiley & Sons, Ltd. J. Organiz. Behav. 28, 451–466 (2007)
DOI: 10.1002/job
A BIOSOCIAL MODEL OF ENTREPRENEURSHIP 455
H4: Those individuals with both higher testosterone level and a family business background are more
likely to be involved with new venture creation (i.e., there is a positive interaction effect).
Organizational Context
The subjects for this study were Master of Business Administration students attending the
Richard Ivey School of Business at The University of Western Ontario. Western is a large, public
institution of higher learning offering a full range of undergraduate, graduate and professional
programs located in London, Canada (population 350 000). The MBA class at the Richard Ivey
School of Business was comprised of four sections of approximately 70 students each (both male
and female). The entire 2002–2003 class was comprised of 272 students, 25 per cent were female,
average age was 30 with 5.5 years of work experience. Self-described ethnicity was 61 per cent
Caucasian, 32 per cent Asian and 7 per cent other.
Each data collection session commenced with a brief explanation of the study protocols, followed
by the collection of the ?rst of two saliva samples from each participant. Prior to the study, students
had been advised not to consume any food or beverages (other than water), smoke, or chew gum for
1 hour prior to the saliva collection. Subjects were provided with sugarless gumto help stimulate the
production of salvia. The saliva was maintained in sealed test tubes for 24 hours at roomtemperature
to allow for settling of particulate matter and then frozen to À20 degrees Celsius. It was not thawed
until the laboratory assays were performed. Data collection took place in February 2002; assays
were done during May 2002.
The number of subjects included in this study was determined by the assaying procedures. The
laboratory performed testosterone assays in ?xed batch sizes based on ‘kits’ of the reagent
chemicals. Our ?nal sample of 33 entrepreneurs, 29 matched pairings, and 53 others totalled to 115
subjects, each of whom provided two saliva samples exhausted the maximum available test kit
capacity of 230 samples.
Method
Sample
Because basal testosterone (T) levels vary during the day and seasonally, and can be affected by
exogenous events it is important to collect T samples under controlled conditions. The desired control
over collection procedures was most easily achieved with a student population. Accordingly
participants in this study were all full-time MBA students at a major North American business school.
The MBA class has four sections of approximately 70 students each (both male and female).
Timetables were arranged so data collection took place in a short time frame. Consistent with university
research policies students were free to opt out of any or all parts of the study; to ensure con?dentiality
Copyright # 2007 John Wiley & Sons, Ltd. J. Organiz. Behav. 28, 451–466 (2007)
DOI: 10.1002/job
456 R. E. WHITE ET AL.
student identities were not recorded. Numbers were assigned to all volunteers and used to link the data
elements including: entrepreneurial background and personal and demographic data, and two saliva
samples to be assayed for T.
All students were invited to participate in this study but because of the small number of females
participating (21 of 67 students) only male student data was used. (Subjects taking oral contraceptives
were asked to exclude themselves fromthe study). Of the population of 205 male students, 166 chose to
fully participate in the study (81 per cent).
Measures
Entrepreneurship
Within the subset of 166 male participants, 46 self-identi?ed as having prior involvement in a new
venture start-up. Using a convergent sorting process the researchers (professors in strategy and
entrepreneurship) assessed the reported new venture involvement of the self-identi?ed entrepreneurs.
This check on self-identi?cation was blind, done prior to the determination of T levels. After immediate
disquali?cation of 13 subjects and review and eventually disquali?cation of 2 others, a total of 31
subjects were retained in the entrepreneurship experience (EE) category. The raw proportion of
agreement between the two researchers was 74 per cent, representing an adjusted inter-rater agreement
coef?cient of 0.6 (Cohen, 1960; Zwick, 1988) or ‘good’ according to Landis and Koch (1977).
The individuals classi?ed as entrepreneurs had led a new venture, personally investing in and
managing the business. Those eliminated from the entrepreneurial sample did not have signi?cant
full-time involvement in the new venture; often they were part-time employees, passive investors, or
board members. Ventures ranged from low-tech (coffee shops) to high-tech (web support for medical
research labs) and also included intelligence testing services, retail stores, manufacturers, and
exporters. The majority of the ventures were based in Canada; ?ve were in China and three in the United
States. Mean values for ?rm size were seven employees and annual revenues were C$600 000.
Testosterone
Saliva was collected in polystyrene test tubes, individually labeled and pretreated with sodium azide as
a preservative. After the ?rst saliva sample was collected, participants completed a questionnaire
capturing personal data and their entrepreneurial experience. After completion of the questionnaire
students provided a second saliva sample, concluding the process. Shortly afterwards the saliva was
frozen and not thawed until the laboratory assays were performed.
The saliva analysis kit could assay 220 samples. With two saliva samples per participant, this limited
our maximum number of observations to 110 students. Beginning with the list of 31 entrepreneurs, we
?rst developed a set of 31 matched pairs. The pairing was based on the time period during which the
saliva was collected, and then age, ethnicity, and undergraduate degree. T levels changes during
the day, declining signi?cantly from early to late morning (Nieschlag, 1974). Pairs were also matched
on age because of the inverse relationship between age and testosterone levels (Lamberts, van den Beld,
& van der Lely, 1997). Education, speci?cally the level and nature of prior schooling, was selected to
control for opportunity exposure. As such, engineers were matched with engineers, business majors
with business majors, etc. To expand the sample size for this study another 48 male subjects, in addition
to the identi?ed entrepreneurs and matched pairs, were randomly selected from the participant pool for
inclusion in the samples to be assayed. The pool of pair matched and additional non-entrepreneurs was
selected prior to the assays and without knowledge of the participants’ testosterone levels. Subsequent
analysis indicated no signi?cant differences between the pair-matched non-entrepreneurs and other
non-entrepreneurs in our sample. All analysis in this paper includes the total sample of 31 entrepreneurs
Copyright # 2007 John Wiley & Sons, Ltd. J. Organiz. Behav. 28, 451–466 (2007)
DOI: 10.1002/job
A BIOSOCIAL MODEL OF ENTREPRENEURSHIP 457
and 79 non-entrepreneurs. Participants who had self-identi?ed as entrepreneurs, but were later
disquali?ed by the screening process, were not included in the non-entrepreneurial sample.
The saliva was submitted to a double ether extraction assay and employed a single Count-A-Count
Total Testosterone kit (Diagnostic Products, Los Angeles, CA), modi?ed to accommodate the lower
concentrations of T found in saliva. Details of the procedure are described in Moffat and Hampson
(1996). Reported T-levels are the average values of the two samples collected from each participant in
picograms of testosterone per milliliter (pg/ml) of saliva. The testosterone values obtained were
consistent with those reported in prior research (Moffat & Hampson, 1996; Read, 1993). Internal
consistency reliability of the saliva samples was 0.85 (Nunnally, 1978).
Family business
Family business background (FBB) is a dichotomous variable, coded in response to the question: ‘Did
your parent(s) have a family business?’ Like our binary measure for EE, this measure provides a simple
means of classifying participants into categories for analysis. In the present study we are not attempting
to evaluate entrepreneurial success or qualitative aspects of the family business experience and,
accordingly, our measures favor clarity and simplicity over richness and complexity.
Results
Table 1 presents T values by EE and FBB. It can be seen that T values are highest in the top right cell;
those participants who grew up in a family business background and created a new venture themselves.
The upper right cell is statistically different from each of the other three cells ( p <0.05), while none of
the other cells differ statistically from one another.
Table 2 presents the incidence of entrepreneurial behavior as a function of both T-level and FBB. We
split the sample into high and low T based on the sample median (78.7 pg/ml). Within our total sample,
the incidence of entrepreneurs is 31 out of 110 or 28 per cent. This is approximately the frequency
found in the off-diagonal cells of Table 2. However, the frequency is notably greater in the top right cell
(14 entrepreneurs, 13 non-entrepreneurs: 51 per cent) and lower in the bottom left cell (15 per cent).
Taken together, the results presented in Tables 1 and 2 generally support our hypotheses of direct as
well as an additive and interactive in?uence of biology and family socialization on entrepreneurial
behavior.
Table 1. Testosterone level by family business background and entrepreneurial experience
Family business (FBB)
Entrepreneurship experience (EE)
No Yes
Yes 71.0
a
90.8 n ¼49
n ¼29 n ¼20
No 75.2 77.4 n ¼61
n ¼50 n ¼11
n ¼79 n ¼31 n ¼110
Copyright # 2007 John Wiley & Sons, Ltd. J. Organiz. Behav. 28, 451–466 (2007)
DOI: 10.1002/job
458 R. E. WHITE ET AL.
To more rigorously test the hypothesized relationships we employed logistic regression using
entrepreneurial experience (EE) as the dichotomous dependent variable. Pregibon’s (1981) diagnostic
d-beta test indicated no unduly in?uential observations. Equation 1 estimates the direct relationship
between family business background and entrepreneurship. Equation 2 estimates the direct relationship
between T and entrepreneurship. Both effects are included in Equation 3, and an interaction term
is added in Equation 4. The equations correspond to the column entries reported in Table 3. (T is
known to vary with subject age and time of day. We also ran models using the residual of T after
partialling out age and time of day effects. The results are qualitatively identical to those reported in
Table 3.)
Entrepreneurship ðEEÞ ¼ g
0
þ g
1
FBB þ "
1
(1)
Entrepreneurship ðEEÞ ¼b
0
þ b
1
T þ "
2
(2)
Entrepreneurship ðEEÞ ¼ d
0
þ d
1
T þ d
2
FBB "
3
(3)
Entrepreneurship ðEEÞ ¼ u
0
þ u
1
T þ u
2
FBB þ u
3
ðT Ã FBBÞ þ "
4
(4)
The ?rst column results indicate family business background is signi?cantly associated with starting
a newbusiness (H1). Testosterone level is also signi?cantly associated with entrepreneurial behavior as
indicated by signi?cant coef?cient for T in column 2 (H2). These effects are not attenuated when both
variables are included in column 3. (Note the increase in Pseudo R
2
from 0.053/0.056 to 0.102.) These
?ndings support H3. Finally, an interaction term is introduced in column 4. The coef?cient for the
Table 2. Entrepreneurial experience by family business background and testosterone level
Family business (FBB)
Testosterone level (T)
Low High
Yes 27% 52% n ¼49
(6E, 16 N) (14 E, 13 N)
No 15% 21% n ¼61
(5 E, 28 N) (6 E, 22N)
n ¼55 n ¼55 n ¼110
Table 3. Logistic regression analysis
DV: Entrepreneurial experience
[1] [2] [3] [4] [5a] FBB 1 [5b] FBB 0
Family business (FBB) 1.14
ÃÃ
1.10
Ã
1.02
Ã
Testosterone (T) 0.03
ÃÃ
0.03
Ã
0.01 0.04
Ã
0.01
T
Ã
FBB 0.70
y
Constant À1.51
ÃÃ
À3.10
ÃÃ
À3.54
ÃÃ
À1.51
ÃÃ
À3.44
ÃÃ
À1.99
Pseudo R
2
0.053 0.056 0.102 0.117 0.124 0.002
Sample Size
110 110 110 110 49 61
Note: Result reported as coef?cients, not odds ratios.
y
p-values <0.10;
Ã
p-values <0.05;
ÃÃ
p-values <0.01.
Copyright # 2007 John Wiley & Sons, Ltd. J. Organiz. Behav. 28, 451–466 (2007)
DOI: 10.1002/job
A BIOSOCIAL MODEL OF ENTREPRENEURSHIP 459
interaction between FBB and T is positive and signi?cant at p <0.08, supporting Hypothesis 4;
although the effect is not as strong as those evident for the direct relationships. Columns 5(a) and 5(b),
respectively, report the relationship between T-level and entrepreneurial behavior within the
subsamples of family business background and no family business background. These results, shown
graphically in Figure 1, illustrate that T is a signi?cant predictor of new venture creation only in the
context of a family business background.
Limitations
There are several possible limitations to the ?ndings fromthis research. First, only males were included
in the current study. All students, both male and female, were invited to participate in the data collection
procedure. The number of female participants was small; 21, and of those, only four self-identi?ed as
having a prior entrepreneurial experience. As a result, there was insuf?cient data on the female
population to do statistical tests and sample size constraints limited our study to males. Basal
testosterone levels are substantially different for males and females and the affects of testosterone may
differ, so pooling male and female data is not advisable (Bateup, Booth, Shirtcliff, & Granger, 2002).
Males and females have biological differences and whether these differences affect business behaviors
is a sensitive question with wide ranging implications (Foss, 1998). Some prior research has found that
Toften has a similar (but not always identical) effect in a female population as it does in a population of
males, even though the basal levels are much lower in females (Bateup et al., 2002; Dabbs et al., 1998;
Harris, Rushton, Hampston, & Jackson, 1996). We suspect the same may be true for entrepreneurial
behaviors but research is required with a larger sample of female subjects to explore the relationships.
Our study was done with MBA students and is subject to the usual caveats about generalizing to the
population of practicing entrepreneurs. However, only those subjects with actual new venture start-up
experience were designated as entrepreneurs. Therefore, these results should generalize to
entrepreneurs, at least to that subset of entrepreneurs that return to higher education after their
entrepreneurial episode. There is no reason to suspect the relationship would be different for this
T level
Prob
(EE)
FBB = 0
FBB = 1
Figure 1. Interaction of T-level and family business background.
Copyright # 2007 John Wiley & Sons, Ltd. J. Organiz. Behav. 28, 451–466 (2007)
DOI: 10.1002/job
460 R. E. WHITE ET AL.
subpopulation. Studying the T level of active entrepreneurs and comparing them to similar
non-entrepreneurs would address the question of broader generalizability.
There is the potential for a causal ordering problem in the design of this study because the
entrepreneurial behavior was exhibited some time prior to our measurement of T. However, this
ordering is not of concern since T levels in males show a high degree of stability under normal
conditions, after the in?uence of endogenous rhythms are taken into account. Vermeulen and Verdonck
(1992) reported an excellent correlation (r ¼0.85) between a single point measure of T level and the
mean of seven samples taken over 1 year. Other studies, using testosterone samples gathered over 6
years (Booth & Dabbs, 1993) and 10 years (Mazur & Michalek, 1998), have also reported that basal
testosterone levels are predictable over time. By the end of adolescence, the basal level of testosterone
is generally consistent from year to year, with a slow decline as each individual ages. ‘Men with
relatively high Tat one time tend to be relatively high at other times too... Furthermore, because basal
levels are stable, it follows that they can be adequately measured at any time, whether before or after the
behavior, and therefore can be adequately assessed in a cross-sectional study’ (Mazur et al., 1998a:
361, italics ours). In the controlled conditions of the present study, the measured level of T is re?ective
of long-term individual differences.
An individual’s production rate of T is over 80 per cent heritable (Meiklie, Stringham, Bishop, &
West, 1988). Therefore high T parents are more likely to have high Toffspring. They may also be more
likely to found (family) businesses (White et al., 2006). Thus the two dependent variables employed in
this research may be casually correlated. If so our research would overstate the importance of nature
(FBB) and understate the signi?cance of nature (T level). Disentangling these effects would require
intergenerational information on both the biology (T level) and sociology (FBB) of the subjects’
forbearers.
Discussion and Conclusion
These ?ndings are supportive of a biosocial theory of entrepreneurial behavior. Nature and nurture
taken together help us to better understand entrepreneurial behavior. However this type of research is
still very much in its infancy and these results must be interpreted with some caution. A true biosocial
model requires more than just independent biological and sociological effects (Equations 1 through 3 in
Table 3). The interaction of these effects must have an impact. For our data set, as modeled in Equation
4, the interactive effect of FBB with T upon the likelihood of EE has intermediate signi?cance. This
research was exploratory and the relatively small sample size limited the signi?cance of the
relationships. Overall we interpret the ?nding as supportive of a biosocial theory of entrepreneurship
(H4) but further research is needed to verify this relationship. More biosocial research needs to be done.
This study helps to inform the broader nature-nurture debate. Most researchers in the organizational
sciences have assumed often implicitly nurture; people are born devoid of inherited or innate
predispositions. Recently this blank slate assumption has been challenged (Pinker, 2002). The
challengers do not argue that biological determinism should replace sociological determinism. Their
case is not for nature to the exclusion of nurture; rather that nurture and nature work together,
hand-in-glove. Upon re?ection most social science researchers accept this basic premise of
co-determination. Only the autonomic nervous system and other basic re?exes cannot be in?uenced by
conscious thought and learned behaviors; yet the brain, the seat of learning, is an organ like all others
‘designed’ by evolution. What we learn and how we act is affected by our biologically evolved
character. The basic premise of biosocial research—the interaction of evolved biological factors with
social forces—is nowrecognized if not employed by most behavioralists. Yet studies by organizational
Copyright # 2007 John Wiley & Sons, Ltd. J. Organiz. Behav. 28, 451–466 (2007)
DOI: 10.1002/job
A BIOSOCIAL MODEL OF ENTREPRENEURSHIP 461
scientists examining this combined relationship are rare. This research suggests just such a relationship
exists for an important class of business behaviors: entrepreneurship.
Analysis of the data in this study indicates the preponderance of T’s effect on EE occurs in the
presence of FBB. In other words for nature (i.e., T) to have an effect on the likelihood of EE the
individual needs to have the nurture component (i.e., FBB). T has no signi?cant independent effect
upon EE in the absence of FBB. Interestingly this effect is not symmetric. FBB still explains some of
the likelihood of EE, even after the biosocial interaction of T and FBB are included. It may be that
nurture directs the inclinations inherent in the nature component of the individual. T has been
associated with risk-taking (Dabbs, Hopper, & Jurkovic, 1990b; Dabbs, & Morris, 1990). Family
business background may direct but not fully determine the choice of risk-taking behavior. High T
individuals can channel their risk-taking propensity into a variety of activities (i.e., high risk sports,
dominance contests inside established organizations, etc.), and these outlets for innate risk-taking
propensities are also available to individuals with a FBB. However, individuals with a FBB and high T
are more likely than similar high T individuals without a FBB to direct their risk taking into new
venture creation. We did not expect all of the variance in EE to be explained by the interaction of Tand
FBB; there are many other factors in play. But this research ?nds a portion of the variance in EE is
explained by this biosocial interaction.
More generally our research coupled with the work of Booth et al. (2003) suggests that social factors,
especially an individual’s family situation can channel the risk-taking inclinations associated with high
T toward prosocial, asocial or anti-social behaviors. The likelihood of a particular kind of risky
behavior is in?uenced by the individual’s early socialization. This insight is important to biosocial
research and merits fuller examination and explanation as researchers try to better understand all types
of risk-taking behaviors. To explore this proposition future biosocial research should examine early
socialization experiences, T levels and how they relate to a fuller range of risk-taking behaviors by
individuals.This research is indicative of the potential for biosocial research to explore and explain
important business behaviors. Yet research that even hints at biological determinism can still stir
controversy (Miller & Costello, 2001; Udry, 2001). But we believe exploring the combined effect of
biological and sociological factors will lead to a fuller understanding of interesting business behaviors.
The implications for management practice raise interesting questions and possible dilemmas. First it
needs to be restated that this study was exploratory, to our knowledge the ?rst of its kind in the
organizational sciences. This research associated a speci?c business behavior with individual
differences in a particular hormone and the subject’s social/family background. It would be premature
to make prescriptions for managerial practice. We do not yet know if these individual differences are
associated with successful new ventures. However, what if future research veri?es and extends the
general ?ndings of this research, that in combination individual biological and sociological differences
in?uence the likelihood of successful new venture creation? What if sex differences are found to play a
role? What could practitioners do with this knowledge? More signi?cantly, what should practitioners
do with this knowledge? We believe this research should be conducted. It will help us to better
understand ourselves, our children and the underlying factors driving the entrepreneurial dynamic of
our economy. Nevertheless, we also recognize that how the ?ndings from this type of research are
utilized have broader implications that need to be debated.
Acknowledgements
The authors express their appreciation to the SSHRC for providing ?nancial support (MCRI grant #
412980025), Professor James Dabbs for motivating and encouraging this research, Deborah Chiodo
Copyright # 2007 John Wiley & Sons, Ltd. J. Organiz. Behav. 28, 451–466 (2007)
DOI: 10.1002/job
462 R. E. WHITE ET AL.
and Bavani Rajakumar for their research assistance, and the MBA students who participated in this
study.
Author biographies
Roderick White is an associate professor at The University of Western Ontario’s Richard Ivey School
of Business. He is interested in how evolution can inform behaviors of interest to managers and
organizational scientists; more speci?cally his research explores the evolved basis for social structure.
He recently co-edited a special issue of the Journal of Organizational Behavior and serves on the
editorial board of the Strategic Management Journal.
Stewart Thornhill is an assistant professor of Strategic Management and Entrepreneurship and
Colnett-Love Faculty Fellow at the University of Western Ontario’s Richard Ivey School of Business.
Research interests include competitive strategy, ?rm growth and survival mechanisms, and entre-
preneurial behavior. He is a senior research fellow at Statistics Canada and serves on the Editorial
Boards of the Journal of Business Venturing and the International Entrepreneurship and Management
Journal.
Elizabeth Hampson is a professor of Psychology and a faculty member in the Graduate Program in
Neuroscience at the University of Western Ontario. Her research explores the roles of androgens and
estrogens in human behavior and cognitive processes.
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Explanation related to a biosocial model of entrepreneurship the combined effects of nurture and nature.
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A biosocial model of entrepreneurship: the
combined effects of nurture and nature
RODERICK E. WHITE
1
*
, STEWART THORNHILL
1
AND ELIZABETH HAMPSON
2
1
Richard Ivey School of Business, The University of Western Ontario, London, Ontario, Canada
2
Department of Psychology, The University of Western Ontario, London, Ontario, Canada
Summary Why do people get involved in the creation of new ventures? Prior research suggests
entrepreneurial behavior has multiple causes. Nurture explanations; often couched in terms
of sociological theories like social learning have been popular. Aspects of nascent entrepre-
neurs’ social contexts, notably their family business background, have been associated with
newventure creation. But nature also appears to play a role. Other research has linked heritable
biological factors, including testosterone, with the career choice to launch a new venture. This
study presents theory and evidence linking the combination of both sociological and biological
factors with new venture creation: a biosocial model of entrepreneurship. Empirical results
indicate new venture creation is more likely among those individuals having a higher
testosterone level in combination with a family business background. Copyright # 2007
John Wiley & Sons, Ltd.
It has been known for some time that individuals raised in a family business environment are more
likely to express a preference for, and be involved in a new venture start-up (Collins & Moore, 1970;
Ronstadt, 1983). Early socialization or social learning theory is typically posited as the explanation for
this relationship (Scherer, Adams, Carley, & Wiebe, 1989). Like most of the social sciences this view
assumes, often implicitly, that the human mind is a blank slate written upon by our parents, our schools
and our culture (Pinker, 2002). Nurture dominates over nature. Recently this assumption has been
challenged; most directly by evolutionary psychologists (Barkow, Cosmides, & Tooby, 1992; Buss,
1999). This line of thinking contends that nature matters when we are attempting to understand human
behavior. Management researchers are just beginning to consider how evolutionary forces may affect
business related behaviors (Colarelli, 2003; Lawrence & Nohria, 2002; Nicholson, 1997, 2000;
Nicholson & White, 2006). With regard to entrepreneurship, research has shown that the likelihood of
engaging in new venture creation is explained, at least in part, by an heritable biological trait,
speci?cally testosterone (T) level (White, Thornhill, & Hampson, 2006).
Journal of Organizational Behavior
J. Organiz. Behav. 28, 451–466 (2007)
Published online 5 January 2007 in Wiley InterScience
(www.interscience.wiley.com) DOI: 10.1002/job.432
* Correspondence to: Roderick E. White, Richard Ivey School of Business, The University of Western Ontario, London, Ontario,
N6A 3K7, Canada. E-mail: [email protected]
Copyright # 2007 John Wiley & Sons, Ltd.
Received 12 December 2005
Revised 23 June 2006
Accepted 19 October 2006
The biological explanation argues for a nature effect; the social learning rationale for a nurture effect.
Historically these domains have been largely separate, but convergence appears to be occurring
(Massey, 2002). While these two research paradigms have rarely intersected it is not an either/or
choice. Biosocial research brings together and combines biological and sociological explanations for
behavior. Our research adopts this biosocial perspective and ?nds an entrepreneurial behavior, new
venture creation, is in?uenced by the combination of nature and nurture; a biosocial model of
entrepreneurship.
Nature, Nurture, and Entrepreneurship
Most of the research exploring why some people choose to become entrepreneurs and others do not has
examined individual differences in psychological variables (Rauch & Frese, 2000) like risk propensity
(Stewart & Roth, 2001), need for achievement (McClelland, 1961; Miner, 2000), locus of control
(Mueller & Thomas, 2000; Robinson, Stimpson, Huefnor, & Hunt, 1991) and self-ef?cacy (Krueger &
Dickson, 1994; Scherer et al., 1989). The origins for these differences, whether nurture or nature, are
rarely explored.
Nurture effects
At least since McClelland’s study of Asian entrepreneurs the importance of social forces in molding
entrepreneurial aspirations, speci?cally the need for achievement, has been recognized (McClelland,
1961). Social forces include the general legitimacy accorded by the society to an entrepreneurial career,
peer expectations, the availability of mentors and role models but most importantly the impact of
family. Prior research has found that individuals with entrepreneurial role models are more likely to
engage in entrepreneurial activity (Carsrud, Olm, &Eddy, 1987). Family members feature prominently
as entrepreneurial role models (Cooper & Dunkelberg, 1987; Ronstadt, 1984). Brockhaus and Horwitz
(1986: 43) noted that as role models ‘family members, particularly the mother and father are considered
key.’ In their review of the literature Matthews and Moser observed that ‘. . . the most salient factor for
entry into an entrepreneurial career remains the parental role model (1996: 30). While social contextual
factors beyond the family can affect the manifestation of entrepreneurial behavior (Carsrud & Johnson,
1989), we know empirically that individuals raised in a family business environment are more likely to
be involved in new venture start-up (Krueger, 1993; Matthews & Moser, 1996; Scherer, Adam, &
Wieke, 1989). The explanations advanced for this relationship mostly have to do with social and
learning processes: role modeling, imitation, basic values or utilities for certain kinds of behaviors
passed from parent to child.
Of course, the effect of family context upon entrepreneurship is more complex and complicated than
learning and adoption of extrinsic values and preferences. Entrepreneurship is deeply embedded in the
family context (Aldrich & Cliff, 2003). We know family members can be a source of support: both
moral and ?nancial for aspiring entrepreneurs (Aldrich & Zimmer, 1986; Steier & Greenwood, 2000).
Families with members having entrepreneurial or small business experience may be a more credible
and willing source of support than families without this background.
Research has found that becoming an entrepreneur is associated with an array of contextual factors
(Bloodgood, Sapienza, &Carsrud, 1995). Family is one of the most important factors. Aldrich and Cliff
conclude, ‘mounting empirical evidence suggests that families play an important role in the venture
Copyright # 2007 John Wiley & Sons, Ltd. J. Organiz. Behav. 28, 451–466 (2007)
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452 R. E. WHITE ET AL.
process and thus deserve greater consideration in the entrepreneurship literature’ (2003: 577). It is
apparent from the existing research that family context is one of the social factors having a signi?cant
relationship with entrepreneurship. Unsurprisingly the available empirical evidence indicates
individuals from nurturing family contexts, rich in entrepreneurial role models and supportive of
new venture creation, are more likely to identify and initiate new ventures.
The nature effect
There is comparatively little evidence for an association between biological factors and
entrepreneurship. However, the absence of evidence does not prove the absence of a relationship.
Until recently no one has looked for such associations. More generally, associations between careers
and biological factors have been found.
Studies of twins show that genetic similarity and differences explain a lot about vocational interests
and career choice (Arvey et al., 1989; Moloney, Bouchard, & Segal, 1991). By studying identical and
fraternal twins researchers have been able to identify the genetic component of certain attitudes, values,
and interests and to lesser extent behavioral outcomes (Loehlin, 1992). Identical twins share the same
genes; fraternal twins like all siblings of the same parents share on average 50 per cent of their genes.
Thus by studying twins it is possible to associate genetic similarity with a host of psychological
characteristics and behaviors. Of particular interest to this study is the twin research that has examined
things like vocational interest, job satisfaction, work values, job switching, and career choices (Arvey
& Bouchard, 1994). Genetic similarities explain 40 per cent to 50 per cent of the variance in vocational
interests (Lykken, Bouchard, McGue, & Tellegen,1993; Moloney et al., 1991), 40 per cent of work
values (Keller, Bouchard, Arvey, Segal, & Dawis, 1992), 36 per cent of the variance in job switching
(McCall, Cavanaugh, Arvey, &Taubman, 1997), 30 per cent of job satisfaction (Arvey et al., 1989) and
48 per cent of the tendency to become self-employed (Nicolaou, Shane, Hunkin, Cherkas, & Spector,
2006). There is anecdotal evidence to suggest that genetic similarity may lead to similar careers
(Segal, 1999) and more systematic evidence that it explains the general type of occupation (complexity,
motor skill and physical demands; Arvey et al., 1989).While twin studies can point to a genetic
basis for behavioral differences this research does not indicate what biological mechanisms are
implicated. Speci?c endocrinal differences have been related to general occupation categories
(Dabbs, 1992; Dabbs & Morris, 1990); and more speci?c career choices (Dabbs, 2000; Dabbs,
Alford, & Fielden, 1998; Dabbs, de La Rue, & Williams, 1990a; Fannin, & Dabbs, 2003). White et al.
(2006) explored the relationship between a biological variable and entrepreneurship. They found a
heritable biological factor; T level was positively associated with the increased likelihood of an
entrepreneurial experience. This effect was partially mediated by a psychological variable (risk-taking
propensity): testosterone affected risk-taking, which in turn affected the likelihood of an
entrepreneurial experience.
Initiating a new venture amounts to a career choice and there is substantial evidence associating
biology with careers and vocational interests. The exact physiological and psychological mechanisms
linking genetic and endocrinal attributes to career predispositions are as yet undiscovered. There are
fears that a better understanding of these relationships will somehow validate biological determinism.
These fears are unfounded. Our biology affects but does not fully determine complex intentional
actions. The decision to start a new venture is not a re?ex reaction to a single stimulus. Higher order
cognitive functions are involved in this behavior. However, our nature, our evolved psychology
predisposes an individual to think and act in particular ways. But those endogenous predispositions are
affected by a host of exogenous factors, not the least of which is the individual’s family context.
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A BIOSOCIAL MODEL OF ENTREPRENEURSHIP 453
A Biosocial Theory of Behavior
As Ellis (1993): xiii) explains, a biosocial perspective simply assumes ‘both biological and social
environmental factors are important for explaining variations in human behavior.’ Biosocial theorizing
is not newto the social sciences. Indeed, there is a society devoted to bringing together researchers from
the biological and social sciences (Human Behavior and Evolution Society). However to our
knowledge, no prior empirical research has employed this perspective to explore a business related
behavior.
Put simply most biosocial theory argues that nature predisposes and nurture disposes. Our biology
provides certain behavioral predispositions or propensities but socialization and other learning
processes develop and channel these predispositions. Humans have been a social species for millions of
years. Evolution has both helped to mold, and taken advantage of our social nature and our ability to
learn. Language, that most social of behaviors, provides an example of a biosocial phenomenon.
Chomsky (1986) demonstrated that humans are born with an innate ability, or predisposition to acquire
language. Basic grammatical structures come naturally to us (Pinker, 1994). But actual language is
acquired through social interactions between infants and adults, principally family members. Infants
deprived of these social interactions will not develop sophisticated language, even though they are
biologically inclined to do so. Nature and nurture interact in rich and complex ways.
In much the same way that humans have specialized cognitive mechanisms facilitating the
acquisition of language, it is believed our species has other evolved cognitive abilities. The facility to
detect cheaters may be another. There is a strong evolutionary argument for why a social species needs
to be able to detect cheaters: individuals who take advantage of social relationships but do not
reciprocate (Axelrod & Hamilton, 1981; Trivers, 1971). Research has shown that humans have an
innate cognitive ability to solve cheater detection problems (Cosmides, 1989; Cosmides & Tooby,
1992; Cummins, 1996). But Cummins (1999) has demonstrated that this ability is conditioned by social
rank: persons of higher social rank are more likely to detect cheaters than individuals of lower rank.
This ?nding illustrates the activation of an endogenous evolved ability, cheater detection, conditioned
by the exogenous social circumstances—another type of biosocial interaction.
The biological predispositions to acquire language and detect cheaters are believed to be human
universals. Yet there are many biological traits that differ within the species. And these differences can
interact with social processes in interesting ways. Biosocial studies, especially those using biological
traits that differ within the population are not commonplace. One such study demonstrated how
hormone experiences (testosterone) ‘facilitate or dampen the effects of socialization and environment
on gendered behavior’ (Udry, 2000: 443). Speci?c behaviors were associated with hormonal history
and subsequent socialization experiences. Exposure to testosterone signi?cantly moderated the effect
of socialization experiences upon certain types of behavior. Strong interactions were evident. Other
types of biosocial interactions have been observed. Schultheiss, Campbell, and McClelland (1999)
have shown that in particular behavioral settings (i.e., competitions) individual motivations, which are
in part learned, affect the level of testosterone. There is a rich two-way relationship between
testosterone and socialization with behavior.
A biosocial study of the relationship between adolescents and their parents is directly relevant to our
research. Booth et al. (2003) found that the quality of the parent–child relationship mediated the effect
of testosterone upon certain behaviors. Speci?cally, when the parent–adolescent male child
relationship was of low quality and testosterone was high, there was more evidence of (antisocial)
risk-taking, behaviors like skipping class and shoplifting. The propensity for testosterone to directly
increase risk-taking (or be less fearful) has been observed in other studies (Boissy & Bouissou, 1994;
Dabbs et al., 1990b). But Booth et al. (2003) demonstrated an interactive association between a familial
Copyright # 2007 John Wiley & Sons, Ltd. J. Organiz. Behav. 28, 451–466 (2007)
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454 R. E. WHITE ET AL.
variable (parent–child relationship) in conjunction with a biological variable (testosterone level) upon a
behavior (risk-taking). Our study takes a similar approach with a signi?cant difference, as explained
below.
Booth, Johnson, Granger, Crouter, and McHale (2003) only studied the impact of testosterone and
parent–child relationship quality upon anti-social risk-taking behaviors. But some evolutionary
theorists have suggested this is one end of a continuum of behaviors (Ellis, 2004; Mof?t & Walsh,
2003). Just as characteristics of familial relationships can channel risk-taking toward anti-social
behaviors it is plausible that other characteristics of the family can channel this propensity toward
prosocial risk-taking behaviors, like new venture creation. Being raised in a family where other family
members, most notably the mother or father have started and run their own business would help to
direct any innate predispositions toward similar kinds of endeavors.
A biosocial theory of entrepreneurship
Any biosocial theory requires a biological component and a social component, which together
explain behavior. Our behavior of interest is entrepreneurship; speci?cally new venture creation.
Arguably new venture creation requires the taking of risk. Certain biological characteristics,
particularly testosterone, have been theoretically and empirically linked to risk-taking (Mazur &
Booth, 1998a). T levels affect not only obvious physiological characteristics (e.g., muscle
development) but also more subtle psychological processes. T can affect our psychology by
in?uencing brain structure during early development. The circulating level of testosterone can also
affect ongoing neural processes by directly or indirectly activating receptors present in the adult
brain. The effect of Tupon speci?c neural mechanisms and how this in?uences behavior is only just
being explored. However, at a more general level, T is one of the most studied of the endocrine
hormones (Dabbs and James, 2000; Mazur & Booth, 1998a; Mazur & Booth, 1998b).
Social factors, notably family business background, have also been associated with the propensity to
start a new venture. This study extends the prior research relating risk-taking behavior, family
background and testosterone to the prosocial risk taking behavior of starting a new venture. Generally,
we believe individuals with higher testosterone are predisposed toward risky behavior and family
background channels this propensity in a particular direction. When a high testosterone individual’s
family background includes the starting and/or running of a business the two factors, one sociological
the other biological interact to explain the likelihood of that individual being involved in the creation of
a new venture—a biosocial theory of entrepreneurship.
The general proposition consistent with this biosocial model of entrepreneurship is: New venture
creation is more likely to be exhibited by those individuals with a higher basal T level and a family
business background. Each effect is posited to separately and jointly in?uence the likelihood of
entrepreneurial behavior. Stated more formally the sequence of hypotheses is:
H1: Individuals with a family business background are more likely to be involved with the creation
of a new venture.
H2: Individuals with higher testosterone levels are more likely to be involved with new venture
creation.
H3: An individual’s family business background and testosterone level have separate and
independent effects upon the likelihood of involvement with new venture creation (i.e., they have
independent explanatory power).
Copyright # 2007 John Wiley & Sons, Ltd. J. Organiz. Behav. 28, 451–466 (2007)
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A BIOSOCIAL MODEL OF ENTREPRENEURSHIP 455
H4: Those individuals with both higher testosterone level and a family business background are more
likely to be involved with new venture creation (i.e., there is a positive interaction effect).
Organizational Context
The subjects for this study were Master of Business Administration students attending the
Richard Ivey School of Business at The University of Western Ontario. Western is a large, public
institution of higher learning offering a full range of undergraduate, graduate and professional
programs located in London, Canada (population 350 000). The MBA class at the Richard Ivey
School of Business was comprised of four sections of approximately 70 students each (both male
and female). The entire 2002–2003 class was comprised of 272 students, 25 per cent were female,
average age was 30 with 5.5 years of work experience. Self-described ethnicity was 61 per cent
Caucasian, 32 per cent Asian and 7 per cent other.
Each data collection session commenced with a brief explanation of the study protocols, followed
by the collection of the ?rst of two saliva samples from each participant. Prior to the study, students
had been advised not to consume any food or beverages (other than water), smoke, or chew gum for
1 hour prior to the saliva collection. Subjects were provided with sugarless gumto help stimulate the
production of salvia. The saliva was maintained in sealed test tubes for 24 hours at roomtemperature
to allow for settling of particulate matter and then frozen to À20 degrees Celsius. It was not thawed
until the laboratory assays were performed. Data collection took place in February 2002; assays
were done during May 2002.
The number of subjects included in this study was determined by the assaying procedures. The
laboratory performed testosterone assays in ?xed batch sizes based on ‘kits’ of the reagent
chemicals. Our ?nal sample of 33 entrepreneurs, 29 matched pairings, and 53 others totalled to 115
subjects, each of whom provided two saliva samples exhausted the maximum available test kit
capacity of 230 samples.
Method
Sample
Because basal testosterone (T) levels vary during the day and seasonally, and can be affected by
exogenous events it is important to collect T samples under controlled conditions. The desired control
over collection procedures was most easily achieved with a student population. Accordingly
participants in this study were all full-time MBA students at a major North American business school.
The MBA class has four sections of approximately 70 students each (both male and female).
Timetables were arranged so data collection took place in a short time frame. Consistent with university
research policies students were free to opt out of any or all parts of the study; to ensure con?dentiality
Copyright # 2007 John Wiley & Sons, Ltd. J. Organiz. Behav. 28, 451–466 (2007)
DOI: 10.1002/job
456 R. E. WHITE ET AL.
student identities were not recorded. Numbers were assigned to all volunteers and used to link the data
elements including: entrepreneurial background and personal and demographic data, and two saliva
samples to be assayed for T.
All students were invited to participate in this study but because of the small number of females
participating (21 of 67 students) only male student data was used. (Subjects taking oral contraceptives
were asked to exclude themselves fromthe study). Of the population of 205 male students, 166 chose to
fully participate in the study (81 per cent).
Measures
Entrepreneurship
Within the subset of 166 male participants, 46 self-identi?ed as having prior involvement in a new
venture start-up. Using a convergent sorting process the researchers (professors in strategy and
entrepreneurship) assessed the reported new venture involvement of the self-identi?ed entrepreneurs.
This check on self-identi?cation was blind, done prior to the determination of T levels. After immediate
disquali?cation of 13 subjects and review and eventually disquali?cation of 2 others, a total of 31
subjects were retained in the entrepreneurship experience (EE) category. The raw proportion of
agreement between the two researchers was 74 per cent, representing an adjusted inter-rater agreement
coef?cient of 0.6 (Cohen, 1960; Zwick, 1988) or ‘good’ according to Landis and Koch (1977).
The individuals classi?ed as entrepreneurs had led a new venture, personally investing in and
managing the business. Those eliminated from the entrepreneurial sample did not have signi?cant
full-time involvement in the new venture; often they were part-time employees, passive investors, or
board members. Ventures ranged from low-tech (coffee shops) to high-tech (web support for medical
research labs) and also included intelligence testing services, retail stores, manufacturers, and
exporters. The majority of the ventures were based in Canada; ?ve were in China and three in the United
States. Mean values for ?rm size were seven employees and annual revenues were C$600 000.
Testosterone
Saliva was collected in polystyrene test tubes, individually labeled and pretreated with sodium azide as
a preservative. After the ?rst saliva sample was collected, participants completed a questionnaire
capturing personal data and their entrepreneurial experience. After completion of the questionnaire
students provided a second saliva sample, concluding the process. Shortly afterwards the saliva was
frozen and not thawed until the laboratory assays were performed.
The saliva analysis kit could assay 220 samples. With two saliva samples per participant, this limited
our maximum number of observations to 110 students. Beginning with the list of 31 entrepreneurs, we
?rst developed a set of 31 matched pairs. The pairing was based on the time period during which the
saliva was collected, and then age, ethnicity, and undergraduate degree. T levels changes during
the day, declining signi?cantly from early to late morning (Nieschlag, 1974). Pairs were also matched
on age because of the inverse relationship between age and testosterone levels (Lamberts, van den Beld,
& van der Lely, 1997). Education, speci?cally the level and nature of prior schooling, was selected to
control for opportunity exposure. As such, engineers were matched with engineers, business majors
with business majors, etc. To expand the sample size for this study another 48 male subjects, in addition
to the identi?ed entrepreneurs and matched pairs, were randomly selected from the participant pool for
inclusion in the samples to be assayed. The pool of pair matched and additional non-entrepreneurs was
selected prior to the assays and without knowledge of the participants’ testosterone levels. Subsequent
analysis indicated no signi?cant differences between the pair-matched non-entrepreneurs and other
non-entrepreneurs in our sample. All analysis in this paper includes the total sample of 31 entrepreneurs
Copyright # 2007 John Wiley & Sons, Ltd. J. Organiz. Behav. 28, 451–466 (2007)
DOI: 10.1002/job
A BIOSOCIAL MODEL OF ENTREPRENEURSHIP 457
and 79 non-entrepreneurs. Participants who had self-identi?ed as entrepreneurs, but were later
disquali?ed by the screening process, were not included in the non-entrepreneurial sample.
The saliva was submitted to a double ether extraction assay and employed a single Count-A-Count
Total Testosterone kit (Diagnostic Products, Los Angeles, CA), modi?ed to accommodate the lower
concentrations of T found in saliva. Details of the procedure are described in Moffat and Hampson
(1996). Reported T-levels are the average values of the two samples collected from each participant in
picograms of testosterone per milliliter (pg/ml) of saliva. The testosterone values obtained were
consistent with those reported in prior research (Moffat & Hampson, 1996; Read, 1993). Internal
consistency reliability of the saliva samples was 0.85 (Nunnally, 1978).
Family business
Family business background (FBB) is a dichotomous variable, coded in response to the question: ‘Did
your parent(s) have a family business?’ Like our binary measure for EE, this measure provides a simple
means of classifying participants into categories for analysis. In the present study we are not attempting
to evaluate entrepreneurial success or qualitative aspects of the family business experience and,
accordingly, our measures favor clarity and simplicity over richness and complexity.
Results
Table 1 presents T values by EE and FBB. It can be seen that T values are highest in the top right cell;
those participants who grew up in a family business background and created a new venture themselves.
The upper right cell is statistically different from each of the other three cells ( p <0.05), while none of
the other cells differ statistically from one another.
Table 2 presents the incidence of entrepreneurial behavior as a function of both T-level and FBB. We
split the sample into high and low T based on the sample median (78.7 pg/ml). Within our total sample,
the incidence of entrepreneurs is 31 out of 110 or 28 per cent. This is approximately the frequency
found in the off-diagonal cells of Table 2. However, the frequency is notably greater in the top right cell
(14 entrepreneurs, 13 non-entrepreneurs: 51 per cent) and lower in the bottom left cell (15 per cent).
Taken together, the results presented in Tables 1 and 2 generally support our hypotheses of direct as
well as an additive and interactive in?uence of biology and family socialization on entrepreneurial
behavior.
Table 1. Testosterone level by family business background and entrepreneurial experience
Family business (FBB)
Entrepreneurship experience (EE)
No Yes
Yes 71.0
a
90.8 n ¼49
n ¼29 n ¼20
No 75.2 77.4 n ¼61
n ¼50 n ¼11
n ¼79 n ¼31 n ¼110
Copyright # 2007 John Wiley & Sons, Ltd. J. Organiz. Behav. 28, 451–466 (2007)
DOI: 10.1002/job
458 R. E. WHITE ET AL.
To more rigorously test the hypothesized relationships we employed logistic regression using
entrepreneurial experience (EE) as the dichotomous dependent variable. Pregibon’s (1981) diagnostic
d-beta test indicated no unduly in?uential observations. Equation 1 estimates the direct relationship
between family business background and entrepreneurship. Equation 2 estimates the direct relationship
between T and entrepreneurship. Both effects are included in Equation 3, and an interaction term
is added in Equation 4. The equations correspond to the column entries reported in Table 3. (T is
known to vary with subject age and time of day. We also ran models using the residual of T after
partialling out age and time of day effects. The results are qualitatively identical to those reported in
Table 3.)
Entrepreneurship ðEEÞ ¼ g
0
þ g
1
FBB þ "
1
(1)
Entrepreneurship ðEEÞ ¼b
0
þ b
1
T þ "
2
(2)
Entrepreneurship ðEEÞ ¼ d
0
þ d
1
T þ d
2
FBB "
3
(3)
Entrepreneurship ðEEÞ ¼ u
0
þ u
1
T þ u
2
FBB þ u
3
ðT Ã FBBÞ þ "
4
(4)
The ?rst column results indicate family business background is signi?cantly associated with starting
a newbusiness (H1). Testosterone level is also signi?cantly associated with entrepreneurial behavior as
indicated by signi?cant coef?cient for T in column 2 (H2). These effects are not attenuated when both
variables are included in column 3. (Note the increase in Pseudo R
2
from 0.053/0.056 to 0.102.) These
?ndings support H3. Finally, an interaction term is introduced in column 4. The coef?cient for the
Table 2. Entrepreneurial experience by family business background and testosterone level
Family business (FBB)
Testosterone level (T)
Low High
Yes 27% 52% n ¼49
(6E, 16 N) (14 E, 13 N)
No 15% 21% n ¼61
(5 E, 28 N) (6 E, 22N)
n ¼55 n ¼55 n ¼110
Table 3. Logistic regression analysis
DV: Entrepreneurial experience
[1] [2] [3] [4] [5a] FBB 1 [5b] FBB 0
Family business (FBB) 1.14
ÃÃ
1.10
Ã
1.02
Ã
Testosterone (T) 0.03
ÃÃ
0.03
Ã
0.01 0.04
Ã
0.01
T
Ã
FBB 0.70
y
Constant À1.51
ÃÃ
À3.10
ÃÃ
À3.54
ÃÃ
À1.51
ÃÃ
À3.44
ÃÃ
À1.99
Pseudo R
2
0.053 0.056 0.102 0.117 0.124 0.002
Sample Size
110 110 110 110 49 61Note: Result reported as coef?cients, not odds ratios.
y
p-values <0.10;
Ã
p-values <0.05;
ÃÃ
p-values <0.01.
Copyright # 2007 John Wiley & Sons, Ltd. J. Organiz. Behav. 28, 451–466 (2007)
DOI: 10.1002/job
A BIOSOCIAL MODEL OF ENTREPRENEURSHIP 459
interaction between FBB and T is positive and signi?cant at p <0.08, supporting Hypothesis 4;
although the effect is not as strong as those evident for the direct relationships. Columns 5(a) and 5(b),
respectively, report the relationship between T-level and entrepreneurial behavior within the
subsamples of family business background and no family business background. These results, shown
graphically in Figure 1, illustrate that T is a signi?cant predictor of new venture creation only in the
context of a family business background.
Limitations
There are several possible limitations to the ?ndings fromthis research. First, only males were included
in the current study. All students, both male and female, were invited to participate in the data collection
procedure. The number of female participants was small; 21, and of those, only four self-identi?ed as
having a prior entrepreneurial experience. As a result, there was insuf?cient data on the female
population to do statistical tests and sample size constraints limited our study to males. Basal
testosterone levels are substantially different for males and females and the affects of testosterone may
differ, so pooling male and female data is not advisable (Bateup, Booth, Shirtcliff, & Granger, 2002).
Males and females have biological differences and whether these differences affect business behaviors
is a sensitive question with wide ranging implications (Foss, 1998). Some prior research has found that
Toften has a similar (but not always identical) effect in a female population as it does in a population of
males, even though the basal levels are much lower in females (Bateup et al., 2002; Dabbs et al., 1998;
Harris, Rushton, Hampston, & Jackson, 1996). We suspect the same may be true for entrepreneurial
behaviors but research is required with a larger sample of female subjects to explore the relationships.
Our study was done with MBA students and is subject to the usual caveats about generalizing to the
population of practicing entrepreneurs. However, only those subjects with actual new venture start-up
experience were designated as entrepreneurs. Therefore, these results should generalize to
entrepreneurs, at least to that subset of entrepreneurs that return to higher education after their
entrepreneurial episode. There is no reason to suspect the relationship would be different for this
T level
Prob
(EE)
FBB = 0
FBB = 1
Figure 1. Interaction of T-level and family business background.
Copyright # 2007 John Wiley & Sons, Ltd. J. Organiz. Behav. 28, 451–466 (2007)
DOI: 10.1002/job
460 R. E. WHITE ET AL.
subpopulation. Studying the T level of active entrepreneurs and comparing them to similar
non-entrepreneurs would address the question of broader generalizability.
There is the potential for a causal ordering problem in the design of this study because the
entrepreneurial behavior was exhibited some time prior to our measurement of T. However, this
ordering is not of concern since T levels in males show a high degree of stability under normal
conditions, after the in?uence of endogenous rhythms are taken into account. Vermeulen and Verdonck
(1992) reported an excellent correlation (r ¼0.85) between a single point measure of T level and the
mean of seven samples taken over 1 year. Other studies, using testosterone samples gathered over 6
years (Booth & Dabbs, 1993) and 10 years (Mazur & Michalek, 1998), have also reported that basal
testosterone levels are predictable over time. By the end of adolescence, the basal level of testosterone
is generally consistent from year to year, with a slow decline as each individual ages. ‘Men with
relatively high Tat one time tend to be relatively high at other times too... Furthermore, because basal
levels are stable, it follows that they can be adequately measured at any time, whether before or after the
behavior, and therefore can be adequately assessed in a cross-sectional study’ (Mazur et al., 1998a:
361, italics ours). In the controlled conditions of the present study, the measured level of T is re?ective
of long-term individual differences.
An individual’s production rate of T is over 80 per cent heritable (Meiklie, Stringham, Bishop, &
West, 1988). Therefore high T parents are more likely to have high Toffspring. They may also be more
likely to found (family) businesses (White et al., 2006). Thus the two dependent variables employed in
this research may be casually correlated. If so our research would overstate the importance of nature
(FBB) and understate the signi?cance of nature (T level). Disentangling these effects would require
intergenerational information on both the biology (T level) and sociology (FBB) of the subjects’
forbearers.
Discussion and Conclusion
These ?ndings are supportive of a biosocial theory of entrepreneurial behavior. Nature and nurture
taken together help us to better understand entrepreneurial behavior. However this type of research is
still very much in its infancy and these results must be interpreted with some caution. A true biosocial
model requires more than just independent biological and sociological effects (Equations 1 through 3 in
Table 3). The interaction of these effects must have an impact. For our data set, as modeled in Equation
4, the interactive effect of FBB with T upon the likelihood of EE has intermediate signi?cance. This
research was exploratory and the relatively small sample size limited the signi?cance of the
relationships. Overall we interpret the ?nding as supportive of a biosocial theory of entrepreneurship
(H4) but further research is needed to verify this relationship. More biosocial research needs to be done.
This study helps to inform the broader nature-nurture debate. Most researchers in the organizational
sciences have assumed often implicitly nurture; people are born devoid of inherited or innate
predispositions. Recently this blank slate assumption has been challenged (Pinker, 2002). The
challengers do not argue that biological determinism should replace sociological determinism. Their
case is not for nature to the exclusion of nurture; rather that nurture and nature work together,
hand-in-glove. Upon re?ection most social science researchers accept this basic premise of
co-determination. Only the autonomic nervous system and other basic re?exes cannot be in?uenced by
conscious thought and learned behaviors; yet the brain, the seat of learning, is an organ like all others
‘designed’ by evolution. What we learn and how we act is affected by our biologically evolved
character. The basic premise of biosocial research—the interaction of evolved biological factors with
social forces—is nowrecognized if not employed by most behavioralists. Yet studies by organizational
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DOI: 10.1002/job
A BIOSOCIAL MODEL OF ENTREPRENEURSHIP 461
scientists examining this combined relationship are rare. This research suggests just such a relationship
exists for an important class of business behaviors: entrepreneurship.
Analysis of the data in this study indicates the preponderance of T’s effect on EE occurs in the
presence of FBB. In other words for nature (i.e., T) to have an effect on the likelihood of EE the
individual needs to have the nurture component (i.e., FBB). T has no signi?cant independent effect
upon EE in the absence of FBB. Interestingly this effect is not symmetric. FBB still explains some of
the likelihood of EE, even after the biosocial interaction of T and FBB are included. It may be that
nurture directs the inclinations inherent in the nature component of the individual. T has been
associated with risk-taking (Dabbs, Hopper, & Jurkovic, 1990b; Dabbs, & Morris, 1990). Family
business background may direct but not fully determine the choice of risk-taking behavior. High T
individuals can channel their risk-taking propensity into a variety of activities (i.e., high risk sports,
dominance contests inside established organizations, etc.), and these outlets for innate risk-taking
propensities are also available to individuals with a FBB. However, individuals with a FBB and high T
are more likely than similar high T individuals without a FBB to direct their risk taking into new
venture creation. We did not expect all of the variance in EE to be explained by the interaction of Tand
FBB; there are many other factors in play. But this research ?nds a portion of the variance in EE is
explained by this biosocial interaction.
More generally our research coupled with the work of Booth et al. (2003) suggests that social factors,
especially an individual’s family situation can channel the risk-taking inclinations associated with high
T toward prosocial, asocial or anti-social behaviors. The likelihood of a particular kind of risky
behavior is in?uenced by the individual’s early socialization. This insight is important to biosocial
research and merits fuller examination and explanation as researchers try to better understand all types
of risk-taking behaviors. To explore this proposition future biosocial research should examine early
socialization experiences, T levels and how they relate to a fuller range of risk-taking behaviors by
individuals.This research is indicative of the potential for biosocial research to explore and explain
important business behaviors. Yet research that even hints at biological determinism can still stir
controversy (Miller & Costello, 2001; Udry, 2001). But we believe exploring the combined effect of
biological and sociological factors will lead to a fuller understanding of interesting business behaviors.
The implications for management practice raise interesting questions and possible dilemmas. First it
needs to be restated that this study was exploratory, to our knowledge the ?rst of its kind in the
organizational sciences. This research associated a speci?c business behavior with individual
differences in a particular hormone and the subject’s social/family background. It would be premature
to make prescriptions for managerial practice. We do not yet know if these individual differences are
associated with successful new ventures. However, what if future research veri?es and extends the
general ?ndings of this research, that in combination individual biological and sociological differences
in?uence the likelihood of successful new venture creation? What if sex differences are found to play a
role? What could practitioners do with this knowledge? More signi?cantly, what should practitioners
do with this knowledge? We believe this research should be conducted. It will help us to better
understand ourselves, our children and the underlying factors driving the entrepreneurial dynamic of
our economy. Nevertheless, we also recognize that how the ?ndings from this type of research are
utilized have broader implications that need to be debated.
Acknowledgements
The authors express their appreciation to the SSHRC for providing ?nancial support (MCRI grant #
412980025), Professor James Dabbs for motivating and encouraging this research, Deborah Chiodo
Copyright # 2007 John Wiley & Sons, Ltd. J. Organiz. Behav. 28, 451–466 (2007)
DOI: 10.1002/job
462 R. E. WHITE ET AL.
and Bavani Rajakumar for their research assistance, and the MBA students who participated in this
study.
Author biographies
Roderick White is an associate professor at The University of Western Ontario’s Richard Ivey School
of Business. He is interested in how evolution can inform behaviors of interest to managers and
organizational scientists; more speci?cally his research explores the evolved basis for social structure.
He recently co-edited a special issue of the Journal of Organizational Behavior and serves on the
editorial board of the Strategic Management Journal.
Stewart Thornhill is an assistant professor of Strategic Management and Entrepreneurship and
Colnett-Love Faculty Fellow at the University of Western Ontario’s Richard Ivey School of Business.
Research interests include competitive strategy, ?rm growth and survival mechanisms, and entre-
preneurial behavior. He is a senior research fellow at Statistics Canada and serves on the Editorial
Boards of the Journal of Business Venturing and the International Entrepreneurship and Management
Journal.
Elizabeth Hampson is a professor of Psychology and a faculty member in the Graduate Program in
Neuroscience at the University of Western Ontario. Her research explores the roles of androgens and
estrogens in human behavior and cognitive processes.
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