The relationship between entrepreneurial intent, gender and personality

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The purpose of this study is to examine gender differences in personality traits of people with and without entrepreneurial intent to assess whether women who intend to become entrepreneurs exhibit particular tendencies that can be fostered. Participants completed an online battery of well-established questionnaires to cover a range of personality traits relevant to entrepreneurship and gender. Participants also answered items concerning intent to become an entrepreneur. A factor analysis of personality traits produced four factors (esteem and power, ambition, risk propensity and communal tendency, the latter reflecting openness and cooperation, without hubris). The authors constructed four parallel regression models to examine how gender, entrepreneurial intent and the interaction of gender with intent related to these four personality factor scores. Participants who endorsed a desire to become an entrepreneur reported higher ambition. Women with entrepreneurial intentions endorsed higher levels of communal tendency than men with entrepreneurial intent. Those without entrepreneurial intent did not show gender differences in communal tendency. Current findings suggest that men and women who intend to become entrepreneurs share many traits, but women with entrepreneurial intent show unique elevations in communal tendencies. Thus, a worthwhile locus for intervention into the gender disparity in self-employment would be providing space and acknowledgement of prosocial motivation and goals as one highly successful route to entrepreneurship. Given the underused economic potential of women entrepreneurs, there is a fundamental need for a rich array of research on factors that limit and promote women’s entry into entrepreneurship. Current findings indicate that personality may be one piece of this puzzle.

Gender in Management
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Mackenzie Zisser
Mackenzie Zisser
Doctoral Student in Clinical Psychology

My research focuses on the application of novel technologies to better understand mechanisms in depression.