Where is my partner? The role of gender in the formation of entrepreneurial businesses

Abstract

This study examines the ownership structure of nascent businesses with a particular focus on the role of gender. Based on theories of gender and entrepreneurship, we examine how male and female entrepreneurs differentially mobilize their preexisting social and cultural capital to launch new businesses. With their limited social and cultural capital, we expect that female entrepreneurs are more likely to establish either a solo or a family-only enterprise rather than a non-family business in comparison to male counterparts. Moreover, we explore the possibility that female-led solo or family businesses tend to show lower performance compared to the male counterpart. Using a nationally representative data of nascent entrepreneurs in the USA, the results suggest that female entrepreneurs are more likely to found enterprises alone or with family members than their male counterparts especially when they lack social or cultural capital. In addition, our findings show that solo or family businesses run by female entrepreneurs tend to display lower initial performance compared to males. The results have important implications for broadening our understanding of the role of gender in the formation of entrepreneurial businesses.

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Fig. 1

Notes

  1. 1.

    71.6% of family ties that female respondent-entrepreneurs utilize to launch businesses are spouses (i.e., husbands), the percentage of which is slightly larger than that of male entrepreneurs (63.2%) who rely on spousal relationships (i.e., wives).

  2. 2.

    We examine whether entrepreneurs’ characteristics differ between the initial sample of all entrepreneurs and this sub-sample of those who have already received revenues from their business activities. The results from chi-square tests suggest that there is no difference in terms of entrepreneurs’ sex (χ2 = 1.356). At the same time, however, difference exists in terms of ownership structure (χ2 = 10.612, p < 0.05). Specifically, entrepreneurs who opened either a solo or a family business are more likely to be included in our sub-sample.

  3. 3.

    As to more detailed information on firm performance, only expected annual revenue is asked in the survey.

  4. 4.

    In this variable, there are a few outliers who report from 700 up to 1500 in the number of individuals they supervised. We dropped these cases in our main analysis to check for robustness of results, and the results do not change in any qualitative sense.

  5. 5.

    Regarding the gender difference in industrial types, the chi-square analysis shows that females are more likely to open businesses in the sector of retails (e.g., retail store, restaurant, bar, or nightclub), service (e.g., health, education, social, business), and finance (e.g., finance, insurance, real estate), while males tend to engage in manufacturing, construction, agriculture/mining, and transportation sectors (χ2 = 45.34***). As to ownership type, solo enterprises are more likely to be established in service, construction, and finance, while family enterprises are more often organized in agriculture and mining (χ2 = 47.42***).

  6. 6.

    The variable with the highest VIF is the White variable; the VIF score for the White variable is 2.51.

  7. 7.

    We include all three interaction terms in a single saturated model since the correlation among any pairs of the interaction terms is very weak. None of the correlation coefficients exceed 0.15. In addition to our saturated model, we include each interaction terms in separate models and, as expected, the results do not change in any qualitative sense.

  8. 8.

    A majority of family ties that the respondent entrepreneurs rely on are spouses (66.6%). In a separate analysis, we explored the possibility that partnership with a spouse is different from partnership with family members in general. The dependent variable is whether the respondents specifically recruit their spouses to establish businesses. The results are not significantly different from our main model. The effect size slightly decreases from 1.781 times (p < 0.05) for family members in general to 1.520 times (p < 0.05, one-tailed) for spouses only.

References

  1. Adler, P. S., & Kwon, S. W. (2002). Social capital: prospects for a new concept. Academy of Management Review, 27(1), 17–40.

    Article  Google Scholar 

  2. Aldrich, H. E. (1989). Networking among women entrepreneurs. In O. Hagan, C. Rivchun, & D. Sexton (Eds.), Women-owned businesses (pp. 103–113). New York: Praeger.

    Google Scholar 

  3. Aldrich, H. E., & Cliff, J. E. (2003). The pervasive effects of family on entrepreneurship: toward a family embeddedness perspective. Journal of Business Venturing, 18(5), 573–596.

    Article  Google Scholar 

  4. Aldrich, H. E., Elam, A. B., & Reese, P. R. (1995). Strong ties, weak ties, and strangers: do women business owners differ from men in their use of networking to obtain assistance? Washington: Small Business Foundation of America.

    Google Scholar 

  5. Alsos, G. A., Isaksen, E. J., & Ljunggren, E. (2006). New venture financing and subsequent business growth in men-and women-led businesses. Entrepreneurship Theory and Practice, 30(5), 667–686.

    Article  Google Scholar 

  6. Baron, R. A., & Tang, J. (2008). Entrepreneurs’ social skills and new venture performance: mediating mechanisms and cultural generality. Journal of Management, 35(2), 282–306.

    Article  Google Scholar 

  7. Bird, B., & Brush, C. (2002). A gendered perspective on organizational creation. Entrepreneurship Theory and Practice, 26(3), 41–66.

    Article  Google Scholar 

  8. Boden, R. J., & Nucci, A. R. (2000). On the survival prospects of men’s and women’s new business ventures. Journal of Business Venturing, 15(4), 347–362.

    Article  Google Scholar 

  9. Bosma, N., Van Praag, M., Thurik, R., & De Wit, G. (2004). The value of human and social capital investments for the business performance of startups. Small Business Economics, 23(3), 227–236.

    Article  Google Scholar 

  10. Bourdieu, P. (1973). Cultural reproduction and social reproduction. London: Tavistock.

    Google Scholar 

  11. Bourdieu, P. (1986). The forms of capital. In J. Richardson (Ed.), Handbook of Theory and Research for the Sociology of Education (241–258). New York: Greenwood Press.

    Google Scholar 

  12. Bradley, H. (2007). Gender. London: Polity Press.

    Google Scholar 

  13. Brannon, D. L., Wiklund, J., & Haynie, J. M. (2013). The varying effects of family relationships in entrepreneurial teams. Entrepreneurship Theory and Practice, 37(1), 107–132.

    Article  Google Scholar 

  14. Brush, C. G., de Bruin, A., & Welter, F. (2014). Advancing theory development in venture creation: signposts for understanding gender. In K. Lewis, C. Henry, E. J. Gatewood, & J. Watson (Eds.), Women’s entrepreneurship in the 21st century: an international multi-level research analysis (pp. 11–31). Cheltenham: Edward Elgar.

    Google Scholar 

  15. Burke, R. J., & McKeen, C. A. (1994). Career development among managerial and professional women. In M. Davidson & R. Burke (Eds.), Women in management: current research issues. London: Chapman.

    Google Scholar 

  16. Burt, R. S. (1992). Structural holes. Cambridge: Cambridge University Press.

    Google Scholar 

  17. Campbell, K. E., & Rosenfeld, R. A. (1985). Job search and job mobility: sex and race differences. Research in the Sociology of Work, 3, 147–175.

    Google Scholar 

  18. Carter, N. M. & Williams, M. L. (2003). Comparing social feminism and liberal feminism: The case of new firm growth. In J. Butler (Ed.), New perspectives on women entrepreneurs (pp. 25–50). Charlotte: Information Age Publishing.

  19. Carter, S., Shaw, E., Lam, W., & Wilson, F. (2007). Gender, entrepreneurship, and bank lending: the criteria and processes used by bank loan officers in assessing applications. Entrepreneurship Theory and Practice, 31(3), 427–444.

    Article  Google Scholar 

  20. Chaganti, R., DeCarolis, D., & Deeds, D. (1995). Predictors of capital structure in small ventures. Entrepreneurship Theory and Practice, 20(2), 7–18.

    Article  Google Scholar 

  21. Coleman, J. S. (1988). Social capital in the creation of human capital. American Journal of Sociology, 94, S95–S120.

    Article  Google Scholar 

  22. Coleman, S., & Robb, A. (2009). A comparison of new firm financing by gender: evidence from the Kauffman Firm Survey data. Small Business Economics, 33(4), 397–411.

    Article  Google Scholar 

  23. Cromie, S., & Birley, S. (1992). Networking by female business owners in Northern Ireland. Journal of Business Venturing, 7(3), 237–251.

    Article  Google Scholar 

  24. Davidson, M. J., & Cooper, C. L. (1992). Shattering the glass ceiling: The woman manager. London: Paul Chapman Publishing.

    Google Scholar 

  25. Davidsson, P., & Honig, B. (2003). The role of social and human capital among nascent entrepreneurs. Journal of Business Venturing, 18(3), 301–331.

    Article  Google Scholar 

  26. De Bruin, A., Brush, C. G., & Welter, F. (2007). Advancing a framework for coherent research on women’s entrepreneurship. Entrepreneurship Theory and Practice, 31(3), 323–339.

    Article  Google Scholar 

  27. Dyer, W. G. (2006). Examining the “family effect” on firm performance. Family Business Review, 19(4), 253–273.

    Article  Google Scholar 

  28. Fairlie, R. W., & Robb, A. M. (2009). Gender differences in business performance: evidence from the characteristics of business owners survey. Small Business Economics, 33(4), 375–395.

    Article  Google Scholar 

  29. Fischer, E. M., Reuber, A. R., & Dyke, L. S. (1993). A theoretical overview and extension of research on sex, gender, and entrepreneurship. Journal of Business Venturing, 8(2), 151–168.

    Article  Google Scholar 

  30. Fukuyama, F. (1995). Social capital and the global economy: A redrawn map of the world. Foreign Affairs, 74(5), 89–103.

    Article  Google Scholar 

  31. Gopalakrishnan, S., Scillitoe, J. L., & Santoro, M. D. (2008). Tapping deep pockets: the role of resources and social capital on financial capital acquisition by biotechnology firms in biotech–pharma alliances. Journal of Management Studies, 45(8), 1354–1376.

    Article  Google Scholar 

  32. Granovetter, M. (1985). Economic action and social structure: the problem of embeddedness. American Journal of Sociology, 91(3), 481–510.

    Article  Google Scholar 

  33. Greene, P. G., Brush, C. G., Hart, M. M., & Saparito, P. (2001). Patterns of venture capital funding: is gender a factor? Venture Capital: An International Journal of Entrepreneurial Finance, 3(1), 63–83.

    Article  Google Scholar 

  34. Greve, A., & Salaff, J. W. (2003). Social networks and entrepreneurship. Entrepreneurship Theory and Practice, 28(1), 1–22.

    Article  Google Scholar 

  35. Gupta, V. K., Turban, D. B., Wasti, S. A., & Sikdar, A. (2009). The role of gender stereotypes in perceptions of entrepreneurs and intentions to become an entrepreneur. Entrepreneurship Theory and Practice, 33(2), 397–417.

    Article  Google Scholar 

  36. Gupta, V. K., Turban, D. B., & Pareek, A. (2013). Differences between men and women in opportunity evaluation as a function of gender stereotypes and stereotype activation. Entrepreneurship Theory and Practice, 37(4), 771–788.

    Article  Google Scholar 

  37. Hughes, K. D. (2003). Pushed or pulled? Women’s entry into self-employment and small business ownership. Gender, Work & Organization, 10(4), 433–454.

    Article  Google Scholar 

  38. Ibarra, H. (1992). Homophily and differential returns: sex differences in network structure and access in an advertising firm. Administrative Science Quarterly, 37, 422–447.

    Article  Google Scholar 

  39. Ireland, R. D., Hitt, M. A., & Sirmon, D. G. (2003). A model of strategic entrepreneurship: the construct and its dimensions. Journal of Management, 29(6), 963–989.

    Article  Google Scholar 

  40. Jennings, E. J., & Brush, C. G. (2013). Research on women entrepreneurs: challenges to (and from) the broader entrepreneurship literature? The Academy of Management Annals, 7(1), 663–715.

    Article  Google Scholar 

  41. Klyver, K. (2011). Gender differences in entrepreneurial networks: adding an alter perspective. Gender in Management: An International Journal, 26(5), 332–350.

    Article  Google Scholar 

  42. Lerner, M., Brush, C., & Hisrich, R. (1997). Israeli women entrepreneurs: an examination of factors affecting performance. Journal of Business Venturing, 12(4), 315–339.

    Article  Google Scholar 

  43. Liao, J., & Welsch, H. (2005). Roles of social capital in venture creation: key dimensions and research implications*. Journal of Small Business Management, 43(4), 345–362.

    Article  Google Scholar 

  44. Lin, N. (2000). Inequality in social capital. Contemporary Sociology, 29(6), 785–795.

    Article  Google Scholar 

  45. Lin, N., Cook, K. S., & Burt, R. S. (Eds.). (2001). Social capital: theory and research. New Brunswick: Transaction Publishers.

    Google Scholar 

  46. Linehan, M. (2000). Senior female international managers: why so few? Aldershot: Ashgate Publishing.

    Google Scholar 

  47. Long, J. S., & Freese, J. (2005). Regression models for categorical outcomes using Stata (2nd ed.). College Station: Stata Press.

    Google Scholar 

  48. Marsden, P. (1988). Homogeneity in confiding relations. Social Networks, 10(1), 57–76.

    Article  Google Scholar 

  49. Maurer, I., & Ebers, M. (2006). Dynamics of social capital and their performance implications: lessons from biotechnology start-ups. Administrative Science Quarterly, 51(2), 262–292.

    Article  Google Scholar 

  50. McPherson, J., & Smith-Lovin, L. (1982). Women and weak ties: differences by sex in the size of voluntary organizations. American Journal of Sociology, 87, 883–904.

    Article  Google Scholar 

  51. Moore, G. (1990). Structural determinants of men’s and women’s personal networks. American Sociological Review, 55(5), 726–735.

    Article  Google Scholar 

  52. Munch, A., McPherson, J. M., & Smith-Lovin, L. (1997). Gender, children, and social contact: the effects of childrearing for men and women. American Sociological Review, 62(4), 509–520.

    Article  Google Scholar 

  53. Orhan, M. (2001). Women business owners in France: the issue of financing discrimination. Journal of Small Business Management, 39(1), 95–102.

    Article  Google Scholar 

  54. Payne, G. T., Moore, C. B., Griffis, S. E., & Autry, C. W. (2011). Multilevel challenges and opportunities in social capital research. Journal of Management, 37(2), 491–520.

    Article  Google Scholar 

  55. Powell, G. N., & Eddleston, K. A. (2013). Linking family-to-business enrichment and support to entrepreneurial success: do female and male entrepreneurs experience different outcomes? Journal of Business Venturing, 28(2), 261–280.

    Article  Google Scholar 

  56. Putnam, R. D. (2000). Bowling alone, the collapse and revival of civic America. New York: Simon & Schuster.

    Google Scholar 

  57. Randerson, K., Bettinelli, C., Fayolle, A., & Anderson, A. (2015). Family entrepreneurship as a field of research: exploring its contours and contents. Journal of Family Business Strategy, 6(3), 143–154.

    Article  Google Scholar 

  58. Reagans, R., & Zuckerman, E. W. (2001). Networks, diversity, and productivity: the social capital of corporate R and D teams. Organization Science, 12(4), 502–517.

    Article  Google Scholar 

  59. Renzulli, L. A., Aldrich, H., & Moody, J. (2000). Family matters: gender, networks, and entrepreneurial outcomes. Social Forces, 79(2), 523–546.

    Article  Google Scholar 

  60. Reynolds, P. D., & Curtin, R. T. (2007). Business Creation in the United States in 2006: Panel Study of Entrepreneurial Dynamics II. Hanover: now Publishers, Inc.

    Google Scholar 

  61. Reynolds, P. D., Carter, N. M., Gartner, W. B., & Greene, P. G. (2004). The prevalence of nascent entrepreneurs in the United States: evidence from the panel study of entrepreneurial dynamics. Small Business Economics, 23, 263–284.

    Article  Google Scholar 

  62. Robb, A. M. (2002). Entrepreneurial performance by women and minorities: the case of new firms. Journal of Developmental Entrepreneurship, 7, 383–397.

    Google Scholar 

  63. Robb, A. M., & Watson, J. (2012). Gender difference in firm performance: evidence from new ventures in the United States. Journal of Business Venturing, 27, 544–558.

    Article  Google Scholar 

  64. Ruef, M. (2010). The entrepreneurial group: social identities, relations, and collective action: Social identities, relations, and collective action. Princeton: Princeton University Press.

    Google Scholar 

  65. Ruef, M., Aldrich, H. E., & Carter, N. M. (2003). The structure of founding teams: homophily, strong ties, and isolation among US entrepreneurs. American Sociological Review, 68(2), 195–222.

    Article  Google Scholar 

  66. Scase, R., & Goffee, R. (1989). Reluctant managers: their work and lifestyles. London: Unwin Hyman.

    Google Scholar 

  67. Tatli, A., Vassilopoulou, J., Özbilgin, M., Forson, C., & Slutskaya, N. (2014). A Bourdieuan relational perspective for entrepreneurship research. Journal of Small Business Management, 52(4), 615–632.

    Article  Google Scholar 

  68. Uzzi, B. (1997). Social structure and competition in interfirm networks: the paradox of embeddedness. Administrative Science Quarterly, 42(1), 35–67.

    Article  Google Scholar 

  69. Wellman, B. (1985). Domestic work, paid work and net work. In S. W. Duck & D. Perlman (Eds.), Understanding personal relationships (pp. 159–191). London: Sage.

    Google Scholar 

  70. Welter, F., & Smallbone, D. (2006). Exploring the role of trust in entrepreneurial activity. Entrepreneurship Theory and Practice, 30(4), 465–475.

    Article  Google Scholar 

  71. West, G. P. (2007). Collective cognition: when entrepreneurial teams, not individuals, make decisions. Entrepreneurship Theory and Practice, 31(1), 77–102.

    Article  Google Scholar 

  72. Williams, R. (2017). Marginal effects for continuous variables. Retrieved November 20, 2017. https://www3.nd.edu/~rwilliam/stats3/Margins02.pdf.

  73. Yang, T., & Aldrich, H. E. (2014). Who’s the boss? Explaining gender inequality in entrepreneurial teams. American Sociological Review, 79(2), 303–327.

    Article  Google Scholar 

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Acknowledgments

We are grateful to M. Diane Burton, Brian Rubineau, Wesley Sine, Pam Tolbert, and the project members of Creativity, Innovation, and Entrepreneurship in the Institute of Social Science at Cornell University for their valuable comments. We also thank anonymous reviewers for their helpful and insightful suggestions.

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Correspondence to Chan S. Suh.

Appendices

Appendix 1

Table 6 Correlations among independent variables

Appendix 2

We analyze the SBO dataset in order to test if our findings on nascent businesses using PSED II can be replicated in the case of new businesses that have already been launched. The SBO dataset covers all non-farm businesses that file tax forms to the Internal Revenue Service (IRS). Therefore, the data provides very comprehensive information on the socio-demographic characteristics and entrepreneurial activities of business owners in the USA. In order to match with the PSED II that was collected between 2005 and 2006, we use the SBO’s Public Use Micro-data Sample (PUMS) that was surveyed in 2007. Within this data, we limit our analysis to young firms with short business histories (5 years or less), and our sample includes over 300,000 firms. Since the data does not include detailed information on the backgrounds and the social relationships of business owners, we fail to include a few important control variables in our models. Despite its shortcomings, however, we believe that the supplementary analysis on the SBO PUMS data can serve as a robustness check for our main analysis using PSED II. While information on the social relationships among business owners is limited, we can at least examine the association between the owners’ sex and the basic ownership structure of their businesses.

In this supplementary analysis, we employ multinomial logistic regression models to explain the determinants of different ownership structure of new businesses. The SBO data provides information on whether the respondents run their businesses by themselves and, if not, whether their businesses are co-owned by family members or not. While we are unable to distinguish between family enterprises and mixed enterprises due to lack of information, we are able to distinguish among solo, family, and non-family enterprises. Among 335,501 young businesses in the data, 197,848 respondents (59.0%) are running solo enterprises, 86,259 respondents (25.7%) own their businesses with at least one family member, and 51,394 respondents (15.3%) run their businesses only with non-family members.

The key independent variable in our analysis is entrepreneurs’ sex. In addition to our main variable, we control for entrepreneurs’ socio-demographic characteristics that are available in this dataset such as race (Whites, Blacks, Hispanics, and others), age, and educational backgrounds (less than college education, college education, and graduate education). We also control the respondents’ prior entrepreneurial experience as a proxy for their professional career and experience. Due to the lack of information in the SBO data, however, we are unable to include the respondents’ extent of social and cultural capital, their marital status, and their status of having a child as control variables in our models. The descriptive statistics of the variables we use in the SBO PUMS data is presented in Table 7.

Table 7 Descriptive statistics of dependent and independent variables: the SBO PUMS dataset (N = 335,501)

Next, we run multinomial logistic regression models to test the effect of entrepreneurs’ sex on the ownership types of new businesses. We measure the likelihood that an entrepreneur runs either a solo enterprise or a family enterprise relative to running a non-family enterprise. Family enterprises include entrepreneurial teams with at least one family member, while non-family enterprises means teams with no family member. We use robust standard errors to adjust the clustered feature of the data by industrial categories. We do not include industrial categories as a series of binary independent variables in our supplementary analysis, since the number of industrial categories in the SBO data, following the North American Industry Classification System (NAICS) code, is much larger than that in the PSED II. Results from our regression analysis are presented in Table 8.

Table 8 Multinomial logistic regression on the relationship between entrepreneurs’ sex and business type using the SBO PUMS dataset

The results are consistent with our main findings on the gendered formation of nascent businesses from the PSED II dataset, namely that female entrepreneurs are more likely to open either a solo enterprise or a family enterprise rather than a non-family business relative to male entrepreneurs. The results indicate that being a female entrepreneur is positively associated with founding a solo enterprise by 2.625 times (b = 0.965, p < 0.001). Also, being a female is positively associated with a 1.476 times increase (b = 0.389, p < 0.001) in founding a family business relative to opening a non-family business. Thus, the results support our expectation that female entrepreneurs are more likely to establish either a solo or a family enterprise.

Among the control variables, our findings on the effect of previous self-employment experience are noteworthy. The results show that having prior experience as an entrepreneur is associated with a 0.495 times decrease (b = − 0.684, p < 0.001) in founding a solo enterprise and with a 0.296 times decrease (b = − 0.351, p < 0.001) in opening a family enterprise in comparison to a non-family enterprise. Thus, experienced entrepreneurs are more likely to recruit a non-family member in forming an entrepreneurial team. Regarding entrepreneurs’ race, the results indicate that Whites are significantly less likely to open a solo business, while Blacks and Hispanics are more likely to do so. Also, Black entrepreneurs are less likely to form a family business than those in the other race category. In terms of age, our findings show that entrepreneurs are less likely to open a solo business and more likely to found a family business as they get older. Finally, one’s years of education also matter in the ownership structure of new businesses. The results show that entrepreneurs with college or graduate education are more likely to form an entrepreneurial team with non-family members rather than a solo or a family enterprise. All in all, the results from our supplementary analysis corroborate our findings on the relationship between entrepreneurs’ sex and the ownership structure of new businesses.

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Lim, Y., Suh, C.S. Where is my partner? The role of gender in the formation of entrepreneurial businesses. Small Bus Econ 52, 131–151 (2019). https://doi.org/10.1007/s11187-018-0027-3

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Keywords

  • Gender
  • Family
  • Female entrepreneurship
  • Entrepreneurial team

JEL classification

  • J15
  • L26