The Global Entrepreneurship Monitor (GEM), which studies entrepreneurial processes across 35 countries, reports nascent entrepreneurial activity as varying greatly across countries (Minniti, Bygrave & Autio, 2005).Footnote 1 , Footnote 2 For example, some countries exceed a 10% nascent entrepreneurship rate (e.g., Venezuela 19%, Jamaica 11%), while others range from 5 to 10% (e.g., US 9%, Australia 7%, Canada 7%, China 6%), and some are below 5% (e.g., France 4.7%, Italy 3%, UK 3%, Germany 3%, Japan 1%). Regardless, however, of the rate of nascent entrepreneurial activity “Men are more likely to start a business than women. In no country are women more active in starting and owning businesses than men” (Minniti et al., 2005, p. 11). In Canada, between 1999 and 2004, the self-employment rate shows an increase of 0.3% for men and decrease of −0.5% for women (Statistics Canada, 2004). Furthermore, as of 2000 in Canada, only 15% of SMEs were led by a female entrepreneur, while men were lead entrepreneurs in 67% of SMEs. Furthermore, female-owned and led SMEs were reported to be smaller scale, with fewer employees, less often incorporated, had slower growth and were less inclined to exporting than male owned SMEs (Statistics Canada, 2002).Footnote 3 Unfortunately, research into women and entrepreneurship is sparse and underdeveloped (Baker, Aldrich, & Liou, 1997; Brush, 1992; Brush, Carter, Gatewood, Greene, & Hart, 2001, 2004; Menzies, Diochon & Gasse, 2004; Menzies & Tatroff, 2006), but then, so is research into nascent entrepreneurs.

Early attempts to study the venture start-up process involved model building (Cooper, 1970; Gibb & Ritchie, 1982; Greenberger & Sexton, 1988; Martin, 1984; Shapero, 1985) which was subsequently criticized for adopting a narrow theoretical perspective, attempting to develop “universal” theories, and for using flawed methodology (Gartner, 1985; Mason, 1989; Shane, Kolvereid & Westhead, 1991; Reynolds & White, 1997). The methodological criticisms are due to the reliance on retrospective information about the start-up process. The study of nascent entrepreneurs (NEs) was largely spearheaded by Reynolds (2000) to address methodological shortcomings and to build knowledge in an area about which little was known. For example, few studies report on the process of starting a business with real time data, also, owners of operating businesses can be located and interviewed, albeit retrospectively, but people in the process of starting a business, who subsequently abandon their efforts, are not easy to locate and have not been a focus of entrepreneurship research.

A group of international scholars, under the leadership of Reynolds (2000), initiated a large-scale study of NEs and the start-up process (Fig. 1), called the Panel Study on Entrepreneurial Dynamics (PSED).Footnote 4 The ERC conceptual framework, in part, is shown in Fig. 1, and contextualizes the variables we will examine in this study.

Fig. 1
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Conceptual framework

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In this paper we provide a theoretical background to assist with the development of our hypotheses. We explain our methodology and then present results examining the personal characteristics, gestational activities, business characteristics and outcomes of the start-up effort of a sample of Canadian nascent entrepreneurs in relation to gender.

Theoretical framework and hypotheses development

Personal characteristics

With regards human capital, it is well documented that women have a tendency to major at university in health-related subjects, while men are more predominant as science, computers and technology majors (Carter & Brush, 2004; Menzies et al., 2004). There are mixed results regarding growth expectations with one study finding a difference by gender (Schoett & Bager, 2004) whereby Danish male nascent entrepreneurs having higher growth expectations. A study by Matthews and Human (2000) found no gender difference in growth expectations amongst the US PSED respondents. A relationship was found between growth aspirations and start-up motives for female nascent entrepreneurs but not for men in the US PSED study (Cassar, 2004). The proposition that women are more prone to “fear of failure” (Wagner, 2004), has not been supported by GEM studies (Kollinger & Minitti, 2005). Although there are only limited findings, in this, as yet, under-researched area, we can hypothesize that based on these early results of PSED and GEM nascent entrepreneur studies:

  • H1 Nascent entrepreneurs will differ by gender according to university degree major.

  • H2 Growth expectations are higher for male nascent entrepreneurs than for female nascent entrepreneurs.

Gestational (Process) activities, business characteristics and outcomes

In a review of nascent entrepreneurship research, Davidsson (2006) summarized the gender findings as follows: “In essence the results indicate no differences in outcomes; some rather small differences in process, and a marked and consistent difference in entry” (p.37).Footnote 5 Davidsson & Honig (2003) analyzing the Swedish ERC data, found process variables or outcomes did not differ by gender, apart from a slightly lower number of months for business gestation for women compared to men.

Alsos and Ljunggren, (1998) found some gender differences, for example, that women were slightly less likely to prepare a formal business plan, but were significantly more likely to apply for government funding and were less likely to hire employees. GEM data indicate that the growth trajectory for female-led new business is less steep than that for male-led new businesses, with women generally expecting to hire fewer employees (Minniti, Arenius, & Langowitz, 2004). Davidsson and Honig (2003) tentatively suggested that women completed the gestational period more quickly than men, but the effect was slight. We thus hypothesize as follows:

  • H3 Nascent entrepreneurs differ by gender according to completion of a formal business plan, with women less frequently completing a formal business plan.

  • H4 Nascent entrepreneurs differ by gender according to their expectations of hiring employees, with women having lower expectations of employee hiring.

  • H5 Nascent entrepreneurs differ by gender according to the length of the gestation period, with women taking a shorter time-frame to achieving an operating business.

Based on H5, we thus hypothesize;

  • H6 Nascent entrepreneurs differ by gender according to the number of activities they complete during the gestation period, with women completing fewer, due to the shorter time-frame assumed in H5.

GEM findings indicate some gender differences in early-stage business characteristics. For example, businesses started by men used an average of $65,000 (US) start-up capital, but the average for women was only $33,000. The type of new business created has been found to vary according to gender, with women utilizing “known technology” and “targeting existing markets” (Minniti et al., 2004, p. 13), whereas Newbert (2005) found no gender effect according to type of business, whether hi-tech or not. We thus hypothesize that:

  • H7 Nascent entrepreneurs will differ by gender according to the type of business created.

  • H8 Nascent entrepreneurs will differ by gender according to the business target market.

There is no established position on whether human, social and financial capital variables influence the achievement of an operating business (Davidsson & Honig, 2003). Diochon, Menzies and Gasse (2003) reporting on the early stages of the PSED Canadian study as well as Parker and Belghitar (2004) and Newbert (2005) for the US PSED study, found no relationship between outcomes and gender. Based on these findings, we hypothesize that:

  • H9 There are no gender differences regarding the outcome of being able to achieve an operating business.

Methodology

The ERC longitudinal methodology was adopted for this research (Reynolds, 2000). The sample of Canadian nascent entrepreneurs was generated from an initial 49,763 randomly selected telephone numbers. Our unit of enquiry was the “household”, and we limited our study to adults, 18 years of age and older. We ascertained that nascent entrepreneurs were present in 1.8% of households (margin of error less than 0.2%) as of 2000. Our stratified proportional sample is representative of all Canadian households from all provinces. We subsequently phoned and interviewed our respondents, yearly for five years, and also mailed surveys.Footnote 6

In this study, respondents were asked in the four follow-up calls, whether the business was operating. By operating, it was meant that the business had to have been operating at a profit for a period of 6 months, including paying salary to the entrepreneur. This variable constitutes the major outcome of the study. Positive responses at time 4 or responses of those missing at time 4 but operating at time 3 were coded as operating, and all other responses were coded as not operating. As appropriate, t and chi-square tests were used to compare the answers of male and female respondents. Variables with relatively little missing cases were chosen for study. Following the lead of Davidsson and Honig (2003), an index of business gestation activities was formed from the variables listed in Table 2. As listed, all components were dichotomies, although some represented successive steps of a single activity, higher steps being weighted more heavily.Footnote 7 One activity, opening a bank account, was added. In this paper we used gestational activities as completed by the third year of the study. With the dichotomous outcome of whether or not an operating business was created, logistic regression was chosen as the basic statistical model. Variables were entered hierarchically, but for brevity of presentation only summary tables are presented below.

Results

Sixty-two percent (94) of respondents were male and 36% (54) were female. Table 1 shows descriptive statistics of the entrepreneurs. Table 2 illustrates the gestational activities undertaken by respondents with the mean number of activities completed being 15, with a minimum of 3 and a maximum of 30. The business characteristics are shown in Table 3. Although these results present interesting information about nascent entrepreneurs, the start-up process and the businesses, we do not discuss these results in this paper, but present them here for information purposes and to show the variables we utilized in our analysis.

Table 1 Personal characteristics of entrepreneurs
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Table 2 Nature and distribution of business gestation activities
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Table 3 Business characteristics
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Gender differences

The differences between our male and female nascent entrepreneurs are presented in Table 4. We found support for H1 (Nascent entrepreneurs will differ according to university degree major), as there were significant differences for area of university education, with men more concentrated in applied science and computers, and women more often majoring in health related subjects. Not unexpectedly, females reported performing a higher percentage of household tasks than did males. H2 (Growth expectations are higher for male nascent entrepreneurs than for female nascent entrepreneurs.) was supported, at least partially, in that males estimated a higher probability that their business would be operating in 5 years. In addition, males had more startup experience, were more likely to own their home, and had more friends and neighbors with businesses.

Table 4 Personal and business characteristics with gender differences
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We found no support for H3, that nascent entrepreneurs differ by gender according to completion of a formal business plan. H4, that nascent entrepreneurs differ by gender according to their expectations of hiring employees, was also not supported. H5, that nascent entrepreneurs differ by gender according to the length of the gestation period, was also not supported. We found no support for H6 as there was no difference between the total number of gestational activities completed by male and female entrepreneurs.

Of the component activities there were significant differences only on two. Women were significantly less likely than men, to have a copyright for materials used in their business, at 6% and 21% respectively (χ 2(2) = 7.89, p < 0.05). Whether the business was reported to be high tech differed between male and female entrepreneurs, supporting to some extent H6 (Nascent entrepreneurs will differ by gender according to the type of business created). In addition, women (37%) also were significantly less likely to have a dedicated phone line for the business than were men (84%), (χ 2(1) = 4.07, p < 0.05). Of the variables describing the nature of the business, two pertaining to the geographical range of activities and target market were significant. Women estimated that a higher percentage of their customers would be local than did men, while men estimated that a higher percentage of their customers would be international (Table 4), thus supporting H7 (Nascent entrepreneurs will differ by gender according to the business target market).

Regarding outcomes, the creation of an operating business, the difference between males and females was not significant, but there was a trend. Women were somewhat more successful in creating operating businesses (χ 2(1) = 3.64, exact one-sided p = 0.08). Thus we found an indication that H8 (there are no gender differences regarding the outcome of being able to achieve an operating business), though supported, requires further investigation.

Predicting the creation of an operating business

With special interests in gender of entrepreneur and in gestational activities, our first model used those two variables and the interaction to predict the outcome. It was found that the best model included only gender and gestational activities (G3) with results as follows (Table 5). This model is significant (χ 2(2) = 19.18, p < 0.001).

Table 5 Predicting the creation of an operating business from gender and other variables
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It is interesting to note that gender, when entered on step 1 was not significant, and became so only when G3 was added to the model. When the interaction was subsequently added the step did not explain significant variance. The Nagelkerke R Square statistic for this model was 0.19. Having established this basic prediction model, we wished to find variables which either directly or in interaction with gender, would increase the prediction of operating outcome. Variables were entered with gender on step one, G3 added on step 2, and the interaction between gender and each variable on step 3. Since the interaction of G3 and gender was not significant in the model below, it was not entered in subsequent models. None of the personal variables added significant prediction to the model (Table 5). Of the business variables, the interaction of gender and being a member of a startup team added significantly to the model which was significant (χ 2(4) = 23.16, p < 0.001) (Table 6). In this model the direct effects of neither gender nor startup team was significant. G3 was significant, and when the interaction was added to the model, the step test was significant (χ 2(1) = 3.86, p < 0.05). The Wald test is also significant for the interaction term. It would appear that when G3 is controlled, being a woman as well as a member of the startup team increases the odds of success by a factor of almost 6. The Nagelkerke R Square statistic for this model is 0.22 and the Hosmer and Lemshow test of fit is good at 0.58. Follow-up contingency table testing shows that there is a strong relationship between gender and success in establishing an operating business (χ 2(1) = 4.45, p < 0.05) for those who were members of a startup team, but no relationship among those who were not. Thus, team membership seems to benefit women more than men.

Table 6 Predicting the creation of an operating business from gender and other variables
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Summary and conclusion

Our paper presents an exploratory longitudinal study of a random sample of Canadian nascent entrepreneurs. We examined the differences between male and female personal characteristics, gestational activities and the ability to achieve an operational business. We tested nine hypotheses which were generated from the early-stage research into this relatively new research stream of nascent entrepreneurship and the results are summarized in Table 7. We ascertained that male and female nascent entrepreneurs differ according to university degree major. We also found that males tend to have greater growth expectations and started businesses more frequently that were hi-tech. Female nascent entrepreneurs tended to expect to do business more with local clients than men who had higher expectations of doing business internationally. We did not find any evidence to support gender differences in relation to completion of a formal business plan, a greater likelihood to hire employees, or different duration of gestational activities.

Table 7 Hypotheses: Results of testing
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In sum, there appear to be few differences between male and female nascent entrepreneurs. Among the many personal characteristics which were compared, only a few were significantly different (Table 4). The differences that do exist, we tentatively suggest, point to male nascent entrepreneurs having more factors that lead to confidence building. For example, owning a home, being less burdened by household or childcare task, having friends and neighbours who own businesses, having previous start-up experience, expecting that the business will be around in 5 years, having a hi-tech business and expecting to trade internationally are all factors that could be construed as contributing to enhanced self efficacy, networking opportunities and time to work on the start-up. Despite these differences between men and women, there is no significant difference in the likelihood between men and women of achieving an operating business. There is a slight tendency that shows women may be more likely to more frequently achieve an operating business.

In terms of predicting who will be able to achieve an operating business, we found that women who were members of a start-up team were significantly more likely, in fact six times more likely, to achieve an operating business. This is an important finding which has implications for a range of stakeholders. For example, practitioners, educators and policy makers can work to find ways to facilitate team building and through this, directly or indirectly, encourage team starts.

Our study attests to the largest predictor of operating success being good preparation, as represented by the number of gestational activities completed. Only when the number of gestational activities completed is controlled statistically is there a significant difference between women and men which predicts operating success, and more for women who are members of a team.

The limitations of this study are the small size of the sample, and the relatively small number of respondents whose businesses reached operating status. Future studies need to include more respondents so that more subtle predictive relationships may be studied. Furthermore, we aim to study the nature of the teams that our nascent entrepreneurs were part of. We are in the early stages of work on nascent entrepreneurship, but the findings of this study have identified two directions, in particular, for future research, namely nascent entrepreneurial teams and confidence factors as mediated by gender.