2005-08 - a comparison of female and male...

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Paper presented at the GEM second Conference, Budapest, Hongrie, May 25, 2005.

A Comparison of Female and Male Entrepreneurs – Insights from GEM Canada

Yves Robichaud, Roland Lebrasseur, Nathaly Riverin, Thierry Zinger

Working Paper # 2005-08

May 2005 ISSN : 0840-853X

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ABSTRACT: In Canada and other industrialized countries, female participation in the work force has been accelerating steadily. At the same time, the level of female entrepreneurship has also been increasing: Statistics Canada's Labour Force Survey (2003) reported that there were 826,000 self-employed women in Canada in 2003, accounting for about one third of all self-employed persons. Over the past 10 years, the number of self-employed women has grown by 26 percent, compared with a 16 percent growth rate in male self-employment. Similarly, according to OECD sources (Baygan, 2000, Table A2), the Canadian proportion of women self-employed and business owners has increased steadily over the last three decades, from 25.4 percent in the 1970’s, and 30.8 percent in the 1980’s, to 37.1 percent in the 1990’s. While the earliest of these ratios approximated the OECD average, the Canadian data surpassed this benchmark during the 1980’s (30.8 % versus 26.4%) as well as in the 1990’s (37.1% versus 28.2%). This proliferation of women entrepreneurs has been accompanied by increased research activity on a number of related fronts. For example, based on an exhaustive literature review, Carter et al. (2001) employed six categories to delineate the study of female entrepreneurship: 1) characteristics and motivation of women entrepreneurs, 2) start-up issues - resources and constraints, 3) management style of the female entrepreneur, 4) financing and access to credit, 5) networking and 6) performance and growth of women-owned businesses. Nonetheless, much of the research into this phenomenon has been of limited value in that it lacked a longitudinal approach and/or consistency in methodology (Campbell, 1996; Moore, 1990, Orser et al., 2004; St-Cyr and Gagnon 2004; Vanderwerf and Brush, 1989). The “GEM” project provides an opportunity for researchers to address this research gap. The Global Entrepreneurship Monitor (GEM) is a longitudinal collaborative study dedicated to the measurement of global entrepreneurial activities (Reynolds, Bygrave and Autio, 2004). Since its inception in 1999, GEM has expanded to include 34 participating nations, with the database for each country being updated every year. As such, this study provides a comprehensive platform for exploring the gender/entrepreneurship dynamic. GEM allows for inter-country comparisons using a “total entrepreneurial activity index” (TEA), which represents the sum of “nascent entrepreneurs” and “new firms.”1 A TEA of 8.9 was reported for Canada in 2004 – other country scores ranged from a high of 40.3 for Peru to a low of 1.5 for Japan (the 2004 TEA for the United States was 11.3). More to the topic of this article, the 2004 data indicated that “… men are about twice as likely to start a new business as women” 1 Nascent entrepreneurs are defined as those actively involved in creating a business in the past 12 months, but have not paid salaries or wages for more than three months; in cases where the firm has paid salaries or wages for more than three months, but less than 42 months, it is classified as a new business (Reynolds, Bygrave and Autio, 2004). For purposes of the current study, we have referred to businesses that are beyond this 42 month threshold as established firms; for purposes of simplicity, we have grouped nascent and new firms into a single category, namely emerging firms.

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(Reynolds, Bygrave and Autio, 2004, p. 13). A key driver of these outcomes is ‘propensity for entrepreneurship,’ a concept that has been studied extensively, not only within the context of socioeconomic conditions and government policy (Gnyawali and Fogel, 1994), but also through the prism of the entrepreneur’s background, experience and skills. Entrepreneurial propensity, coupled with a perceived business opportunity, provides the impetus for individuals to initially assemble the resources necessary to create the enterprise and then strive to cultivate a sustainable market position. The aim of this study is to provide some new insights into the dynamics of women-owned enterprises and the implications for business creation and policy making. Accordingly, the paper consists of four sections. In the first section, we review the relevant literature and examine the theoretical platforms that have been used to frame the discussion of male versus female entrepreneurship. In the next section, there is a description of the sample used in this research, as well as a presentation of the salient variables. We then report our empirical results and based on these findings, in the last section, we discuss implications and propose areas for further research.

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Authors :

Nathaly Riverin

Literature Review Entrepreneurs and Gender Differences Many scholars have investigated the premise that female entrepreneurs differ in fundamental ways from their male counterparts, particularly in terms of psychological and demographic characteristics (Brush, 1992; Fischer, Reuber and Dyke, 1993; Sexton and Bowman-Upton, 1990), training needs (Carter, 2000), and/or financing (Coleman, 2002). Other gender differences have been found vis-à-vis the balance between work and family (Bullers, 1999; Carter and Cannon, 1992), and networking skills (Aldrich, Reece and Dubini, 1989; Filion, 1990; Staber, 1993).

Female entrepreneurs also appear to display a distinctive management style (Chaganti, 1996; Cuba et al.,1983; Hisrich and Brush, 1984) involving a greater focus on human relations and active listening. Empirical research suggests that female managers prefer consensus-building with their subordinates (Belle, 1998). Clearly, this type of participative management entails a highly personalized approach with employees; for example, Mionne (2002) has found evidence of this management style among samples of Canadian and French female entrepreneurs. This is often referred to as a maternalistic style, wherein “…employees, especially females, are seen as being part of a family” (Carter and Cannon, p. 71, 1992). In a similar vein, studies by Hisrich and Brush (1984) and Chaganti (1986) have highlighted the fact that females tend to perceive their financial skills as being inferior to those of their male counterparts, but at the same time, believe that they possess superior interpersonal skills.

In addition, other studies have revealed that female business owners are often the beneficiaries of training and experience in fields other than business (Fischer et al., 1993; Hisrich and Brush, 1984). It has also been found that female-owned firms are smaller (Kaplan, 1988; Lee-Gosselin and Grise, 1990; Robichaud and McGraw, 2003) and grow more slowly (Chaganti, 1986; Fischer et al., 1993; Orser et al., 1997; Rooney et al., 2003) than businesses owned by males. These outcomes may well be largely attributable to women’s greater commitment to household responsibilities. For example, a comparative study of Canadian male and female entrepreneurs (Cliff, 1998) indicated that women devote approximately 50 percent more time than men to housework and child care.

Nonetheless, it is important to consider these findings within the context of motivational factors. Indeed, studies of entrepreneurial motivation suggest a wide range of reasons for self-employment: a strong desire for independence and autonomy (Bayad and Nebenhaus, 1994;


Filion, 1997; Ray and Trupin, 1989; Sexton and Bowman, 1985); a desire to be challenged (Cooper et al., 1989); a strong need for achievement and for establishing a reputation within the community (Brockhaus, 1986; Carland et al., 1984; Dubini, 1989). More specifically, much of the research into motivational differences between females and males - Cadieux et al., (2002), Chaganti (1986), Cliff (1998), Hisrich and Brush (1987), Holmquist and Sundin (1988), Kaplan (1988), Rosa et al. (1996) - suggests that while male entrepreneurs often place greater weight on economic objectives, such as profit and growth (Kent et al., 1982; and Stevenson and Gumpert, 1985), the key motivators for female small business owners are the desire for challenge, intellectual growth, personal enjoyment and self-determination (Brush, 1992; Buttner and Moore, 1997; Moore, 1990). Feminist theoretical models Entrepreneurship scholars have adapted certain theories in economics, sociology, and psychology in an attempt further our understanding of the unique characteristics of female entrepreneurs and their firms.

Brush (1992) has provided evidence that female entrepreneurs perceive and manage their business differently than do men. In a sense, when the businesswoman creates a business, she does not simply acquire a separate economic entity, but instead she involves herself in a new network of relationships, which includes family, community, and business - It is perhaps noteworthy that based on their qualitative study of female entrepreneurs in the U.K., Carter and Cannon concluded that for their sub-group of failed enterprises, “…networking was conspicuous by its absence” (Carter and Cannon, p. 130, 1992). Consequently, women would have a tendency to evaluate their performance through a variety of non-financial criteria, such as employees’ and clients’ satisfaction, as well as the balance between work and family commitments. While female entrepreneurs place a great deal of weight on the formation of interpersonal ties, male entrepreneurs would be likely to have a greater need for autonomy and structured decision-making. Sociologists, suggest that such diverging perspectives are the result of social conditioning and role expectancies at home, in school, and in the workplace (Aldrich et al,. 1989).

According to feminism theory, society is based on patriarchy – a hierarchical system of power in which males possess greater economic and social privilege than females (Kendall et al., 2004, p. 30, Table 1.A). An understanding of two differing feminist perspectives, namely liberal and social feminism, can enhance our appreciation of the issues and challenges of female entrepreneurship (Calixte et al., 2005). Each of these paradigms takes a critical approach to the status quo, but suggests different measures to foster female entrepreneurship.

Liberal feminism is rooted in European liberal philosophy that gives primacy to the rational individual in society. The core belief is that each and every person can develop and contribute to society so long as opportunities to do so are available and accessible. When an obstacle exists, the state should remove it. Education is viewed as one of the key opportunities that must be accessible to all. Liberal feminism postulates that women can rationalize and solve problems as effectively as men, but are at a disadvantage because of their lack of experience, lack of management training, as well as the presence of discrimination, for example in terms of financing. Consequently, one can attribute gender differences to the fact that women have not been able to develop their full potential: these differences should evaporate when women are given access to the same opportunities as men (Fisher et al.,1993).


In contrast, social feminism draws on a different, but equally established, tradition of Marxism, in which the individual is viewed as acting within and influenced by economic and social structures (Calixte et al., 2005). Both gender and work are considered social constructions that are collectively maintained, renewed, and occasionally challenged. There are no simple solutions because power differences tend to maintain the existing inequalities that exist in the social structures (Clement and Myles, 2001). The woman is burdened with the “double day” of paid labour and unpaid domestic labour. Her male partner often claims rest privileges because of his full-time employment that contributes more revenue to the household. Many women who desire to work outside the home compromise by pursuing part-time employment and accepting a more gradual pace of career development. With respect to entrepreneurship, women are constrained to small, often micro-businesses, preferring flexibility by working part-time and possibly at home. Social feminists argue that the situation will remain unchanged until the domestic work of women is recognized through some type of monetary consideration and there is an equitable sharing of household responsibilities between men and women.

Other discussions of social feminism (Fisher et al., 1993) emphasize that women develop different skills, understandings, and outlooks on life inasmuch as young girls go through a different socialisation process than that experienced by young boys. Males and females follow different paths to acquire distinctive skills, thus giving rise to gender-specific entrepreneurial behaviours. Hence, women find motivation in tasks they like to perform, rather than in the financial motives that often characterize male-controlled enterprises. For instance, if the female entrepreneur elects not to pursue a rapid growth strategy, it is not because she is handicapped in any way from doing so, but rather because she places less value on expansion of her enterprise.

Method Sampling To ensure that participating GEM researchers have access to uniform, comparable, and reliable data, all primary research data is collected using the same methodology. In Canada, an annual survey involving a minimum of 2,000 respondents is conducted by a local private market research firm. The sample is then weighted in order to ensure a balanced representation from each province by gender (50 percent are females), population and age. For the purpose of this paper, GEM data from 2002 and 2003 have been grouped together. By aggregating this data, we effectively boost the sample size and in turn, are able to execute more robust statistical analyses, including logistic regression with several variables.

Variables The GEM questionnaire encompasses a wide range of variables, and usable responses vary considerably across these variables. Only selected variables have been included as part of the current exploration of the database.

This study focuses on gender differences by evaluating certain of these variables, including but not limited to: age, education, marital status, size of household, knowledge/skills necessary to initiate the venture, income level and motivation to launch the business (necessity or opportunity).


Furthermore, we also examine a number of business variables; for example: number of jobs now and in five years, economic sector (extractive, transforming, business services, and consumer services), selected business strategy variables (newness of technology, newness of product/service, percentage of sales represented by exports), and expected level of competition.

Statistical Tests Descriptive statistics were compiled for the total sample and Chi-square analysis was utilized to compare the male and female sub-groups. Significant findings were sought for individual characteristics as well as business characteristics. In the next stage of analysis, logistic regression analysis was conducted, with gender as the dependent variable and the above-noted variables as predictors. Three models were computed: (1) an overall model including both emergent and established firms; (2) a model specific to only the emerging firms; and (3) a model including only the established firms. The forced method was used, entering all variables simultaneously, in order to compare the potential predictors across the three models. Though the data set suffered from missing data, mean substitution for missing values was not considered appropriate because of the categorical nature of most of the variables. As a result, it was decided to run the regressions on the available data, and omit those variables where the missing cases exceeded 20 percent of the sample. Prior to the regression analysis, a Spearman’s rho correlation, a non-parametric version of the Pearson correlation (Norusis, 1999), was computed for all of the possible predictor variables. Only two correlations above 0.40 emerged from this analysis:

• 0.52 Household size and Number of children (0-9 years old) • 0.55 Household size and Number of teenagers (10-17 years old)

Thus, only the “household size” variable was included in the regressions. With the omission of the two variables that are moderately correlated with household size, there is little evidence of multi-collinearity in the data. The “number of jobs now” variable was also omitted, because of missing data (n=351); but “number of jobs in 5 years” was retained (n=455). These variables were correlated at 0.70, and therefore “number of jobs in 5 years” serves as a strong indication of the current number of jobs. Similarly, “number of owners now” was omitted, because of missing cases (n=381), in favor of “expected number of owners in the future” (n=525). These two items were correlated at 0.997. The final adjustment involved deleting the variable “head of household,” which identified whether the respondent was the main contributor to the household revenues. This variable was correlated at 0.79 with gender.2

2 More specifically, 92% of the female respondents indicated that they were the head of the household. However, 89% of the male respondents also made the same claim. The researchers were concerned about the reliability of this data in that the respondents may have misunderstood the question. Furthermore, inclusion of this variable in the regression model gave extremely robust results that seemed suspect, given such a wide variety of variables.


Also, for reasons outlined in the next section, a second set of regressions was conducted, employing a more select group of explanatory variables.

Results

General Profile of Sample A descriptive analysis of the data identifying the personal traits of the adult respondents (18-64 years old) is provided in Table 1. Some 59 percent were less than 45 years of age; it is also interesting to note that 68 percent held a postsecondary degree or diploma, and three-quarters of the sample are homeowners. Moreover, a wide majority of the respondents i) believed that they possessed the skills necessary to start a business (88 percent) and ii) indicated that they had been motivated to launch the venture because of an opportunity (86 percent)3. Eighty percent of these entrepreneurs work full-time in their firm.

Table 1 Profile of Sample: Entrepreneur’s Personal Traits

Characteristics

Females (n = 206)

Males (n = 369)

Total Sample (n = 575)

% of Sample

36 64 100

Age* • 18-24 • 25-34 • 35-44 • 45-54 • 55-64

6 18 33 31 12

8 25 27 25 15

7 23 29 27 14

Education • Up to secondary • Postsecondary • Postgraduate

30 63 7

33 59 8

32 61 7

Marital status** • No partner • Live with a partner

27 73

38 62

34 66

Knowledge/skills for start-up*** • No • Yes

18 82

9 91

12 88

Work Status**** • Full-time • Part-time

69 31

86 14

80 20

3 This statistic is noticeably higher than the worldwide ratio of 65 percent for opportunity entrepreneurs (Reynolds, Bygrave and Autio, 2004, p. 13).


Work Status – partner**** • Full-time • Part-time • Not working

81 7 12

56 22 22

66 16 18

Head of Household**** • Man • Woman

8 92

89 11

60 40

Income*** • 0-$20,000 • $20,000-$50,000 • $50,000-$100,000 • $100,000+

7 44 36 13

6 30 38 26

6 35 38 21

Fear of failure prevents start-up • No • Yes

82 18

85 15

84 16

Motivation • Necessity • Opportunity

16 84

13 87

14 86

Home ownership*** • Own home • Rent

82 18

71 29

75 25

Household size*** • 1 • 2 • 3+

7 24 69

15 30 55

12 28 60

Perceived business opportunity in next six months****

• No • Yes

60 40

40 60

47 53

Personally know entrepreneur in past 2 years

• No • Yes

42 58

36 64

38 62

Occupation**** • Professional • Business executive • Sales • Clerical • Skilled worker • Unskilled worker • Farmer

25 23 7 18 12 11 3

21 30 6 9 24 7 4

22 28 7 12 20 8 3

*:p<0.10 ; ** : p<0.05 ; *** : p<0.01 ; **** : p<0.001 (Chi-square test)


The women in this sample account for 36 percent of the respondents; this proportion is in line with the OECD data cited in the first paragraph of this paper, thus providing supporting evidence for the trend towards more women choosing self-employment as a career path.

With respect to the following personal variables - level of education, fear of business failure, acquaintance with a practicing entrepreneur or motives for being in business (necessity or opportunity) - no appreciable differences were found between male and female respondents. The similarity in educational backgrounds is consistent with earlier studies (Cohen, 1996; Fischer et al., 1993). At the same time, the current data reveal that a significantly larger proportion of women felt that they did not have enough knowledge and skills to start a business: 18 percent versus 9 percent of men. This variation appears previous work by Watkins and Watkins (1984), which indicated that most women are unprepared for business start-up.

Significant gender differences were also observed in a number of other areas. For instance, women were less likely to work full time in their firm than were men (69 percent versus 86 percent, p<0.001); not surprisingly then, income was lower among women (only 49 percent reported personal income of more than $50,000 per annum, p<0.01). Yet, the women entrepreneurs in the sample were more likely than males to be homeowners.

As illustrated in Table1, the females were much more likely to live with a partner. They also had a greater tendency to be part of a larger household, a result that is reinforced by the fact that 39 percent of the women had two or more teenaged children compared to just 26 percent for the men (p< .01), as well as their slightly higher tendency than men to be in the 35-54 age bracket. It may be then, that rather than representing an impediment to self-employment for women, a larger family simply fits into the broad social network of community, business and family (Brush, 1992); this finding seems to reinforce an earlier Canadian study which suggested a positive relationship between the woman’s number of children and the likelihood that she is self-employed (Arai, 2000).

One of the more robust predictor variables appears to be the perceptions of near-term business opportunities (p< .001). This may reflect a more cautious, deliberate attitude on the part of the women, and again, perhaps a greater tendency to consider the impact of business growth on their entire social network.

Table 2 outlines the ‘business’ characteristics, both for the entire sample and by gender. Nearly 40 percent can be classified as ‘established’ firms, having carried at least one paid employee for over 42 consecutive months. Fully 65 percent of the sample operate within the business services or personal services sectors and only 25 percent employ more than five people (although this proportion increases to 39 percent when the respondents are asked to estimate their future employment complement (five years hence). In light of the relatively small size of these firms and the heavy weighting of service businesses, it is interesting that 20 percent rely on export sales for at least one-quarter of their revenues.


Table 2 Profile of Sample: Business Characteristics

Characteristics

Females (n = 206)

Males (n = 369)

Total Sample (n = 575)

% of Sample

33 67 100

Type of firm • Nascent and new firms • Established

59 41

62 38

61 39

Expected number of owners*** • 1 • 2 • 3+

45 36 19

56 21 23

52 26 22

Current number of jobs • 0-5 • 6-19 • 20+

76 13 11

75 14 11

75 14 11

Number of jobs in 5 years** • 0-5 • 6-19 • 20+

66 14 20

59 17 24

61 16 23

Sales out of the country** • 0% • 1-24% • 25%+

39 44 16

28 50 22

32 48 20

Technology available last year • No • Yes

10 90

13 87

12 88

Product/service new to customers • No • Yes

64 36

60 40

61 39

Economic sector** • Extractive • Transforming • Business services • Consumer services

16 14 28 42

9 28 38 26

11 23 34 31

Expected level of competition • Many competitors • Some • None

53 34 13

49 36 15

50 35 15

*:p<0.10 ; ** : p<0.05 ; *** : p<0.01 ; **** : p<0.001 (Chi-square test)

In terms of male/female comparisons, the business characteristics of these firms were similar in terms of such variables as the expected level of competition and the newness of the


technology and product/service. The main differences were with respect to hiring expectations (only 34 percent of female entrepreneurs expected to have more than five employees in five years, compared to 41 percent for the male respondents), the expected number of owners (that is, females were less likely to continue as sole owners), the greater export intentions of the males, and the economic sector (confirming previous research pointing to a greater frequency of female-owned enterprises within the consumer services sector: Cohen, 1996; Industry Canada, 2003; Watson, 2003). Finally, the greater propensity of women entrepreneurs to anticipate the eventual sharing of ownership with a business partner (p< .01) appears to reinforce their relational approach to business ownership and control.

Results of Regression Analysis

As delineated in Table 3, each of the three logistic models successfully discriminated between genders. These models have both common and distinct predictors of gender. Model 1 includes the entire sample - both emerging and established firms, and best represents the adult population active in entrepreneurial activity. Gender was predicted by five variables at p< .05. When compared to males, female entrepreneurs were more likely to be married (or in a common law relationship), were less likely to perceive a business opportunity in the near future, and were likely to expect a lower level of jobs in five years. In addition, women were likely to report lower levels of exports, and were more likely to be in customer services. In general, these women entrepreneurs appear to be cautious and operate within a niche customer-oriented market.


Table 3 Regression Results using Gender as Dependant Variable

Betas (and Standard Errors) Model 1 - All firms

N=262 Model 2 - Emerging

N=145 Model 3 - Established

N=117 Age Education Marital status Knowledge/skills for start-up Work status Income Failure fear prevents start-up Motivation Home ownership Household size Perceived business opportunity in next 6 months Personally know entrepreneur in past 2 years Expected number of owners Number of jobs in five years Sales out of the country Technology available last year Product/service new to customer Expected level of competition Extractive Transforming Business services Customer services Constant

-0.098 (0.167) 0.362

(0.312) 1.370*** (0.433) -0.412 (0.590) -0.771* (0.412) -0.177* (0.100) 0.453

(0.437) 0.152

(0.483) -0.368 (0.443) -0.179 (0.147)

-0.758** (0.318) -0.064 (0.341) 0.290

(0.195) -0.391** (0.173)

-0.593** (0.258) 0.752

(0.599) 0.098

(0.230) -0.209 (0.235) 1.203* (0.721) -0.248 (0.600) -0.509 (0.559)

1.959**** (0.561) 5.560

(4.044)

-0.233 (0.280) -0.160 (0.517) 1.569** (0.660) 1.072

(0.961) -0.599 (0.642) -0.272* (0.163) 1.179

(0.732) 0.430

(0.801) -0.249 (0.591) -0.378 (0.232)

-1.358*** (0.498) -0.275 (0.524) 0.466

(0.312) -0.701** (0.295) -0.400 (0.378) 2.044** (1.034) 0.516

(0.322) -0.508 (0.370) 1.947* (1.178) -0.582 (0.965) -0.184 (0.924)

2.875*** 90.862) 8.147

(6.240)

0.139 (0.309) 1.059** (0.539)

2.341*** (0.832)

-2.283** (1.167) -1.308* (0.766) -0.258 (0.168) 0.044

(0.738) 0.315

(0.860) -0.796 (1.005) -0.272 (0.262) -0.300 (0.542) 0.248

(0.626) 0.166

(0.327) -0.222 (0.299)

-1.091** (0.514) -0.323 (1.044) -0.541 (0.494) 0.143

(0.379) 0.501

(1.281) 0.258

(0.995) -0.226 (0.958) 1.104

(1.001) 0.262

(6.940) Nagelkerke R² Chi-square Percent accurately classified

0.313 66.442****

78.6%

0.457 56.216****

80.7%

0.424 43.122***

80.3% *p<0.10; **p<0.05; ***p<0.01; ****p<0.001


In ‘model 2’ (emerging firms), gender was predicted by five variables at p< .05, namely marital status, perceived business opportunities in six months, number of jobs in five years, availability of the technology in the last year, and classification of the firm as a customer services enterprise. The female entrepreneurs in this group of emerging firms were more likely to be in a relationship (married or common law), were less likely to perceive business opportunities in the near future, expected lower levels of jobs in five years time, and were more likely to be using new technology and to be operating in the customer services area. These women appear to have modest plans for their firm, but are embracing new technology somewhat more vigorously (p< .05) than their male counterparts. Within ‘model 3’ (established firms), four variables could be identified as useful predictors (p< .05) of gender. Compared to males, female entrepreneurs indicated higher levels of formal education, were more likely to be married, were less likely to think that they had the required knowledge and skills to succeed, and were less likely to export their goods and services. These women have a successful business, and yet seem unsure of their competencies. Their postsecondary education may well be insufficiently business-oriented.

As indicated in Table 3, the effective samples for these analyses are modest in size within the context of twenty-two predictor variables. Errors in Beta estimations are likely, thus eroding our confidence in these models. In order to support our findings, a second set of regressions was computed, including only those predictor variables with p< .12. With a smaller list of variables, the issue of missing data was minimized and the effective sample size increased. However, there was an reultant drop in R2 in these regressions, indicating that the excluded variables originally made some explanatory contribution. With this second regression analysis, the number of observations for ‘model 1’ increased from 262 to 304, and rhe R2 decreased from 0.313 to 0.23. The original regression findings were confirmed with two qualifications : women continued to report lower levels of exports, but « p » increased from <.05 to .07 and thus became only marginally significant; and women reported a lower likelihood of working full-time, with « p » decreasing from <.10 to .02, a significant finding. Similarly, the analysis for ‘model 2’ (emerging firms) resulted in an increase in “n” (145 to 201), and a decrease in the R2 factor (0.457 to 0.233). The findings are somewhat inconsistent with original regression findings. In particular, there was no evidence that women were likely to expect lower levels of employment in five years (p increased from <.05 to .15). However, women were significantly more likely to report lower levels of income than men (p decreased from <.10 to .03). Model 3’ (established firms) also experienced an increase in »n » from 117 to 148, and a decrease in R2 from 0.424 to 0.267. The original regression findings were confirmed with two qualifications : women appeared to be much more likely to indicate a low level of skills and knowledge (p decreased from <.05 to .009); and education was no longer a significant predictor (p increased from <.05 to .19).


In conclusion, in light of the second set of regressions, one is inclined to interpret the original findings (especially those of ‘model 2’) with caution.

Discussion

In several respects4, our findings reaffirm the conventional wisdom pertaining to gender differences. For instance, in contrast to her male counterpart, the self-employed woman is more likely to operate a consumer services business, often on a part time basis – these findings parallel the recent results reported by Rooney et al. (2003). Furthermore, her business will have a lower level of export sales, and her expectations will be relatively modest with respect to both new business opportunities and future hiring of employees; these tendencies are consistent with the idea that “… female entrepreneurs are less willing than male entrepreneurs to become involved in situations with uncertain outcomes…” (Sexton and Bowman-Upton, 1990, p. 29-30). In terms of the study’s comparison of emerging and establish firms, the only variable that was a consistent discriminator was marital status. It may be that for these women entrepreneurs, the concomitant stability and support is an important condition for new business formation, at least more so than for men. This support may come in a variety of forms, including the safety net of having an employed spouse (Cohen, 1996): indeed our descriptive analysis (Table 1) indicates a significant likelihood that the females will have a partner who is employed on a full time basis (p < .001).

For the emerging firm sub-sample, we found support for the conventional notion of women entrepreneurs generating lower earnings and focussing on the service industry (Cohen, 1996; Rooney et al., 2003). In addition, their low propensity for perceiving new business opportunities seems to reinforce the concept of women deliberately keeping their business small for an extended period and eschewing rapid growth strategies as a threat to their relationships – family and other (Carter and Cannon, 1992; Goffee and Scase, 1985). However, these effects are pronounced only within the emerging firms; apparently, once these ventures are more established, women and men entrepreneurs are more alike than different. This may attributable to a ‘survival of the fittest’ phenomenon, whereby the ‘established’ women-owned firms have reached that stage because they did not possess certain of these traits. Yet, it is curious that it within the context of the established firms where we witness a significantly lower export orientation (relative to men) on the part of the female-owned businesses. A recent study by Orser et al. (2004, p. 170) indicated that “... for many women business owners, exporting begins early in the life of the firm.” It appears that the similarity in our sample between male and female owned firms at the emerging stage is consistent with these results, but for some reason, the male firms become relatively more active as exporters once they have crossed the 42 month threshold (as defined in footnote #1).

As we consider the established firms (n=117), the primary differentiation between male and female entrepreneurs is in their sense of whether or not they possessed the necessary knowledge and skills when starting up the venture. This finding may be a function of the women who have reached this stage with their business now retrospectively recognizing their deficiencies; with experience in running the business, perhaps they have acquired a clear awareness of the demands of new venture

4 The five discriminators noted here were consistent throughout both the chi-square and regression analyses.


creation and are less prone than those in the nascent and new stages to overestimate their capabilities. At a more general level, our results serve to inform the earlier discussion of the liberal/social feminism dichotomy. As noted, social feminism emphasizes the centrality of women in a network of social relationships, whereas liberal feminism holds that differences between genders exist only to the extent that women are deprived of experiential and educational opportunities. To the extent that our findings support the perception that at start-up, female owner-managers often lack the opportunities to develop management skills and relevant industry experience (Carter and Cannon, 1992; Cliff, 1998; Kalleberg and Leicht, 1991), there is support for the liberal feminism view. But in contrast, the absence of meaningful differences in terms of educational background serves to contradict this perspective, as do the aforementioned significant results, which depict the woman entrepreneur as being averse to seeking new opportunities or growing her enterprise. These fundamental differences in attitude and behaviour will not be effectively addressed through the gradual removal of perceived barriers or easier access to generic business training programs. While the evidence offered here is tentative, it may be indicative of a shift away from liberal feminism as an effective model for evaluating female entrepreneurship. However, within the current Canadian context, it appears that policy makers are implicitly guided by the liberal feminism perspective, because it provides them with an agenda that is congruent with their political goals within a liberal economy: fostering economic growth through free enterprise. Those responsible for program development want to identify and remove barriers that women experience in their pursuit of entrepreneurship. Examples are access to business education and training, capital, and daycare, and the removal of the “glass ceiling” in large corporations.

We would postulate that Canadian policy makers are less comfortable with the agenda of social feminists, as it calls into question the separation of the family and work spheres, and deviates dramatically from the free-enterprise culture that permeates North America. That being said, policy makers have recognized the influence of social structures on the “glass ceiling.” Business leaders also reject the social feminism paradigm, insofar as they attribute unequal workplace experiences of women to deficiencies or trade-offs on their part (Gazso, 2004). This ideology has been built on the assumption of a dominant male breadwinner and a female caregiver. Gender as a social structure of inequality remains intact despite recent efforts at creating equal workplaces through pay equity and family-friendly work policies Recent GEM data (Filion and Riverin, 2003, Figure 13) reveals that Canadian women have an entrepreneurial activity rate (TEA) that is statistically lower than that of Canadian men (5.3 versus 10.6). These results for 2003 reinforce the GEM data of previous years, thereby revealing a distinct ‘participation gap’ in entrepreneurial activity between females and males, notwithstanding the aforementioned OECD data, which reveals a growing base of Canadian women entrepreneurs..

In order to close the participation gap of women in the workforce, and particularly in entrepreneurial initiative, it may be useful for both policy makers and business leaders to consider a new paradigm where the work and household spheres are inter-connected, instead of separate. This would entail viewing entrepreneurship as a phenomenon that develops in a different manner for women, many of whom do not see business growth as a primary impetus. For example, training would be based on an acceptance of the female modus operandi and accordingly might


involve a greater emphasis on mentoring or even apprenticeship programs (Fischer et al., 1993). The guiding principle for public policy would be the quantity of new enterprises that are formed, instead of the quantity of jobs in each enterprise. Future Research We see an opportunity to replicate the current study within other industrialized countries in an effort to confirm or refute the major differences between genders. For instance, although our findings in terms of age differences were somewhat mixed (p<.10), this would be an interesting line of inquiry to the extent that the way in which women approach business start-up varies according to their age and domestic relationships (Carter and Cannon, 1992, p.15). As already noted, we do find marital status to be a compelling predictor variable. In addition, further research could investigate the impact of the industry sector in which the woman operates on income differences, hiring plans, export intentions and the like. It may be that certain of the differences with male entrepreneurs have much to do with the industry setting and the constraints it imposes on the self-employed female. Also, the recognition of the significant overlap between women’s household and work spheres suggests the need for additional research. When a rigid boundary exists between these two settings, women supposedly strive to maintain and renew the boundary. They would have distinct goals for each sphere of activity. When this boundary breaks down, they presumably resort to trade-offs, for instance, part-time employment or the suppression of business growth to minimize their time commitment. However, our findings suggest that a permeable boundary exists between the domestic and work worlds, and that women entrepreneurs manage them simultaneously in a flexible and integrated manner. Accordingly, women are not focused on the boundary per se but on meeting a variety of goals tied to their family and extended social networks. Trade-offs between household and work concerns are replaced by balancing these concerns within a larger social framework. How do women strive to maintain this balance when it is inevitably challenged by the changing contexts of home and work. Does home-based work represent a solution for most women entrepreneurs? What steps can government take in order to help women entrepreneurs meet their goals, and support them through their periods of financial insecurity brought on by economic downturns, illness and/or care giving (Rooney et al., 2003)? The reality of women entrepreneurs integrating their household and work spheres suggests a second research theme for future investigation: the role of community. Within a relational framework, women entrepreneurs manage a network of relationships that radiates from the household and work settings. Both of these settings are situated within a community in a dynamic exchange of tangible and intangible resources. The fact that most women entrepreneurs create businesses for a local market means that they are important contributors to local economic development. Wong (2002) identified eleven factors widely regarded as determinants of local economic development. While some of these factors, such as financial resources available for investment, are tangible, many others are intangible: quality of life, entrepreneurial culture, community identity, and institutional capacity. The latter refers to local policies (e.g. zoning for home-based businesses) and cooperation within the small business support network. Some relevant issues here might be: What are the appropriate policies and support practices that would


strengthen women’s entrepreneurial efforts? How do issues of quality of life, entrepreneurial culture, and community identity inform these policies and practices? To what extent can a framework of three integrated spheres of activities – home, work, and community – guide the efforts of government to support women entrepreneurs? Limitations This exploratory study is bound by the methodology of the GEM international project. As such, a wide variety of variables are available for investigation, but there are few variables on any given subject. For example, there is only one questionnaire item that deals with the issue of competition. On the other hand, notwithstanding the fact that this study’s results could only be generalized to other industrialized countries, the opportunity to study gender with a national sample is of great value, and can be instrumental in building a reliable base of knowledge in the area of female entrepreneurship.

Conclusions

In general, this research has entailed an exploration of the Canadian GEM data in an effort to develop a particular gender profile, and identify implications for public policy. With regard to the former, this study has addressed two of the dimensions that comprise the aforementioned Carter et al. typology (2001) - characteristics and motivation of women entrepreneurs, and the management style of the female entrepreneur - providing insights into the primary differences between male and female entrepreneurs, and their firms. As the economic contributions of female entrepreneurs continue to expand, it becomes increasingly apparent that countries that fail to fully support women in their business creation and development endeavours will not be realizing their full economic growth potential (Reynolds et al., 2000). In this paper, we propose that the social feminism approach to thinking about females and venture creation and support may well represent an effective response to addressing this challenge at the policy level.


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