Entrepreneurial capital,social values and Islamic traditions: Exploring the growth of women-owned enterprises in Pakistan

Abstract

This study seeks to explore the variables contributing to the growth of women-owned enterprises in the Islamic Republic of Pakistan. Based on a previously established multivariate model, it uses two econometric approaches: first classifying variables into predetermined blocks; and second, using the general to specific approach. Statistical analyses and in-depth interviews confirm that women entrepreneurs’ personal resources and social capital have a significant role in their business growth. Further, it reveals that the moral support of immediate family, independent mobility and being allowed to meet with men play a decisive role in the sales and employment growth of women-owned enterprises in an Islamic country such as Pakistan.

Keywords

entrepreneurial capital growth Islamic traditions social values women-owned enterprises

Introduction

Internationally, research suggests gender differences in business ownership at the personal, professional and institutional levels (Brown et al., 2002; Brush and Hisrich, 1999; Carter et al., 2001; Orser and Riding, 2003; Young and Sexton, 1997). By implication, these differences become manifold in Islamic societies where women are further discriminated against and subjugated due to sociocultural values and traditions in the name of religion (Roomi and Harrison, 2008). In such societies it is difficult for women to embark upon entrepreneurial initiatives; those who are able to do so face additional barriers in growing their businesses.

Research investigating women-owned businesses has developed considerably over the past two decades, yet most of the women’s entrepreneurship development theories have emerged primarily from research undertaken in developed countries with specific social norms and values regarding women’s participation in economic activities (Al-Dajani and Marlow, 2010; Fielden and Davidson, 2005). There is a dearth of studies conducted in differing social contexts, particularly in Islamic societies, where social and familial control over women, their economic dependence on men and restrictions on their mobility determine differential access to education and other critical resources. This raises concern regarding the applicability of theories and models pertaining to women’s entrepreneurship developed mostly in western societies; it also challenges the extent to which these theories apply to Islamic countries such as Pakistan. As far as we are aware, no study has been conducted to date which focuses on the factors contributing to the growth of women-owned businesses in Pakistan (Roomi and Harrison, 2008). This study is an attempt to address this gap. Its main objective is to create an understanding of the factors influencing the growth of women-owned businesses in Pakistan, given the barriers of gender and sociocultural norms.

Theoretical framework

Growth and women-owned enterprises

The literature on women’s entrepreneurship points out that the dearth of entrepreneurial capital is one of the main reasons for women’s low entrepreneurial activity as well as the slow growth of their businesses (Brush et al., 2004; Shaw et al., 2008, 2009). Carter and Allen (1997) argue that access to financial resources and other financial constraints have stronger effects on business rather than choice or intention. Gundry and Welsch (2001) determine that the selection of strategies that focus on market expansion and new technologies, and a willingness to incur greater opportunity costs for the superior performance of their firms, are key factors for the high growth of women-owned businesses, as compared to low- or no-growth firms. They also pointed out adequate capitalization, access to a wider range of financial resources, organized structure, quality control and earlier planning as the differentiating factors for the better performance and growth of women-owned enterprises.

Under the Diana Project, Brush et al. (2004, 2005, 2006) confirmed that ‘women often lacked the economic power and the social and family support structure to grow their ventures’ (2004: 8), and that lack of adequate childcare might cause them to keep their businesses smaller and more manageable. It was also found that one of the most important reasons for the slower growth of women-owned businesses gender related constraints regarding work, family and social life that influence the development of human and social capital. This lack of appropriate social capital to make meaningful exchanges within business networks limits opportunities to raise growth capital and other resources crucial for the development and growth of businesses (Brush et al., 2005).

Although considerable work has been undertaken in recent years to study the factors contributing to or affecting the growth of women-owned enterprises, especially under the Diana Project, the role of social values and cultural traditions in different societies is notably absent. Throughout history, women have been deprived of equal rights to men in almost every field. Even today, the subordination of women in society prevails to varying extents, irrespective of country and culture (Indra and Bharti, 2005). Although the degree of the reasons and their impacts may vary, gender discrimination still persists by having roots in social systems worldwide (Alila and Pederson, 2001; Dhameja, 2002).

Women entrepreneurs in Islamic societies: Pakistan

Some progress has been made over recent years in terms of social, economic, political and technological changes which have supported a new social structure facilitating the gradual movement of women into the public arena from the confinement of the homes (Larty and Hamilton, 2011). The situation in most Islamic countries differs from that of western and other developed or developing countries. No matter to which class or region Islamic women belong, their situation relative to men is one of systemic subordination determined by specific patriarchal forces. Two factors especially influence women’s occupational roles: the cultural norm of pardah (wearing a veil) and the notion of izzat (honour) (Roomi and Parrott, 2008). Pardah has significance as an instrument of sexual segregation and seclusion based on spatial boundaries, where women’s activities are confined mainly inside the home while men work outside, or where women’s extramural activities are concealed behind the portable boundary of the veil (Papanek, 1982). Izzat is the notion that women are repositories of a family’s honour and therefore, that their chastity and good reputation, being highly valued, must be guarded (Shaheed, 1990).

Religious prescriptions, cultural norms and actual practices related to a woman’s status and role vary widely, and are sometimes highly contradictory:

There is considerable diversity in the status of women across classes (the socio-economic status of a woman’s family), geographical regions, ethnic origin and the rural/urban divide due to uneven socioeconomic development and the impact of tribal and feudal social formations on women’s lives. (Roomi and Harrison, 2008: 2)

For example, additional female subordination arises from restrictions on spatial mobility (Shabbir and Di Gregorio, 1996). Often, women are not permitted to move around freely in some families; from early childhood, they are not allowed to go out of the home or mix with males independently. Throughout life, they are protected and discouraged from acting independently. However, for others who allow women to be educated and participate in the economic arena, the inadequacy of transportation facilities, both private and public, limits their physical movement (Roomi and Harrison, 2010).

Despite all of these sociocultural problems, the condition of women is not homogeneous in Pakistan. Many women are able to cross these barriers and actively participate in economic activities. Women’s involvement in the family and other household affairs is perceived to be a social duty rather than an economic contribution (Kamal, 1997). However, due to globalization and societal advancement, the scenario has changed now. Women are playing an increasingly active role in Pakistan’s economy and are now coming into the job market and struggling for income-oriented jobs so as to become independent and to have the same social status as males (Shabbir and Gregorio, 1996). A woman staying at home to take care of the family is no longer described as typical within Pakistani society, especially in the developed urban areas of Pakistan where both husband and wife work to meet their family needs. For those women who start their own businesses, moral support from immediate family members, actual perception of Islamic values regarding women’s participation in economic activities, their mobility and access to transport and their interaction with opposite gender for business, can help them to be successful in their enterprises (Roomi and Harrison, 2010).

Method

Research design

The theoretical models developed by Altinay and Altinay (2006), Basu and Goswami (1999), Evans (1987) and Jovanovic (1982) were used to develop the theoretical model as a basis for econometric estimation for this study. It considered purely economic (Jovanvic, 1987), socio-economic (Altinay and Altinay, 2006) and sociocultural variables (Basu and Goswami, 1999). The model contained the entrepreneur’s personal resources, firm characteristics, social capital, human resource strategy and sociocultural values as different blocks of variables and can be presented as follows:

y i = f (x i 1, \dots, x i j 1, x i j 1 + 1, \dots, x i j, \dots \dots ε i)

(1)

Where yi refers to business growth for the ith firm, where xi1, . . ., xij1 refer to entrepreneur’s personal resources variables ranging from 1 to J 1 and xij1 + 1, . . ., xij refer to firm’s characteristic variables ranging from J 1 + 1 to J, for the ith firm and so on. ϵi is a firm-specific stochastic variable, independent across firms. Basu and Goswamy (1999) partitioned variables into initial factors and expansion strategy variables, as described below:

y i = f (x i 1, \dots, x i j 11, x i j 11 + 1, \dots, x i j 1, x i j 1 + 1, \dots, x i j 12, x i j 12 + 1, \dots, x i j, ε i)

(2)

Equation 2 is transformed into a double log linear specification for the purpose of statistical analysis as follows:

\begin{array}{l} j \log y i = α + \sum β j \log x i j + u i \\ j = 1 \end{array}

(3)

where ui = log ϵi (i = 1, . . ., N), ui ~ N(0, σ2), and yi = (Yt/Ys)1/(t – s) – 1, Yt refers to the ith firm’s sales turnover in period t (which is the last financial year) and Ys is the sales turnover in the first year after start-up, adjusted for inflation.

The variables included in these blocks are explained in Table 1, which specifies their nature and measurement in detail. It also describes whether these are log or dummy variables. All dummy variables with a prefix ‘D’ were used to ‘incorporate qualitative explanatory variables into a linear model’ (Altinay and Altinay, 2006: 211), whereas continuous variables represented numerical data.

Table 1.

Independent variables

Variables	Abbreviation	Name of variable and transformation
Entrepreneur’s personal resources:
Business entry decision	DENTMOT	Dummy variable if negative motives influence business entry decision = 1 otherwise = 0
Business family tradition	DFATH	Dummy variable Businessman/trader = 1 otherwise = 0
Age at business entry	AGENT	Age at business entry
Educational qualifications	DGRAD	Dummy variable Degree holder =1 otherwise = 0
Competent in English (official language)	DLANG	Dummy variable Fluent in English = 1 otherwise = 0
Work experience in the same sector	DEXP	Dummy variable Yes =1 otherwise = 0
Firm characteristics:
Business location	DENTLOC	Dummy variable in the least deprivation Index = 1 otherwise = 0
Business age	AGE	Business age
Legal status at start	DLIMIT	Dummy variable Limited company = 1 otherwise = 0
Entrepreneur’s human resource strategy:
Delegation of functions to non-family members	DOUT	Dummy variable delegation of more than 3 Function ( of 6 ) = 1 otherwise = 0
Employee business training	DTRAIN	Dummy variable if invested in employee Business training = 1 otherwise = 0
Employee incentives	DINCENT	Dummy variable if invested in employee Incentives = 1; otherwise = 0
Formal recruitment	DFORMR	Dummy variable most favourable recruitment method is formal = 1; otherwise = 0
Entrepreneur’s social capital:
Help of close relative(s) in business	DCLSRETV	Dummy variable Yes = 1 otherwise = 0
Help of friend(s) in business at start-up	DFRNDS	Dummy variable Yes = 1 otherwise = 0
Membership of formal groups	DMFGP	Actual number
Importance of informal networking	DINFNTG	Dummy variable Yes = 1 otherwise = 0
Participation in community activities	DPCOMACT	Dummy variable Yes = 1 otherwise = 0
Getting along with …(trust)	DGETTST	Dummy variable Yes = 1 otherwise = 0
Business advice from friends, family	DBSADVS	Dummy variable Yes = 1 otherwise = 0
Sociocultural values and traditions:
Moral support of immediate family	DMORSUP	Dummy variable Yes = 1 otherwise = 0
Awareness of Islam’s actual perspective	DARISLAM	Dummy variable Yes = 1 otherwise = 0
Meeting with opposite gender	DINTMEN	Dummy variable Yes = 1 otherwise = 0
Independent mobility	DINDMOB	Dummy variable Yes = 1 otherwise = 0
Overnight stay for business	DONTSTY	Dummy variable Yes = 1 otherwise = 0

Source: Adapted from Altinay and Altinay (2006) and Basu and Goswamy (1999)

Sample and data collection

The study was undertaken in the Islamic Republic of Pakistan. The names of 1400 women entrepreneurs were randomly sampled from lists at the Federation of Pakistan Chambers of Commerce and Industry, Trade Development Authority, First Women’s Bank and local directories and Yellow Pages. Random sampling was employed to minimize bias in the data collection, although it must be acknowledged that the sample was not representative of a fully broad social spectrum, and mainly comprised small and medium-sized enterprises (SMEs), excluding micro-enterprises.

Data were collected through a questionnaire which included a mixture of scaled, multiple-choice, rank-order items and open-ended questions designed to analyse the factors influencing the growth of women-owned enterprises in Pakistan. The questionnaire was sent to 1200 women entrepreneurs across the country. An online version of the questionnaire was sent to 900 women entrepreneurs through email with some cross-posting. Initial data were collected through 767 completed questionnaires from all over the country. There was a question in the survey regarding respondent interest in being contacted for a detailed face-to-face interview: 96 respondents gave consent, 50 respondents were selected at random and the interviews took place at their business premises. It was not easy for a male researcher to contact and interact with women entrepreneurs to conduct the interviews, especially in isolation, as women usually hesitate to communicate with men in Muslim countries, especially in Pakistan. However, a number of factors created a favourable environment. First, many of the women entrepreneurs participating in the study have been interacting with men independently for the purpose of running and managing their businesses. Second, the researcher has been involved in the capacity-building activities of women entrepreneurs in Pakistan for the last two decades and is well known among women entrepreneurs. His credibility helped in creating an environment of ease and comfort, as well as providing respondents with the necessary assurance of expressing their views in a free and open manner. It is also notable that while 17 out of 50 women entrepreneurs were observing pardah, they were not at all shy in describing their viewpoints with confidence and conviction.

The key factors influencing the growth of these enterprises were grouped into five categories: entrepreneur’s personal resources, sociocultural situation, nature of business/firm characteristics, human resource strategy and social capital (Altinay and Altinay, 2006; Basu and Goswamy, 1999; Roomi and Harrison, 2008). Multiple regression analysis was performed using the Statistical Package for the Social Sciences (SPSS) to test the hypotheses that these groups of factors influence business growth independently and significantly.

A variety of financial measures have been utilized in the literature to evaluate business growth, such as sales revenue (Rosa et al., 1996), number of employees (Birley, 1989; Birley and Westhead, 1990), profit level (Edleman et al., 2005) and number of customers (Baldwin et al., 1994). However, for this study, only compound sales growth and compound employment were adopted. One of the main reasons for doing so was the fact that extracting information from entrepreneurs about annual sales turnover and number of employees is considered to be least problematic through a structured questionnaire (Edleman et al., 2005; Rosa et al. 1996), as these two are recorded mostly for administrative and legal reasons (Barkham et al., 1996; Freel and Robson, 2004; Rosa et al., 1996). The majority of the respondents were reluctant to share information about their customers and profit figures; this confirms the findings of Birley and Westhead (1990) and Edleman et al. (2005).

Based on the method adopted by Altinay and Altinay (2006) and Basu and Goswamy (1999), business employment growth was measured by change in employment since start-up:

E i = E j {(1 + r / 100)}^{a}

where Ei is current employment (i.e. as of 2007–08), Ej is employment at start-up, a denotes the number of years since start-up, and r is the compound average growth rate of employment since start-up.

Compound annual revenue growth was measured by change in annual revenue since the end of the first year of business:

S i = S j {(1 + r / 100)}^{a}

where Si is the annual revenue generated in the most recent year, Sj is the annual revenue generated at the end of the first year of business, a denotes the number of years since start-up and r is the compound average revenue growth rate since start-up.

Depending on the multivariate nature of the relationship between dependent variable (business growth) and independent variables, multiple regression analysis was performed. The main reason for using multiple regression compared to a simple bivariate analysis was due to the problem of not being able to ‘show one variable’s influence on business growth without controlling for the influence of other variables’ (Altinay and Altinay, 2006: 212). The F-test was applied to investigate the significance of a block. The purpose of using this method was to test the effect of all five sets of variables one-by-one on the growth of women-owned enterprises. After identifying the significance of specific blocks of variables, the significance of specific variables was identified through second econometric method. Based on previous studies (Altinay and Altinay, 2006; Basu and Goswamy, 1999) the ‘kitchen sink’ model was used and all the listed variables were included as follows, in order to move to a simpler model for the estimation of regression:

\log y i = α 0 + β i 1 D x i 1 + β i 2 D x i 2 + β i 3 \log x i 3 + \dots + β i 26 D x i 26 + u i

(4)

where D represented a dummy variable and i had a range from 1 to N. In the first stage, all variables were included in the model. The consequent stages involved eliminating the insignificant ones (with p values of greater than 0.9, 0.7, 0.5, 0.3 and 0.1 respectively).

Due to the complexity of the notion of growth, the research question was unfolded in five categories, as mentioned above. The purpose of the enquiry was to gain sufficient understanding of the situation in order to predict future outcomes. Therefore, the method used in this study involved collecting data from women entrepreneurs in Pakistan through a structured questionnaire as well as face-to-face interviews with 50 women entrepreneurs. The triangulation approach helped in unravelling the off-quadrant or deviant dimensions of the phenomenon under investigation. Divergent results emerging from this approach led to describing conclusive and enriched explanations regarding the research problem, and enabled the researcher to be more confident in the presentation of results.

While investigating the role of different factors affecting the growth of women-owned enterprises, the roles of situational factors cannot be ignored because they serve to illuminate contextual behaviour. Accordingly, this approach gave the potential to generate a holistic description, because qualitative data or information complements quantitative data in order to produce the much-sought-after vividness, density of information, reproducibility, precision and clarity of meaning (Weiss, 1968). Informed by this philosophical approach, this research employed surveys (through questionnaires and one-to-one interviews) to obtain data about the situations, practices and views at a given point in time. Quantitative analytical techniques were employed to make inferences from the gathered data about the factors affecting growth. Utilizing a survey enables investigation of variables particularly in that they can be collected about real-world environments. The qualitative data utilized in this research acts as the critical counterpoint to the quantitative approaches. It was inductively analysed and interpreted in response to open-ended questions. The analysis benefits from viewpoints and perceptions which are drawn from the first-hand observations and personal experiences of women entrepreneurs.

Findings and discussion

Compound sales growth

The analysis was conducted for two dependent variables, compound sale growth rate and compound employment growth rate. The ANOVA test for the block of variables showed that the entrepreneur’s personal resources, her social capital and favourable sociocultural factors made a significant contribution to the compound sales growth rate of women-owned enterprises. The general to specific approach to test the significance of independent variables was applied and the results are presented in Table 2. White’s test and Lagrange multiplier tests were conducted for the sample’s heteroskedasticity (Basu and Goswamy, 1999), which confirmed that the sample was homoskedastic. Variance inflation factor ratios for all the excluded variables at each stage confirmed that multicollinearity was not a problem for the variables in the model.

Table 2.

Kitchen sink model equation I

Coefficient
No.	Variable	β	t	Sig.
	Constant	0.018769978	0.432	.783
1	Business entry decision	−0.058657421	−.444	.419
2	Business family tradition	0.187650437	2.014	.001
3	Age at business entry	0.015653987	.329	.421
4	Educational qualifications	0.047689365	.296	.337
5	Competent in English (official language)	−0.069834787	−.674	.575
6	Work experience in the same sector	0.197859898	6.682	.000
7	Business location	0.065676583	.487	.184
8	Business age	−0.056007650	−.191	.719
9	Legal status at start	0.043498974	1.256	.329
10	Delegation of functions to non-family members	0.234354554	.905	.227
11	Employee business training	−0.065367543	−2.776	.765
12	Employee incentives	0.098798767	1.648	.662
13	Formal recruitment	0.235325675	1.696	.564
14	Help of close relative(s) in business	0.076767690	.441	.298
15	Help of friend(s) in business at start-up	−0.065776892	−.764	.624
16	Membership of formal groups	−0.005667987	−.561	.454
17	Informal networking	0.198987245	5.540	.000
18	Participation in community activities	0.165472735	2.265	.207
19	Getting along with… (trust)	0.145987568	.911	.455
20	Business advice from friends, family	−0.023839730	−.369	.581
21	Moral support of immediate family	0.118475923	2.998	.000
22	Awareness of Islam’s actual perspective on women’s entrepreneurship	0.023683248	.539	.281
23	Meeting with opposite gender	0.186518765	1.125	.001
24	Independent mobility	0.289874539	.877	.000
25	Overnight stay for business	0.002344574	.117	.783

Note: Includes all variables. Dependent variable is compound sales growth since start-up.

The final model/equation for compound sales growth rate based on only those variables having significance up to 10 percent was found as follows: compound sales growth = 0.0411+ 0.141 business family tradition** + 0.297 previous work experience*** + 0.222 informal networking** + 0.199 moral support of immediate family** + 0.175 meeting with opposite gender* + 0.311 independent mobility*** (where * = significant at 5%, ** = significant at 1%, *** = significant at 0.1% and the variable without * is significant at 10%; F-value = 58. 544*** means significant at 0.001 level, R² =0.733, R^-2 =0.716, N = 739).

Table 2 shows the kitchen sink model, including all the variables. The results for significant variables are illustrated in Table 3.

Table 3.

Kitchen sink model equation II

Coefficient
No.	Variable	β	t	Sig.
	Constant	0.041148	3.98	.008
2	Business family tradition	0.141675	4.98	.006
6	Work experience in the same sector	0.297387	5.65	.000
17	Informal networking	0.222476	5.69	.002
21	Moral support of immediate family	0.198768	8.65	.001
23	Meeting with opposite gender	0.175185	3.97	.023
24	Independent mobility	0.311445	7.12	.000

Note: Excludes variables with p>0.10 in equation I. Dependent variable is compound sales growth since start-up.

The model has quite a high F-value (58.544*** significant at 0.001 level) with R² value of 73.3 percent. This illustrates that OLS estimation for this model describes 73.3 percent of the variation in the dependent variable, compound sales growth. The adjusted R² is 71.6 percent, demonstrating that this empirical model can illustrate about 71 percent sales growth of women-owned entrepreneurs in Pakistan. The absolute values of all the coefficients (β) between 0 and 1 indicate that the functional relationship between the dependent variable and all independent variables is estimated to be concave (irrespective of being positive or negative). This means that the marginal contribution of each explanatory factor to growth is subject to diminishing returns (Altinay and Altinay, 2006; Basu and Goswamy, 1999).

The equation for compound sales growth shows the significant influence of work experience in the same sector and independent mobility (at .001 level), business family traditions, informal networking, moral support of family members (at .01 level) and (able/allowed to have) meeting with opposite gender (at .05 level). The detailed discussion with 50 respondents helped in gaining an in-depth understanding of the factors contributing to the growth of their businesses. Women entrepreneurs having business family traditions (i.e. immediate family members running their own businesses) and the moral support of their family members appeared to be confident and aware of the problems and issues, they agreed that family members (husband, brother or father) helped them with guidance, advice, providing contacts and in mobilizing resources when needed. Two of the research participants¹ stated:

In the eight years of my entrepreneurial career, whenever I was stuck in a situation or any problem arose, I knew my father and brother were there, at least to give me advice, if not for firefighting. (Asma, entrepreneur, Lahore)

My husband has been running a business for 17 years. Prior to starting my own four years ago, I worked for him for seven years. The experience I gained, the contacts I made and the tricks of the trade I learned during those seven years help me almost every day. It gives me confidence and courage to take calculated risks. And I know I can always get a free advice from my husband whenever I need it. (Samina, entrepreneur, Karachi)

While living in a society reluctant to let women actively participate in mainstream economic activities, although it is slowly and steadily changing, the importance of family moral support was quite evident from the interviews. One of the respondents described this:

The biggest barrier to growth for any women entrepreneur is her male family members if they are not supportive – and they can be her biggest strength if they are supportive of her business activities. I was lucky that my father always supported me. He was the one who not only appreciated my business idea, but also introduced me to a couple of investors for financial resources. (Zareen, entrepreneur, Lahore)

Among the entrepreneur’s personal variables, age at business entry, educational qualifications and competency in English were not significant. It was evident that most of the entrepreneurs were operating enterprise in the service or manufacturing sectors. Most of their stakeholders including labour, customers and suppliers were local and therefore, educational qualifications and English language proficiency were not necessary for communication. The same was described by one of the respondents, Shagufta:

When I started my business I was a bit nervous about my communication skills, as I was not well educated. However, within two weeks I realised that I was dealing mostly with people whom I could communicate in Urdu or Punjabi. I was more practical, rather emphasizing on theoretical aspects. My main emphasis was on creativity in my designs. Once my business grew, I hired two MBAs to take care of the management and accounting aspects of the business. (Shagufta, entrepreneur, Rawalpindi)

The literature describes women entrepreneurs’ endowment in financial, human and social capital as one of the factors restricting their growth (Chell and Baines, 1998; Boden and Nucci, 2000; Brush et al., 2006). However, it also suggests that building and using social capital in an appropriate manner can solve this problem (Brush et al., 2004, 2005). Both the quantitative and qualitative findings of this study confirmed the same, which was explained well by Aasiya:

One year before starting my business, I started going to women entrepreneurs’ networks, attending seminars and training programmes and consciously meeting other women in business. It took a lot of my time, effort and energy, but I tell you, it was worth it. I got my first investor, first supplier of raw material and first customer through my contacts I made during that year. The process has not stopped, even in the fifth year of my business. I still get my clients, my suppliers and even investors from my contacts. I am going to open my fourth branch in two months’ time with the financial share of someone I met at a housewarming party. (Aasiya, entrepreneur, Karachi)

The unequal status of women in Islamic societies is due to the connection of gender with various forms of exclusion, although not uniformly so (Roomi and Harrison, 2008). The same is evident in Pakistani society. In certain classes, women’s interaction with men is frowned upon and in others it is considered highly objectionable; their mobility is also restricted, especially for women belonging to the middle and lower-middle classes. Upper class women have access to private transport and there are very few families which put restrictions on their mobility. For the lower classes it is a matter of economic survival, and most of the women are part of mainstream economic activities. The study showed that women’s independent mobility was highly significant (at .01 level) and meeting with the opposite gender was a significant factor (at 0.1 level) contributing to the sales growth of their businesses. Two of the participants appreciated the importance of these factors:

Any woman entrepreneur’s family has to trust her as far as meeting with the opposite gender is concerned. Until she has restrictions on her mobility and access to other business owners (most of whom are men), it is near-impossible to develop and grow her business. The only other option left is to jump on the bandwagon and work in traditional women-based businesses, where margins are quite low and the competition is cut-throat. (Rabia, entrepreneur, Lahore)

You ask me about the secret of my success. There could be many, but the most important of them all is the trust my husband has in me. Never has he put any restriction on my mobility or my interaction with men. (Namreen, entrepreneur, Rawalpindi)

Compound employment growth

The ANOVA test for the block of variables for compound employment growth rate as a dependent variable showed that personal resources, social capital and favourable sociocultural factors made a significant contribution to employment growth. The general to specific approach to test the significance of independent variables was applied and the results are presented in Table 4. The final model/equation for compound employment growth rate based on only those variables having a significant value in the range of 0 to 10 percent was found as follows: compound employment growth = -.0527 + 0.331 educational qualification*** + 0.076 employee incentives* + 0.288 informal networking** + + 0.219 trust*** + 0.181 moral support of immediate family** + 0.197 meeting with opposite gender* (where * = significant at 5%, ** = significant at 1%, *** = significant at 0.1% and the variable without * is significant at 10%), F-value = 52. 144*** means significant at 0.001 level, R² =0.687, R^-2=0.668, N = 739).

Table 4.

Kitchen sink model equation III

Coefficient
No.	Variable	β	t	Sig.
	Constant	0.078534456	0.645	.467
1	Business entry decision	−0.086765459	−.734	.272
2	Business family tradition	0.185654544	2.674	.058
3	Age at business entry	0.026765654	.426	.868
4	Educational qualifications	0.199767852	2.879	.000
5	Competent in English (official language)	0.024834676	.558	.042
6	Work experience in the same sector	0.117645468	2.217	.008
7	Business location	0.023874678	.243	.387
8	Business age	−0.002657890	−.277	.291
9	Legal status at start	0.047565975	.376	.562
10	Delegation of functions to non-family members	−0.039871234	−1.983	.065
11	Employee business training	0.003464571	.298	.512
12	Employee incentives	0.074645474	1.127	.013
13	Formal recruitment	0.465758432	1.992	.029
14	Help of close relative(s) in business	−0.017354758	−1.002	.301
15	Help of friend(s) in business at start-up	−0.004576849	−.449	.817
16	Membership of formal groups	−0.005765686	−.265	.761
17	Informal networking	0.127657558	2.567	.002
18	Participation in community activities	0.427365464	1.388	.029
19	Getting along with…(trust)	0.290199283	4.365	.000
20	Business advice from friends, family	0.011897239	.112	.816
21	Moral support of immediate family	0.298091876	2.992	.000
22	Awareness of Islam’s actual perspective on women’s entrepreneurship	0.026454786	.427	.311
23	Meeting with opposite gender	0.217564365	1.198	.003
24	Independent mobility	0.225436782	.619	.004
25	Overnight stay for business	0.032765432	.425	.662

Note: Includes all variables. Dependent variable is compound employment growth since start-up.

Table 4 shows the kitchen sink model including all the variables. The results for significant variables are illustrated in Table 5. The model has high F-value than the model for compound sales growth (52.14*** significant at 0.001 level) with R² value of 68.7 percent. This illustrates that OLS estimation for this model describes 68.7 percent of the variation in the dependent variable, compound employment growth. The adjusted R² is 66.8 percent, demonstrating that this empirical model can illustrate about 67 percent employment growth of women-owned entrepreneurs in Pakistan. As for compound sales growth, the absolute values of all the coefficients (β) between 0 and 1 indicate that the functional relationship between the dependent variable and all independent variables is estimated to be concave (irrespective of being positive or negative). This means that the marginal contribution of each explanatory factor to growth is subject to diminishing returns (Altinay and Altinay, 2006; Basu and Goswamy, 1999).

Table 5.

Kitchen sink model equation IV

Coefficient
No.	Variable	β	t	Sig.
	Constant	−0.052745	−2.34	.005
4	Educational qualifications	0.331476	7.87	.000
12	Employee incentives	0.074645474	1.127	.021
17	Informal networking	0.288243	6.14	.002
19	Getting along with… (trust)	0.219231	3.98	.000
21	Moral support of immediate family	0.181487	2.16	.002
23	Meeting with opposite gender	0.196787	1.787	.034

Note: Excludes variables with p>0.10 in equation III. Dependent variable is compound employment growth since start-up.

Three of the variables: informal networking; moral support of immediate family; and meeting with opposite gender, have significant influence on both the compound sales and employment growth rates. Other factors include educational qualifications, employee incentives and presence of trust, which is an important variable for building and maintaining social capital contributing to access, mobilize and generate the human and financial resources needed to develop and grow a business in the long run (Boden and Nucci, 2000; Brush et al., 2004, 2005, 2006; Deakins et al., 2007). One of the respondents, Jeehan, explained her experience as follows:

I believe that one of the most important aspects of making one’s business successful is by building trust with other stakeholders – be it suppliers, employees, existing customers or potential clients. Once I was able to develop trust, other things were easy to follow. (Jeehan, entrepreneur, Multan)

One of the reasons for educational qualifications being an important influencing factor for compound employment growth could be deduced from the following statement:

I completed my degree in management from the university and learned that building powerful teams was one of the most effective ways to achieve success in business. From the very beginning of my business I looked for the best talent in the industry, and those creative and innovative people never let me down. (Noor, entrepreneur, Karachi)

A number of respondents talked about employee incentives and termed them as a win–win situation to retain valuable human capital. One of them, Mussarrat, considered it to be the most valuable tool to restrict brain drain:

It takes at least six to nine months to train an employee, especially for technical jobs. I always try to save those expenses and, above all, my time and energy. I give all my employees lucrative incentives, sometimes even shares in my business, to retain them and make them an effective and efficient stakeholder in my business – and I know it works. (Mussarrat, entrepreneur, Bahawalpur)

It is notable that in this study, those variables pertaining to social capital and favourable sociocultural factors proved to be highly significant contributing factors in the growth of both sales and employment rates of women-owned businesses. However, other factors considered to be significant in previous studies, such as the entrepreneur’s characteristics including behaviour, personality, attitude (Storey, 1994), location (Merrett and Gruidl, 2000; Smallbone and Wyer, 2000), business age (Burns, 2010), size (Cliff, 1998; Grant, 1998), sector as well as age of the entrepreneur, were not significant influencing factors in the growth of women-owned enterprises.

Conclusion

This article addresses a gap in the literature exploring women’s entrepreneurship development in Islamic societies. The analysis, based on two econometric approaches; first, by classifying variables into predetermined blocks and second, using the general to specific approach (Altinay and Altinay, 2006; Basu and Goswamy, 1999), illustrates the factors contributing to the growth of women-owned businesses in the Islamic Republic of Pakistan. It finds six important factors each for both the sales and employment growth of women-owned businesses with three overlapping factors: namely, informal networking, the moral support of immediate family and independence in meetings with the opposite gender. Two blocks of variables, i.e. social capital as well as sociocultural values and traditions, were found to be highly significant for both employment and sales growth. This confirms that sociocultural variables play an important role in the growth of women-owned enterprises in Pakistan. Women entrepreneurs do not enjoy the same opportunities as men due to a number of deep-rooted discriminatory sociocultural values and traditions. Only few receive encouragement from immediate male family members, resulting in limited spatial mobility and a dearth of social capital for most (Roomi and Harrison, 2010). Women whose husbands and families tend to be less discouraging, and those who can afford to have private transportation means for spatial mobility, undoubtedly have an advantage.

The study also found educational qualifications, employee incentives and trust to be important contributing factors to compound employment growth, whereas business family traditions, work experience in the same sector and independent mobility were other important factors for the sales growth of enterprises. This fortifies the findings of previous studies (Henry et al., 2005; Storey, 1994), that education and work experience are important factors for the growth of enterprises. However, the unique contribution of this article is the identification of sociocultural variables affecting or contributing to the growth of women-owned enterprises in Islamic countries. The qualitative analysis authenticates the quantitative findings of the multivariate analysis, strengthening the case for building and using social capital as well as favourable sociocultural conditions for women’s entrepreneurial growth. In addition, the findings of human capital as a vital factor, as measured by educational qualification and work experience in the same sector, reinvigorate the need for development of human capital at the national level, especially for women.

The findings also suggest that most of the women entrepreneurs are concentrated in low growth-oriented, service, handicrafts and textiles sectors. They operate in the local market where most of their customers are women. This is in line with women’s enterprises in other Islamic countries where initial investment is relatively small, as life experiences, hobbies and interests develop into fledgling businesses (Al-Riyami et al., 2003; Roomi and Parrott, 2008). Either they tend to remain small or face enormous problems because of endowment in their entrepreneurial (financial, human and social) capital. Only some who are ambitious, creative, innovative and with adequate human capital, the support of their immediate family members and are able to access, mobilize or generate resources, cross the barrier and grow their businesses.

Implications of the study

There are a number of implications from this anaysis. First, there should be the ‘true interpretation’ of the status of women in Islamic society. Nowhere in the Qu’ran or in the hadith literature are women’s entrepreneurial activities forbidden or even frowned upon: the Prophet Muhammad’s first wife, Khadija, was one of the most prominent traders of Makkah, and even the Prophet himself worked as the general manager of her trade. Therefore, in Islamic societies, there is a need to change the current thinking at school level to promote the inclusion of women in economic activities. This would help by changing the stereotypical images of women in society and encourage family support and help, thereby encouraging young women to develop entrepreneurial ambitions. Second, there is a pressing need to change the current public transport system. Government should take the lead in revising the provision of these services, thereby enabling more women to access transport services and allowing them to travel more freely in the course of running their enterprises. Third, print and electronic media should play a role in portraying appropriate images of a modern Muslim woman who has the right to acquire knowledge through education, own property and manage her own enterprises. This could be facilitated by publishing images of inspirational and positive role models of successful women entrepreneurs. This would not only provide a source of inspiration for women to make specific career choices, but will also create an environment for family members to provide encouragement, as female entrepreneurs seek to establish enterprises.

Footnotes

Funding

This research received no specific grant from any funding agency in the public, commercial or not-for-profit sectors.

Notes

Muhammad Azam Roomi is a principal lecturer and Director of Research at the Centre for Women’s Enterprise, University of Bedfordshire. His research focuses on entrepreneurship education, enterprise development, the growth and performance of SMEs and women’s entrepreneurship development in Asia, Europe, the Middle East and the UK.

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