Critical Evaluation of Research and Theory #5

10 International Journal of Management Vol. 30 No. 3 Part 1 Sept 2013

The Performance of Female Entrepreneurs: Credit, Training and the Moderating Effect of Attitude towards Risk-Taking Isidore Ekpe Universiti Utata Malaysia, Malaysia Razli Che Razak Universiti Utara Malaysia, Malaysia Norsiah Binti Mat Universiti Utara Malaysia, Malaysia

The objective of this study was to examine the moderating effect of attitude towards risk-taking on the relationship between credit and training, and women entrepreneurs’ performance. Entrepreneurship performance is considered a vital link to an overall economic growth of a nation through its positive impact on economic development in terms of job creation and innovations especially at the grassroots. However, despite their crucial role in the economy, entrepreneurs especially women lack micro-finance services such as credit and training for their businesses due to their low income, low educational attainment, societal discriminations and lack of government’s support, mostly in developing countries. Important as credit and training may be to entrepreneurial performance, the attitude of the business entrepreneur towards risk-taking plays a vital role in the utilization of the acquired resources for business performance. A quantitative research method (survey) was used to solicit responses from women entrepreneurs in Nigeria. Data were analysed using descriptive statistics, Pearson Correlation and hierarchical regression analyses. The results indicated that training had significant influence on women entrepreneurs’ performance in Nigeria. Attitude towards risk-taking (ability to expand) moderated the relationship between training and women entrepreneurs’ performance.

Introduction Women entrepreneurs face peculiar challenges in an attempt to achieve success (Hatcher, Terjesen and Planck, 2007) and women entrepreneurs in less developed countries face much more barriers to formal economic participation than those in advanced economies (Allen, Elam, Langowitz and Dean, 2008). Such barriers include lack of education and training, limited access to capital and limited choice of industry. In Nigeria especially, most women entrepreneurs do not have adequate formal education, basic literacy skills or training, and market knowledge for successful business performance (Akanji, 2006; Ibru, 2009).

Limited education invariably provided limited social networks for women entrepreneurs in Nigeria. Availability of social capital should have provided more access to information and resources for the women. It has been observed that most women entrepreneurs in Nigeria possess primary and/or secondary school education; yet skill training and

International Journal of Management Vol. 30 No. 3 Part 1 Sept 2013 11

tertiary education has positive relationship with women entrepreneurs’ performance (Kuzilwa, 2005). Gender-related discriminations in the distribution of social wealth such as education and health could be one of the causes of low education of women in Nigeria. This is the situation in most developing countries (Porter and Nagarajan, 2005; Roomi and Parrot, 2008). Aside education and training, another critical issue to women entrepreneurs in Nigeria is lack of business capital and credit. Competition from bigger firms and unfavourable external business environment are also a cause of concern for women entrepreneurs in Nigeria (Ojo, 2009; Iheduru, 2002). Lack of capital and credit due to lack of savings (occasioned by unemployment), collaterals and family demands forces women entrepreneurs into less lucrative ventures such as retailing (Akanji, 2006).

Credit and training are some of the micro-finance factors needed by women entrepreneurs, mostly in developing countries, for enterprise performance. Micro-finance occupies a central position in the development of micro-enterprises in any economy; and it has received a world-wide acceptance as one of the leading strategies for fighting poverty globally (Eversole, 2009) because its impact is much felt in the informal sector as a tool for grassroots development (Morduch,1999; Roomi and Parrot, 2008; Rushad, 2004). Again, Carter and Shaw (2006) stated that 70% of the world’s poor are women and 88% of micro-finance institutions’ clients are women; hence the need for micro-finance to generate entrepreneurship and reduce poverty among women.

People, especially women, embark on entrepreneurial activity so as to tap opportunities in the market; and mostly out of necessity in most developing economies. It is also to gain satisfaction as business owners, profit to support families, and to produce goods and services to the society (Harrison and Mason, 2007). However; Hatcher et al. (2007) had a contrary opinion to the issue of entrepreneurial activity as a necessity. To them, women see their entrepreneurial activities as opportunities, rather than a necessity, which could be actualized through micro-finance.

There is a growing recognition that entrepreneurship could significantly contribute to economic development of women (Ibru, 2009) as well as improve the economies of developing countries. Thus, it is arguable that promoting entrepreneurship among women is an effective way to revitalize an ailing economy. Among other types of business venture, however, women enterprises are a leading sector in contributing to economic and social development of poor women due to their distinct characteristics (Iheduru, 2002).

Despite the crucial role of women entrepreneurs in economic development of their families and their countries; it is, however, discovered from the literature that women entrepreneurs do not have adequate credit and training to pursue their business profits. This led to their low business performance than their male counterparts, for example in UK and USA (Carter and Shaw, 2006), though they have significantly higher rates of informal economic participation than their male counterparts (Allen et al., 2008).

Importance of credit and training aside; women entrepreneurs’ ability to achieve good business performance depends on their attitude towards risk-taking (Shane, 2003). Entrepreneurship theory (Shane, 2003) stated that entrepreneur’s ability to discover and

12 International Journal of Management Vol. 30 No. 3 Part 1 Sept 2013

exploit opportunity for entrepreneurial activity differs between individuals and depends on individual’s attitude towards risk-taking. For instance, a risk-averse individual is less likely to exploit entrepreneurial opportunity (Shane, 2003). As such, a person may not search for or discover entrepreneurial opportunity if he/she has a negative attitude towards risk-taking. In the same vein, an individual may have an innovative business or service idea, and great likelihood to access micro-finance but may not utilize such advantage if he/she fears risk. Behavioural theories such as the Theory of Planned Behaviour, specifically the Intention Theory (Ajzen, 1991) concluded that attitude towards behaviour leads to intention which eventually leads to actual behaviour. Other supporting behavioural theorists (e.g Crisp and Turner, 2007) found that attitude and behavioural intention are positively related.

Many studies abound on micro-finance and women entrepreneurship growth, success and household income (Akanji, 2006; Carter and Shaw, 2006; Eversole, 2009; Gatewood et al., 2004; Harrison and Mason, 2007; Ibru, 2009) but limited studies are available on the effect of credit and training on women entrepreneurs’ performance with attitude as a moderating variable. For example, Vob and Muller (2009) studied entrepreneurial attitude and entrepreneurial behaviour. Though Ajzen (1991), Crisp and Turner (2007) measured attitude as a moderating variable; however their study related to intention and self perception; not between micro-finance and performance. Hence, there is the need for more research in this area, and this study provides such a research.

Therefore, the objective of this study is to examine the effect of credit and training on women entrepreneurs’ performance; moderated by attitude towards risk-taking.

Literature Review Credit Women entrepreneurs have limited physical, social and technological capital which forces them into micro-enterprises and the need for micro-finance (Brana, 2008; Carter and Shaw, 2006). Lack of these resources led them to start under-funded enterprises which have negative impact on their business performance in the long run (Brana, 2008; Gatewood, Brush, Carter, Green and Hart, 2004). Women’s lack of capital at the start-up and growth stages is due to low household income (Allen, 2000) and so they require start-up and working capital from micro-finance institutions (Carter and Shaw, 2006). Women clients do not have physical capital as collaterals demanded by conventional banks (I.F.C, 2007) but could use social capital demanded by micro-finance institutions (Brau and Woller, 2004). Hence, they need credit for their businesses.

Credit or loan is very necessary for new and growing enterprises. Riding (2006) stated that higher percentage of enterprises especially in Canada mostly seek external finance than use personal savings. Much dependence on credit by entrepreneurs, especially women, is due to their inability to raise capital through personal savings (Brana, 2008). The problem is much pronounced in developing countries due to unemployment and gender discrimination in high-paid jobs (Brana, 2008; Carter and Shaw, 2006). However, Gatewood et al. (2004) contended that women use more of personal savings than credit,

International Journal of Management Vol. 30 No. 3 Part 1 Sept 2013 13

to start and grow their enterprises. Salman (2009) also argued that loan is not usually good for business start-up but for growing or existing enterprises due to inability of the new business to pay back the loan at the initial business stage. While Karnani (2007) contended that credit does not lead to women’s improved welfare rather the government should create jobs for the women. These arguments aside, numerous evidences abound in the literature that credit has positive impact on enterprise performance. For instance, previous studies found that credit had positive impact on enterprise profit in Nigeria, Canada, Nicaragua and Croatia respectively (Ojo, 2009; Wycklam and Wedley, 2003; Martin, 1999; I.F.A.D, 2006). We therefore hypothesize that:

H1: Credit is positively related to women entrepreneurs’ performance.

Training This is a vital micro-finance institutions’ service. Education and/or training produce prior experience which leads to preparedness for entrepreneurial activity (Shane, 2003). But women entrepreneurs, mostly in developing countries, lack such prior business experience due to lack of former paid employment (Brana, 2008). Literature asserted that women who were in paid employment were more likely to be engaged in entrepreneurships (Allen et al; 2008; Carter and Shaw, 2006). However, unemployment in developing countries have hindered most women from participating in paid employments; hence the need for the provision of training service to entrepreneurs by micro-finance institutions. Women have less confidence, less entrepreneurial and management skills (Brana, 2008) and so require training. It is also reported that few women have ever moved their enterprise into formal sector due to inappropriate training (Braw and Woller, 2004). There is the need for training because only few micro-finance institutions provide formal business training to their clients as they assume that all clients are already entrepreneurs in business (Ibru, 2009). Arguing for the importance of training as a non-credit aspect of micro-finance, Harrison and Mason (2007) advocated for training for women entrepreneurs. Therefore, training is a vital micro-finance service required by women entrepreneurs especially in developing economies. Training produces the required skill needed for business start-up or improvement (Kickul et al., 2007; Kuzilwa, 2005) and women entrepreneurs need to possess adequate skills, acquired through education and training, for entrepreneurial success (Reavley and Lituchy, 2008). Again, Robinson and Malach (2004) emphasized the importance of practical business training and education in small businesses in USA; while Ying (2008) emphasized entrepreneurial education to University students in Malaysia.

There are also suggestions from literature of the need to study credit jointly with training on entrepreneurship performance (Ibru, 2009; Kuzilwa, 2005; Tazul, 2007) because women entrepreneurs in high-income countries are better educated than those in low or middle income countries (Ibru, 2009); and skill training and tertiary education may lead to business opportunities and impact on entrepreneurship (Gatewood et al., 2004). Exploitation of entrepreneurial opportunity also depends on the entrepreneur’s level of education, skills or knowledge acquired through training, experience and social network (Shane, 2003). Training was found to have positive impact on women’s business growth

14 International Journal of Management Vol. 30 No. 3 Part 1 Sept 2013

in New Hampshire and Pennsylvania, U.S.A (Kickul et al., 2007), on women’s business success in Canada (Reavley and Lituchy, 2008) and in Haiti, Kenya, Malawi and Nigeria (UNCDF/UNDP, 2003). We therefore hypothesize that:

H2: Training is positively related to women entrepreneurs’ performance.

Attitude towards risk-taking Attitude to risk used in this study is supported by the Entrepreneurship Theory of Shane (2003), and Intention Theory of Ajzen (1991). For instance, Entrepreneurship Theory states that an entrepreneur’s ability to identify and tap the opportunity provided by the external environment (financial, economic, legal and socio-cultural) to improve his/her business differs between individuals and depends on individual’s willingness and ability to engage in risky activity. The theory consists of opportunity discovery, evaluation of the opportunity and the decision to exploit the opportunity. Others elements of the theory include entrepreneurship, business operation and performance. The Theory of Planned behaviour of Ajzen (1991) also discussed entrepreneur’s attitude. It states that behavioural intentions are the most vital determinants of behaviour; and that attitudes, subjective norms, and perceived control converge to predict behavioural intentions. Attitude was defined as one’s beliefs about the consequences of performing the behaviour and one’s evaluation of the possible consequences of performing the behaviour. Crisp and Turner (2007) stated that attitude and behavioural intention are positively related. Attitude towards the behaviour leads to intention which eventually leads to actual behaviour (Ajzen, 1991). We therefore hypothesize that:

H3: Attitude towards risk-taking moderates the effect of credit and training on women entrepreneurs’ performance.

Methodology Survey Procedures A quantitative research method (survey) was used to collect data from women entrepreneurs. A total of 280 questionnaires were distributed to the clients of three homogenous micro-finance banks in the north, east and west regions of Nigeria. From the returned questionnaires, 161 were usable after data cleaning. Data were analyzed using descriptive statistics (mean and standard deviation), correlation analysis and hierarchical regression analysis.

Measures In line with established literature, credit was measured in terms of loan size, use of loan and loan repayment (e.g Kuzilwa, 2005; Lakwo, 2007; Peter, 2001). Training was measured in terms of skill acquisition and management training (e.g Ibru, 2009; Kuzilwa, 2005). Attitude was measured in terms of willingness and ability to engage in risky activity (e.g. Shane, 2003). While women entrepreneurs’ performance was measured in terms of net profit, output, investment and number of employees (e.g Kuzilwa, 2005; Reavley and Lituchy, 2008). All the measures were tapped on a 7-point scale. The conceptual framework for this study is shown in Figure 1.

International Journal of Management Vol. 30 No. 3 Part 1 Sept 2013 15

The moderator-interaction effects were determined in line with the procedure suggested by Baron and Kenny (1986). A moderator-interaction effect would occur if a relation is substantially reduced instead of being reversed (Baron and Kenny, 1986). Again, a moderator hypothesis is supported if the interaction or the product of a predictor variable and the moderator is significant when the predictor and the moderator were being controlled (Baron and Kenny, 1986).

Results Data cleaning The data used were free from errors. For instance, outliers were detected by comparing the Mahalanobis distance (D2) or chi-square value of each respondent with the critical or table chi-square value, using the number of predictor variables as the degrees of freedom, p < 0.001 (Hair et al., 2010). Extreme observations in a sufficient number of variables in multivariate and univariate detections were deleted (Hair et al., 2010). Normality was handled through skewness and kurtosis. Observations with Z-score above or below the critical value of 1.96, p = 0.05 were deleted (Hair et al., 2010). Linearity was detected through the Pearson Correlation matrix as shown in Table 1, and all predictors correlated with the criterion variable. The output of the hierarchical regression analysis indicated that the error term (as indicated by Durbin Watson statistics) were all within the recommended range of 1.50-2.50. There was no case of multicollinearity as the collinearity statistics of the regression output indicated Tolerance > 0.10, Variance Inflationary Factor < 10 and Condition index < 30 in most cases (Hair et al., 2010). Homoscedasticity (equality of variance) was verified through an examination of the residuals of the regression output which showed no clear relationship between the residual and the predicted values (Coakes and Steed, 2003).

Figure 1. Conceptual Framework

20

The conceptual framework for this study is shown in Figure 1

Figure 1 Conceptual Framework

Table 1 Pearson Correlations of the Variables LA SA Abexp Sconf PerSales LA 1.000 SA .076 1.000 Abexp -.043 .457** 1.000 Sconf -.024 .352** .427** 1.000 PerSales .085 .685** .544** .321** 1.000 **. Correlation is significant at the 0.01 level (2-tailed). Note: LA=Loan access, SA=Skill acquisition, Abexp.=Ability to expand business, Sconf.=Self-confidence in business, PerSales= Sales performance

Credit: Loan Access

Training: Skills Acquisition

Attitude: Ability to expand business

Women entrepreneur’s performance

16 International Journal of Management Vol. 30 No. 3 Part 1 Sept 2013

Goodness of measures The principal component analysis for the predictor variables revealed the presence of two components with eigenvalues greater than one, using Varimax with Kaiser’s normalization rotation method. These two components factors were renamed skill acquisition and loan access. The naming was done according to the items with the highest factor loadings on each component. The two components explained a total variance of 70.1%. Communalities were above 0.6 for most variables, anti-image (MSA) was above 0.5 for each item and Barlett’s test of sphericity (sig.) was 0.000 which was <0.05. Kaiser- Meyer-Olkin’ measure of sampling adequacy was 0.843 and factor loadings were above 0.5 as suggested by Hair et al. (2010). The moderator, attitude towards risk converged into two components renamed ability to expand business and self-confidence in doing business; with a total variance explained as 74.4%. Communalities were above 0.6 for most items, MSA was also above 0.5 and Barlett’s test of sphericity (sig.) was 0.000. Factor loadings were above 0.5 and KMO was 0.809. The criterion variable converged into one component renamed increased sales; with a total variance explained of 71.2%. Communalities were above 0.6 for most items, MSA was above 0.5 and Barlett’s test of sphericity (sig.) was 0.000. Factor loadings were above 0.5 and KMO was 0.730.

After the principal component factor analysis, the data was standardized by finding the mean of items of each factor or construct which then became the variables for subsequent analyses such as reliability. However, for hierarchical regression, the variables were centralized to avoid high multicollinearity (Aiken and West, 1991). Prior to hierarchical multiple regression, the independent variables were multiplied with the moderator to get the product of interaction terms that were entered into specific levels of the hierarchical regression analysis.

Reliability test was performed on the factors after the exploratory factor analysis. Loan access had Cronbach’s alpha of 0.840 and skill acquisition had alpha of 0.920. Alpha for ability to expand business was 0.898 and self-confidence in doing business was 0.705. Alpha for sales was 0.863.

Table 1 above provided a summary of the results of the correlation analysis. The values of the coefficient (r) indicate the strength of the relationship between the variables. When

Table 1. Pearson Correlations of the Variables LA SA Abexp Sconf PerSales

LA 1.000 SA .076 1.000 Abexp -.043 .457** 1.000 Sconf -.024 .352** .427** 1.000 PerSales .085 .685** .544** .321** 1.000

**. Correlation is significant at the 0.01 level (2-tailed). Note: LA=Loan access, SA=Skill acquisition, Abexp.=Ability to expand business, Sconf.=Self-confidence in business, PerSales= Sales performance

International Journal of Management Vol. 30 No. 3 Part 1 Sept 2013 17

r = 0.10 to 0.29, the relationship is small; r = 0.30 to 0.49 (medium), and r = 0.50 to 1.0, the relationship is large (Cohen, 1988). Table 1, therefore, indicated that training (skill acquisition) r = 0.685 (p < 0.01) had high significant positive correlation with women entrepreneurs’ performance in Nigeria. However, credit (loan access) was not significant.

Table 2 above provided a summary of the descriptive statistics of the variables. It indicated that among the independent variables, training (skill acquisition) had a higher mean value (6.570) and standard deviation (0.672). This proved that women entrepreneurs perceived skill acquisition training as having more influence on their business performance than loan access. Equally, ability to expand (moderator) had a higher mean value (6.825) and standard deviation (0.379) than self-confidence (moderator).

Table 3 provided a summary of the hierarchical regression analysis. As shown in Table 3, the R Square value which is an indicator of how well the model fits (coefficient

Table 2. Descriptive Analysis of the Variables (Mean and Standard Deviation) and Cronbach’ Alpha Coefficient

Variable Mean Std. Deviation Cronbach’ alpha N

Loan access (LA) 5.816 1.528 0.840 161 Skill acquisition (SA) 6.570 0.672 0.920 161 Ability to expand (Abexp) 6.825 0.379 0.898 161 Self-confidence (Sconf) 6.733 0.487 0.705 161 Performance (Perf) 6.721 0.478 0.863 161

Table 3. Results of Hierarchical Regression on Sales Performance

Variables Beta 1(Step 1) Beta 2 (Step 2)

Beta 3 (Step 3)

Independent Variables: Loan Access (LA) Skill Acquisition (SA)

.034

.683*** .057 .545***

.075

.310***

Moderator: Ability to Expand Business (Abexp) .297*** .220**

Interaction Term: LA * Abexp SA * Abexp

-.024 .347**

R Square Adjusted R Square R Square Change F Value Sig. F. Change

.471***

.464

.471 70.260 .000***

.540***

.531

.069 23.603 .000***

.581**

.568

.042 7.697 .001**

Note: *p<.05; **p<.01; ***p<.001

18 International Journal of Management Vol. 30 No. 3 Part 1 Sept 2013

determination) is .581. In other words, a multiple regression model fits the data adequately and significantly explains 58.1% of the variation in the outcome variable, sales performance and is left with 41.9% residual variability. Loan access and training acquisition as a construct significantly predict sales performance and explain an additional 47.1% of the variance in sales performance (R square change = .471, p < 0.01). The overall regression model was significant, R square = .471, F (5,155) = 27.99, p < 0.01. However, interaction of self-confidence was not significant; and so was not reported.

Hypothesis 1 predicted a positive relationship between credit and women entrepreneurs’ performance. The regression analysis result, Table 3 (step 1) reveals that loan access had no significant relationship with women entrepreneurs’ performance. Thus, hypothesis 1 is not supported. However, the regression analysis result, Table 3 (step1) indicates a positive relationship between skill acquisition and women entrepreneurs’ performance (Beta = .68, p <. 001). Thus, hypothesis 2 is supported. Hypothesis 3 examines the moderating effect of ability to expand business on the relationship between credit and training, and women entrepreneurs’ performance. As shown in Table 3 (step 3), ability to expand business interacted with skill acquisition (but not with loan access) to predict women entrepreneurs’ performance. Thus, hypothesis 3 is partially supported. The significant beta coefficient for interactive term (beta = .347, p < .01) indicated that the impact of skill acquisition on women entrepreneurs’ performance (sales performance) differ by the degree of emphasis on ability to expand business on the part of women entrepreneurs. This variation is best shown in Figure 2.

Figure 2. Interaction between skill acquisition and sales performance of women entrepreneurs

3.002.001.00

SKILL ACQUISITION

7.00

6.90

6.80

6.70

6.60

6.50

6.40

SA LE

S PE

RF

6.452

6.92

6.731

6.789

6.42

6.663

MODERATE HIGH

ABILITY TO EXPAND

International Journal of Management Vol. 30 No. 3 Part 1 Sept 2013 19

Discussion and Conclusions Figure 2 shows the moderating effect of ability to expand business on skill acquisition with respect to sales performance. It is observed that when ability to expand business among women entrepreneurs is high (shown by straight line), the impact of skill acquisition on sales performance is also positively high. In case where the ability to expand business is moderate (as shown by dotted line), the impact of skill acquisition on sales performance is strongly positive from low to moderate. Beyond the moderate level of skill acquisition, the impact becomes negative (slopes down). This indicates that with moderate ability to expand business, skill acquisition becomes irrelevant since knowledge acquisition is mostly for corporate performance (VanHome, 1980).

The current findings support previous studies that training or skill acquisition is positively related to entrepreneur’s performance (Kickul et al., 2007). However, this study fails to support the relationship between loan access and women entrepreneurs’ performance.

This could possibly be because without training, loan in itself could not lead to women entrepreneurs’ performance in Nigeria. This is why Kuzilwa (2005), in Tanzania for example, advocated for joint effect of credit and training on women entrepreneurs’ performance in developing countries.

The results of these analyses confirm that the overall model of loan access and skill acquisition was significant but skill acquisition had the greater influence on sales performance of women entrepreneurs in Nigeria. Loan access individually was found to be insignificant. This study recommends that the government should tie-in loan with training to women entrepreneurs, with more emphasis on skill acquisition training. This will enhance their business performance and subsequent wellbeing. The women entrepreneurs too should have the ability to expand their businesses as a positive attitude towards risk-taking in order to achieve business performance.

Acknowledgement The suggestions and comments of the reviewers and participants of International Conference on Rural Development and Entrepreneurship (ICORE, 2011), Kuching, Sarawak, Malaysia, where the paper was presented are hereby acknowledged.

References Aiken, L. S. and West, S. G. (1991). Multiple regression: Testing and interpreting interactions. Newbury Park, London: Sage.

Ajzen, I. (1991). “The Theory of Planned Behavior”. The Organizational Behavior and Human Decision Processes , 50, 1: 179-211.

Akanji, O. O. (2006). “Microfinance as a strategy for poverty reduction”. Central Bank of Nigeria Economic and Financial Review, 39, 4.

Allen, D. W. (2000). “Social networks and self-employment”. Journal of Socio- Economics, 29, 1: 487-501.

20 International Journal of Management Vol. 30 No. 3 Part 1 Sept 2013

Allen, I. E., Elam, A., Langowitz, N. and Dean, M. (2008). 2007 Global Entrepreneurship Monitor report on women and entrepreneurship. Babson College: The Center for Women’s Leadership. Baron, R. M. and Kenny, D. A. (1986). “The moderator-mediator variable distinction in social psychology research: Conceptual, strategic, and statistical considerations”. Journal of Personality and Social Psychology , 51, 6: 1173-1182 Brana, S. (2008). “Microcredit in France: Does gender matter?” A paper presented at the 5th Annual Conference-Nice. European Microfinance Network. Brau, J. C. and Woller, G. M. (2004). “Microfinance institutions: A comprehensive review of the existing literature and an outline for future financial research”. Journal of Entrepreneurial Finance and Business Ventures , 9, 1: 1-26. Carter, S. and Shaw, E. (2006). Women’s business ownership: Recent research and policy developments. UK: Small Business Service. Coakes, S. J. and Steed, L. G. (2003). SPSS: Analysis without anguish, version 11.0 for windows. Singapore: Kyodo. Crisp, R. J. and Turner, R. N. (2007). Essential Social Psychology. London: SAGE Publication. Eversole, R. (2009). Solving poverty for yourself: Microenterprise development, microfinance and migration. Australia: Foundation for Development Co-operation. Gatewood, E. J., Brush, C. G., Carter, N. M., Greene, P. G. and Hart, M. M. (2004). Women entrepreneurs, growth and implications for the classroom. USA: Coleman Foundation whitepaper series for the USA Association for Small Business and Entrepreneurship. Hair, J. F., Black, W. C., Babin, B. J. and Anderson, R. E. (2010). Multivariate data analysis, a global perspective (7th ed.). New Jersey, USA: Pearson Education Inc. Harrison, R. T. and Mason, C. M. (2007). “Does gender matter? Women business angels and the supply of entrepreneurial finance”. Entrepreneurship Theory and Practice , 31 (3), 445-472. Hatcher, C., Terjesen, S. and Planck, M. (2007). Towards a new theory of entrepreneurship in culture and gender: A grounded study of Thailand’s most successful female entrepreneurs. Australia: AGSE. Ibru, C. (2009). “Growing microfinance through new technologies”. A paper presented at a foundation day lecture, Federal University of Technology, Akure, Nigeria. Iheduru, N. G. (2002). “Women entrepreneurship and development: The gendering of microfinance in Nigeria”. A paper presented at the 8th International Interdisplinary Congress on Women. Makerere University, Kampala, Uganda. International Finance Corporation (IFC). (2007). Gender entrepreneurship markets, GEM country brief. Afghanistan: GEM. International Fund for Africa Development (IFAD). (2006). Assessing and managing social performance in microfinance. Retrieved February 2, 2009, from http://www.ifad. org/ruralfinance/pub/performance.pdf

International Journal of Management Vol. 30 No. 3 Part 1 Sept 2013 21

Karnani, A. (2007). Microfinance misses its mark. Retrieved February 18, 2009, from Standford Social Innovation Review:http://www.ssireview.org/articles. Kickul, J. R., Page, T. C., Gundry, L. K., and Sampson, S. D. (2007). “Women entrepreneurs preparing for growth: The influence of social capital and training on resource acquisition”. Journal of Small Business and Entrepreneurship , 20, 1: 169-181. Kuzilwa, J. (2005). “The role of credit for small business success: A study of the National Entrepreneurship Development Fund in Tanzania”. The Journal of Entrepreneurship , 14, 2: 131-161. Lakwo, A. (2007). Microfinance, rural livelihood, and women’s empowerment in Uganda. Retrieved August 3, 2009, from African Studies Center Research Report 85/2006: http:// www.ascleiden.nl/pdf/rr85lakwo.pdf Mayoux, L. (1999). “From access to empowerment: Gender issues in microfinance”. Women’s Caucus Position Paper for CSD-8; 2000. CGAP. Martin, T. G. (1999). Socio-economic impact of microenterprise credit in the informal sector of Managua, Nicaragua. Retrieved January 21, 2009, from http://scholar.lib. vt.edu/thesis/ May, N. (2007). “Gender responsive entrepreneurial economy of Nigeria: Enabling women in a disabling environment”. Journal of International Women’s Studies , 9, 1. Morduch, J. (1999). “The microfinance promise”. Journal of Economic Literature , 37: 1569-1614. Ojo, O. (2009). “Impact of microfinance on entrepreneurial development: The case of Nigeria”. A paper presented at the international conference on economics and administration, Faculty of Administration and Business, University of Bucharest, Romania. Otero, M. (1999). Bringing development back into microfinance. Latin America: ACCION International. Peter, B. K. (2001). “Impact of credit on women-operated microenterprises in UASIN GISHU district, Eldoret, Kenya”. In P. O. Alila and P. O. Pedersen (eds), 2001, Negotiating social space: East African microenterprises . Retrieved September 18, 2009, from http:// books.google.com.my/book? Porter, E. G. and Nagarajan, K. V. (2005). “Successful women entrepreneurs as pioneers: Results from a study conducted in Karaikudi, Tamil Nadu, India”. Journal of Small Business and Entrepreneurship , 18, 1: 39-52. Reavley, M. A. and Lituchy, T. R. (2008). “Successful women entrepreneurs: A six- country analysis of self-reported determinants of success-more than just dollars and cents”. International Journal of Entrepreneurship and Small Business , 5, 3-4: 272-296. Riding, A. (2006). Small Business financing profiles. Canada: SME Financing Data Initiative. Robinson, P. and Malach, S. (2004). “Multi-disciplinary entrepreneurship clinic: Experiential education in theory and practice”. Journal of Small Business and Entrepreneurship , 17, 1: 317-331.

22 International Journal of Management Vol. 30 No. 3 Part 1 Sept 2013

Roomi, M. A. and Parrot, G. (2008). “Barriers to development and progression of women entrepreneurs in Pakistan”. The Journal of Entrepreneurship , 17, 1: 59-72. Rushad, F. (2004). Essays on microcredit programs and evaluation of women’s success. Retrieved January 21, 2009, from htttp://www.scholar.lib.vt.edu/theses// Salman, A. (2009). How to start a business: A guide for women. Pakistan: Center for International Private Enterprise, Institute of National Endowment for Democracy, affiliate of the USA Chamber of Commerce. Shane, S. (2003). A general theory of entrepreneurship: The individual-opportunity nexus. UK: Edward Elgar. Tazul, I. (2007). Microcredit and poverty alleviation. Hampshire, England: Ashgate Publishing Limited. UNCDF/UNDP. (2003). Microfinance Program: Impact assessment (2003) based on case studies in Haiti, Kenya, Malawi and Nigeria. United Nations Capital Development Fund in conjunction with United Nations Development Program. Vob, R. and Muller, C. (2009). “How are the conditions for high-tech start-ups in Germany”. International Journal of Entrepreneurship and Small Business , 7, 3: 285-311. Wycklam, G. R. and Wedley, W. (2003). “The need of small business owners: Perceptions of entrepreneurs and service providers”. Journal of Small Business and Entrepreneurship, 16, 1: 21-39. Ying, L. Y. (2008). “How industry experience can help in the teaching of entrepreneurship in Universities in Malaysia”. Sunway Academic Journal , 5, 1: 48-64.

Contact email addresses: [email protected] [email protected] [email protected]

Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.