1. Introduction
Women entrepreneurship has been an interesting topic for researchers all over the world for the last few decades. This is due to the substantial increase in the number of women entrepreneurs and their contributions to economic growth, innovation, and job creation (Dangi & Ritika, 2014). However, while women are increasingly a recognized workforce, women entrepreneurship still lags behind men. Chowdhury et al. (2018) added that women entrepreneurs play a substantial role in the sustainable economic development of various developed as well as developing nations in the world. Taking a closer look, the contributions of women toward entrepreneurial activity is inevitable in any region although they still lag behind men. Table 1 and Figure 1 show the percentage of involvement of males and females in entrepreneurial activities by region, respectively.
Table1: Percentage of Involvement of Male and Female in Entrepreneurial Activities by Region
Source: Global Entrepreneurship Monitor (GEM) (VandeBrug, 2013).
Figure1: Percentage of Male and Female Involved in Entrepreneurial Activity by Region
(Source: Global Entrepreneurship Monitor (GEM) (VandeBrug, 2013)
Given the low female labour force and business participation in the country, fostering women entrepreneurs can be an effective way of exploiting the potential of women in the development process of Sri Lanka. Women entrepreneurs account for improved economic growth and stability within a country. Women entrepreneurs inspire other women to start businesses. This leads to more job creation for women which ultimately helps in reducing the gender gap in the workforce. Although women entrepreneurs are becoming major contributors and players, they face many challenges including accessing capital and markets, fierce competition, maintaining cash flow, access to training and technical assistance, managing business growth and expansion, and overcoming the negative perceptions of women entrepreneurs (Zimmerman & Chu, 2013).
Islamic traditions play a significant role in the lives of women (Ilhaamie, 2017; Ilhaamie et al., 2014; McIntosh & Islam, 2014). Islam clearly emphasizes trade and commerce, including women as entrepreneurs as evident in Al-Quran (The Holy Book for Muslims). However, in some Muslim communities, women show less interest in accessing financial resources because they need to pay high interest which is strictly prohibited in Islam (Dechant & Lamky, 2005). These gaps necessitate research on the factors influencing the business performance of Muslim women entrepreneurs in Sri Lanka
Muslim women face stiff challenges due to family beliefs and traditions in Sri Lanka (Swati, 2018) which may limit their resource accessibility that influences business performance. Hence, there is a need to identify what are the specific industrial factors influencing the business performance of Muslim women entrepreneurs in Sri Lanka. Thus, the objective of this study to investigate the effect of industrial factors on the business performance of Muslim women entrepreneurs in Sri Lanka.
2. Literature Review
Business performance has been an area of study for many researchers. Business models and entrepreneurial orientation are important for any enterprise (Machado, 2015; Ruliati et al., 2020). A business model describes the rationale of how an organization creates, delivers, and captures value, [2] in economic, social, cultural or other contexts. A business model identifies the products or services the business plans to sell, its identified target market, and any anticipated expenses. Business models are important for both new and established businesses. They help new, developing companies attract investment, recruit talent, and motivate management and staff (Lee, 2020). Entrepreneurial orientation (EO) is a firm level strategic orientation that captures an organization’s strategy-making practices, managerial philosophies, and firm behaviors that are entrepreneurial in nature. EO is a key concept when executives are crafting strategies in the hope of doing something new and exploiting opportunities that other organizations cannot exploit. EO refers to the processes, practices, and decision-making styles of organizations that act entrepreneurially (Sanyal et al., 2020).
Business performance is defined as a change in size during a determined time span (Dobbs & Hamilton, 2007). Hence, growth or performance is a vital indicator of a flourishing enterprise. Measuring performance is a vital part of monitoring the growth and progress of any business. It entails measuring the actual performance of a business against intended goals. Regularly checking the business performance protects the business against any financial or organizational problems. It helps businesses in lowering process costs and improving productivity. To measure business performance, entrepreneurs need to track relevant business metrics, also known as key performance indicators (return on asset, return on investment, return on equity, etc) that display a measurable value and show the progress of the business goals (Maharati, 2010).
In the case of women entrepreneurs, business performance is measured based on the entrepreneurial actions which are often instrumental in delivering success (Ahamed, 2011). Islam et al. (2011) defined performance/growth as the ability of firms to create acceptable outcomes and actions. Based on the literature, this study defines business performance as the expansion of the enterprise in terms of sales, profit, and net asset growth, as well as an increase in the number of employees, customers, and the number of products or services for at least three years of the business operations. Hence, subjective measures were used to measure the business performance in this study.
Industrial factors that influence business performance include business opportunities, access to proper location, and institutional support (i.e. availability of government and nongovernmental assistance), which are critical determinants of business performance (Rashid et al., 2015). The government takes initiatives in assisting entrepreneurs by providing them opportunities such as training and offering technical assistance programs to enhance their business performance. Similarly, there are also non-governmental organizations that provide business development support services to women entrepreneurs. Such structured programs provide sufficient knowledge, skills, and abilities for women entrepreneurs to grow their businesses and make them more successful. Educational institutions have also created new opportunities for women’s entrepreneurial development. Educational institutions and business enterprises have formed strategic collaborations through the development of national and global marketing initiatives to better meet the need of women businesses.
There is a substantial disparity between men and women regarding access to as well as the use of finance (Ghosh & Vinod, 2017). According to Kuratko and Hodgetts (2009), there are some other factors, such as loan facilities for business start-ups and business expansion that significantly contribute to the success of women entrepreneurs. In fact, there are micro-financial institutions that grant loans to entrepreneurs in general. At the same time, there are some special schemes for women entrepreneurs with concessionary interest rates. Particularly for Muslim women entrepreneurs, there are facilities to obtain business loans without interest from Islamic banks. Farida et al. (2015) pointed that, despite the availability of financing options, Muslim women entrepreneurs are constrained by their reluctance to use interest-based microfinance services.
In addition, Lerner et al. (1997) and Dharmaratne (2012) found that resource accessibility of women entrepreneurs is a critical factor for the growth of women entrepreneurs. However, Muslim women entrepreneurs face challenges such as lack of access to finance (Ahamed, 2011; Ilhamie et al., 2017), as well as challenges related to demand and access to proper location (Ilhamie et al., 2017). Similarly, the lack of institutional support is another disadvantage (Dharmaratne, 2012). When Muslim women entrepreneurs are confined to their homes, accessing resources and seeking institutional support becomes a challenge.
Therefore, it is expected that the business performance of Muslim women entrepreneurs in Sri Lanka is influenced by resource availability and government and non-governmental support. This leads to the following hypothesis:
H1: Resource Accessibility has a significant influence on the business growth of Muslim women entrepreneurs in the Eastern province of Sri Lanka.
H2: Government and non-governmental support have a significant influence on the business growth of Muslim women entrepreneurs in the Eastern province of Sri Lanka.
3. Methodology
3.1. Research Design
A sampling frame of 260 respondents was determined using the simple random sampling technique. The criteria for sample selection include businesses owned by Muslim women entrepreneurs which have been registered with any chamber and run for more than three years. A structured questionnaire was used as the data collection technique. A five-point Likert scale was used, which is a type of psychometric response scale in which responders specify their level of agreement to a statement typically in five points: (1) Strongly disagree; (2) Disagree; (3) Neither agree nor disagree; (4) Agree; (5) Strongly agree. The face validity of the questionnaire was also tested by getting opinions from industry experts and relevant academicians in this area before issuing the questionnaires. Structural equation modeling (SEM) with AMOS and Statistical Package for Social Science (SPSS) version 23.0 software was employed to confirm the measurement model for construct validity and discriminant validity and to test the hypotheses constructed.
3.2. Operational Definition of the Constructs used in the Study
The main constructs used in the study were industrial factors and business performance. Industrial factors were assessed by two sub-variables namely resource accessibility and institutional support.
1. Industrial Factors: In this study, industrial factors refer to the factors such as business opportunities, access to proper location, and institutional support (i.e. availability of government and non-governmental assistance). They are measured with the following dimensions namely resource accessibility and institutional support.
2. Resource Accessibility: In this study, resource accessibility refers to the availability of the resources such as raw material, human resources, and sources of finance.
3. Government and Non-Governmental Support: In this study institutional support is the policies and regulations enacted by the government and non-government entities in creating the friendly atmosphere necessary for women entrepreneurs to strive, such as access to finance, access to training and development programs, access to market and other support mechanism provided by the government as well as non-governmental organizations.
4. Business Performance: This includes an increase in sales and profits/revenue, employment growth, assets expansions, growth of the business, customer expansion, and expansion of products/services.
3.3. Measures
Industrial factors are conceptualized using two dimensions developed by Lerner et al. (1997) and these dimensions include resource accessibility, and government and non-governmental support. The scale developed by Lerner et al. (1997) was adapted with little modification to suit the context of this study to measure the industrial factors. Business performance is conceptualized using the five dimensions introduced by Walker and Brown (2004) namely sales revenue, profitability, employee additions, increase in net assets, and business expansion, and was adapted with little modification to suit the context of this study to measure the business performance.
The industrial factors construct in this study include two latent variables namely: Resource accessibility (RA) that has 5 indicators i.e., RA1, RA2, RA3, RA4, and RA5 and Government and Non-Governmental Support (GS) that has 5 indicators i.e. GS1, GS2, GS3, GS4, GS5, and GS6. Similarly, business performance (BP) consists of 6 indicators namely BP1, BP2, BP3, BP4, BP5, and BP6. All the items in the constructs resource accessibility, government and non-governmental support, and business performance were confirmed without cut off during EFA as well as CFA. Hence, CFA was carried out for this study’s measurement model. Accordingly, the instrument developed for this study is shown in Table 2 where RA refers to Resource Accessibility and GS refers to Government and Non-Governmental Support.
Table 2: Items and Measures
4. Results
4.1. Measurement Model
The data was analysed using the two-method approach (Hair et al., 2010). In the first approach, confirmatory factor analysis (CFA) was used to determine the adequacy of the measurement model, in the second approach (i.e. the structural model), CFA was performed using SEM to test the hypotheses. Hair et al. (2010) suggested three or four indices to ascertain model fit of the proposed model. The recommended fit indices include relative chi-square, (χ2/ DF), Root Mean Square Error of Approximation (RMSEA). In addition, and any one or two from the goodness-of-fit index (GFI), adjusted goodness-of-fit index (AGFI), comparative- fit-index (CFI), normal-fit-index (NFI) and Turker-Lewis index (TLI). The relative chi-square is recommended to be less than 3.0, whereas GFI, AGFI, CFI, IFI, NFI, and TLI should be greater than 0.90. Similarly, RMSEA and RMR should be less than 0.08 (Hair et al., 2010).
4.1.1. Confirmatory Factor Analysis (CFA) for Industrial Factor
Industrial factors construct in this study consist of two sub-variables namely, resource accessibility and institutional support. Hence, then first-order CFA was carried out for the constructs of resource accessibility and institutional support, and then the second-order CFA was carried out for the construct of industrial factors.
a) First Order CFA for Resource Accessibility (RA)
Figure 2 shows the results of first-order CFA measurement model, indicating that the all five items confirmed the composite indicators of resource accessibility. The model fit the data in an acceptable level as follows: x2 (df = 3) = 5.153; p = 0.1 61; x2/df = 1.625; GFI = 0.993; AGFI = 0.966; CFI = 0.996; IFI = 0.996; RMSEA = 0.049. The results showed that four goodness-of-fit indices namely GFI, AGFI, CFI, and IFI surpassed the cut-off value (including RMSEA of 0.049).
Figure 2: First-Order CFA for Resource Accessibility
b) First Order CFA for Institutional Support (GS)
Figure 3 shows the results of first-order CFA measurement model, indicating that the all six items confirmed the composite indicators of institutional support. The model fit the data in an acceptable level as follows: with x2 (df = 6) = 13.913; p = 0.031; x2/df = 2.319; GFI = 0.985; AGFI = 0.949; CFI = 0.991; IFI = 0.991; RMSEA = 0.067. The results showed that four goodness- of-fit indices namely GFI, AGFI, CFI, and IFI surpassed the cut-off value (including RMSEA of 0.067).
Figure 3: First-Order CFA for Institutional Support
4.1.2. Second-Order CFA for Industrial Factors
Figure 4 shows the results of second-order CFA, indicating that the two components confirmed the composite indicators of industrial factors. The model fit the data in an acceptable level as follows: x2 (df = 5) = 97.215; p = 0.000; x2/df = 2.778; GFI = 0.945; AGFI = 0.896; CFI = 0.977; IFI = 0.977; RMSEA = 0.079. The results showed that four goodness-of-fit indices namely GFI, AGFI, CFI, and IFI surpassed the cut-off value (including RMSEA of 0.079). The most important sub-scale in industrial factors was institutional support due to its higher loading amongst the two sub-scales.
Figure 4: Second-Order CFA for Industrial Factor
4.1.3. Confirmatory Factor Analysis (CFA) for Business Performance
Figure 5 shows the results of first-order CFA or the final measurement model, indicating that the six items confirmed the composite indicators of business performance (BP). The model fit the data in an acceptable level as follows: with x2 (df = 4) = 14.317; p = 0.006; x2/df = 3.579; GFI = 0.984; AGFI = 0.918; CFI = 0.993; IFI = 0.993; RMSEA = 0.095. The results showed that four goodness-of-fit indices namely GFI, AGFI, CFI, and IFI surpassed the cut-off value (including RMSEA of 0.095).
Figure 5: CFA for Business Performance
4.2. Convergent Validity
Table 3 shows that the composite reliability (CR) was between 0.839 and 0.968. In addition, the average variance explained (AVE) values are above 0.50, which is acceptable (Hair et al., 2010). All the items had factor loadings of 0.50 or more. Hence, the results provide evidence for reliability and validity.
Table 3: Composite Reliability
5. Discussion and Conclusion
Figure 6 depicts the path between the exogenous and endogenous variables. It showed that the model fit the data for the structural model in an acceptable level as follows: x2 (df = 112) = 205.530; p = 0.000; x2/df = 1.835; CFI = 0.958; IFI = 0.959; RMSEA = 0.053. It also showed that at least three indices surpassed the cut-off value. Hence, the structural model can be used for hypothesis testing.
Figure 6: Structural Model
5.1. Hypothesised Effect of Industrial Factor Dimensions on Business Performance
The path analysis between the dimensions of industrial factors was conducted to see which dimension impacts the business performance of Muslim women entrepreneurs. Table 4 shows the relationship between the dimensions of industrial factors and business performance.
Table 4: Regression Weights for the Industrial Factor Dimensions and Business Performance
Source: Study Survey.
Based on Table 4, only resource accessibility was significant (β = 0.289, CR = 4.531, p = 0.000) whereas government and non-governmental support was not significant (β = 0.057, CR = 0.950, p = 0.342) at a 0.05 level of significance. This is even though industrial factors as a whole had a significant association with the business performance of Muslim women entrepreneurs in Sri Lanka.
5.2. Conclusion
The results showed that only resource accessibility had a significant impact on business performance (β = 0.289, p = 0.000 < 0.001) and institutional support had no significant impact (β = 0.057, p = 0.342 < 0.05). The findings of this study showed that there is a difference in the business performance of Muslim women entrepreneurs who were able to access resources and Muslim women entrepreneurs who were not able to access resources (strong market, adequate raw material, human resources, and sources of internal finance). These study findings are consistent with previous findings (Dharmaratne, 2012; Lee et al., 2012; Lerner et al., 1997; Roomi & Harrison, 2010; Dissanayake, 2018). Institutional support did not significantly impact the business performance of Muslim women entrepreneurs in Sri Lanka. However, Jahed et al. (2011) in Bangladesh as well as Dharmaratne (2012) in Sri Lanka found that government support had a positive association with the business performance of women entrepreneurs.
In this study, there is no difference in the business performance of Muslim women entrepreneurs who were able to obtain institutional support from governmental or non-governmental organizations, and Muslim women entrepreneurs who were not able to obtain institutional support from governmental or non-governmental organizations. This might suggest that Sri Lankan Muslim women entrepreneurs do not rely on governmental and non-governmental supports. The fact is that most Muslim women are confined at home rather than going out in search of getting assistance or participating in training/ market promotion campaigns. Hence industrial factors had a significant impact on the business performance of Sri Lankan Muslim women entrepreneurs. In that, resource accessibility had a significant impact on business performance whereas institutional support did not have a significant impact on business performance.
5.3. Limitation
There are some limitations in the areas of theoretical background, methodology, and scope of the study which need to be addressed in future studies. This research is limited to Muslim women entrepreneurs registered with the District Chamber of Commerce and Industry in the three districts of the Eastern province of Sri Lanka. Hence, it disregards women entrepreneurs who have not been registered with the District Chamber of Commerce and Industry. So, future researchers may extend its scope to various groups, and even across countries.
5.4. Implications
To act upon these findings, that is, resource accessibility significantly impacts the business performance of Muslim women entrepreneurs, it is recommended that policymakers and regulators promote the importance of entrepreneurship and develop strategies for women entrepreneurs in Sri Lanka to access resources such as finding a good location, strong market demand, access to raw materials and human resources and sources of internal finance (family members, personal savings, etc.). Nascent and prospective women entrepreneurs also should have a look at the industrial factors which impact their business performance.
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피인용 문헌
- The Effect of Entrepreneurial Orientation and Talent Management on Business Performance of the Creative Industries in Indonesia vol.9, pp.1, 2021, https://doi.org/10.13106/jafeb.2022.vol9.no1.0105