DOI: JEL codes: G21, D90, D91 /

Received 4 July 2021; Revised 5 November 2021, 3 December 2021; Accepted 5 January 2022.

This is an open access article under the CC BY license (

Muhammad Farhan Jalil, Lecturer, School of Business School, University of Technology Sarawak, Sibu, Sarawak, Malaysia, e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.
Azlan Ali, Associate Professor, School of Business and Management, University of Technology Sarawak, Sibu, Sarawak, Malaysia, e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.
Zeeshan Ahmed, Assistant Professor, Lahore Business School, University of Lahore Gujrat Campus, Gujrat, Punjab 50700, Pakistan, e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.


PURPOSE: In the era of globalization and competition in a vigorous market, micro and small enterprises (MSEs) look for sustainable growth by consuming diverse resources. Previous studies have identified that financial services of microfinance are essential drivers for SMEs’ survival. Yet, the feature role of other microfinance services, such as micro-credit, micro-savings, micro-insurance, training, and social networking, to achieve substantial growth of the MSE sector is still lacking, which explains why MSEs make such a small contribution to Pakistan’s economy. Therefore, the main purpose of the research is to consider the impact of microfinance services on the growth of MSEs in Pakistan, as MSEs are the most vulnerable group in the country and throughout the world. Moreover, this study also identified the mediating role of social and psychological capital in enhancing the productivity of microfinance services for MSEs. METHODOLOGY: 770 respondents from metropolitan cities in Pakistan were contacted for the survey, and the response rate was 64%. After screening the data, only 357 questionnaires appeared to be completed in all respects, so they were initially fed into the computer spread and then imported for further analysis.Structured questionnaires were used to collect the data from 357 micro and small enterprises operating in the developing market of Pakistan. Derived hypotheses were verified through Structural Equation Modelling (SEM) using AMOS 21. FINDINGS: The study’s findings revealed that microfinance services have an essential role in promoting MSE growth. Microfinance institutions’ services, such as micro-credit, micro-savings, micro-insurance, and training, play an important role in the development of MSEs. Moreover, social and psychological capital are the crucial factors that partially mediate the relationship between microfinance services and MSE growth in Pakistan. The limitation of this study is the adaptation of a cross-sectional design to collect the data. Longitudinal research at different time frames may present diversified results. IMPLICATIONS: The study gives the impression that institutions of microfinance, practitioners, and other policymakers should enhance their perimeter to offer microfinance services and support group-based lending or training to maximize their social and psychological capital, through which MSEs may be able to attain substantial growth. ORIGINALITY/VALUE: This empirical study contributes to the literature on microfinance services and MSE growth by focusing on the mediating effect of social and psychological capital, and providing the foundation for further studies.

Keywords: microfinance services, social capital, psychological capital, micro and small enterprises, structural equation modeling.


Worldwide, micro and small enterprises (MSEs) show significant contributions to the economy. For this reason, they are in a stable position to make up the economic movements with the fulfillment of primary objectives like creating employment opportunities (Chen et al., 2017), increasing household income level (Santoso et al., 2020), and the opportunity to increase the living standard in the country (Agbola et al., 2017). In developed countries, the significant contribution of MSEs accounts for 51% of GDP via formal sources and 13% via informal sources, 16% of GDP is through formal businesses, and 47% through informal ones in developing economies (Demirgüç-Kunt et al., 2020).

Similarly, like in other developing countries, the government of Pakistan also encourages financial and economic stability for MSEs because of their important role in the growth and development of the economy. According to Ahmad and Yaseen (2018), there are 3.2 million businesses, of which 90% of this approximated figure are micro and small businesses, and they contribute up to 30% of the GDP in Pakistan, with 25% of the whole employment. MSEs’ contributions are highly valued, so they require special attention to build–up and pave the way for them (Raza et al., 2018), but they still face basic challenges in operating optimistically and contributing to a country’s economic expansion.

The concept of microfinance signifies the provision of loan services, particularly to lower-income communities, to raise their household income through escalated entrepreneurial activities and support sustainability in economic development (Mohiuddin et al., 2020; Estrin et al., 2018; Newman et al., 2017). The essential purpose of credit services is to help MSEs by granting the opportunity to attain growth in emerging markets and to become more self-contained (Wakunuma et al., 2019). In an emerging market like Pakistan, microfinance provisions towards alleviating poverty have been the subject of research in the area of sustainable economic growth (Tasos et al., 2020; Hussain et al., 2019; Ghalib et al., 2015; Naveed, 2014). The randomized studies show that most of the researchers have attempted to assess the key aspects that may disturb the sensation of microfinance interventions in terms of poverty alleviation and credit repayment services. These aspects bring in the attention to which microfinance providers help clients enhance their social contacts and trust (Ahmad & Rusdianto, 2020; Ojong & Simba, 2019; Newman et al., 2014; Brown et al., 2011), and microfinance institutions can raise the level of MSE practical support during the loaning process (Kakembo et al., 2021).

The concept of the microfinance program is not new in Pakistan. It started in the 1980s but matured in the 1990s, and now a lot of microfinance institutions (MFIs) are working for the development of MSEs with the help of the government (Bashir & Hassan, 2018). Moreover, Awan and Juiya (2015), found that the acceptance rate of applications for a loan by the banks is 65% for the medium enterprises while around 75% of loan applications have been rejected for MSEs. This caused an effect on the growth of MSEs in Pakistan.

In comparison to the vast body of previous studies investigating the effects of microfinance program interferences on credit repayment agendas for poor communities and reducing poverty, there is a lack of empirical shreds of evidence found in the literature, particularly for the emerging market of Pakistan, as to whether microfinance interventions impact the growth of existing MSEs. Though the empirical investigation by development economists (Vassallo et al., 2019; Banerjee et al., 2015) has begun, the conclusions of such research findings are unsatisfying and find narrow attention on the fundamental methods which can support the provision of microfinance effects on small businesses’ activities. In view of the debate about whether microfinance programs help the growth of MSEs, researchers have advocated a greater emphasis on identifying which micro-credit customers succeed in growth while others fail (Dutta & Banerjee, 2018; Siwale & Okoye, 2017).

The early models of microfinance programs, such as the Pakistan Microfinance Network (PMN) and Akhuwat, which followed the Grameen Bank basic model, were founded on the assumption that the small entrepreneur’s primary problem was a shortage of economic resources. Single-handedly, financial capital is insufficient to ensure the sustainable growth of existing MSEs and attain competitive advantage (Khan et al., 2019; Rungani & Potgieter, 2018). The microfinance program’s sustainability is important, as small entrepreneurs could be dependent on the expertise, social contacts, and mindset with their degree of psychological capital and social capital to seek the growth of MSEs. According to the resource-based view of the firm, the combined effect of financial, social, and psychological capital can enable even MSEs to gain a competitive advantage in an emerging market (Baluku et al., 2018). Many institutions are investigating interconnected successful microfinance programs that are accessible with a diversified variety of skills and social assistance with financial resources. Therefore, the aim of the current study is to fill this void and contribute to the entrepreneurial finance literature by empirical investigation of a proposed model that recognizes social and psychological capital as paths by which microfinance programs can lead to increased growth among MSEs.

The current study argues that microfinance programs, along with the guidance and resources for engagement provided to micro-entrepreneurs during the group-based lending process, will help develop efficient social and psychological capital. This, in turn, is assumed to help existing MSEs grow, particularly for low-income and informal entrepreneurs who would have limited access to financial, psychological, and social capital. This study suggests that the degree to which microfinance programs can improve social and psychological capital is determined by the microfinance providers’ support for the clients and the extent to which they promote social contact among lenders during the skillful training sessions and group-based lending process. Therefore, this research provides answers to the following questions: RQ1, “Does microfinance services improve MSE growth in Pakistan?” And RQ2, “Does social and psychological capital mediate the relationship between microfinance services and MSE growth in Pakistan?”


Theoretical perspective of psychological capital

The theory of psychological capital, presented by Luthans (2002), aims to describe the psychological abilities of an individual that might be evaluated, created, and used for personal and organizational success. Luthans et al. (2008) include a collection of incorporation conditions in order for a construct to be considered a component of psychological capital: it must be supported in theory, provide relevant interventions, and be like a state, meaning it can be built by preparation and deliberate practice.

Although there have been several expeditions into building psychological capital within an organizational context, the factors that can elicit psychological capital from small business owners, especially in the beginning steps of the entrepreneurial phase (Ribeiro et al., 2021), have received relatively little attention. Given the often stressful and unstable institutional climate that emergent economies face (Piperopoulos et al., 2021), microfinance programs can improve psychological capital and mitigate tension levels and distress resulting from insufficient access to financial capital in situations where small business owners find it a challenging method to mobilize economic resources beyond their immediate friends and family networks. Small entrepreneurs in deprived areas, in particular, may lack the types of resources required to be effective in business and possibly be drawn to entrepreneurship through need rather than opportunity (Farooq, 2020; Aksoy et al., 2019), with few chances for schooling, social ties, or formal jobs in the immediate vicinity (Helmy & Wiwoho, 2020; Anglin et al., 2018). Greater financial stability and opportunities can assist businesses in becoming more competitive in the face of adversity, more ambitious and optimistic about the future, and more confident in their ability to overcome challenges (Akhter, 2018). It is obvious that credit services may also cause fear, as micro and small entrepreneurs are subjected to strict repayment schedules imposed by debt collectors from microfinance institutions (Diaz-Serrano & Sackey, 2018). Diaz-Serrano and Sackey (2018) discover that the credit lender and borrower partnership positively impacts client empowerment. We conclude that while credit demand is strong and there is a supply deficit, lending has a favorable net impact on psychological wealth (Kar, 2016; Newman et al., 2014).

Theoretical perspective of social capital

Microfinance programs, particularly those focused on community loan practices or facilitating involvement, can evoke greater social capital in addition to psychological capital (Nahapiet & Ghoshal, 1998), since they usually encourage social contact between borrowers (Newman et al., 2017). The present and future wealth contained in social networks that are critical to individuals’ survival is referred to as “social capital” (Ojong & Simba, 2019). It encompasses the network’s structure and the resources that can be obtained as a result of it (Ojong & Simba, 2019). In the networks of entrepreneurs, the social capital gained from collaboration with other economic performers makes it easier to provide facts in a timely manner, facilitating opportunity discovery and exploitation (Ceci et al., 2019).

Nahapiet and Ghoshal (1998) drew two dimensions of social capital that can be encouraged by microfinance programs: structural capital and relational capital. These social capital aspects were studied extensively in the past, and they were demonstrated to promote the exchange of information, resources, and material goods among individuals (Kim & Shim, 2018). The arrangement of interactions among individuals inside a network is referred to as structural capital (Yan & Guan, 2018). Individuals’ network ties make it easier to get timely access to valuable services and intelligence, which are essential for identifying and exploiting entrepreneurial opportunities (Liu et al., 2017). The tools and knowledge made available by a network of small business owners have been shown to significantly improve the growth of existing businesses in both developed and developing markets (Adomako et al., 2018). Relational capital refers to long-term relationships established by a person’s encounters with other individuals in their social circle (Han et al., 2019). Though structural capital relates to the existence of social linkages that improve access to services and knowledge as well as the individual’s role within the network, human capital refers to the individual’s position within the network (AlQershi et al., 2021). Relational capital is concerned with the consistency of people’s relationships regarding respect, loyalty, and interpersonal assistance; in other words, to attain valuable network connections (Aaltonen & Turkulainen, 2018). While micro and small business owners may have common roles in a network, the strength of their links with other participants in the network may vary, affecting their capability to approach externally updated information and economic services.


Microfinance and MSE growth

The microfinance program gives micro and small enterprises opportunities to increase entrepreneurial activities. Some recent empirical evidence suggests that microfinance programs can influence the growth of MSEs. The empirical study conducted by Aladejebi (2019), which collected data from 205 enterprise owners in Lagos, Nigeria, found that the microfinance program led to the expansion of enterprises and generated more employment opportunities. As a result, it had a positive impact on the growth of micro and small businesses. In India, Banerjee et al. (2015) found a positive impact of microfinance on the growth of enterprises. Crépon et al. (2011) collected data from rural small enterprises in Morocco and found the fact that microfinance programs enhanced the activities of micro-enterprises had a positive impact on their growth. Another researcher, Hameed et al. (2020), found an empirically positive relationship between microfinance services and sustainable growth of MSEs in Pakistan. They supported that microfinance programs provide financial and non-financial services like micro-credit, micro-savings, micro-insurance, and training, which keep enterprises moving towards growth and competitive advantage.

Micro-credit refers to the quantity of money that clients (maybe low-income households, MSEs, or entrepreneurs) of microfinance institutions receive as a credit, with repayment required within a term period. Empirically, Kisaka and Mwewa (2014) collected data from 100 small businesses in Kenya and assessed that micro-credit creates opportunities to enhance their operations. Zakaria et al. (2020) assessed the effect of micro-credit on the well-being of poor entrepreneurs in Malaysia and found a positive impact. In the same way, the empirical study of Manaf (2017) showed the positive impact of micro-credit on the growth of small businesses.

Micro-savings is a microfinance service that refers to capital deposited in microfinance institutions under the terms of a contract between the institution and the client. Moreover, microfinance clients were mostly MSEs or poor entrepreneurs who used the deposited amount for future reinvestment (Hameed et al., 2020). Some empirical studies, for instance, Zhiri (2017), collected data from 300 small enterprises within Zaria, Nigeria, and found micro-savings enhanced entrepreneurial activities, substantial growth, and attained competitive advantages. Similarly, in Sabah, Malaysia, Ayub et al. (2020) gathered data from 97 respondents to evaluate the relationship between micro-savings and small business growth and discovered a significant connection.

The microfinance program helps with micro-insurance, which is one of the most important services for small business owners because it involves the purchase of assets with insurance coverage, but many commercial banks overlook this provision (Hameed et al., 2020). Alhassan and Magazi (2020) found that in South Africa, micro-insurance is one of the tools that moderates the consequences of susceptibility to increase welfare. Similarly, Alshebami et al. (2020) collected data from 201 borrowers of microfinance in Yemen and found that micro-insurance improved the level of protection of assets from uncertainties and the probability of the success of micro and small enterprises. Since insurance is one of the precautions against any unforeseen risks, not having insurance raises the danger of using microfinance (Bernard, 2020). Moreover, the study by Hameed et al. (2020) showed that in Pakistan, the provision of insurance coverage for microfinance borrowers improves the likelihood of micro and small enterprise growth. Akotey and Adjasi (2016) found that microfinance programs are a combination of services that consist of micro-insurance to improve the welfare of poor households and that there has been substantial growth for micro and small enterprises.

In microfinance provision, training for entrepreneurs is a structured process by which relevant knowledge is transferred in a manner that improves the participants’ social capital worth. As a result, the entrepreneur training program provided a promising future for MSE development (Galvão et al., 2020). Entrepreneurs gained awareness through a microfinance training program that improved their efficiency and avoided business loss (Dalla Pellegrina et al., 2021), which enhanced competitive advantages and, therefore, had a positive effect on the growth of businesses (Huis et al., 2019). According to Badullahewage (2020), group-based loan training facilities of microfinance programs have a positive impact on small business growth in Sri Lanka. Santoso et al. (2020) provided empirical evidence that training programs had a substantial effect on clients of microfinance for the growth of MSEs. As a result, the findings of previous empirical studies support the following hypothesis:

H1: Micro-credit has a positive relationship with microfinance.

H2: Micro-savings have a positive relationship with microfinance.

H3: Micro-insurance has a positive relationship with microfinance.

H4: Training has a positive relationship with microfinance.

H5: Microfinance has a positive relationship with MSE growth.

Social capital, microfinance, and MSE growth

A microfinance program, particularly involving group-based training or other participative initiatives, would have a positive effect on the growth of existing small enterprises by encouraging clients to build more social capital (Worokinasih & Potipiroon, 2019). Social capital, it is argued, promotes the exchange of information and services between microfinance borrowers (Ul-Hameed et al., 2018), and improvements to micro and small enterprise processes, the discovery of potential markets, and better strategies for risk reduction are also possible outcomes (Sani et al., 2019). Empirical work by Kala et al. (2020) on the suitability of such claims in the microfinance context is supported, and it is discovered that both the amount and efficiency of microfinance borrowers’ social relations improve micro and small enterprises’ success in terms of growth. Feigenberg et al. (2010) conducted an empirical study in Peru and found that group-based microfinance practices had a positive impact on borrowers’ social networks. The research also discovered that weekly microfinance consumer meetings resulted in close social interaction with microfinance clients (Bongomin et al., 2017). Similarly, Mosley (2001) discovered that group-based loan lending affected social capital positively among microfinance clients in Romania, Slovakia, and Russia, leading to the growth of enterprises. The findings of Sanyal’s (2015) work show that microfinance programs in India are dependent on group lending, with such programs helping to improve social capital among lenders and having a positive effect on their business development. On the basis of these arguments, the following hypotheses are made:

H6: Microfinance has a positive relationship with social capital.

H7: Social capital has a positive relationship with MSE growth.

Social capital as a mediator

Newman et al. (2014) found that microfinance services influence MSE growth through social capital. This argument assumes that social capital serves as a mediating factor in the relationship between microfinance services and MSE growth. Theoretically, the role of social capital in mediating the relationship between microfinance services and MSE growth is undeniable (Kamukama & Natamba, 2013). While theoretical arguments support the significance of social capital as a mediating factor in the relationship between microfinance and MSE growth, empirical evidence in the literature is scarce. A relationship analysis that overlooks the mediating mechanism, according to Rosenberg (1968), ends up with facts but an incomplete understanding. In a similar context, Bennet (2000) claimed that research that does not take into account the probability of a mediator effect in the results might miss out on additional reasons for an outcome. In view of the foregoing, the purpose of this research was to investigate the practical role of social capital in the relationship between microfinance services and MSE growth. Therefore, the following hypothesis emerges:

H8: Social capital mediates the relationship between microfinance services and MSE growth in Pakistan.

Psychological capital, microfinance, and MSE growth

A microfinance program can positively impact the growth and success of existing small businesses by cultivating higher levels of psychological capital among clients. Individuals with high psychological capital have been found to have the skills they need to cope with the emotional pressures that come with expanding entrepreneurial activities (Baron et al., 2016), particularly in complex, competitive environments characterized by high risk and instability, such as those confronting small business owners in developing countries (Jin, 2017).

According to previous studies, small entrepreneurs with high-pitched psychological capital are more likely to form close interpersonal bonds with one another in their social networks (Obeng et al., 2021; Digan et al., 2019). These positive practices can help with small business activities and encourage owners to thrive in environments that other entrepreneurs could find difficult (Margaça et al., 2020). Despite the fact that there is little research into the influences that may contribute to the creation of psychological capital in small business owners, a small number of studies have started to look into its effect on their growth ambitions (Hizam-Hanafiah et al., 2017). For instance, Andri et al. (2019) discovered that psychological capital was favorably linked to the success of small enterprises and that it explained a large portion of the variation in performance, in addition to conventional sources of financial, social, and human capital.

While recent research (such as, Dalla Pellegrina et al., 2021; Huis et al., 2019; Agbeko et al., 2017) has focused on the effect of training on the effectiveness of microfinance programs provided by financial institutions, earlier studies (such as Dutta & Banerjee, 2018; Panda, 2016) have still not looked at whether microfinance, when combined with financial services (credit, savings, and insurance) and non-financial services (training), has a direct effect on small enterprises borrowers’ psychological resources. Even so, growing evidence suggests that psychological capital can be built through non-financial services of microfinance like training for small entrepreneurs (Newman et al., 2014) and that a positive enterprise climate will have an effect on the growth of psychological capital and the growth of existing small businesses in an emerging market setting (Ismail et al., 2017). As a result of the above research, the following hypotheses are formed:

H9: Microfinance has a positive relationship with psychological capital.

H10: Psychological capital has a positive relationship with MSE growth.

Psychological capital as a mediator

Entrepreneurial capital is determined by the sum of the entrepreneur’s assets (Shaw et al., 2009). Psychological capital plays a mediating role and refers to an entrepreneur’s belief that he or she has the ability to get financial and non-financial microfinance services to achieve sustainable development in competitive marketplaces (Newman et al., 2014). The role of psychological capital in mediating the relationship between microfinance services and MSE growth is evident (Nordin et al., 2019). Although theoretical arguments indicate the importance of psychological capital as a mediating component in the relationship between microfinance and MSE growth, empirical evidence is lacking in the literature (Ismail et al., 2017). Friedrich (1982) continued by stating that examining the mediating impact of variables in a relationship explicates the nature of the relationship and the amount to which the mediating variable influences the link between the two variables. Therefore, this study established the following hypothesis:

H11: Psychological capital mediates the relationship between microfinance services and MSE growth in Pakistan.

Conceptual framework

As previously discussed, it is critical to comprehend the significant impact of microfinance services on MSE growth with the help of social and psychological capital. Therefore, the study’s first aim is to identify the significant influence of microfinance services on MSE growth in Pakistan. The second aim is to assess the mediating impact of social and psychological capital on microfinance services and MSE growth in Pakistan. Hence, the conceptual model (see Figure 1) proposed in this research is best suited to MSEs’ owners with insufficient resources, skills, and networks, who are driven by their businesses due to a lack of other economic prospects in the emerging markets. Perceiving the importance of financial, social, and psychological capital in MSE growth would contribute to resolving the debate over whether, and under what conditions, microfinance programs succeed.

Figure 1. Conceptual framework


Research paradigm and design

Antwi and Hamza (2015) refer to the term “research paradigm” as a methodical discipline’s theoretical structure, which is based on hypotheses, theories, aims, assumptions, and techniques that characterize a scientific investigation. For this research, a positivism approach was chosen as the paradigm of the study that stressed quantitative methods. Inferential logic is used in the adoption of the positivism method to define a theoretical confirmation of variables, which is then followed by empirically accepting or rejecting the proposed hypothesized relationships (Kock et al., 2017). Venkatesh et al. (2016) argued that the methods used to lead the research must be on the same path as the main objective. Hence, a quantitative method was carried out in this study to test the hypotheses and achieve the aim of the study. Similarly, Smith and Hasan (2020) relate a quantitative approach to assist scholars in developing statistical proof on the depth of relationships between dependent and independent constructs.

Measurement of variables

Shirali et al. (2018) recommended using the utilized instrument since its reliability and validity had already been investigated. Thus, already tested and examined instruments were employed in this research. For micro-credit, micro-savings, micro-insurance, and training are considered major services provided by microfinance programs. To measure these constructs, the items were adapted from the previous studies of Hameed et al. (2020), Bernard et al. (2016), and Babajide (2012). The mediating effect of social capital between microfinance and MSE growth. The items were adapted from Hameed et al. (2020) and Naala (2016). Psychological capital is considered as a moderator in this study. The items were adapted from Digan et al. (2019). Similarly, for the construct of MSE growth, the items were adapted from Kisaka and Mwewa (2014) and Babajide (2012).

Data collection and sample

According to Etikan and Bala (2017), a population is a set of people who are situated in the particular region in which academicians desire to investigate the wanted information. This research adopts quota sampling, which is the reason the sample size is split by sectors (services and manufacturing). Based on Krejcie and Morgan (1970), the final sample size is 769. While the data was collected from MSEs of preselected cities in Pakistan (such as Islamabad, Karachi, Abottabad, Lahore, Peshawar, Multan, and Quetta), the questionnaires were given to the MSEs through the enumerators. By using this method, all the questionnaires were distributed. In this case, the MSEs had the chance to fill out the questionnaire on time. According to Zikmund (2003), this approach is known as “drop-off,” because the researcher goes to the respondent’s locations to drop-off the questionnaires and pick them up after they have finished. The questionnaires were provided in Urdu and English, and MSEs had the choice to fill out any version they liked. 770 respondents from metropolitan cities in Pakistan were contacted in the survey, and the response rate was 64%. After screening the data, only 357 questionnaires appeared to be completed in all respects, so they were initially fed into the computer spread and then imported for further analysis. Meanwhile, the percentages of the missing items were less than 5%, and, therefore, they were replaced through the mean replacement procedure (Kwak & Kim, 2017).

Method of data analysis

Structural equation modeling (SEM) was used to examine the structural and measurement models in a two-stage technique. The interactional influence of the structural and measurement models is reduced in these two stages. The measurement model was investigated in the first step by using confirmatory factor analysis (CFA) to evaluate the convergent validity and causal relationship among adapted items and variables (Byrne, 2013). Moreover, following the recommendation of Hair et al. (2017), the instrument’s validity and reliability were also verified for further analysis. The structural model was used to investigate the relationship between the exogenous variable (microfinance services) and the endogenous variables (social capital, psychological capital, and MSE growth) in the second stage.


Sample characteristics

The demographic characteristics are personal and enterprise information of the respondents through survey questionnaires from different cities in Pakistan. A total of 357 respondents’ profiles have been classified based on their gender, age, marital status, education, income, business activities, the year the business started, and the number of employees. Demographic analysis was performed using a descriptive statistic to determine the respondents’ backgrounds based on the questions in the questionnaire. Table 1 provides detailed information.

Table 1. Profile of respondents



Percentage (%)









Less than 20












Above 50



Marital status














High school or less






Bachelor degree









Income level

Less than Rs 20,000



Rs 20,001 to 30,000



Rs 30,001 to 40,000



Rs 40,001 to 50,000



Rs 50,001 and above



Business activities










Business started

Before 2018












No. of employees

2 or less









5 and more



Normality statistics

Skewness and kurtosis were utilized to determine the normalcy of the data in this study. Each construct’s skewness and kurtosis have been calculated (see Table 2). As recommended by Qu et al. (2020), the results show that the skewness and kurtosis were both within the permissible range of the ± 3.

Table 2. Descriptive statistics




Std. dev.



























Social Capital






Psychological Capital













Reliability was utilized to assess the consistency of the items used in the survey. Internal consistency is measured by Cronbach’s alpha, which is better than 0.70 and above (Pallant, 2020). All of the constructs utilized in this study have reliabilities of 0.70 to 0.90. Micro-savings (= 0.851), training (= 0.863), social capital (= 0.885), psychological capital (= 0.876), and growth (= 0.893) all have reliabilities of 0.80 or higher. On the other hand, micro-credit (= 0.916) and micro-insurance (= 0.927) have a reliability of 0.90 or higher.

Discriminant validity

To establish discriminant validity, the correlation of all of the constructs used in this study was calculated (see Table 3). According to the discriminant validity results, the correlation between the pairs of variables is less than 0.85, as recommended by Carter (2016).

Table 3. The correlation of the constructs









































Social Capital








Psychological Capital
















Confirmatory Factor Analysis (CFA) results

The measurement model was put to the test in this study via CFA validation of variables. If somehow the model was determined to be inaccurate, it was re-specified using Hair et al. (2017) and Byrne’s (2013) criteria. Variables were then tested for reliability and validity in the following phases. As a result, the measurement model was put to the test in two stages: (1) determining the factor’s unidimensionality, and (2) determining the constructs’ reliability and validity. The findings of the numerous fit indices were tested following Mueller and Hancock’s (2018) guidelines to see if the CFA findings for the specified variables were acceptable (see Table 4). The specified and assessed fit indices are: chi-square, degrees of freedom (df), relative chi-square (CMIN/df), goodness of fit index (GFI), root mean square error of approximation (RMSEA), adjusted goodness of fit index (AGFI), and comparative fit index (CFI).

Table 4. CFA results









































Social Capital








Psychological Capital








MSE Growth








Measurement model testing

The measurement model was assessed after the CFAs for each measure were completed. The measurement model specifies the procedure for loading each measure into a specific variable (Hair et al., 2017). All of the observed variables were used to test the measurement model, such as microfinance services, social capital, psychological capital, and MSE growth. The findings revealed that the entire measurement model was well-fitting, resulting in an RMSEA of 0.038 and chi-square value of 606.108 with 356 degrees of freedom (p<0.005). The statistics for the test of fit were GFI= 0.917, AGFI=0.914, CFI =0.949 and CMIN/df = 1.703. Finally, the confirmatory factor analysis demonstrated that the measurement model is effective (see Figure 2).

Figure 2. Measurement model

Note: MC (Micro-credit), MS (Micro-savings), MI (Micro-insurance),
T (Training), SC (Social Capital), PC (Psychological Capital), G (Growth).

Reliability and validity of the instrument

After performing the CFAs for each variable, the instrument’s reliability and validity were assessed (Hair et al., 2017). Average variance extracted (AVE), composite reliability (CR), and Cronbach alpha coefficients were used to examine the reliability and validity. The variables’ reliability was also assessed by looking at the CFA and Cronbach alpha values. Cronbach alpha values of less than 0.50 are considered unacceptable, values between 0.50 and 0.60 are considered low yet acceptable, and values greater than 0.70 are regarded as a good fit (Kline, 2005). All of the alpha values of the observed variables were determined to be good matches according to the prior acceptable values. The parameters of AVE and CR were calculated using Fornell and Larcker’s (1981) formula. According to Byrne (2013), the AVE values should be 0.50 or above , and the CR values should be 0.60 or above. As a result of this study, the data results were satisfactory (see Table 5).

Table 5. Measurement model evaluation



Measurement path

Factor loading


alpha (α)








The interest rate on the loan is affordable.




The amount of the loan is sufficient.




The repayment time for the loan is enough.




The method for securing a loan is simple.





Measurement path

Factor loading


alpha (α)








Savings interest is reasonable.




The saving products are appealing.




The methods are simple.




Withdrawing money from your savings account is simple.





Measurement path

Factor loading


alpha (α)








Benefits from insurance are effective.




The variety of policies available is satisfactory.




The cost of insurance coverage is reasonable.




Insurance claims are processed quickly.





Measurement path

Factor loading


alpha (α)








Training programs are beneficial to the operation of my business.




The frequency with which skills development programs are offered is adequate.




Training programs can help me advance in my career.



Social capital


Measurement path

Factor loading


alpha (α)








Interactions with my social contacts assist me in improving our business performance.




My training participation has aided in the development of a strong network.




My relationships with potential and current customers (or suppliers) assist me in growing and improving our business.




My own business’s social contacts assist me in growing and improving my business.



Psychological capital


Measurement path

Factor loading


alpha (α)








I am confident in my ability to achieve my business objectives.




I am confident in my ability to work under pressure and in difficult situations.




In my opinion, all business challenges, will always have a positive aspect to them.




“I may fall but I am able to rapidly pull through” when faced with business disappointment.



Business growth


Measurement path

Factor loading


alpha (α)








My business will benefit from the entrepreneurship training.




My assets have increased in value as a result of the loan.




In my company, new employment are created.




My business’s production has increased due to loan services.




Services have aided in the growth of my business earnings.



Note: CR = Composite Reliability; AVE = Average Variance Extraction.

Structural model

Once all constructs have been validated and an acceptable fit has been achieved in the measurement model (stage one), a structural model can be tested and obtained as the second and most important stage of the research (Byrne, 2013). In this study, the exogenous variables (microfinance services, micro-credit, micro-savings, micro-insurance, and training) and endogenous variables (social capital, psychological capital, and MSE growth) are illustrated in Figure 3. This figure illustrates the standardized estimates as well as the values of model fit. The findings displayed are that the structure model was well-fitting, resulting in a RMSEA of 0.038 and a chi-square value of 674.309 with 356 degrees of freedom (p<0.001), GFI = 0.915, CFI = 0.954, AGFI = 0.900 and CMIN/df = 1.894. In conclusion, the outcomes indicated that the structural model is good.

Using AMOS 21.0, the CFA and two-step SEM approach was used in this study to investigate the hypothesized associations, as recommended by Hair et al. (2017). The hypotheses H1, H2, H3, H4, H5, H6, H7, H9, and H10 were statistically significant in testing the hypothesized relationship, as shown in Table 6. These hypotheses all had significant standardized estimates. As a result, these hypotheses were supported.

Figure 3. Structural model

Table 6. Testing hypotheses using standardized estimates

Hypothesized path

Standardized estimate




H1: MC-->MFS





H2: MS-->MFS





H3: MI-->MFS





H4: T-->MFS





H5: MFS-->G





H6: MFS-->SC





H7: SC-->G





H9: MFS-->PC





H10: PC-->G





The mediation analysis

Hypothesis 8 (H8) and hypothesis 11 (H11) tested whether social capital and psychological capital mediate the association between microfinance and MSE growth. This study used the Awang et al. (2015) identified technique to measure the mediation effect. According to Awang et al. (2015), the indirect effect between the constructs is greater than the direct effect. Once the direct effect is also significant, it is called partial mediation. In this study, the indirect effect of social capital was 0.37 (0.68 x 0.54 = 0.37), while the direct effect was 0.31, and the indirect effect of psychological capital was 0.34 (0.72 x 0.48 = 0.34), while the direct effect was 0.31. Hence, social capital and psychological capital partially mediate the relationship between microfinance and MSE growth in Pakistan.

Resampling, often known as “bootstrapping,” is another way to deal with the sampling distribution of the constructs. The properties of the sampling distribution can be derived without assuming normality in this method, as it was formed from the estimations of constructions calculated from thousands of newly created samples.

The bootstrapping strategy for obtaining the mediating effect performs exceptionally well in methodological evaluations (Demming et al., 2017). According to Awang et al. (2015), bootstrapping was consistently the most influential. According to Demming et al. (2017), today’s researchers feel the bootstrap is the best method for determining the mediation effect. As a result of this study, hypotheses 8 (H8) and 11 (H11) were accepted (see Table 7), when the bootstrapping technique indicated partial mediation had occurred.

Table 7. Bootstrapping results


Effect results


Social capital


Indirect effect


0.000 (Significant)

Direct effect


0.000 (Significant)

Psychological capital

Indirect effect


0.000 (Significant)

Direct Effect


0.000 (Significant)


According to the findings of the current study, microfinance services (micro-credit, micro-savings, micro-insurance, and training) have a substantial positive relationship with MSE growth. The association between micro-credit, micro-savings, micro-insurance, and training and microfinance institution program (H1, H2, H3, and H4) yielded significant t-values and positive β-value (see Table 5). These estimates show that when all of these services improve, the value of microfinance programs to MSE growth will rise. The findings were in line with previous research, such as the study of Kisaka and Mwewa (2014), which discovered that micro-credit, micro-insurance, and micro-savings have a significant impact on microfinance programs for small enterprises to attain the substantial growth in emerging markets. Furthermore, according to Dutta and Banerjee (2018), many microfinance borrowers lack specific skills, making it difficult for them to make good use of such program. Microfinance programs have resulted in more opportunities for skilled entrepreneurial activity, which has had a favorable impact on microfinance performance (Hameed et al., 2020). As a result, Ekpe et al. (2015) discovered that training has a favorable impact on microfinance clients.

The study’s findings revealed a strong relationship between microfinance services and MSE growth (H5) in Pakistan. This demonstrated that microfinance has a positive impact on MSE growth. According to research done in the Philippines by Garrity and Martin (2018), microfinance helped business growth and create more job prospects. As a result, it left a positive influence on the performance of MSEs. In the same vein, Banerjee et al. (2015) discovered that microfinance services positively impact business growth in India.

The hypotheses H6 and H7 in this study investigated the direct relationship between social capital, microfinance services and MSE growth, and discovered a substantial association. The hypothesis H8, on the other hand, looked at the role of social capital in mediating the relationship between microfinance services and MSE growth. According to the findings, social capital in Pakistan partially mediates the relationship between microfinance services and MSE growth. The empirical evidence from Hameed et al. (2020) discovered that microfinance clients and members of group borrowers increased social capital, which had a favorable influence on small business growth. Kamukama and Natamba (2013) discovered that social capital played a favorable mediating role between microfinance services and growth of businesses. They also discovered that microfinance group-based lending increased customer social capital and had a positive impact on the growth of micro and small enterprises. Similarly, in Newman et al. (2014) study, social capital was used as a mediator between microfinance and the growth of existing small businesses.

Similarly, significant t-values and positive β-value were identified in the direct relationship between psychological capital (H9 and H10), microfinance services, and MSE growth. The hypothesis H11, on the other hand, looked into the role of psychological capital in mediating the relationship between microfinance services and MSE growth. According to the findings, psychological capital in Pakistan partially mediates the relationship between microfinance services and MSE growth. Microfinance services may encourage the development of psychological capital in businesses and the growth goals of micro and small businesses (Nordin et al., 2019). Bockorny and Youssef-Morgan (2019) discovered that psychological capital was positively connected to MSE growth and that it explained a considerable portion of the variance in performance beyond traditional types of financial capital. According to Haji et al. (2020), psychological capital has a favorable impact on MSE growth.


The current study focuses on the role of microfinance services in the growth of MSEs in Pakistan. In addition, the study looked into the impact of social and psychological capital on the growth of micro and small enterprises. For this quantitative study, a survey tool was used to collect data from MSE clients of microfinance institutions. It was discovered that microfinance services play a key role in assisting MSE growth. Microfinance services, including micro-credit, micro-savings, micro-insurance, and training, play an important role in the growth of micro and small enterprises. These services make it easier for MSEs to operate, which results in increased revenue, competitive advantages, and growth in emerging markets. Furthermore, social and psychological capital have a positive impact on MSEs’ long-term growth. Microfinance services improve the positive contribution of social and psychological capital to micro and small enterprises, resulting in increased growth.

From a theoretical perspective, this research contributed to the existing literature in the domains of entrepreneurial finance, social capital, psychological capital, and micro and small enterprises. Previous empirical research has focused on microfinance programs’ interferences on credit repayment agendas for poor communities and reducing poverty, but none has examined how social and psychological capital connect microfinance services and MSE growth. Therefore, our findings show that social and psychological capital might partially mediate the relationship between microfinance services and MSE growth, which is unique in the literature on the issue. This research implies that social and psychological capital are important for MSE growth and sustainability in Pakistan. As a result of the findings, researchers are now debating the impact of social and psychological capital on micro and small businesses. Moreover, the study leads researchers to investigate numerous social and psychological capital components, as well as how these are managed to promote sustainable growth in the sector.

Furthermore, the consequences have shed light on the financial capital, social capital, and psychological capital that need to be improved in the development and expansion of micro and small businesses. This is critical in encouraging entrepreneurial practices and boosting MSE growth in Pakistan’s most vulnerable low-income households. Policymakers in Pakistan can apply the research results to reduce long-term economic vulnerability among low-income households. Also, this research will help microfinance providers achieve their ultimate goal of enhancing MSE growth. Additionally, this study has emphasized the importance of major services delivered by microfinance providers that can help MSEs.

We can certainly conclude that the empirical evidence reported in this research is critical for the Small and Medium Enterprise Development Authority (SMEDA) and the State Bank of Pakistan (SBP) in their pursuit of MSE sustainability. The SMEDA and the SBP both have a good understanding of what makes microfinance services better. In addition to the services provided by microfinance institutions, the Pakistani government should also help micro and small enterprises through various loan initiatives. As a result, measures to boost the growth of micro and small enterprises will always be supported and raised to a significant level.

Due to individual and environmental factors, the study had several limitations. These constraints give plenty of room for future research and academic endeavors. First, the sample size is a potential constraint of the study, which may have been increased further to emphasize the importance of some well-crafted research questions. Because of COVID-19 travel restrictions, the study only included micro and small enterprises in Pakistan’s urban areas; nonetheless, it would have been preferable if more rural MSEs had participated. Second, the results’ generality is limited in its relevance to other sectors. Because the behaviors of the services and manufacturing sectors differ from those of other sectors, studies using different sectors may give different conclusions than those presented in this study. Third, the study’s findings were based on cross-sectional data derived from self-completed survey questionnaires, making it impossible to draw hard conclusions about causality. It is not possible to rule out the possibility that causation would act in the opposite direction of what was expected. As a result, a sequential longitudinal study is required. Finally, in order to generalize the findings of this study, more research in diverse geographic areas and sectors is required. It is also interesting to look at the impact of microfinance services on other major outcome variables like MSEs’ performance or new venture creation.


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CEL: W dobie globalizacji i konkurencji na prężnie rozwijającym się rynku, mikro i małe przedsiębiorstwa (MSE) poszukują zrównoważonego rozwoju poprzez konsumpcję różnorodnych zasobów. Wcześniejsze badania wykazały, że usługi finansowe i mikrofinansowania są podstawowymi czynnikami przetrwania MŚP. Jednak nadal brakuje charakterystycznej roli innych usług mikrofinansowych, takich jak mikrokredyty, mikrooszczędności, mikroubezpieczenia, szkolenia i sieci społecznościowe, w osiąganiu znacznego wzrostu sektora MSE, co wyjaśnia, dlaczego MSE tworzą tak mały wkład w gospodarkę Pakistanu. Dlatego głównym celem badania jest rozważenie wpływu usług mikrofinansowych na rozwój MSE w Pakistanie, ponieważ MSE są najbardziej wrażliwą grupą w kraju i na całym świecie. Ponadto badanie to określiło również pośredniczącą rolę kapitału społecznego i psychologicznego w zwiększaniu produktywności usług mikrofinansowych dla MŚP. METODYKA: Skontaktowano się z 770 respondentami z miast metropolitalnych w Pakistanie, a odsetek odpowiedzi wyniósł 64%. Po przejrzeniu danych tylko 357 kwestionariuszy zostało wypełnionych pod każdym względem, więc zostały one początkowo wprowadzone do programu komputerowego, a następnie zaimportowane do dalszej analizy. Ustrukturyzowane kwestionariusze posłużyły do zebrania danych od 357 mikro i małych przedsiębiorstw działających na rozwijającym się rynku Pakistanu. Wyprowadzone hipotezy zweryfikowano za pomocą modelowania równań strukturalnych (SEM) przy użyciu AMOS 21. WYNIKI: Wyniki badania wykazały, że usługi mikrofinansowe odgrywają zasadniczą rolę w promowaniu rozwoju MSE. Usługi instytucji mikrofinansowych, takie jak mikrokredyty, mikrooszczędności, mikroubezpieczenia i szkolenia, odgrywają ważną rolę w rozwoju MŚP. Ponadto kapitał społeczny i psychologiczny są kluczowymi czynnikami, które częściowo pośredniczą w związku między usługami mikrofinansowymi a wzrostem MSE w Pakistanie. Ograniczeniem tego badania jest dostosowanie projektu przekrojowego do zbierania danych. Badania podłużne w różnych ramach czasowych mogą dawać zróżnicowane wyniki. IMPLIKACJE: Badanie sprawia wrażenie, że instytucje mikrofinansowe, praktycy i inni decydenci powinni poszerzyć swój zasięg, aby oferować usługi mikrofinansowe i wspierać pożyczki lub szkolenia grupowe, aby zmaksymalizować swój kapitał społeczny i psychologiczny, dzięki któremu MŚP mogą w stanie osiągnąć znaczny wzrost. ORYGINALNOŚĆ/WARTOŚĆ: To badanie empiryczne wnosi wkład do literatury na temat usług mikrofinansowych i wzrostu MSE, koncentrując się na pośredniczącym efekcie kapitału społecznego i psychologicznego oraz zapewniając podstawę do dalszych badań.

Słowa kluczowe: usługi mikrofinansowe, kapitał społeczny, kapitał psychologiczny, mikro i małe przedsiębiorstwa, modelowanie równań strukturalnych.

Biographical notes

Muhammad Farhan Jalil is currently the Programme Coordinator for Master of Science in Business & Management and Ph.D. in Business & Management, School of Business and Management, University College of Technology Sarawak since October 2020. He has five years of professional experience at higher education institutes in Malaysia and Pakistan. His current research interest includes entrepreneurial finance, MSMEs development, entrepreneurship and innovation, and financial inclusion.

Azlan Ali is an Associate Professor at the University College of Technology Sarawak and has 27 years of professional development and vast experience in industry and academia. Dr. Azlan Ali was appointed as Deputy Vice-Chancellor (Academic) from March 2019 until February 2021. Before, he worked with AmBank Berhad and the Department of Corporate Banking. Dr. Azlan Ali was also chosen to be a researcher at the Varna University of Economics,Bulgaria. In 2011, he joined Universiti Kuala Lumpur Business School and his last position was Deputy Dean.

Zeeshan Ahmed is working as an Assistant Professor in the Department of Management Sciences at the University of Lahore Gujrat campus. He has four years of professional experience at the university level and five years’ experience in banking sector. His core areas of interest are corporate finance and risk management.

Conflicts of interest

The authors declare no conflict of interest.

Citation (APA Style)

Jalil, M.F., Ali, A., & Ahmed, Z. (2022). Microfinance services and MSE growth in Pakistan: The mediating perspective of social and psychological capital. Journal of Entrepreneurship, Management, and Innovation, 18(1), 93-129.