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Article

Fostering Youth Entrepreneurship Development through Social Business—Evidence from Bangladesh

by
Farhana Ferdousi
1,*,
Parveen Mahmud
2 and
Kazi Tanvir Mahmud
3
1
Southeast Business School, Southeast University, Dhaka 1213, Bangladesh
2
Grameen Telecom Trust, Dhaka 1213, Bangladesh
3
Department of Economics, Southeast University, Dhaka 1213, Bangladesh
*
Author to whom correspondence should be addressed.
Sustainability 2023, 15(1), 756; https://doi.org/10.3390/su15010756
Submission received: 8 October 2022 / Revised: 14 December 2022 / Accepted: 28 December 2022 / Published: 31 December 2022
(This article belongs to the Special Issue Social Business and Impact for Sustainable Growth)
Browse Figure
Review Reports Versions Notes

Abstract

:
A social business fund is a novel financial instrument that can assist micro-entrepreneurs. Extensive research has been conducted on the effects of microcredit on the income, expenses, health, and living standards of entrepreneurs. In this study, we expand on previous research by analyzing a novel financial instrument called social business funds. Specifically, this study investigated the impact of social business funds on micro-entrepreneurs’ income. Primary data were collected from the young micro-entrepreneurs. The Propensity Score Matching (PSM) technique was used to assess the impact of social business funds on the livelihood of entrepreneurs in terms of income and expenditure. Binary Logistic Regression (BLR) was also used to assess the opinion of the micro-entrepreneurs on the increase in their entrepreneurial income. The results showed that the social business fund significantly impacted entrepreneurs’ incomes. Along with funds, some entrepreneurial training and support services were recommended. Government and non-government organizations are advised to take appropriate policy initiatives.

1. Introduction

Governments across the globe have battled over the past two decades to meet the demands and expectations of their constituents [1]. In addition, they have made it a top priority to find solutions to the world’s most pressing social problems [2,3]. Social enterprise is one of the most powerful tools to combat these societal ills [4,5]. As a result, social entrepreneurs continuously try to address such complex social problems through their entrepreneurial means. Given the rise of these social enterprises, scholars and practitioners alike are trying to comprehend their practice and outcome.
Businesses with social missions differ from conventional corporations that prioritize shareholder returns [2,3]. As stated previously [2,5,6,7], social businesses are structured and run just like any other firm, complete with products, services, customers, markets, expenses, and revenues; however, the goal of profits is subverted in favor of maximizing social benefit. While social entrepreneurs are motivated by a desire to do good in the world, they are equally motivated by the need to profit [5]. It is important to remember that a social business does not provide dividends, but uses its earnings to grow, innovate, and increase its positive impact on society [4,7].
Unemployment is one of the major impediments to the country’s economic growth in Bangladesh. Generally, it is assumed that a significant portion of the youth population is unemployed due to insufficient funds, a lack of skills, and gender disparities. For example, social norms and employer misconceptions frequently prevent young women in Bangladesh from working in the formal sector [8]. As Shahriar et al. [9] argue, youth are frequently unattractive in the job market due to a lack of appropriate job-related skills and experiences. Furthermore, due to information asymmetry, youth are unattractive to banks when taking out loans for small start-ups [10,11]. In addition, rural and peri-urban societies often fail to create sufficient job opportunities for unemployed youth [12]. A country can make tremendous progress by improving entrepreneurship skills among its youth [13]. Thus, youth participation in a country’s development policies should be ensured [14].
The Government of Bangladesh (GOB) has established policies and initiatives to boost young entrepreneurship by developing effective partnerships among NGOs, donor agencies, and other social stakeholders. The GOB has provided youth entrepreneurs with financial, technological, and infrastructural support. For example, the government and NGOs in Bangladesh operate microcredit initiatives for poor rural women to create entrepreneurship prospects [15,16]. Numerous impact studies related to microcredit have been conducted in Bangladesh. These findings show that providing financial assistance to poor people in the form of collateral-free loans through microcredit programs plays a critical role in increasing their income and expenditure, creating employment opportunities, and improving rural women’s decision-making and risk-management capacity [15,16,17,18,19,20,21,22,23]. Microcredit initiatives have also failed to achieve social and economic goals [24]. Many microcredit borrowers have fallen into the loan trap due to strict repayment schedules and hefty interest rates [24,25,26]. Some researchers have criticized microcredit schemes for producing social tension, increasing physical and verbal abuse towards female borrowers, and increasing their workload [24,27].
Unlike microcredit, a social business fund (SBF) is provided as an equity fund, which is more accessible for low-income micro-entrepreneurs. SBF is not like a loan; thus, it is free from interest and can potentially eliminate poverty by assisting young entrepreneurs [7,28]. Funders have established a few conditions for SBF eligibility. For example, SBFs are only available to youth under 35 years old to start or expand their businesses [6].
Prior research has focused on concepts of social business, characteristics of social entrepreneurs, reducing moral hazards, developing a theoretical framework for social business, obstacles to establishing social enterprises, and a bibliometric analysis of social business [2,3,4,5,29,30]. However, the studies related to the impact of SBF on the youth entrepreneur are scant. So far, according to our knowledge, very few studies have been conducted on SBFs in Bangladesh [7,31]. For example, it was observed that SBFs positively empowered women in Bangladesh regarding socioeconomic and political aspects [28]. However, the impact of SBFs on the economic status of the youth entrepreneur still needs to be clarified and documented more extensively. It is assumed that receiving SBFs will empower the youth entrepreneurs regarding income and expenditure. Therefore, this study was conducted to address the following question:
Q1. Can the social business fund improve the living standard of young entrepreneurs in terms of income and expenditure?
Thus, this study aims to assess the impact of social business funds on the living standard of poor entrepreneurs in terms of income and expenditure using the Propensity Score Matching (PSM) technique. Along with describing the entrepreneurs, this study focused on assessing the entrepreneurs’ perspectives on their economic well-being under the Nobin Equity Program (NEP). Our research adds to the existing body of knowledge in several important ways. First, this research contributed to the social entrepreneurship literature by focusing on one specific kind of social business initiative. Second, the research advanced our understanding of social entrepreneurship through the lens of agency theory and utility theory. NEP is a contractual mechanism between the principal (Grameen Companies providing SBF) and the agent (micro-entrepreneurs utilizing the fund). According to the utility theory, any additional unit of investment in the form of SBF will increase the livelihood of young micro-entrepreneurs in terms of income and expenditure. Third, our empirical findings will contribute to the growing body of research on the impact of social businesses, which will be helpful to practitioners in the sector. Fourth, this study’s findings would assist policymakers in creating and facilitating effective social business programs in Bangladesh and elsewhere. Finally, our paper lays the groundwork for future study in the social entrepreneurship field, which is still developing.

1.1. Role of Youth Entrepreneurship

Undoubtedly, global economic progress largely depends on the youth, as they are considered potential human resources and future leaders [13,32]. A country can progress tremendously by encouraging the use of entrepreneurship skills among the youth [13,33,34,35].
A significant portion (about 85 percent) of the world’s youth population lives in developing countries, mainly in Asian countries [36,37]. Youth unemployment has become a severe problem in many countries, even in industrialized countries, and unfortunately, the youth unemployment rate has been increasing over time [35,36,38,39,40]. Increasing youth unemployment will harm the economy of a country. For example, the increasing unemployment rate among youth has threatened the economic stability in Sri Lanka [41] and South Africa [42]. It is difficult for young people to find a well-paying job in the formal sector. They mainly work poorly paid, low-quality jobs in the informal sector [43]. Therefore, youth employment has become an important policy issue for national and international development organizations [13,43].
Youth entrepreneurship is believed to promote employment opportunities, foster innovation and resilience among young people, and increase their social and cultural identity, which, in fact, promotes empowerment [44]. Nowadays, every country is concerned about the importance of developing entrepreneurial skills among the youth to fight against economic crises or recessions. As a result, different types of programs, e.g., entrepreneurial education [35,40,45], financial literacy [13] training, and credit programs, are being launched by the multilateral agencies for youth to start or to facilitate business activities [14,32,33].
However, there are still many challenges remaining in the development of youth entrepreneurship. Lack of financial and infrastructural support, unsupportive economic policies, a lack of vocational education facilities, and a slow rate of technological development, for example, are major barriers to the development of young entrepreneurship [12,46]. Promoting youth entrepreneurship is often constrained by several common barriers: access to information, access to credit, acquisition of relevant skills, access to the market, and relevant institutional support [47]. This study contributed to the literature on young entrepreneurship by investigating the impact of the NEP program, which is given to young micro-entrepreneurs to promote entrepreneurship among the youth.

1.2. Nobin Equity Program for Youth Entrepreneurship Development

Nobin Equity Program (NEP) is an innovative social business program that was founded in 2014. This program is designed and dedicated to identifying, incubating, and promoting young entrepreneurs whose mothers or mothers-in-law were members of Grameen Bank (GB). Through NEP, social business equity funds are usually distributed to potential young entrepreneurs (local term: Nobin Udyokta), which is a joint investment project between young entrepreneurs and Grameen companies. A NEP field officer conducts preliminary screenings to identify aspiring business owners. After initial assessments, Grameen social business companies hold design labs through their regional offices. This is where entrepreneurs present their ideas for starting new businesses or growing old ones. Business proposals are evaluated and approved by a group of expert officials. Following the evaluation, social business funds are finally distributed. This screening process is known as the social business design lab.
Social Business companies and entrepreneurs’ businesses become joint initiatives where ownership is shared between two companies, but profits are not; profits stay with the entrepreneur. This shared ownership helps entrepreneurs to work under the supervision of an experienced company, which becomes a kind of mentoring and training opportunity for young entrepreneurs. This network with professional investor companies helps young entrepreneurs to sustainably expand their businesses. It is also expected that NEP will reduce unemployment through self-employment and create job opportunities for others through business expansion. This sort of initiative will reduce frustration among unemployed people and decrease the rate of rural migration and violence among the youth. Thus, this program is expected to contribute toward the socio-economic development of Bangladesh through sustainable entrepreneurship development.
According to Nobin Newsletter, 2018, the average size of SBF is BDT (Bangladeshi currency) 106,344, usually given for 3–5 years. A monthly repayment is usually expected, and 3–6-month grace periods are allowed depending on the entrepreneur’s need. Among several Grameen Social Business Companies, Dhaka, Bangladesh, SBFs are provided by three Grameen Companies: Grameen Telecom Trust (GTT), Dhaka, Bangladesh; Grameen Trust, Dhaka, Bangladesh; and Grameen Shakti Shamajik Byabosha Ltd., Dhaka, Bangladesh.

1.3. Theoretical Underpinnings and Hypothesis Development

Entrepreneurs are regarded as important economic growth agents [48]. Entrepreneurs contribute to the economy by creating jobs and innovating in society [49,50]. Several researchers have used agency theory to better understand entrepreneurship development [51,52]. According to agency theory, society has a vested interest in creating more entrepreneurs [53] to grow the economy, develop innovations, and solve social problems [54,55,56,57,58]. Policymakers often prioritize entrepreneurship when making macroeconomic decisions [59]. Solomon et al. [60] employed agency theory in their research, portraying entrepreneurs as agents and society’s people or customers as principals. According to agency theory, principals hire agents because they are more skilled or knowledgeable about certain issues [61,62]. Additionally, any barriers to agents, such as a lack of appropriate policies, sources of financing, and so on, limit the utility agents’ ability to provide principals [60]. Furthermore, the risk aversion mechanism underlying agency theory [63] may exaggerate entrepreneurship failure and encourage entrepreneurs to seek salaried employment.
As a result, Solomon et al. [60] expressed concern that risk aversion might discourage potential entrepreneurs from starting their own businesses. In contrast, the principal wishes for the general public to become entrepreneurs. These inconsistencies raise the prospect of forming a contractual relationship to mitigate the losses associated with entrepreneurial failure. Thus, by creating a contractual mechanism, principals and agents contribute to the growth of entrepreneurship. This study proposes social business as a means of encouraging entrepreneurship. The principals are social business funding companies, and the agents are fund recipient entrepreneurs. Davis et al. [1] applied agency theory to social entrepreneurship by identifying principal and agent factors. If the agents are competent and trustworthy, the principal may be persuaded to allocate more funds to entrepreneurship support [1].
Therefore, the availability of SBF might be an option to encourage young entrepreneurs to continue as entrepreneurs without being salaried employees. One of the most significant challenges for a young entrepreneur is ensuring the availability of funds. SBF may be one viable mechanism for reducing losses associated with entrepreneurial failure. Agency theorists believe that incentive alignment is an essential mechanism for motivating agents to serve the principles correctly. Social business funds provide entrepreneurs with a strong incentive to prioritize their own interests, with the added benefit of maximizing the welfare of the principals. Therefore, hypothesis 1 can be developed as
H1. 
Social business fund has a significant relation with entrepreneurs’ income.
Principals and agents are at different risk levels. Potential entrepreneurs would be encouraged to take more entrepreneurial risks if SBF changed the significant income of the entrepreneurs, because an incentive, namely, a higher income, would offset the risk. On the other hand, principals face the risk of moral hazard and information asymmetry [1]. The agent may act opportunistically by investing funds into less risky non-entrepreneurial projects (such as purchasing land, spending on children’s education, traveling abroad, and so on). The contractual mechanism between the principal and agent assists the principal in mitigating risk by increasing monitoring and establishing a monthly repayment schedule. NEP has also established a monitoring mechanism and a monthly repayment system to reduce risk.
One of the primary goals of providing financial assistance to entrepreneurs is to improve their economic standing in terms of income and expenditure. Utility theory postulates that giving financial support (e.g., credit/grant/social enterprise fund) will lower their budget limitations and boost their capacity to invest in Income-Generating Activities (IGAs), resulting in a higher level of income [64]. This study is also consistent with the utility theory, given that SBF can boost their ability to invest, resulting in more income and leading to larger expenditures, indicating a higher standard of life.
According to some studies [65,66,67,68], demographic factors such as marital status, educational attainment, family size, employment history, age, ethnicity, gender, socioeconomic status, religion, personality traits, etc., play a significant role in fostering entrepreneurial development. In addition to ensuring available funds, other enabling environments such as entrepreneurial and capacity development, education and training [69,70,71], physical infrastructure and technology (e.g., electricity, the internet), research and development, information sharing and communication, a sound macroeconomic policy, business support, and access to raw materials and key networking relationships [72,73,74] are all critical to entrepreneurial success [32,75,76,77].
Education has the potential to play a significant role in the acquisition of knowledge, the enhancement of skills in the pursuit of IGAs, and the creation of awareness about social and economic elements [16,69,78]. Undoubtedly, an entrepreneur with a higher level of education would be more capable of gaining access to information, building networks, managing risks, and earning a higher income by pursuing the IGAs than an entrepreneur with a lower level of education. Therefore, hypothesis 2 has been drawn as follows:
H2. 
Education has a significant relation with income.
Training is often considered one of the most significant factors that is highly correlated with the business skills of a person [78]. Undoubtedly, a trained entrepreneur is more capable than an untrained entrepreneur when it comes to managing financial risks, negotiating, and making decisions regarding economic aspects such as income and expenditure. Based on the reasoning presented above, a hypothesis can be formulated as follows:
H3. 
Training has a significant relation with income.
Undoubtedly, productive working hours are connected to economic activities. It can logically be assumed that an entrepreneur who invests more time in IGAs will be in a better position than one who invests less time in business activities for building business networks, diversifying IGAs, and gaining access to financial (credit) and non-financial (training) supports, all of which can help him or her to generate more revenue. Therefore, hypothesis 4 has been developed as follows:
H4. 
Working hours invested in business have a positive relationship with income.
The size of a family can also impact the economic activities of the household [78,79]. In fact, family labor is more accessible and less expensive than hired labor, especially in distress situations. A household with more employed individuals is more likely to have a greater financial capacity to deal with risk than one with fewer employed members. Thus, increasing the number of family members who can work for the entrepreneur immediately impacts the business by lowering external labor costs. Therefore, hypothesis 5 is developed as follows:
H5. 
The number of family members has a significant relationship with income.
In Bangladesh, infrastructure facilities are quite inadequate, resulting in low productivity and income for entrepreneurs. Access to rural infrastructure amenities can significantly improve the economic and social living conditions of the country’s people [69,78]. It can be assumed that access to banks can play a crucial role in providing finance and training facilities to small business owners, enabling them to conduct their business activities in a manner that generates a more significant income. Access to banks helps entrepreneurs to mobilize and secure resources by using banks to pay for financial activities. Therefore, it is easier for the entrepreneur to make money.
H6. 
Access to the bank has a positive relationship with an increase in entrepreneurial income.
Age is a significant demographic factor directly related to a person’s experience and decision-making capacity [78,80]. Because of his or her many years of experience in running business activities, it is reasonable to expect that an elderly entrepreneur will be able to deal with risks and uncertainties far more effectively than a young and inexperienced entrepreneur. The entrepreneurs in this study belong to the 18–35 age group, because SBFs were given to those age groups. Entrepreneurs under the age of 20 and those over the age of 30 will have different levels of maturity regarding business management and decision-making. The results of studies that looked at age as a predictor of income or performance were mixed [81]. Therefore, hypothesis 7 will be tested.
H7. 
Age has a significant positive relationship with income.
The following conceptual framework has been designed depending on the above hypothesis: (Figure 1)

2. Materials and Methods

2.1. Location and Time of the Survey

From March to July 2019, a survey was conducted on Grameen Telecom Trust’s (GTT) NEP. Since 2014, GTT has been running this program in several Bangladeshi districts (currently 17). The survey was carried out in the Bangladeshi cities of Jessore, Cumilla, Rangpur, and Chattagram.

2.2. Sampling

A comprehensive list of entrepreneurs who took the SBF was collected from The Head Office (HQ) of GTT. All the business owners in these four areas who met the following requirements were selected for this analysis. After compiling a list of 411 entrepreneurs, samples were drawn using the Simple Random Sampling (SRS) method, yielding a total of 199 entrepreneurs who participated in the study. It is worth noting that we conceived a 5% error at the 95% confidence level in determining the sample size. We used the web-based software “Survey system” to calculate the sample size. Entrepreneurs for the treatment group were selected based on the following criteria:
(i)
Age of the entrepreneurs, within the range of 18–35 years;
(ii)
Entrepreneurs who joined the program first time in 2016;
(iii)
Entrepreneurs who utilized the fund for at least three years. The logic behind the three-year requirement was that funds are usually given for three to five years. Those who had completed their repayment were automatically excluded from our sample. We also excluded entrepreneurs who participated in the program before and after the reference year. The ethical standard was maintained during the survey.
Similar types of evaluation criteria (e.g., age of the program participant, joining year in the credit program, and years of land utilization by program participant) were also applied by Mahmud et al. [16] in selecting samples. To form a control group, 117 entrepreneurs between the age of 18–35 years were purposively selected from the other Upazilas (Upazilas are a local administrative term that indicates sub-districts) of those districts. The purposive sampling technique was also used for selecting the control group in other, similar studies by Mahmud et al. [16]. It is important to note that these entrepreneurs never took any social business funds or other interventions from GTT or any other organizations.

2.3. Data Collection

The primary data for this study were collected through the use of questionnaires. Data were primarily collected on the following topics: (i) demographic profile, (ii) household income, (iii) types of business pursued, (iv) training, (v) opinions regarding the SBF, and (vi) opinions about their well-being under the GTT program. Eight unit officers from those districts were involved in data collection. The researcher, along with a program coordinator of GTT, supervised the data collection process.

2.4. Analytical Techniques

This analysis used Propensity Score Matching (PSM) methods to assess the impact of SBF on the total income of the entrepreneur. Researchers have used this method extensively since its introduction by Rosenbaum and Rabin in 1983 [16,20,82,83]. For example, Mahmud et al. [16] used PSM to assess the impact of the Monthly Repayment System (MRS) on the income and expenditure of female borrowers. In Bangladesh, the PSM technique was also used by Sohag et al. [83] to measure the impact of zakat funds on the household income of the zakat recipients. Zakat refers to the proportion of wealth which an eligible Muslim is bound to pay every year to underprivileged people of society, as per Islamic rules and regulations [16,83].
PSM focuses on the counterfactual outcomes of estimating the effect of treatment on the treated group [16,20,82,83,84]. One of the major advantages of using the PSM technique is that it can overcome the selectivity bias problem. However, PSM is only partially flawless, as it fails to consider the effect of unobservable variables on the outcomes and it is grounded primarily on the non-parametric analysis. In the PSM approach, developing a control group is necessary to compare the treatment outcome between the treated and untreated groups. The control group must be identical to the treatment based on selected control variables [16,20,26,84]. In this study, entrepreneurs who received SBF from GTT were treated as the “Treatment Group”, and those who did not receive funds were treated as the “Control Group”.
In the PSM approach, the logit or probit model can estimate the propensity score [16,26,83]. It is important to note that this study used the probit model to estimate propensity scores. Later, each unit of the treatment group is matched with the units of the control group based on the propensity score [20,82]. Nearest Neighbor Matching (NNM), Kernel Matching (KM), and Radius Matching (RM) techniques are used by the researchers for matching variables. For this study, NNM and KM techniques were used, and the matching variables were the age and family size of the entrepreneur. For the validity of PSM, the Conditional Independence Assumption (CIA) needs to be satisfied [16,84].
The individual causal effect of treatment would be the difference between the value of the outcome in the current situation and the value of the outcome if the participants did not take the treatment [83]. From the propensity score matching, we obtain an Average Treatment effect on the Treated (ATT), which can be written as follows:
ATT = E(Y1 − Y0 |D = 1) = E(Y1|D = 1) − E(Y0|D = 1)
The term E(Y1|D = 1) is the average outcome that the treated individuals have obtained, and E(Y0|D = 1) is the average outcome that the treated individuals would have obtained in absence of treatment, which is not observed.
The study also used the Binary Logistic Regression (BLR) technique to assess the opinions of the entrepreneurs on their economic well-being under the NEP. Since the dependent variable was dichotomous, the BLR technique was applied in this study. The BLR technique is appropriate when the dependent variable is dichotomous [85,86]. The BLR technique is also being used widely by researchers to assess opinions about the economic well-being of microcredit borrowers [16,87] and the food security status of zakat recipients [64]. In this study, we attempted to assess the impact of SBF on income. However, a person’s income cannot be affected by just one factor. Instead, it is affected by many factors, such as age, family size, economic factors (work hours, SBF), social factors (education, training), and physical factors (rural bank), all of which were used as independent variables in the BLR analysis. Other researchers also used these factors to assess the impact on household income [16,23].
The model can be specified as follows:
Ln[Pi/(1 − Pi)] = δ0 + δ1X1 + δ2X2 + δ3X3 + δ4X4 + δ5X5 + δ6X6 + δ7X7 + μ
Pi = probability that the income of the entrepreneur would be increased; 1-Pi = probability that the entrepreneur’s income would not be increased; δ0 = constant; δi = coefficient to be estimated; μ = error term of the equation; X1 = social business fund, which was measured as 1 for having a social business fund and 0 for not having a social business fund; X2 = education, which was measured by the number of years in school; X3 = training, which was measured as 0,1, where 1 indicates that training was received and 0 indicates that training was not received; X4 = number of hours worked for the business; X5 = number of family members who usually eat in the same kitchen; X6 = distance of the nearest bank from the workplace was measured in miles; and finally, X7 = age of the entrepreneurs, measured in years.

3. Results and Discussion

The demographic characteristics of the treatment group (entrepreneurs who had received SBF) and the control group (entrepreneurs who had not received SBF) are discussed in this section. The opinions of the entrepreneurs on their economic well-being under the NEP are also analyzed in this section.

3.1. Socioeconomic Characteristics of the Respondents

This section listed the average age, number of years of education, marital status, number of family members, number of working family members, and number of hours worked, among other statistics. A slight difference was found between the average age of treatment (30.14 years) and the control group (29.06 years) (Table 1). The education levels of the participants in the control and treatment groups did not differ significantly. There were differences in the number of years of schooling. The average years in school for the treatment group was 9.92, and for the control group, it was 10.66. (Table 1). Most of the participants who answered the survey in both the treatment and control groups were married. Table 1 shows more married people in the treatment group (73.37%) than in the control group (70.08%). The average number of people in each family was almost the same: 5.43 for the treatment group and 5.55 for the control group (Table 1). In Bangladesh, family-run microbusinesses frequently hire members of the same family. In addition, due to the microcredit movement, many women in Bangladesh are now actively participating in IGAs. It has been found that the treatment and control groups had at least two working family members, and the differences are not very significant. On average, there were 2.19 working family members in the experimental group and 2.34 in the control group. In the treatment group, entrepreneurs worked harder than those in the control group. The average working hours of the treatment group were 10.33 h, while the average working hours of the control group were 9.54 h (Table 1).

3.2. Opinion of the Entrepreneurs on the Impact of NEP

The new entrepreneurs provided their opinions on the five aspects of social business funds closely related to their business performance and household properties. Responses were recorded on a Likert-type scale, where 0 indicates no response; 1, strongly disagreed; 2, disagreed; 3, agreed; and 4, strongly agreed (Table 2). Table 2 shows that almost 100% of participants stated that their sales, profits, and assets improved because they have access to social business funds. Roughly three-quarters of those surveyed thought they had more personal property due to their increased business income. In addition, after receiving funding, entrepreneurs were monitored by a social business team or venture incubator, which improves their ability to manage risk. Table 2 shows that 80 percent of respondents felt that their ability to manage risk improved after taking SBF.

3.3. Impact of Social Business Fund on Entrepreneurs’ Income

Undoubtedly, a person’s economic and social prosperity are intertwined with their level of income [16]. A higher income allows for more significant investment into IGAs, which, in turn, allows for more outstanding production, income, and savings. Micro- and youth business owners in developing nations often face financial constraints that prevent them from giving their businesses the attention and resources they need to thrive. The difficulties they already face in running their businesses are multiplied by the lack of options for acquiring commercial financing. Accordingly, the NEP’s provision of SBF would aid young entrepreneurs in facilitating their economic improvement. It is worth noting that the recipients of SBF were young entrepreneurs who were essentially the children of poor Grameen bank borrowers. The young business owners in this study relied primarily upon (i) agricultural sources and (ii) non-agricultural sources of income.
It was hypothesized in this study that the SBF would increase the incomes of entrepreneurs. As anticipated, this research shows that the treatment group’s income increased due to SBF’s intervention (Table 3). After NNM and KM matching, the treatment group’s incomes grew by BDT 15,386.618 and BDT 16,093.959, respectively (Table 3). Similarly, other researchers have also observed that providing funds to small businesses increased the income of the micro-entrepreneurs in Bangladesh [7,15,16,28]. Therefore, this research’s findings are consistent with the agency theory’s incentive mechanism.
Additionally, the NEP’s exceptional features included training, mentoring, and monitoring of beneficiaries at various application stages and SBF administration, which ultimately helped the entrepreneurs to improve their financial situation. By doing so, SBF helps young business owners to make more money and guarantee that their entrepreneurial endeavours would continue to thrive in the future. Ebiringa [88] emphasized the significance of mentoring and monitoring in his study. This method aids young entrepreneurs by improving their creativity, ability to serve customers, resilience, and risk management.

3.4. Impact of Social Business Fund on Entrepreneurs’ Expenditure

Increased income would allow micro-entrepreneurs to spend more on food, education, and better healthcare, among other things. In this study, household expenditure included food, social events, children’s schooling, healthcare, and input purchases. This study demonstrates that the household expenditure of the treatment group increased significantly. Household expenditure increased by BDT 5978.256 and BDT 5895.097 based on NNM and KM methods, respectively (Table 4). Similarly, Mahmud et al. [26] found that microcredit intervention led to higher household expenditures among rural female business owners.

3.5. Factors Influencing Income of the Entrepreneur

As mentioned earlier, young entrepreneurs in this study were provided with the SBF because they had limited financial capacity to start up or pursue their existing business activities smoothly. These SBFs were mainly invested in entrepreneurs pursuing non-agricultural activities, such as handicrafts; grocery items; pharmacy; electronic accessories; tailoring; clothing and garments; sale of agricultural inputs; poultry business (sale of egg, chicks, and broilers); fishery-related businesses; hotels and restaurants; mobile phone services; computers; electronic accessory maintenance; and repair services and manufacturing, which include light engineering; producing furniture; garment manufacturing; production of soap, oils, and carpets, etc. Undoubtedly, income is closely related to the improvement of the living standard of an individual [15]. It was expected that by utilizing this fund, these young entrepreneurs would be able to increase their incomes. Social business funds, as predicted, were found to have a strong and positive relationship with income (Table 5). This indicates that income increases if SBF is invested into business activities. Similarly, Mahmud et al. [16] conducted a study in Bangladesh. They found that poor women who used microcredit to start an agribusiness increased their incomes. With each extra unit of SBF, there is a 90% probability that the entrepreneur’s income will increase (Table 5).
Training plays a pivotal role in increasing the skills of an individual [16,65]. Increasing skills leads to a higher level of productivity which, in turn, can help one make more money. Most of the young entrepreneurs in this study had no or little training related to business activities, which is also a significant barrier for them to pursue their business activities properly. It is expected that entrepreneurial training will lead to a general improvement in business acumen. Through NEP, entrepreneurs obtained opportunities to participate in the training program. It is logically assumed that a trained person will have a better entrepreneurial capacity than an entrepreneur with no training. The results of this study show a strong and statistically significant association between entrepreneurial training and the outcome variable. Entrepreneurs can expect a 78% boost in earnings for every additional unit of training they receive. Studies by Murshed-E-Jahan and Pemsl [89] and Mahmud and Hilton [80] also confirmed that training is a significant predictor of income.
More family members means more potential business workers, which should help entrepreneurs to cut expenses and boost profits. The business owners in our sample relied heavily on their relatives rather than external employees. When a crisis strikes, relying on family members instead of paid workers can be beneficial, because they are often more accessible and cost-effective. This study demonstrated that the number of family laborers was positively and significantly related to the dependent variable (Table 5). The probability of increasing the income of the entrepreneurs was 58%, due to employing each additional unit of a family member in business activities (Table 5).
Although education is expected to enhance entrepreneurs’ advanced knowledge and skills, this study did not find any significant relation. A previous study conducted on microcredit borrowers found a significant relationship between education and borrowers’ economic well-being [16]. The age of most of the entrepreneurs in the sample was 18–35, indicating that all of them were young. Hence, significant variations in income due to their age were not followed. However, previous researchers found age to predict entrepreneurial performance significantly [81]. Finally, access to finance was also considered as a significant predictor of the income of entrepreneurs. Nevertheless, this study did not find any significant relationship. Technological innovation in financial sectors has brought financial services to the doorsteps of entrepreneurs. Therefore, the bank’s physical location may not play a significant role nowadays.

4. Limitation and Future Research

Like many other studies, our research is not free from limitations. Our research was limited to a particular social business, developed and implemented exclusively by Grameen Companies in Bangladesh. How this social business fund operates in different nations and settings is a question that needs to be investigated further. Second, we did not consider the individual characteristics or personality dimensions (such as self-efficacy and locus of control) or the socio-economic factors of entrepreneurs (family income, land, assets, and other capital). Future studies should combine more parameters by moving beyond these few variables. Third, this study did not observe any gender dimensions in entrepreneurial performance since, in its early stages of development, the NEP attracted very few female entrepreneurs. Future empirical research may strive to include gender variables to better capture the impact of such diversity.

5. Conclusions and Implications

The prime objective of this study was to assess the impact of social business funds on entrepreneurs’ business performance. It was anticipated that the social business intervention would increase the entrepreneurs’ overall business income. This study investigated whether SBF positively impacted entrepreneurs’ living standards in terms of income and expenditure. A substantial portion of the entrepreneurs expressed their satisfaction with NEP. This study demonstrated that entrepreneurs believed that their involvement in the NEP improved their business performance (sales, profit, asset and risk management, etc.). Therefore, policymakers should concentrate on a few aspects to ensure that entrepreneurs can obtain full business support and substantially contribute to the economy.
Entrepreneurs should receive timely assistance in obtaining SBF. The duration between the fund’s application and disbursement should be reduced substantially. Furthermore, efficiency in disbursement of funds needs to be improved. Entrepreneurs had typically received some informal business education. Additional training is required to enhance their risk management capabilities and company performance. Entrepreneurs usually do not have enough time to participate in more formal training; therefore, night programs can be launched to provide them with business education and training. Some basic business-related books can be composed using easy language, and these can be provided along with training manuals. Affordable business education can be provided in various formats, including evening classes for young entrepreneurs.
In addition, entrepreneurial network services can be provided by arranging regional, national, and international trade fairs for entrepreneurs. Support from Grameen Check, Dhaka, Bangladesh (cotton-based products that the village-based traditional weavers generally supply) and Grameen Poshra, Dhaka, Bangladesh (a retail shopping outlet) needs to be made more vibrant so that entrepreneurs may obtain secure access to the market through the Grameen Distribution network. Appropriate insurance policies must be taken to protect entrepreneurs’ businesses from theft, fire, flood, fraud, and other problems.
Our findings add to the existing body of literature on the consequences of social business funds. Although much entrepreneurship literature is supported by agency theory, reports on incorporating them into social entrepreneurship are scarce [1,90]. Due to the nature of their social missions, social entrepreneurs engage in various risk mechanisms. Therefore, our research incorporates additional values into the social entrepreneurship literature. Moreover, providing SBF through NEP is a specialized project of Yunus Social Business initiatives, which is still in the experimental stage and needs to be replicated outside Bangladesh. As a result, there is a lack of accessible, in-depth literature. Thus, our study will augment the existing social business literature and motivate future researchers to conduct further investigations. Our study also contributes to the literature by proposing policies to mitigate entrepreneurial risk by creating an enabling environment. It is highly expected that potential entrepreneurs are aware of the entrepreneurial risk. Adequate enabling environments such as training, networking, facilitating market access, etc., for entrepreneurship development still need to be created. Otherwise, a pool of potential entrepreneurs may favor the less risky option of salaried work income [60]. Both government and non-government groups should undertake the necessary policy actions to foster a climate conducive to entrepreneurship.

Author Contributions

Conceptualization, F.F.; methodology, K.T.M.; software, K.T.M.; validation, F.F., P.M., and K.T.M.; formal analysis, F.F.; investigation, F.F.; resources, P.M.; data curation, P.M.; writing—original draft preparation, F.F.; writing—review and editing, F.F. and K.T.M. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

Not applicable.

Acknowledgments

This study would like to express deep gratitude to Nobel Laureate Professor Muhammad Yunus for his encouragement, guidance and direct assistance during the data collection. The authors acknowledge the Managing Director of Grameen Telecom Trust for her contribution in providing necessary logistic support for conducting the survey and allowing access to other necessary information as required. This study will owe to the Yunus Center team members, Jayanta Kumar Basu, K.M. Saleheen, Shikder M. Zafry, and others for their contribution in data collection, data editing, and compilation. This study also recalls the encouragement and support of Lamiya Morshed, Executive director of Yunus Center. We would like to thank Aliya Shahnoor Ameen for English editing and expression.

Conflicts of Interest

The authors declare no conflict of interest.

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Sustainability 15 00756 g001 550
Figure 1. Conceptual framework.
Figure 1. Conceptual framework.
Sustainability 15 00756 g001
Table
Table 1. Demographic status of entrepreneurs.
Table 1. Demographic status of entrepreneurs.
Treatment Group (N = 199)Control Group (N = 117)T-Test
NumberPercentageMeanNumberPercentageMeanT Valuep-Value
Age - -30.1435 - -29.0603−1.84760.0656
Year of education - -9.923 - -10.662.35340.0192
Marital status:
Married
Unmarried
Divorced		146
52		73.37%
26.13%		 -82
35		70.08%
29.91%
0%		 --
Family members - -5.4375 - -5.55260.35780.7207
Working family members - -2.1875 - -2.33622.34200.0198
Working hours - -10.3299 - -9.535−3.82420.0002
Table
Table 2. Opinion of the new entrepreneurs on the impact of the Social Business Fund (percentage).
Table 2. Opinion of the new entrepreneurs on the impact of the Social Business Fund (percentage).
StatementsStrongly AgreeAgreeDisagreeStrongly DisagreeNot Related with My Business
Fund increases my sales70.429.1 0.5
Fund increases my profit63.336.7
Fund increases my business asset69.829.7 0.5
Fund increases my household property35.739.216.60.58
Fund increases my risk management capacity41.739.38.519.5
Table
Table 3. Results of the propensity score matching (PSM).
Table 3. Results of the propensity score matching (PSM).
Indicator ATTStd Errort
Monthly income of the household (BDT)NNM15,386.6183247.0844.739
KM16,093.9592440.1206.596
1 Note: The number of treated and control refers to actual nearest neighbor matching. 2 Note: BDT indicates Bangladesh Taka (currency of Bangladesh). 3 Note: 1 USD = 82.10 BDT in 2018 (Ministry of Finance, 2018). 4 Note: ATT indicates the average treatment Effect on the treated.
Table
Table 4. Impact of Social Business Fund on entrepreneurs’ household expenditure.
Table 4. Impact of Social Business Fund on entrepreneurs’ household expenditure.
Indicator ATTStandard Errort
Monthly expenditure of the household (BDT)NNM5978.2561725.4443.465
KM5895.0971181.7504.988
Table
Table 5. Factors influencing income of the entrepreneur.
Table 5. Factors influencing income of the entrepreneur.
VariablesOdd RatioLevel of SignificanceProbability
Social business fund (dummy)9.4572370.0000.9044
Education (number)0.95234560.4750.4878
Training received (dummy)3.5986210.0120.7825
Working hours (number)1.0050550.9660.5013
Family members (number)1.3551590.0170.5754
Distance of bank (kilometer)0.95209490.1620.4877
Age (number)1.0228440.0590.5056
Constant0.29023840.4260.2249
Pseudo R2 = 0.2531
1 Note. Probability = [odd/(1 + odd)] × 100.
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Ferdousi, F.; Mahmud, P.; Mahmud, K.T. Fostering Youth Entrepreneurship Development through Social Business—Evidence from Bangladesh. Sustainability 2023, 15, 756. https://doi.org/10.3390/su15010756

AMA Style

Ferdousi F, Mahmud P, Mahmud KT. Fostering Youth Entrepreneurship Development through Social Business—Evidence from Bangladesh. Sustainability. 2023; 15(1):756. https://doi.org/10.3390/su15010756

Chicago/Turabian Style

Ferdousi, Farhana, Parveen Mahmud, and Kazi Tanvir Mahmud. 2023. "Fostering Youth Entrepreneurship Development through Social Business—Evidence from Bangladesh" Sustainability 15, no. 1: 756. https://doi.org/10.3390/su15010756

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