Original Research

Assessing selected biographical factors and entrepreneurial willingness of social grant recipients

Boitumelo Masilela, Jurie van Vuuren, Andries Masenge

Received: 27 Jan. 2025; Accepted: 24 Nov. 2025; Published: 28 Jan. 2026

Copyright: © 2026. The Authors. Licensee: AOSIS.
This work is licensed under the Creative Commons Attribution 4.0 International (CC BY 4.0) license (https://creativecommons.org/licenses/by/4.0/).

Abstract

Purpose: This primary aim of this study was to assess the relationship between selected demographic factors (age, gender, education and marital status) and the entrepreneurial willingness of social grant recipients, framed within Human Capital Theory.

Design/methodology/approach: A descriptive cross-sectional survey design was adopted. Quantitative data was collected in Johannesburg, Tshwane and rural Limpopo from 725 social grant recipients using structured questionnaires in 2021. Analysis of variance (ANOVA) was used to analyse relationships between demographic variables and entrepreneurial willingness.

Findings/results: The findings revealed that education and age were significantly associated with entrepreneurial willingness. Respondents with higher levels of education demonstrated stronger intentions to pursue self-employment, highlighting the importance of education in shaping entrepreneurial behaviour. Younger participants also showed higher entrepreneurial willingness, suggesting the relevance of age-specific interventions. No statistically significant relationships were found between gender or marital status and entrepreneurial willingness.

Practical implications: Policymakers can enhance entrepreneurial willingness among social grant recipients by strengthening access to entrepreneurship education, tailoring support to different age groups and linking grant programmes to entrepreneurial development pathways. Simplifying access to resources and encouraging experimentation may further promote self-employment and reduce long-term dependence on social grants.

Originality/value: This study contributes empirical evidence on how demographic factors relate to entrepreneurial willingness among South African social grant recipients, offering insights to inform targeted policy and programme design.

Keywords: social grants; entrepreneurship; human capital theory; entrepreneurial willingness; self-employment.

Introduction

South Africa faces persistent socio-economic challenges, including high unemployment, widespread poverty and significant inequality. In response, the government has implemented a combination of social welfare programmes and various business development and support programmes aimed at improving living conditions, promoting entrepreneurship and contributing to economic development (Statistics South Africa, 2019; The World Bank, 2021, pp. 3–4). These programmes encompass a range of interventions such as infrastructural development, mentorship, financial assistance, training, advisory services and social funding mechanisms (South African Government, 2019). Among these initiatives, the social grant system serves as a key component, providing financial support to over 18 million beneficiaries (National Treasury, 2023, p. 62; South African Security Agency, 2023, p. 19). While the social grant system offers critical support, this programme has faced criticism, with critics suggesting that access to grants may unintentionally decrease or negatively impact the work and/or entrepreneurial motivation of beneficiaries (Brière et al., 2014, p. 17; Surender et al., 2010, p. 205). A study on agricultural entrepreneurs in KwaZulu-Natal found that access to social welfare services for underprivileged individuals negatively impacted approximately 90% of the rural households (Sinyolo et al., 2017b, p. 66). Additionally, this study also indicated that reliance on government social grants somewhat discouraged entrepreneurial development (Sinyolo et al., 2017b, p. 69). As such, these discussions point to the need for a clearer understanding of how individual characteristics relate to the willingness to pursue entrepreneurship among social grant recipients. Demographic and biographical factors, including, but not limited to marital status, gender, age, educational background and household income, have been identified as key correlates of self-employment (Muchemwa & Odimegwu, 2023, pp. 1322–1323). For instance, higher levels of education are often associated with greater awareness of business opportunities and higher confidence to initiate self-employment (Ahn & Winters, 2023, p. 720). Similarly, age and household responsibilities may influence an individual’s risk tolerance, available resources and time for entrepreneurial activity (Azoulay et al., 2020, p. 66). Guided by human capital theory, this study aimed to assess the relationships between selected demographic factors, specifically age, gender, education and marital status, and the entrepreneurial willingness of social grant recipients in South Africa.

The study did not seek to establish causal relationships; rather, it focused on identifying statistically significant relationships that provide insights into how demographic characteristics correspond with individuals’ readiness or inclination to pursue entrepreneurial opportunities. By contextualising the analysis within the broader framework of social welfare and entrepreneurship development, the research contributes both to theoretical understanding and to policy considerations. The findings achieved the study’s aim by highlighting the relationships between specific demographic factors and entrepreneurial willingness, offering evidence to inform the design of targeted support programmes. Overall, this study enhances knowledge of the intersection between social grants and entrepreneurship while providing guidance for policymakers and practitioners seeking to foster self-employment and reduce reliance on social grants. The study begins with a review of literature on the social grant system, including the criticisms surrounding its impact, with a focus on the country’s entrepreneurial landscape. It then examines how selected demographic factors relate to social grant recipients’ willingness to engage in self-employment. Finally, the study presents the findings, drawing on analysis of variance (ANOVA), and offers recommendations for policymakers and other stakeholders, concluding with strategies to promote self-employment among social grant beneficiaries. Accordingly, the study addresses three key research questions. Firstly, it examines how demographic factors, specifically age, gender, marital status and education, relate to the entrepreneurial willingness of social grant recipients. Secondly, it assesses the extent to which entrepreneurial attitudes, including prior consideration of starting a business and willingness to start a small business, correspond with entrepreneurial willingness. Thirdly, the study explores how the observed relationships between demographic characteristics and entrepreneurial attitudes can inform the design and development of targeted entrepreneurship support programmes tailored to the needs of social grant recipients.

Literature review

The role and impact of social grants in South Africa

Overview of South Africa’s social grant system

South Africa’s social grant system was established to address historical socio-economic inequalities and provide financial relief to vulnerable populations (Bengtsson, 2010, p. 5; Groenmeyer, 2016, pp. 139–140; Mitileni & Sithole, 2016, p. 246). Currently, approximately 29 million South Africans rely on social grants, which constitute a significant portion of household income for low-income families (National Treasury, 2023, p. 62). Despite the poverty-alleviating benefits, concerns persist regarding their long-term sustainability, particularly amid a 32.9% unemployment rate (South African Security Agency, 2023, p. 19). Research presents mixed evidence regarding grants and entrepreneurship. While some studies suggest that financial safety nets can encourage self-employment by reducing perceived risks, others suggest that grant income may reduce entrepreneurial activity, as recipients may perceive the grant as a sufficient safety net (Blume-Kohout, 2024, p. 200; Fairlie et al., 2011, pp. 146–147; Masilela et al., 2020, p. 9; Sinyolo et al., 2017b, p. 69). The Constitution and international policies recognise the link between income and basic human rights (Hall, 2021, p. 169; Mitileni & Sithole, 2016, p. 246). Historically, social welfare was racially discriminatory, with black and Indian populations largely excluded (Liebenberg & Tilley, 1998, p. 5; Reddy & Sokomani, 2008, pp. 9–10). By the 1930s, grants were extended to all races, although white beneficiaries received substantially higher amounts (Liebenberg & Tilley, 1998, p. 5; Reddy & Sokomani, 2008, p. 10). Social grants aim to alleviate poverty and address social challenges, including food insecurity, risky lifestyle behaviours, educational needs and access to health (Heinrich et al., 2017, p. 628; Zikhali, 2021, p. 17859). They include types of old age pensions, disability, care-dependency and child support grants, among others (South African Social Security Agency [SASSA], 2024; The World Bank, 2021, p. 4). Social grants are well targeted at poorer households, lifting many out of extreme poverty, improving school attendance, child nutrition and healthcare access while also empowering women in household decision-making (Africa Check, 2017; Gadisi et al., 2020, p. 937; Van der Berg et al., 2010, p. 30).

Nevertheless, with 47% of the population relying on social grant income, concerns about sustainability remain, particularly regarding temporary measures like the social relief of distress grant (South African Government News Agency, 2024; The Conversation, 2023).

Sinyolo et al. (2017a, p. 234) found that social grants contributing 20% – 60% of household income may disincentivise smallholder farming, although redistribution within households can mitigate the direct impact on farm labour. This reliance on grants highlights the importance of sustainable alternatives such as entrepreneurship (IOL, 2021; Sinyolo et al., 2017a, p. 234). Furthermore, Sinyolo et al. (2017a) recommended strengthening government-led training and support programmes, as these have been shown to enhance household productivity and reduce dependency. Entrepreneurship thus presents an opportunity for social grant recipients to transition from dependency to self-sufficiency (IOL, 2021; Ryan, 2018). Despite this potential, there remains limited understanding of the factors that influence their entrepreneurial willingness. In this study, entrepreneurial willingness refers to an individual’s readiness to engage in self-employment or business creation, conceptually similar to entrepreneurial intention. Understanding how demographic characteristics, socio-economic conditions and perceptions of self-employment influence this willingness is essential for designing interventions that promote self-sufficiency and reduce dependence on grants.

Demographics and entrepreneurial willingness

Human capital theory in entrepreneurship

Human capital refers to the economic value of a worker’s experience and skills (Abbas et al., 2024, p. 2169; Leoni, 2025, p. 228; Serenko et al., 2024, p. 51). Originating from economics literature, the human capital theory posits that investments in education, training and health enhance productivity and contribute to overall economic growth (Becker, 2009, pp. 15–18; Brewer et al., 2010, p. 194; Rodrı́guez et al., 2004, p. 37). Building on this theoretical foundation, human capital encompasses education, training, health, knowledge and personal attributes that contribute to an individual’s ability to perform work and create economic value (Abbas et al., 2024, pp. 2171–2178).

The concept emphasises that, much like physical capital (machines, tools, etc.), human capital can be invested in, developed and leveraged to enhance productivity and support long-term economic development (Abbas et al., 2024, p. 2169). Therefore, understanding human capital is essential for examining how social grant recipients can use education and their skills as drivers of entrepreneurship and economic self-sufficiency. In entrepreneurship, human capital extends beyond skills and knowledge to include qualities essential for launching and growing a business, such as creativity, problem-solving, leadership and risk-taking (Kerrin et al., 2017, p. 3; Unger et al., 2011, p. 344). Networking and social capital also play a significant role, providing access to funding, mentorship, partnerships and market insights (Wasim et al., 2024, p. 463). Vision, past experience and adaptability are equally vital, as entrepreneurs often rely on industry knowledge, previous ventures and the capacity to learn, innovate and pivot in response to market changes (Abrar et al., 2024, p. 63; Shi & Weber, 2021, p. 1406). While this study primarily draws on human capital theory, additional demographic factors such as age, gender and marital status are introduced. Although not traditional components of human capital, these factors influence how an individual’s human capital is developed and utilised (Goldin, 1990, pp. 23–24). These factors, including educational background, significantly shape individuals’ entrepreneurial willingness by influencing their motivations and perceptions of self-employment (Ahn & Winters, 2023, p. 717; Elizundia, 2017, pp. 5–6; Hubner et al., 2023, pp. 2145–2147; Muchemwa & Odimegwu, 2023, pp. 1322–1323). For instance, marital status may increase self-employment likelihood as married individuals seek financial stability (Muchemwa & Odimegwu, 2023, pp. 1322–1323). Age affects risk tolerance and career flexibility, while education equips individuals with the skills and confidence to manage businesses (Chimucheka, 2014, p. 405; Komal & Sharma, 2023, p. 425). Historical biases have also shown that gender and marital status, for example, previously shaped access to education, career opportunities and lifetime earnings, thereby affecting the accumulation and expression of human capital (Goldin, 1990, pp. 23–24). This study explores the relationship between selected demographic factors and the entrepreneurial willingness of social grant recipients. The independent variables include age, gender, educational background and marital status. Within this context, human capital provides the conceptual rationale, recognising that education, as a key component of human capital, forms the foundation for developing knowledge and capabilities that could enable individuals to pursue entrepreneurship. Although human capital underpins the relevance of education and skills, it is not examined as a separate variable in this study; rather, it serves as the theoretical basis for interpreting the role of education within the biographical context. The factors selected for this study represent measurable demographic characteristics that may influence entrepreneurial willingness. These variables were selected based on their theoretical relevance and empirical significance in previous studies linking demographic factors, entrepreneurial intention and behaviour. While the broader construct of demographic and biographical factors could include elements such as income level, employment history and household size, this study focused on the four factors for which reliable and complete data were collected. Consequently, the results reflect an analysis of selected demographic factors rather than an exhaustive demographic profile.

Figure 1 presents the conceptual model illustrating the relationship between these demographic factors and entrepreneurial willingness. The subsequent sections discuss these relationships and introduce the study’s hypotheses.

FIGURE 1: Relationships between demographic variables and entrepreneurial willingness.

Age and entrepreneurship

Scholars have examined how age influences entrepreneurial disposition, with empirical studies confirming a reversed U-shaped relationship, where entrepreneurial willingness rises to a certain age before declining (Elizundia, 2017, p. 7; Sahasranamam & Sud, 2016, p. 34). Two perspectives explain the effect of age on self-employment. The first suggests a positive relationship, as older individuals benefit from accumulated experience, professional networks and access to human and social capital, increasing their readiness to engage in entrepreneurship (Azoulay et al., 2020, p. 66; Halvorsen & Morrow-Howell, 2016, p. 313). The second emphasises youth, noting that younger individuals may be more cognitively agile, less burdened by familial or financial responsibilities and more capable of generating innovative ideas (Elizundia, 2017, pp. 5–6; Muchemwa & Odimegwu, 2023, pp. 1322–1323). Despite these advantages, young entrepreneurs may face challenges, including limited experience and fewer resources (Azoulay et al., 2020, p. 66). These contrasting views illustrate the complexity of age and entrepreneurship. While expertise, professional experience, confidence and capital increase with age, family responsibilities and a shrinking working horizon may deter entrepreneurial pursuit (Lévesque & Minniti, 2011, p. 273). Given these arguments, the first hypothesis was formulated:

H1: Age has a statistically significant effect on social grant recipients’ entrepreneurial willingness.

Gender and entrepreneurship

Age and gender are prominent factors that often lead to stereotyping in entrepreneurship (Hubner et al., 2023, p. 2145). Studies indicate a tendency for discriminatory bias against females, as entrepreneurs are often perceived as male and possessing masculine characteristics (Johnson et al., 2018, p. 814; Zhao et al., 2021, p. 8). In contrast, women are expected to fulfil familial obligations, and even when they do not have such responsibilities, investors and business partners may still perceive them as less competent because of implicit gender stereotypes (Zhao et al., 2021, p. 8). Additionally, female entrepreneurs face practical disadvantages in accessing private equity, financing and institutional support (Dutta, 2023, p. 8; Dutta & Mallick, 2018, p. 402). Research also highlights a range of factors that influence women’s decisions to pursue entrepreneurship, including human capital, motherhood, health, family position, access to financing and labour market conditions (Brush et al., 2017, p. 106). Given these arguments, the second hypothesis was formulated:

H2: Gender has a statistically significant effect on social grant recipients’ entrepreneurial willingness.

Education and entrepreneurship

Education and entrepreneurship are forms of human capital investment, with education providing foundational skills, knowledge and experience, while entrepreneurship leverages accumulated human capital and resources to create economic opportunities (Ahn & Winters, 2023, pp. 718–720). Although formal education is associated with entrepreneurial activity, it does not directly cause it; instead, both education and entrepreneurship are often shaped by shared factors, such as socio-economic background, access to resources, cognitive abilities and one’s support system (Chimucheka, 2014, p. 403; Odeku & Rudolf, 2019, p. 1). Research indicates that limited educational attainment can undermine entrepreneurial confidence and capability (Inclusive Society Institute, 2023, p. 18; Ngepah et al., 2022, pp. 634–635; Nortje, 2017, p. 48). In their study on the role of education in enhancing entrepreneurship, Ahn and Winters (2023, p. 718) argue that the effects of education on entrepreneurship are theoretically ambiguous; however, they suggest that education will likely facilitate engagement in high-growth ventures that demand advanced knowledge and technical skills. Likewise, individuals with limited education are more likely to enter low-growth sectors that offer fewer reward (Ahn & Winters, 2023, p. 718). In the context of social grant recipients, these dynamics are particularly important, as limited access to education can constrain the development and utilisation of human capital, thereby affecting both their entrepreneurial readiness and long-term capacity for self-employment.

For instance, South African youth with incomplete schooling expressed doubt about their ability to start businesses, while in India, women’s entrepreneurial potential was similarly constrained by inadequate educational opportunities (Chimucheka, 2014, p. 405; Komal & Sharma, 2023, p. 425).

Nonetheless, personal traits such as resilience, motivation, self-efficacy and adaptability remain critical alongside education in determining entrepreneurial success (Ayala & Manzano, 2014, p. 245; Rauch & Frese, 2007, p. 359). Despite these doubts and educational limitations, many young South Africans are compelled to engage in informal sector entrepreneurship as a means of survival, with the continued expansion of the informal sector reflecting both the economic necessity and adaptive resilience of this group, who often rely on informal business activities as a primary source of livelihood (Etim & Daramola, 2020, p. 2; Rogan & Skinner, 2019, p. 5). Recognising the distinction between correlation and causation remains essential when examining the relationship between education and entrepreneurship. Given these arguments, the third hypothesis was formulated:

H3: Education has a statistically significant effect on social grant recipients’ entrepreneurial willingness.

Marital status and entrepreneurship

Marital status has been identified as one of the determinants of self-employment (Muchemwa & Odimegwu, 2023, pp. 1322–1323). Empirical studies also suggest a positive relationship between being married and engaging in self-employment, as women with access to health insurance through their partners are more likely to pursue entrepreneurship (Blume-Kohout, 2024, p. 200; Fairlie et al., 2011, pp. 146–147). According to Startiene and Remeikiene (2009, p. 63), marriage can significantly influence entrepreneurial behaviour, although its impact differs between genders. For women, marriage often exerts a positive influence, as entrepreneurship provides greater flexibility to balance business, childcare and household responsibilities (Leoni & Falk, 2010, p. 174; Startiene & Remeikiene, 2009, p. 63). Conversely, for men, marriage may discourage entrepreneurial engagement as primary breadwinners often perceive business ventures as financially risky and instead prefer the stability of paid employment (Startiene & Remeikiene, 2009, p. 63). Given these arguments, the third hypothesis was formulated:

H4: Marital status has a statistically significant effect on social grant recipients’ entrepreneurial willingness (both male and female).

Literature revealed that entrepreneurial willingness is shaped by multiple demographic factors in complex and context-dependent ways. Age can both facilitate and constrain entrepreneurial engagement, that is, older individuals benefit from accumulated human and social capital, whereas younger individuals often demonstrate higher risk tolerance, cognitive agility and adaptability (Elizundia, 2017, p. 7; Lévesque & Minniti, 2011, p. 273). Education enhances confidence, opportunity recognition and business management skills, providing a foundation for entrepreneurial activity (Chimucheka, 2014, p. 403). Gender disparities persist, as socio-cultural expectations and limited access to finance continue to restrict women’s participation in entrepreneurship despite the enabling potential of education and social grants (Johnson et al., 2018, p. 814; Zhao et al., 2021, p. 8). Also, marital status intersects with gender and socio-economic conditions, influencing self-employment motivations differently for men and women (Leoni & Falk, 2010, p. 174; Startiene & Remeikiene, 2009, p. 63). While government support initiatives aim to promote entrepreneurship, their limited reach among social grant recipients underscores the need for context-specific interventions that integrate human capital development with psychosocial and structural support, enabling a transition from dependency to self-sufficiency (Masilela et al., 2020, p. 6). Given these insights, this study empirically examines the relationships between age, gender, education, marital status and entrepreneurial willingness among social grant recipients, an under-researched and economically significant group. It contributes to the literature by addressing this knowledge gap and provides insights for designing policies that foster self-sufficiency and inclusive economic participation.

Methodology

A descriptive cross-sectional survey design was adopted to capture respondents’ demographic characteristics and entrepreneurial willingness at a single point in time. This design was deemed appropriate as it enables the identification of relationships between variables without manipulating the study environment, making it suitable for exploring behavioural and attitudinal trends within a specific population. Alternative approaches such as longitudinal or experimental designs were considered but deemed impractical because of time and resource constraints, as well as the difficulty of maintaining respondent follow-up among social grant recipients.

The cross-sectional approach therefore allowed for efficient data collection from a large sample within a limited timeframe, offering valuable insights into prevailing patterns of entrepreneurial willingness. However, it is acknowledged that this design does not permit causal inference, and findings are limited to associations rather than direct cause-and-effect relationships. The use of ANOVA complemented this design by allowing for statistical comparison of mean differences across demographic groups, thereby highlighting significant variations in entrepreneurial willingness among the sampled population.

Sampling

The target population for this study comprised primary and secondary social grant recipients across urban areas in Johannesburg and Tshwane, as well as rural regions of Limpopo province. Primary recipients are registered with the SASSA and receive social grants directly, while secondary recipients may benefit financially through family members who receive grants. Participants ranged in age from 18 years to 75 years and received one or more types of South African social grants (SASSA Grant Status Check [SGSC], 2024). Data were collected from participants through the distribution of questionnaires at the various SASSA pay-points. Participants in this study were sampled according to simple random sampling. In this approach, every individual in the population had an equal chance of being selected, ensuring that the sample was representative of the entire population (Noor et al., 2022, p. 79). The participants were randomly selected without any set intervals or patterns, thereby eliminating any systematic bias (Noor et al., 2022, p. 80).

Data collection

Data were collected through self-administered questionnaires distributed to individuals at selected locations within the study areas (Noor et al., 2022, p. 79). To ensure clarity and rigour, the research team explained key terms and assisted participants with literacy challenges, while family members or caregivers completed questionnaires for social grant recipients with disabilities. Although informal discussions supported understanding, no structured interviews were conducted.

Questionnaires were chosen for their efficiency in collecting standardised data from large groups and were appropriate for capturing demographic and attitudinal information. Data collection occurred between September 2021 and October 2021, following the easing of coronavirus disease 2019 (COVID-19) restrictions, with adherence to health and safety protocols. From an initial 750 participants, 725 valid responses were obtained. Rigour and validity were maintained through verification processes and bias-reduction strategies, including diverse collection sites, clear explanations of questionnaire items and consistency checks during data entry.

Demographic variables

The questionnaire included questions on gender, age, home language, level of education and marital status. Nominal scales were used for gender, language, education level and marital status, while an interval scale was applied to gather data on age.

Social grant survey

The study employed a progressive approach, transitioning from nominal scales to interval and ordinal scales for measurement. Eleven items were used to assess this variable. This section of the survey aimed to determine the types of grants received, assess the recipients’ perceptions about social grants and determine whether recipients would be willing to start a business if they were not receiving a grant, among other factors. A combination of single-choice and multiple-choice questions was utilised to capture data on grants received. Likert scales – ranging from 1 (strongly agree) to 5 (strongly disagree) – were used to gauge respondents’ perceptions regarding the significance of social grants in South Africa. Topics included the ability of families to survive without grants, the provision of grants for the unemployed and concerns about potential misuse of grants by some recipients.

Entrepreneurial willingness

The questions on entrepreneurial willingness in the questionnaire were formatted as yes or no questions, which are considered dichotomous and fall under a nominal scale. These questions were designed to assess whether respondents were open to starting a business and to gauge their overall willingness to engage in entrepreneurial activities.

By using this simple yes or no format, the study aimed to clearly determine whether the respondents’ entrepreneurial intentions aligned with the factors being examined in the survey. The key questions in this section were: ‘Have you ever considered starting a business?’; ‘Are you willing to start a small business if you are given the opportunity’ and ‘Would you start a business if you were not receiving a social grant?’

Analysis

A factor analysis was conducted to assess the stability of the relevant constructs. This was followed by an analysis of the demographic data and the study concluded with a more detailed examination using an ANOVA. The results of the factor analysis provided high loadings, indicating strong associations within the constructs. The analysis focused on demographics and entrepreneurial willingness to understand how factors such as age, gender, educational background and marital status influence individuals’ willingness and readiness to engage in entrepreneurial activities. By examining these demographic elements alongside entrepreneurial willingness, the study aimed to identify patterns and variations in entrepreneurial motivations and tendencies across different groups within the sample.

Ethical considerations

Ethical clearance to conduct this study was obtained from the University of Pretoria, Faculty of Economic and Management Sciences, Department of Business Management’s Research Ethics Committee within the Faculty of Economic and Management Sciences (EMS001/21). Prior permission was obtained from the Grants Administration Department at the SASSA on 17 September 2020, and a formal letter of permission was issued to the researchers. This letter was subsequently presented to managers at the local SASSA offices and South African Post Office branches before commencing data collection at their premises between September and October 2021. During the data collection process, respondents were provided with an informed consent form detailing the purpose of the study, the voluntary nature of participation and their right to withdraw at any point. The form also assured respondents of anonymity and confidentiality. Only after signing the consent form were participants given the questionnaire. Every effort was made to ensure the dignity and sensitivity of the social grant recipients involved in the study.

Results

Demographic characteristics of the social grant recipients

Gender

The study analysed the demographic characteristics of the social grant recipients, focusing on gender, age, educational background and marital status. The results showed a significant gender disparity, with 72.4% of respondents being female and 27.4% male, while only 0.1% preferred not to disclose their gender.

Age

The majority of respondents (61.5%) were aged 18–40 years, including 38.3% aged 18–30 years and 23.2% aged 31–40 years, while 28.2% were 41 years and older and 10.2% were under 18 years. This indicates that a large proportion of grant recipients are youth and working-age adults, many of whom are child support grant beneficiaries, typically parents or guardians. These findings reflect the government’s focus on supporting younger age groups and families through social grants, consistent with prior research (Masilela et al., 2020, p. 6; South African Government, 2020, p. 2). Understanding this demographic profile is essential for assessing the entrepreneurial potential of social grant recipients and informing the design of tailored support mechanisms.

Educational background

The findings suggest that formal education, as defined in this study, is linked to greater entrepreneurial readiness by enhancing confidence, problem-solving skills and exposure to opportunities. However, informal or experiential learning may also shape entrepreneurial capacity, particularly among individuals without formal qualifications who have acquired practical business skills through experience. Only 36.1% of respondents had completed matric, 40.4% had not and 23.4% held post-matric qualifications, including certificates, diplomas, degrees or postgraduate qualifications. These results align with prior research emphasising education’s role in reducing unemployment, improving economic performance and addressing poverty and gender inequality (Inclusive Society Institute, 2023, p. 18; Ngepah et al., 2022, pp. 634–635; Nortje, 2017, p. 48).

Low education levels limit skills, confidence and entrepreneurial capabilities, particularly among youth and women (Chimucheka, 2014, p. 405; Komal & Sharma, 2023, p. 425). Respondents with higher education (23.4%) were more likely to possess entrepreneurial knowledge, skills and competencies, highlighting the importance of education in fostering entrepreneurial success and promoting economic empowerment.

Marital status

The study found that 68.3% of respondents had never been married, 22.6% were married, 5.5% were divorced or separated and 3.6% were widowed. Marital status is a key determinant of self-employment, alongside gender, age, education and household income (Muchemwa & Odimegwu, 2023, p. 1323). Their research also indicates a positive relationship between being married and pursuing self-employment, highlighting the potential influence of marital status on entrepreneurial behaviour (Muchemwa & Odimegwu, 2023, p. 1323).

Social grant recipients’ entrepreneurial willingness to be self-employed

Respondents’ consideration about whether to start a business

The findings reveal that 65.3% of respondents had considered starting a business, while 34.7% had not. Those who had not considered it cited reasons such as not having a business idea (43.7%), preferring formal employment (22.4%), lacking business training (17.6%) and not identifying as entrepreneurs (16.3%). Interestingly, 83.4% of the respondents expressed a willingness to start a small business if given the opportunity. However, when asked whether they would start a business without receiving a social grant, 70.9% said they would, while 29.1% indicated they would not. These results align with Patel et al. (2023, p. 5), who noted that social grant recipients seek income-generating activities to supplement insufficient grant income. Barriers such as limited access to funding, inadequate training and competition have also been highlighted in the literature (Kusumaningtyas et al., 2021, p. 158). Scholars such as Karamti and Abd-Mouleh (2022, pp. 3522–3523) emphasised that entrepreneurial opportunities create value, while Lin et al. (2021, p. 2) stressed the importance of evaluating opportunities to guide entrepreneurial actions effectively.

Analysis of variance

To examine whether demographic factors impacted the entrepreneurial willingness of this study’s social grant respondents, an ANOVA was conducted. This analysis tested for statistically significant differences between the independent variables (age, gender, educational background and marital status) and the dependent variable (the participants’ entrepreneurial willingness). Table 1 presents the results of the ANOVA.

In the analysis, univariate analysis was performed using the following items as independent variables: gender, age, education, marital status, ‘Have you ever considered starting a business’ (Q5), ‘Are you willing to start a small business if you are given the opportunity’ (Q12), ‘Start a business if you were not receiving social grants grant’ (Q24) and entrepreneurial willingness as the dependent variable. As indicated, Table 1 presents the results of the ANOVA test conducted to determine whether age, education and prior entrepreneurial consideration significantly influence entrepreneurial willingness among social grant recipients. The statistically significant results indicate that these demographic and attitudinal variables play a meaningful role in shaping individuals’ entrepreneurial willingness or intentions. These findings suggest that interventions aimed at fostering entrepreneurship should account for variations in these factors when designing support initiatives or training programmes.

The following variables age, education, ‘Have you ever considered starting a business’ (Q5) and ‘Are you willing to start a small business if you are given the opportunity’ (Q12) were found to be significant. The following presented analysis is based on these variables.

Table 2 provides a detailed ANOVA across different age and education categories, as well as individuals’ consideration of and willingness to start a small business. The results show where significant differences exist between groups, providing deeper insight into how factors such as age and education affect entrepreneurial motivation. For policymakers and practitioners, these findings emphasise the need for differentiated strategies, such as age-appropriate training and education-based support models, to effectively promote entrepreneurial participation across diverse beneficiary groups.

Hypothesis tests

H1: Age has a statistically significant effect on social grant recipients’ entrepreneurial willingness.

The ANOVA revealed statistically significant differences in entrepreneurial willingness among respondents across different age groups (F = 4.846; p = 0.001). These findings indicate that age significantly influences individuals’ willingness to engage in entrepreneurial activities. Specifically, respondents in the younger age categories [18–30] years and [31–40] years demonstrated higher entrepreneurial willingness compared to those in older groups, as evidenced by the pairwise comparisons shown in Table 2. Therefore, H1 is accepted.

H2: Gender has a statistically significant effect on social grant recipients’ entrepreneurial willingness.

The ANOVA did not yield statistically significant results for gender, indicating that it does not have a measurable impact on entrepreneurial willingness among social grant recipients. As such, gender was excluded from the detailed results presented in Table 2. Therefore, H2 is rejected, as the data do not support the hypothesis that gender significantly affects entrepreneurial willingness among social grant recipients.

H3: Education has a statistically significant effect on social grant recipients’ entrepreneurial willingness.

The ANOVA results for education revealed statistically significant differences in entrepreneurial willingness across education levels. Respondents with higher education levels, that is, Diploma/Degree and Postgraduate Degree, demonstrated significantly higher entrepreneurial willingness, compared to those with lower education levels, that is, No Matric. This is evidenced by the pairwise comparisons shown in Table 2. These findings suggest that education plays a key role in enhancing the entrepreneurial willingness of social grant recipients. Therefore, H3 is accepted.

H4: Marital status has a statistically significant effect on social grant recipients’ entrepreneurial willingness.

The ANOVA did not yield statistically significant results for marital status, indicating that it does not have a measurable impact on entrepreneurial willingness among social grant recipients. As such, marital status was excluded from the detailed results presented in Table 2. Therefore, H4 is rejected, as the data do not support the hypothesis that marital status significantly affects entrepreneurial willingness in this context.

Discussion

Summary of findings

South Africa’s high unemployment rates significantly influence the demand for specific social grants, such as the Child Support Grant. The survey revealed that the majority of recipients are women, highlighting the predominantly female demographic of social grant beneficiaries. Additionally, the data showed that many recipient households are led by single parents, as approximately 68% of the respondents reported they had never been married.

Age was found to be a significant determinant of entrepreneurial willingness. While the differences are not substantial, the findings underscore the role of age in shaping entrepreneurial attitudes, which should be considered in policies or interventions aimed at fostering entrepreneurship across diverse age groups. The findings imply that younger individuals may exhibit varying levels of entrepreneurial intention compared to older individuals, emphasising the importance of tailoring entrepreneurial support programmes to the specific needs and motivations of different age groups. This aligns with previous research suggesting that age plays a critical role in entrepreneurial motivation and behaviour. Additionally, policymakers and practitioners should consider developing targeted interventions to bridge educational gaps and foster entrepreneurial potential among less-educated individuals. Regarding the participants’ educational background, the findings suggest that education is associated with greater entrepreneurial readiness, potentially by increasing confidence, problem-solving skills and exposure to opportunities.

It is important to note, however, that in this study, education is measured only as formal attainment (e.g. no formal education, matric, certificate, diploma, degree or postgraduate degree) and does not measure the full range of entrepreneurial knowledge (e.g. informal learning), practical business experience or skills. Therefore, while education may support entrepreneurial willingness or intention, it is not sufficient on its own to guarantee entrepreneurial success. Other factors, including risk-taking ability, creativity, self-efficacy and access to resources, are essential for reducing the high failure rates often observed in start-up ventures. The ANOVA results also show a significant relationship between entrepreneurial willingness and whether respondents had considered starting a business. This indicates that prior consideration of starting a business is positively linked to entrepreneurial willingness, even if the effect is modest. This insight underscores the value of encouraging individuals to explore entrepreneurship as a viable career path, potentially through awareness campaigns or introductory entrepreneurial programmes. Lastly, the results reveal significant differences in entrepreneurial willingness, based on respondents’ willingness to start a small business if given the opportunity. This finding underscores the importance of creating enabling environments and accessible resources for individuals who demonstrate an interest in entrepreneurial activities. Moreover, these findings suggest that interventions aimed at fostering entrepreneurship among social grant recipients should not rely solely on demographic characteristics such as age or education but also provide opportunities to develop practical skills, mentorship and experiential learning, which are critical for translating willingness into sustainable entrepreneurial activity. In addition to education and skills, personal traits such as resilience, self-efficacy, creativity, adaptability and risk tolerance are critical determinants of entrepreneurial success. These traits enable individuals to cope with uncertainty, manage limited resources effectively and persist despite setbacks, qualities that are often decisive in determining whether a business survives or fails. Addressing South Africa’s persistently high start-up failure rates therefore requires not only expanding access to training and finance but also fostering psychological and behavioural competencies that strengthen entrepreneurs’ ability to navigate real-world challenges.

Managerial recommendations

Based on the empirical findings of this study, the following recommendations are proposed to managers and policymakers to enhance social grant recipients’ entrepreneurial willingness. Each recommendation reflects observed relationships between social grant recipients’ demographic characteristics, particularly education and age, and their entrepreneurial willingness.

Investing in entrepreneurial education programmes

Recommendation: The study found a strong positive relationship between education level and entrepreneurial willingness among social grant recipients. Therefore, policymakers should prioritise both formal and non-formal entrepreneurship-focused education and training, particularly in regions with high unemployment, where such interventions can have the greatest socio-economic impact. While formal education was identified as a significant predictor of entrepreneurial willingness, future interventions should also recognise and support informal learning pathways such as community-based training, practical and experiential learning opportunities and developing context-specific skills applicable to local economic environments. This includes training in business planning, financial literacy, market analysis and opportunity identification tailored to the realities of informal and small-scale enterprise development. By incorporating both formal and informal education approaches, social grant recipients who may not have completed formal schooling can still build entrepreneurial capability. To increase impact, partnerships between government departments, private training providers and non-profit organisations could expand access to affordable, community-based entrepreneurship programmes tailored to undereducated and unemployed individuals. Aligning educational interventions with local labour market needs and resource constraints will enhance entrepreneurial readiness and self-sufficiency among social grant recipients.

Design tailored interventions for different age groups

Recommendation: The study’s findings revealed significant differences in entrepreneurial willingness across age groups. Younger recipients showed higher willingness, whereas older recipients exhibited lower intention, indicating that age-specific interventions, tailored to the distinct needs and motivations of different age groups, are required.

Younger grant recipients, who may be more open to innovation and risk-taking, could benefit from programmes emphasising mentorship, exposure to technology-driven business opportunities and experiential learning to stimulate their entrepreneurial intention. These interventions can stimulate long-term entrepreneurial interest and participation. Conversely, older social grant recipients may require transitional support, refresher training and confidence-building initiatives to leverage their existing skills and adapt to entrepreneurial challenges later in life. By aligning entrepreneurial support interventions with age-specific motivations and capacities, policymakers and practitioners can enhance participation across all age groups and more effectively translate willingness into entrepreneurial action.

Promote early exposure to entrepreneurship

Recommendation: The findings revealed that respondents who had previously considered starting a business exhibited higher entrepreneurial willingness, even if they had not yet acted on their intentions. This suggests that creating safe, practical opportunities to explore entrepreneurship for social grant recipients may enhance overall entrepreneurial intention and participation, particularly in contexts where unemployment and limited access to formal employment constrain opportunities.

Policymakers and managers should therefore promote early exposure to entrepreneurship through awareness campaigns, local mentorship and experiential learning opportunities. These interventions should build on and complement existing government initiatives, such as the Small Enterprise Development Agency (SEDA) programmes and the National Youth Development Agency (NYDA) entrepreneurship training schemes, which have proven successful in providing hands-on learning, mentoring, skills development and start-up support. Evidence suggests that targeted, hands-on programmes, such as the NYDA Youth Entrepreneurship Programmes and SEDA’s sector-specific business support initiatives, tend to achieve higher participation and success rates than broad, generalised training efforts. Therefore, by incorporating early exposure elements, such as entrepreneurship or business clubs and local business showcases, social grant recipients can gain the confidence and motivation necessary to view entrepreneurship as a viable and attainable career path.

Simplify access to resources for aspiring entrepreneurs

Recommendation: The study found that resource constraints, particularly limited access to funding and mentorship opportunities, restrict the ability of social grant recipients to translate entrepreneurial willingness into action. Many social grant recipients possess the desire to start small businesses but are constrained by structural barriers such as lack of finance, limited networks and complex administrative procedures. Policymakers should therefore introduce targeted mechanisms that simplify access to financial and non-financial support. This can be achieved by creating microfinance and seed-funding schemes linked to social grant programmes, providing small, low-interest start-up loans or grants to recipients with feasible business ideas. Establishing community-based mentorship networks that connect experienced entrepreneurs with social grant beneficiaries can also provide much-needed guidance, skills transfer and support. Simplifying administrative processes related to business registration and compliance would further ease entry into the formal economy.

Additionally, integrating entrepreneurial support services within existing social grant service points, such as SASSA centres, can enable recipients to conveniently access information on training, funding and market opportunities. Embedding these resources within the social support infrastructure will empower recipients to act on their entrepreneurial intentions and achieve long-term economic independence.

Integrating entrepreneurship into social grant programmes

Recommendation: While social grants remain vital in providing a safety net for vulnerable households, the study’s findings suggest that integrating entrepreneurship initiatives within these programmes can foster self-reliance and sustainable income generation. Policymakers should consider embedding entrepreneurship awareness, skills development and business incubation components into existing social grant systems. This could include linking social grant recipients to enterprise development agencies, offering training modules as part of the grant renewal process or even establishing pilot projects that provide start-up support to recipients interested in transitioning to self-employment.

Such integration would not only enhance recipients’ economic participation but also complement national objectives of reducing unemployment and dependency on state support. Over time, this approach could transform social grants from instruments of short-term relief into catalysts for long-term economic empowerment and inclusion.

The insights derived from this study provide a foundation for practical interventions and policy actions aimed at strengthening entrepreneurial participation among social grant recipients.

In conclusion, these recommendations, grounded in the study’s empirical findings, emphasise the need for a coordinated, evidence-based approach to fostering entrepreneurship among social grant recipients. By addressing educational disparities, tailoring age-specific interventions, expanding access to resources, promoting early exposure to entrepreneurship and integrating entrepreneurship into existing social support systems, stakeholders can collectively enhance entrepreneurial willingness and contribute to inclusive and sustainable economic development in South Africa. Moreover, adopting a phased, stage-gate approach, piloting, evaluating, refining and scaling interventions can help policymakers manage resources efficiently, monitor impact and reduce uncertainty, ensuring that each initiative effectively contributes to long-term economic empowerment.

Limitations and recommendations or future research

Geographical and contextual scope

Limitation: This study focused on social grant recipients in specific urban and rural areas (Johannesburg, Tshwane and rural Limpopo). The findings may not fully represent the experiences or entrepreneurial intentions of social grant recipients across other regions in South Africa or other countries with different socio-economic contexts.

Recommendation: Future research should expand the geographical scope to include other regions and contexts. Comparing different socio-economic conditions may provide a more comprehensive understanding of entrepreneurial drivers and barriers.

Limited variables on psychological constructs and education

Limitation: While the study examined demographic variables (e.g. age, education, gender, marital status) and entrepreneurial factors (e.g. willingness to start a business), it did not deeply explore psychological constructs such as self-efficacy, resilience or locus of control, which are known to influence entrepreneurial intention. Furthermore, ‘education’ in this study referred to respondents’ highest formal qualification level and not the quality, type or relevance of education received. This may limit interpretation and the depth of policy recommendations based on educational outcomes.

Recommendation: Future research should clarify the operational definition of education and integrate psychological variables to capture a broader range of factors that shape entrepreneurial willingness and capacity among social grant recipients.

Dependence on self-reported data

Limitation: The study relied on self-reported data, which may be affected by social desirability bias or inaccurate recall. These biases can influence the accuracy of responses, particularly regarding hypothetical conditions, such as willingness to start a business without a social grant.

Recommendation: Future studies should consider using mixed-method approaches, incorporating qualitative interviews or longitudinal studies to validate and enrich the self-reported data. Longitudinal designs can track changes in entrepreneurial willingness or intention over time and under varying economic conditions.

Assumptions, interpretation of willingness and causality

Limitation: The study assumes that willingness, combined with enabling interventions, would lead to improved self-employment and socio-economic outcomes although this was not empirically tested. Additionally, ‘willingness’ was measured through a binary (yes/no) question, meaning that respondents may have interpreted ‘if given the opportunity’ differently, introducing potential variability in meaning. While statistical analyses identified relationships between variables, these associations should not be interpreted as causal.

Recommendation: Future studies should adopt refined measures of willingness, specify underlying assumptions and use longitudinal or experimental designs to assess whether stated intentions translate into actual entrepreneurial behaviour and outcomes.

Policy anchoring and evidence-based pathways

Limitation: While the study provides practical policy recommendations, these are based on observed statistical relationships rather than empirically tested interventions, and therefore their effectiveness in real-world policy settings has not yet been established.

Recommendation: Future research should implement incremental, evidence-based approaches to policy design, testing interventions on a smaller scale before broader application to ensure reliability and contextual relevance.

Recommendations for future research

Investigate the role of policy and institutional support

Future research should investigate how specific policies and institutional support mechanisms, such as access to funding and mentorship programmes, influence entrepreneurial willingness among social grant recipients. For instance, a study by Masilela et al. (2020, p. 1) found that while many social grant recipients in their study expressed interest in entrepreneurship, approximately 70% were unaware of existing public or private business support initiatives. This underscores the need for targeted interventions that not only provide resources but also effectively communicate their availability and benefits. Best practice programmes like the NYDA and the SEDA have demonstrated success in fostering entrepreneurship. The NYDA offers mentorship, training and funding opportunities tailored to youth, while the SEDA provides support to small enterprises through various services, including business development and access to markets.

Evaluating the impact of these programmes on social grant recipients could yield actionable insights for enhancing their effectiveness and reach. By examining the interplay between policy, institutional support and entrepreneurial willingness, future studies can inform the design of interventions that bridge the gap between social assistance and self-sufficiency, ultimately contributing to sustainable economic empowerment.

Explore gender differences in entrepreneurial intention

While this study did not focus on gender differences, future research should investigate how gender impacts entrepreneurial willingness and explore tailored strategies to address gender-specific barriers and opportunities.

Analyse the long-term impact of entrepreneurship programmes

Research should evaluate the long-term effects of entrepreneurial training or support programmes on transitioning social grant recipients into sustainable self-employment, identifying best practices for programme design and delivery.

Conclusion

This study explored the factors influencing entrepreneurial willingness among social grant recipients, focusing on demographic variables (age, education, marital status and gender) and entrepreneurial attitudes (consideration of starting a business, willingness to start a small business and hypothetical readiness to start a business without social grants). The findings revealed that education and age significantly influence entrepreneurial willingness, with higher education levels and younger age groups showing stronger entrepreneurial intentions. Moreover, individuals who had previously considered starting a business demonstrated a higher level of entrepreneurial willingness. However, the improbability of social grants being discontinued may have influenced participants’ responses to hypothetical scenarios regarding self-employment readiness.

While these results offer valuable insights into how demographic and attitudinal factors shape entrepreneurial willingness, it remains unclear to what extent willing grant recipients differ from non-grant recipients on similar demographic dimensions. Future comparative studies should examine whether the observed relationships are unique to the social grant recipient population or reflective of broader patterns among non-recipients. Such comparative analyses could help validate the current findings and provide deeper understanding of how social dependency, education and perceived capability interact to influence entrepreneurial behaviour. While this study concentrated on entrepreneurial willingness as an initial stage of self-employment, it is essential to acknowledge that willingness alone does not guarantee successful business establishment.

Moving from willingness to actual entrepreneurship requires comprehensive support systems such as inclusivity, financing, mentorship, practical training and simplified regulatory processes that reduce the fear of failure and support the start-up of new businesses (Global Entrepreneurship Monitor, 2025, p. 13). Therefore, policymakers and practitioners should adopt a holistic approach that not only fosters willingness but also strengthens the entrepreneurial ecosystem that supports the transition from willingness to action. Ultimately, this study underscores the importance of tailoring entrepreneurship interventions according to educational levels, age groups and motivational factors while integrating broader structural and institutional supports to enhance self-employment opportunities and economic inclusion among social grant recipients in South Africa.

Acknowledgements

The authors would like to express their sincere gratitude to all the participants who took part in this study. We also extend our appreciation to the language editors, reviewers and the publishing editor for their valuable comments and suggestions, which have contributed to the development of this article.

This article is partially based on the PhD thesis of Boitumelo Masilela entitled ‘Predicting social grant recipients’ entrepreneurial willingness to be self-employed’, submitted towards the degree of PhD in Entrepreneurship, Faculty of Economic and Management Sciences at the University of Pretoria in 2025, under the supervision of Professor Jurie van Vuuren. The thesis is available at https://repository.up.ac.za/items/d3659966-566b-4012-9a17-89aca3ea9406/full.

The authors, Boitumelo Masilela, Jurie van Vuuren and Andries Masenge, declare that they have no financial or personal relationships that may have inappropriately influenced them in writing this article.

Boitumelo Masilela: Conceptualisation, Data curation, Formal analysis, Investigation, Methodology, Project administration, Writing –original draft. Jurie van Vuuren: Conceptualisation, Formal analysis, Investigation, Methodology, Project administration, Supervision, Validation, Writing – review & editing. Andries Masenge: Conceptualisation, Data curation, Formal analysis, Methodology, Software, Validation. All authors reviewed the article, contributed to the discussion of results, approved the final version for submission and publication and take responsibility for the integrity of its findings.

The authors received no financial support for the research, authorship and/or publication of this article.

The data supporting the findings of this study are available from the corresponding author, Boitumelo Masilela, upon reasonable request.

The views and opinions expressed in this article are those of the authors and are the product of professional research. They do not necessarily reflect the official policy or position of any affiliated institution, funder, agency or that of the publisher. The authors are responsible for this article’s results, findings and content.

References