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.

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.

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.

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 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 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.

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.

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.

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.

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).

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.

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.

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.

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.

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.

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.

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.

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.

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.