Youth entrepreneurship in Africa, and particularly in urban settings, takes various forms influenced by socio-economic realities, access to resources, and institutional support. Across the continent, informal sector activities dominate due to limited access to formal employment. Urban youths often engage in street vending, food sales, and small-scale trading, which require low startup capital and minimal formal education [4]. In transitioning urban-rural areas, agricultural entrepreneurship—such as urban farming and animal husbandry—offers income and food security opportunities [5].

In Southern Africa, similar trends are observed with youths turning to informal commerce and the creative industries such as music, dance, and fashion for economic survival and cultural expression [6]. In Zambia, informal entrepreneurship remains widespread, with urban youths involved in street vending, second-hand clothing sales, and small retail businesses [7]. With improved access to digital technologies, freelancing and self-employment in graphic design, digital marketing, and IT services are emerging as viable options [8]. Furthermore, education and vocational training initiatives such as apprenticeships and entrepreneurship programs are becoming key pathways for enhancing youth employability [9].

Empirical studies echo these observations. [10] highlight the dominance of necessity-driven businesses like kiosks and mobile money booths among Kenyan youth. In Zambia, [11] found over 60% of youth-owned businesses were in informal commerce and services. Studies by [12] underline that most youth enterprises operate in low-barrier sectors like trade, hospitality, and personal services, and often reflect gender-specific patterns.

Youth unemployment remains a critical concern across Africa. The [13] reports that 22.5 million African youths aged 15 - 24 are unemployed, representing a 20.5% unemployment rate. Structural factors such as weak industrialization, education-labor mismatches, and gender disparities exacerbate the crisis. The COVID-19 pandemic further disrupted labor markets, driving up unemployment and underemployment, especially in informal economies.

Southern Africa faces some of the highest youth unemployment rates globally. In 2023, approximately 12.4 million youths in the region were unemployed. South Africa recorded over 62% youth unemployment, while Zambia and Zimbabwe faced rates above 25%. Causes include economic stagnation, deindustrialization, and a lack of market-relevant skills. Although entrepreneurship offers temporary relief, structural reforms and skill-aligned policies are essential for sustainable improvement.

In Zambia, youth unemployment has hovered above 25%, especially in urban areas [14]. Challenges such as skills mismatch, limited job creation, and an oversupply of graduates with few practical competencies have led many youths into informal work. Unemployment rose sharply in 2021 (14.5%) due to pandemic impacts but began to decline to 12.0% by 2023, indicating early signs of recovery [15].

Despite entrepreneurship being a solution to youth unemployment, many young entrepreneurs face formidable challenges. Across Africa, barriers include limited access to finance, weak infrastructure, lack of entrepreneurship training, and inadequate technological access [16][17]. Many youth lack the collateral or credit history to obtain loans, restricting business scalability.

In Southern Africa, youths struggle with market saturation, intense competition, and exclusion from established supply chains. Social norms, especially around gender and family expectations, can limit participation in entrepreneurship, particularly for women [18][19]. In Zambia, access to business support services—such as mentorship, incubation, and market data—is extremely limited.

Empirical evidence reveals poor financial literacy, inadequate business planning, and regulatory constraints as major obstacles. Moreover, gender-based barriers—such as limited mobility, time constraints, and societal bias—further disadvantage young women in the entrepreneurial space [20][21].

Youth entrepreneurship has the potential to contribute significantly to employment creation, especially in the context of high youth unemployment in Africa. Several theoretical frameworks support this role. Human Capital Theory posits that investments in education and skills development enhance productivity and employability [22]. Schumpeterian entrepreneurship emphasizes innovation and risk-taking as drivers of job creation through new ventures [23][24]. Institutional Theory highlights the importance of policy environments and norms in shaping entrepreneurial behavior [25][26], while Social Capital Theory stresses the value of networks and trust in facilitating entrepreneurship [27][28].

However, gaps in the literature remain. Few studies examine long-term outcomes of youth entrepreneurship on employment beyond subsistence-level survival [29]. Intersectional factors such as gender, ethnicity, and socio-economic status remain underexplored [30]. Furthermore, many evaluations rely on anecdotal evidence or cross-sectional data, underscoring the need for more rigorous methodologies such as randomized controlled trials and longitudinal designs [31].

To effectively harness entrepreneurship for job creation, more context-specific research is needed to inform policies that integrate education systems with labor markets, support youth innovation ecosystems, and enhance access to capital, mentorship, and markets (Figure 1Figure 1).

Figure 1. Conceptual model adopted by Author (2025).

While the existing literature establishes a strong link between youth entrepreneurship and its potential to reduce unemployment, several gaps persist that hinder a comprehensive understanding of this relationship. Most studies focus on short-term, subsistence-level outcomes rather than examining the sustainability and long-term employment effects of youth-led enterprises. There is limited empirical evidence on how entrepreneurial activities transition into scalable ventures that can generate stable jobs for others beyond the entrepreneur. Additionally, intersectional variables such as gender, socio-economic background, geographic location, and education levels are often underexplored, leaving out critical nuances that affect entrepreneurial success and impact. Furthermore, most available studies rely heavily on qualitative or cross-sectional data, with a shortage of longitudinal or experimental research designs that can causally link youth entrepreneurship to employment generation. These limitations call for more rigorous, context-specific, and multidimensional research to guide effective policy interventions aimed at maximizing the role of youth entrepreneurship in alleviating unemployment.

The study employed both deductive and inductive approaches, consistent with its mixed-methods design. The deductive approach tested existing theories on entrepreneurship and unemployment using quantitative data from structured questionnaires. Simultaneously, the inductive approach explored new insights from qualitative interviews, uncovering themes around entrepreneurial challenges, motivations, and social impact. This combination allowed the study to be both theory-driven and open to emerging patterns, enhancing the depth and validity of the findings.

This was a cross-sectional study with data being collected between November 2022 and April 2023. Data pertaining to this study was neither collected before nor after this period for this research.

The study employed a mixed-methods approach, integrating quantitative and qualitative methods to provide a comprehensive understanding of how youth entrepreneurship contributes to reducing unemployment in Matero Township. Quantitative data from structured questionnaires enabled statistical analysis of employment trends, while qualitative interviews offered deeper insights into the lived experiences, motivations, and challenges faced by young entrepreneurs. This approach was justified as it allowed for data triangulation, enhanced validity, and a holistic view of the research problem. It aligns with the pragmatist paradigm, which supports methodological flexibility and the use of multiple forms of evidence to address complex social issues [34].

The sampling frame comprised 7343 unemployed youths aged 18 - 35 in Matero Township, along with key stakeholders such as local officials and business support representatives [35]. Although the initial sampling frame comprised 7343 unemployed youths aged 18 - 35 in Matero Township, the study specifically focused on youths who had transitioned from unemployment into entrepreneurship. The ZamStats registry was therefore used as a starting point to identify eligible respondents, who were subsequently screened to establish whether they had started an income-generating activity or micro-enterprise within the past 1 - 5 years. Verification of active business ownership was conducted through self-reports and, where possible, confirmation from local ward offices, youth cooperatives, and business support institutions. As a result, the final analytical sample consisted of youth entrepreneurs, which justified the analysis of outcomes such as jobs created per entrepreneur.

For the qualitative component, 20 participants were purposively selected, including youth entrepreneurs and stakeholders, to ensure data saturation and capture diverse perspectives.

Data were collected using a mixed-methods approach. Quantitative data were gathered through structured questionnaires containing closed-ended and Likert-scale questions on demographics, entrepreneurial activity, barriers, and perceived employment impact. Qualitative data were obtained via semi-structured interviews with selected youth entrepreneurs and key stakeholders to explore experiences, motivations, and challenges. Document review of policy reports and local economic data supplemented the primary data. Quantitative data were analyzed using SPSS to generate descriptive and inferential statistics, while qualitative data underwent thematic analysis to identify recurring patterns and insights. Triangulation of methods enhanced the validity and depth of the findings.

To ensure validity, the study’s instruments were based on established theories and reviewed by experts, with a pilot test conducted to refine clarity and relevance. Reliability was enhanced through standardized data collection procedures and inter-rater checks during qualitative analysis to maintain consistency. Regarding generalizability, although the study focused on Matero Township’s specific context, the use of stratified sampling and a diverse participant pool, combined with alignment to broader literature, supports the transferability of findings to similar urban settings.

Quantitative results showed manufacturing (M = 2.3) and agribusiness (M = 2.1) create significantly more jobs per participant than trading (M = 1.2) and services (M = 1.5) (See Table 1).

Qualitative data supported this, with respondents in agribusiness and manufacturing describing seasonal hiring due to labor-intensive operations, while traders and service providers mostly worked alone due to limited capital and space. For instance, a poultry farmer noted hiring multiple helpers during peak periods, whereas a clothing vendor relied on informal family help.

Table 1. Types of entrepreneurship activities.

Financial constraints, regulatory barriers, and socio-cultural factors were all measured using composite indices derived from multiple five-point Likert-scale items (1 = Strongly Disagree to 5 = Strongly Agree). Financial constraints captured limited access to start-up capital, difficulty obtaining loans or grants, high interest rates, inadequate cash flow, and high operating costs, with higher scores indicating greater financial pressure. Regulatory barriers assessed challenges related to business registration, licensing procedures, taxation requirements, compliance costs, and bureaucratic delays, where higher composite scores reflected more severe regulatory obstacles. Socio-cultural factors measured constraints arising from cultural norms, gender-related barriers, societal attitudes toward youth entrepreneurship, family expectations, and community support, with higher scores indicating stronger socio-cultural limitations faced by youth entrepreneurs.

Regression analysis indicated that financial constraints (B = –0.41, p = 0.001) and regulatory barriers (B = –0.28, p = 0.012) significantly limit employment creation, explaining 28.9% of variance. Socio-cultural factors were not statistically significant but emerged qualitatively as barriers, especially for women facing gender stigma and limited family support (see Table 2). Participants highlighted lack of capital, high loan requirements, and cumbersome registration processes as major obstacles to expansion.

These qualitative insights echo [36] and [37] on financing and regulatory challenges, while [38] discusses socio-cultural constraints affecting female entrepreneurs’ growth and employment capacity.

The regression results indicated that socio-cultural factors were not statistically significant in predicting employment creation (B = −0.09, p = 0.313), suggesting that, in the quantitative model, these factors did not independently explain variations in job creation among youth entrepreneurs. However, the qualitative findings highlighted socio-cultural barriers as critical, particularly for female entrepreneurs who faced gender stigma, limited family support, and societal expectations that constrained business participation and expansion. This divergence may be due to measurement limitations in the survey instrument. For example, the Likert-scale items may not have fully captured the depth and nuance of gender norms, cultural expectations, and social stigma, or respondents may have underreported these experiences in a structured survey format due to social desirability bias. Additionally, socio-cultural barriers may operate indirectly—for instance, by influencing access to resources or shaping entrepreneurial intentions—rather than having a direct, linear effect measurable through regression. Thus, while the quantitative analysis shows statistical non-significance, the qualitative insights reveal the contextual and experiential relevance of socio-cultural constraints, underscoring the value of a mixed-methods approach for understanding complex social phenomena in youth entrepreneurship.

Table 2. Regression summary.

Statistical analysis revealed a positive association between longer unemployment and entrepreneurial engagement (χ² = 9.12, p = 0.010; Exp(B) = 1.79, p = 0.008). See (Table 3). Qualitative interviews confirmed that many youths start businesses after prolonged job searching, often as a survival strategy rather than a first choice. Several participants described transitioning from necessity entrepreneurship to opportunity-driven growth, with some planning to expand and employ others. This is consistent with [39] on necessity entrepreneurship, on informal sector dynamics, and [40] on the evolution of entrepreneurial intent.

Table 3. Binary logistic regression.

Inferential analysis showed that type of entrepreneurship significantly influenced job creation, with manufacturing and agribusiness sectors generating more employment than trading or services (F(3, 146) = 5.82, p < 0.01). A strong positive correlation existed between access to finance and business growth (r = 0.72, p < 0.01), while logistic regression indicated that youths unemployed for over 12 months were 2.4 times more likely to start necessity-driven businesses (p < 0.05). Financial and regulatory constraints were significant barriers to employment expansion (β = −0.59, β = −0.47, both p < 0.05). Qualitative findings supported these results, revealing that many youth turned to entrepreneurship as a survival strategy, often lacking adequate training, mentorship, and policy support. Participants emphasized the need for targeted interventions in manufacturing and agribusiness, and called for simplified registration processes and inclusive financing to scale up youth-led enterprises.

This study found that the type of entrepreneurship significantly affects youth employment creation in Matero Township, with manufacturing and agribusiness generating more jobs per entrepreneur than trading and services, despite trading having higher participation. This highlights the need for policymakers to prioritize support for labor- and capital-intensive sectors through targeted training, financial access, and market development to maximize job creation. Financial constraints and regulatory barriers were identified as the primary obstacles limiting youth entrepreneurs’ ability to expand and hire, while socio-cultural factors, though present, had less immediate impact. The research also revealed a strong link between prolonged unemployment and engagement in entrepreneurship, where many youths start businesses out of necessity rather than choice. However, some transition from survival-driven ventures to opportunity-driven enterprises with growth potential, underscoring the importance of supportive programs that build skills, provide mentorship, and simplify regulatory processes. Overall, fostering an enabling ecosystem that addresses these challenges and nurtures business development is essential to leveraging entrepreneurship as a sustainable strategy to reduce youth unemployment in Matero Township and similar context.

The study’s findings should be interpreted with consideration of several limitations. First, the research was geographically limited to Matero Township, which may constrain the generalizability of the results to other urban or rural settings in Zambia. Second, although the mixed-methods design enhanced the richness of the data, the relatively small qualitative sample size (n = 15) may have limited the diversity of perspectives captured. Additionally, the cross-sectional nature of the study does not allow for the observation of changes over time in youth entrepreneurial behavior or employment outcomes. Self-reported data, especially in the quantitative component, may also be subject to social desirability bias or recall inaccuracies. Despite these limitations, the study offers valuable insights into youth entrepreneurship and unemployment, providing a strong basis for further longitudinal or comparative research. The implications highlight the urgent need for policy reforms in financial access, vocational training, and business regulation to foster sustainable youth-led employment creation.

Based on the findings, this study recommends targeted support for high-impact sectors such as manufacturing and agribusiness, which exhibited stronger employment multipliers. Policymakers should provide sector-specific training, affordable inputs, and improved market linkages. To improve access to finance, youth-friendly loan products with flexible collateral requirements and enhanced financial literacy programs are essential. Streamlining regulatory and administrative processes through one-stop business service centers would reduce formalization barriers and promote business growth. For future research, it is crucial to examine the impact of digital technologies on youth entrepreneurship, assess gender-specific challenges and opportunities, evaluate the effectiveness of support interventions, and further explore the role of socio-cultural factors across different contexts. These steps would enrich understanding and guide more inclusive and evidence-based policy responses to youth unemployment through entrepreneurship.