Abstract
Background: Youth unemployment continues to pose a serious socio-economic challenge in South Africa, especially within township areas. Promoting entrepreneurship has emerged as a key strategy to enhance economic participation and self-employment opportunities among the youth.
Aim: The purpose of this study is to examine the extent to which personal attitudes (PA), social influence (subjective norms [SN]) and perceived behavioural control (PBC) shape entrepreneurial intentions (EIs) among unemployed young people.
Setting: The study was conducted in Mdantsane Township, located in the Eastern Cape province.
Method: The study employed a cross-sectional quantitative research approach, involving a purposive sample of 248 unemployed youth. Data were gathered using a structured and validated questionnaire informed by the Theory of Planned Behaviour (TPB). The results were analysed through confirmatory factor analysis (CFA) and structural equation modelling (SEM).
Results: The results show that PA (β = 0.388, p = 0.023) and PBC (β = 0.364, p = 0.004) significantly predicted EI, indicating that positive perceptions and confidence in one’s ability are strong drivers of intention. However, SN (β = 0.258, p = 0.103) did not have a significant effect, suggesting that social pressure plays a limited role in shaping EI in this context.
Conclusion: Personal attitude and PBC significantly influence intention. Entrepreneurship programmes should therefore focus on enhancing youth self-efficacy and control perceptions while addressing structural barriers that limit agency.
Contribution: The TPB framework effectively explains EIs among unemployed youth in Mdantsane Township.
Keywords: entrepreneurial intention; youth unemployment; theory of planned behaviour; structural equation modelling; township economy; South Africa.
Introduction
Youth unemployment in South Africa persists at alarming levels, especially in provinces like the Eastern Cape, where the youth unemployment rate was approximately 53.3% in 2024 (National Youth Development Agency 2024). While the roots of this challenge can be traced back to colonial and apartheid inequalities (Bundy 2020; Gavaza, Fihla & Stofile 2025; Mayekiso & Obioha 2022). Contemporary challenges, such as ineffective governance, policy inconsistency and corruption, perpetuate the problems (Corruption Watch 2023; National Youth Development Agency 2024). The socio-economic impact is especially severe in many township communities, where limited economic opportunities and poverty prevail. In the face of dwindling formal employment opportunities, entrepreneurship has emerged as a key strategy for youth employment and economic empowerment in these marginalised communities (Magadla 2023; Makwembere, Murire & Ngabase 2024).
Youth unemployment in South Africa is deeply rooted in structural deficiencies in the education system and a misalignment between the skills produced by education and those demanded by the contemporary labour market. Consequently, both the government and the private sector have launched targeted initiatives to foster entrepreneurship, particularly in economically marginalised regions such as the Eastern Cape (Moyo, Mishi & Ncwadi 2022). Within this context, entrepreneurship is increasingly regarded as a strategic mechanism to address the persistent unemployment crisis. Despite these interventions, entrepreneurial participation among township youth remains disappointingly low. Youth entrepreneurship, therefore, represents an underutilised avenue for addressing unemployment (Wang & Wong 2004). Many young people lack the motivation, confidence and necessary institutional support to actively engage in entrepreneurial activities (ASPEN Network of Development Entrepreneurs [ANDE] 2024).
South Africa’s youth unemployment rate was reported to be 46.1% in early 2025, with the rate rising even higher to 62.4% among the youngest cohort aged 15 years to 24 years (Stats SA 2025). Over half of unemployed youth also have no prior work experience, exacerbating their challenges when trying to enter the labour market. This fact highlights the urgent need to strengthen entrepreneurship programmes to realise the potential of youth as drivers of economic growth and job creation.
This study investigates the psychological determinants of entrepreneurial intention (EI) using the Theory of Planned Behaviour (TPB), focusing on unemployed youth in Mdantsane Township, Eastern Cape, South Africa. The research addresses the need for locally relevant evidence to inform policies and interventions. By applying TPB, the study deepens understanding of the factors that influence EIs among unemployed youth in South African townships.
The TPB serves as a prominent theoretical model for understanding and forecasting human actions. It posits that an individual’s intention to engage in entrepreneurship is influenced by three primary factors: their personal attitude (PA) towards entrepreneurial activity, the perceived social expectations or subjective norms (SN) and their sense of perceived behavioural control (PBC), that is, the confidence in their ability to perform entrepreneurial tasks (Thibane et al. 2023). While numerous studies have applied TPB in diverse cultural and economic contexts, a gap remains in its application within the specific socio-economic realities of South African townships, where structural barriers and socio-cultural factors may uniquely influence entrepreneurial aspirations (Maramura, Makaye & Mude 2024).
This study contributes to scholarly literature by examining the EIs of unemployed youth in a South African township through the lens of TPB. Specifically, this study aims to (1) apply TPB to understand the EIs of unemployed township youth, (2) identify which TPB components are most influential and (3) provide evidence-based recommendations for programmes supporting entrepreneurship. Furthermore, the study provides valuable guidance for policymakers, educators and community stakeholders on creating an enabling ecosystem that promotes youth entrepreneurship as a strategy to mitigate the high unemployment levels in the Eastern Cape province.
Theory of planned behaviour
The TPB, developed by Icek Ajzen in 1991, is a widely acknowledged psychological model used to explain and predict human actions and decision-making processes. According to the TPB, an individual’s behavioural intention serves as the strongest and most direct determinant of whether they will engage in a particular action. Ajzen (1991) expanded upon the earlier Theory of Reasoned Action by incorporating the concept of PBC, thereby enhancing the model’s ability to account for a wider variety of behaviours, such as entrepreneurial activities. Theory of Planned Behaviour offers a comprehensive and flexible framework for understanding EIs. Additionally, TPB proposes that intention is the strongest predictor of behaviour. The core components of TPB have been proven to strongly predict EIs across various cultural and educational contexts (Lihua 2022; Mfazi & Elliott 2022).
The application of TPB in entrepreneurship research, including among unemployed youth in South African townships, underscores its relevance in guiding interventions to foster entrepreneurial activities, thereby promoting economic empowerment and self-sufficiency in marginalised communities. These behavioural intentions are shaped by three fundamental components: an individual’s PA towards the behaviour, the perceived social pressure or SN and the PBC, which reflects one’s confidence in one’s ability to perform the behaviour.
Personal attitude denotes an individual’s overall favourable or unfavourable approach towards performing a particular behaviour. In entrepreneurship, this concept refers to the extent to which an individual holds favourable views of being an entrepreneur. Those who perceive entrepreneurship as a pathway to financial independence, personal fulfilment or social contribution are more likely to develop EIs (Krueger, Reilly & Carsrud 2000; Liñán & Chen 2009). Conversely, negative attitudes, such as fears of financial risk or business failure, can hinder the development of these intentions.
Prior South African studies have demonstrated that favourable attitudes towards entrepreneurship significantly enhance the likelihood of EIs (Fatoki 2014; Kolapo et al. 2023). Therefore, promoting positive entrepreneurial attitudes is critical in fostering intention. Drawing from these insights, we propose the following hypotheses:
H10: Personal attitude does not have a significant positive effect on EI among unemployed youth (r ≤ 0).
H1a: Personal attitude has a significant positive effect on EI among unemployed youth (r > 0).
Subjective norm relates to the perceived social pressures or influences from essential others regarding whether to engage in a specific behaviour (Azjen 1991). These ‘others’ could include family, friends and mentors. Within the entrepreneurial context, SNs represent the perceived social expectations or opinions of important individuals such as family, friends or mentors regarding one’s decision to pursue entrepreneurship (Liñán & Chen 2009). They can significantly impact EIs, especially in collectivist societies in which family and community approval are vital (Iakovleva, Kolvereid & Stephan 2011). For instance, individuals who feel supported to pursue entrepreneurship are more likely to form solid EIs. While some research indicates that social support strengthens EI (Arthur & Peprah 2024; Shinnar & Young 2008), others find social support to be a weak or non-significant predictor in under-resourced settings (Acuña-Duran et al. 2021; Iakovleva et al. 2011).
Accordingly, the following hypotheses are formulated:
H20: The SNs do not have a significant positive effect on EI among unemployed youth.
H2a: The SNs have a significant positive effect on EI among unemployed youth.
Perceived behavioural control concerns an individual’s perception of how easy or difficult it is to perform a particular behaviour. It is one of TPB’s key components and incorporates two subdimensions: self-efficacy or belief in one’s own competence (Bandura 1977) and controllability or belief in control over external barriers (Ajzen 2002). While related to self-efficacy, PBC is broader in scope, encompassing both internal and external dimensions of control. Entrepreneurship encompasses assessing skills, knowledge and access to resources that are necessary to start and run a business (Krueger et al. 2000).
People who perceive themselves as having the necessary skills, abilities and resources to start a business are more inclined to develop intentions towards engaging in entrepreneurial activities (Liñán & Chen 2009). Therefore, it is argued that PBC influences actual behaviour. Fayolle and Gailly (2015) and Neneh (2019) state that people with high confidence in their abilities are likelier to act on their EIs, especially when the opportunities align with their perceived control. In township contexts, this construct is particularly important as a result of systemic barriers that may inhibit confidence and perceived feasibility. Therefore, the following hypotheses are set:
H30: Perceived behavioural control does not have a significant positive effect on EI among unemployed youth.
H3a: Perceived behavioural control has a significant positive effect on EI among unemployed youth.
The TPB has been extensively utilised in entrepreneurship research to examine how PAs, SNs and PBC influence EIs in various settings. The theory has also been employed to analyse how these factors differ across cultural and contextual environments, offering insights into the diverse determinants of entrepreneurial behaviour. For example, Iakovleva et al. (2011) compared EIs between developing and developed countries. They found that the predictive strength of TPB components, particularly PBC, was more pronounced in developing economies. These findings underscore the importance of contextual factors, such as cultural norms and economic conditions, in shaping EIs. Entrepreneurship education has also been a vital area in which TPB has been applied to measure the effectiveness of interventions in enhancing EIs.
Fayolle and Gailly (2015) applied the TPB to examine the extent to which entrepreneurship education impacts students’ attitudes, perceived social norms and sense of behavioural control towards entrepreneurial activities. Their study demonstrated that educational programmes emphasising entrepreneurial skills and resources can significantly improve students’ EIs, especially by enhancing PBC. Additionally, the TPB has also been employed to investigate gender-based variations in EIs. Haus et al. (2013) observed that while women tended to report lower levels of EI compared to that of men, the underlying associations between the TPB constructs and EIs were largely consistent across both genders. Their research suggests that interventions to improve PBC and SNs could be particularly effective in encouraging women to pursue entrepreneurship.
Some scholars have expanded TPB to incorporate contextual variables to understand EIs in specific populations. Lüthje and Franke (2003) integrated environmental variables such as the availability of entrepreneurial resources, as well as the perceived feasibility of entrepreneurship, into the TPB model when studying EIs among engineering students. These extensions highlight the adaptability of TPB to different contexts, making it a valuable framework for studying entrepreneurship in diverse settings.
Theory of Planned Behaviour is a valuable theory for understanding EIs among unemployed youth in South African townships, where high unemployment rates and socio-economic challenges influence entrepreneurial aspirations (Mayekiso & Obioha 2022; Meyers-Mashamba 2021).
Applying the TPB framework helps identify critical areas for intervention. These include fostering positive attitudes towards entrepreneurship through success stories, reshaping social norms to support entrepreneurial activity and strengthening PBC by providing training and resources. Educational and community programmes can also leverage TPB components and promote entrepreneurship as a viable career option for young people with limited job opportunities (Dolan & Rajak 2018; Johri et al. 2024; Yan, Huang & Xiao 2023).
Theory of Planned Behaviour has been widely utilised in entrepreneurship studies to elucidate the psychological factors that precede and shape EIs (Liñán & Chen 2009; Neneh 2019). Additionally, the model is especially relevant in developing contexts where resource constraints and socio-cultural factors significantly influence entrepreneurial decisions (Iakovleva et al. 2011). Therefore, in township environments like Mdantsane, understanding how these constructs indicate associations or relationships is important for designing more effective interventions to support youth entrepreneurship.
Empirical literature
The literature reviewed in the study is based on unemployment, educational barriers and entrepreneurship support in the Eastern Cape province.
Unemployment in the Eastern Cape
The Eastern Cape’s unemployment crisis cannot be fully understood without considering the historical context of South Africa’s colonialism, slavery and apartheid, which forged deep-rooted poverty and inequality along racial lines (Bundy 2020; Maramura et al. 2024). The Eastern Cape, as a rural and historically marginalised province, has experienced a deliberate underdevelopment that continues to impact its economic viability (Fiseha, Kachere & Oyelana 2019). As a result, poverty, unemployment and inequality remain pervasive in rural villages and towns (Mayekiso & Obioha 2022).
In the second quarter of 2024, the Eastern Cape entered a technical recession, exacerbated by the collapse of critical sectors like construction, manufacturing and mining. These declines intensified unemployment, with the overall unemployment rate rising from 49.1% to 49.7%, a 6.4% increase compared to that in 2023 (Eastern Cape Socio-Economic Consultative Council 2024). This increase reflects the lack of industrial investment, entrenched corruption and an education system that fails to equip the province’s youth with the skills needed to meet the demand for skilled labour (Meyers-Mashamba 2021; Seekings 2007). The situation is particularly severe among the youth. Unemployment among individuals aged 15–34 years has reached 53.3%, far outpacing the adult unemployment rate of 32.2% (Eastern Cape Socio-Economic Consultative Council 2024). Women, disabled persons and young people face disproportionate levels of unemployment, partly as a result of lingering structural inequalities from the apartheid and colonial eras (Makwembere et al. 2024).
Educational barriers and entrepreneurship support
The Eastern Cape’s education system is marred by low-quality schooling, inadequate infrastructure and a shortage of qualified teachers, particularly in rural areas (Moyo et al. 2022). These issues have resulted in poor educational outcomes, particularly among students transitioning from Grade 10 to 12, with low progression rates (Jama et al. 2024). This result directly links poor education and high unemployment rates, with a limited number of youths attaining tertiary education and qualifying for formal employment opportunities (Magadla 2023; Moyo et al. 2022).
Entrepreneurship is a potential solution to the Eastern Cape’s unemployment crisis (Maramura et al. 2024). Support exists at various levels. Public institutions like the Small Enterprise Development Agency and the Eastern Cape Development Corporation are instrumental in promoting the growth of small and medium enterprises by offering training programmes, financial assistance and access to affordable funding opportunities (Thibane et al. 2023). However, these services are often inaccessible to rural entrepreneurs, highlighting the need for improved reach. Higher education institutions, including universities and Technical and Vocational Education and Training colleges in the Eastern Cape, are increasingly tasked with embedding entrepreneurship within their academic programmes and community outreach activities to cultivate an entrepreneurial mindset among students (Makwembere et al. 2024). Such efforts aim to create an ecosystem that supports entrepreneurship and innovation, fostering future-ready graduates (Makwembere et al. 2024; Sibanda, Ndlela & Nomlala 2020). Private businesses, such as Umtiza Farmers’ Corp and the Eastern Cape Wool Growers Association, provide technical training to emerging farmers, contributing to establishing new farming businesses. These initiatives aim to empower youth and enhance agricultural productivity (Umtiza Farmers’ Corp 2024). By addressing structural challenges in education and creating an environment that supports entrepreneurship, the Eastern Cape can alleviate its unemployment crisis, particularly among its vulnerable youth population (Makwembere et al. 2024).
The literature demonstrates that EI is influenced by psychological, social and structural factors. Psychological factors include self-efficacy, PAs and PBC; social factors comprise SNs shaped by family, peers and cultural expectations and structural factors relate to access to education, finance and institutional support (Cordova-Buiza et al. 2023; Ndovela & Chinyamurindi 2021). Post-apartheid South Africa has introduced youth-targeted entrepreneurship programmes, yet these often falter as a result of implementation gaps and governance failures.
Gender dynamics also shape entrepreneurial activity (Neneh 2019). As some studies suggest, women face more barriers but may demonstrate stronger entrepreneurial intent under specific conditions. Theory of Planned Behaviour remains a leading framework for assessing such behavioural intentions, especially in under-researched, marginalised settings. Theory of Planned Behaviour’s core constructs (attitude towards the behaviour, SNs and PBC) have been extensively validated to predict EIs across diverse cultural and socio-economic contexts, including emerging economies and marginalised groups (Ajzen 1991; Mfazi & Elliott 2022). Studies in less-represented settings demonstrate that TPB explains significant variance in EIs while accounting for contextual and demographic factors unique to marginalised populations (Mfazi & Elliott 2022; Rusteberg 2013). This empirical evidence makes the TPB especially valuable for understanding and promoting entrepreneurship in contexts in which research is limited and barriers are unique.
Research methods and design
The purpose of this study was to examine the extent to which PA, SNs and PBC affect EIs among unemployed youth, while also assessing the relevance and applicability of the TPB within the South African township context.
Research design and approach
A quantitative, cross-sectional research design was employed to test the TPB framework. This approach is appropriate for identifying patterns and testing theory-driven hypotheses with statistical rigour (Hair et al. 2014).
Population and sampling
From a total population of 755 200, an estimated 265 475 individuals are unemployed youth, representing 35.1% of the population. The study targeted unemployed youth aged 18–35 years residing in Mdantsane Township. A non-probability purposive sampling method was used, appropriate for targeting specific, information-rich subpopulations (Pace 2021). A final sample of 248 respondents was deemed sufficient, based on structural equation modelling (SEM) sample size guidelines (Kline 2016). This non-probability method is justified due to the targeted nature of the population and study objectives.
Instrumentation
The study employed measurement scales adapted from previously validated instruments: personal attitude (Liñán & Chen 2009), SN (Krueger et al. 2000), PBC (Fayolle & Gailly 2015) and EI (Neneh 2019). The reliability and validity of the constructs were verified through CFA. All variables were assessed using a five-point Likert scale ranging from 1 (strongly disagree) to 5 (strongly agree).
Data analysis
Data analysis was conducted by using the Statistical Package for the Social Sciences version 29 and Analysis of Moment Structures (AMOS) version 22. Confirmatory factor analysis was performed in AMOS to assess and validate the measurement model’s construct reliability and validity. Reliability was assessed by using Cronbach’s alpha, McDonald’s omega coefficients and the Jöreskog rho. A descriptive approach was used to describe the study’s demographic characteristics and the established main theoretical variables. A one-tailed test of the significance of the correlation (Pearson’s r) was used. Path analysis using structural equation modelling was used to determine the direct effects of the hypothesised frameworks. A bootstrapped maximum likelihood approach was used as an estimation approach for both the measurement and the structural models. To assess the significance of the beta estimates, 95% bias-corrected bootstrapped confidence intervals and the associated p-values were used.
Ethical considerations
Ethical clearance for this study was obtained from the Walter Sisulu University Research Ethics Committee (No. FEDREC15-06-23-3).
Results
Demographic information
Descriptive statistics were generated to provide an overview of the respondents’ demographic profiles and to summarise the key study constructs, including PA, SN, PBC and EI. The demographic details of the study participants are presented in Appendix 1 Table 1–A1.
| TABLE 1: Goodness-of-fit indices summary and their accepted values according to the literature. |
Validity and reliability assessment
The measurement instrument underwent preliminary evaluation to assess its validity and reliability. Confirmatory factor analysis was performed to verify construct validity and to establish the measurement model. Additionally, reliability analysis was conducted to examine the internal consistency of the identified factors and ensure the robustness of the measurement scales. As the measurement tool was adopted by other authors, literature about the measurement instrument was used to guide the empirical factors to be loaded for the CFA. To examine the model fitness, we used some goodness-of-fit indices coupled with their respective criteria (Table 1).
Overall, the findings from the validity and reliability assessments of the measurement instrument derived from the CFA and reliability coefficients demonstrated strong psychometric properties. The most parsimonious measurement model was attained after removing items with low factor loadings. As in Table 2, all retained items exhibited factor loadings exceeding 0.60, confirming their statistical significance and construct relevance. The average variance extracted values for all constructs were above the recommended threshold of 0.50, indicating satisfactory convergent validity. Furthermore, reliability analysis revealed Cronbach’s alpha and McDonald’s omega coefficients greater than 0.80 across all constructs, signifying excellent internal consistency and measurement reliability.
| TABLE 2: Confirmatory factor analysis and reliability output for the measurement model. |
Additionlly, the assessment of composite reliability (CR) using Jöreskog’s rho indicated values exceeding 0.80 for all significant constructs, confirming a high level of CR for the established measurement model. The finalised measurement model (see Figure 1) demonstrated substantial factor loadings, reflecting a strong and satisfactory alignment between the observed items and their corresponding latent factors.
An evaluation of the overall model fit indices further supported the adequacy of the measurement model. As presented in Table 3, the chi-square to degrees of freedom ratio (CMIN/df = 3.234) falls within the acceptable range of 3 to 5, indicating a reasonable fit. The standardised root mean square residual (SRMR = 0.041) is below the 0.05 threshold, suggesting a good model fit. Similarly, the root mean square error of approximation (RMSEA = 0.086; 90% CI [0.072, 0.100]) indicates an acceptable level of fit. In terms of incremental fit indices, the comparative fit index (CFI = 0.942) and Tucker-Lewis index (TLI = 0.926) both exceed the recommended minimum of 0.90, providing further evidence of an acceptable and well-fitting measurement model.
| TABLE 3: Goodness-of-fit indices for the established measurement model. |
Descriptive summary of main theoretical variables
Table 4 provides a descriptive summary and correlation matrix for the principal theoretical constructs. The mean values (measured on a five-point Likert scale) indicate moderately high levels across the key study variables. A correlational analysis examined the linear relationships among the main constructs, serving as a preliminary step for subsequent inferential analyses aimed at testing the hypothesised model.
| TABLE 4: Descriptive summary of main theoretical variables. |
A one-tailed Pearson’s correlation test was employed to determine the statistical significance of the relationships. The interpretation of correlation strength followed the thresholds proposed by Cohen (1988), in which coefficients between 0.10 and 0.29 indicate a weak relationship, those between 0.30 and 0.49 represent a moderate relationship, and values above 0.50 denote a strong association.
The results revealed that EI demonstrated strong, positive and statistically significant correlations with SN (r = 0.755), PBC (r = 0.753) and PA (r = 0.780), all significant at p < 0.001. These findings suggest a substantial effect size, indicating that higher levels of EI are associated with corresponding increases in SN, PBC and PA.
Hypotheses testing
Figure 2 illustrates the structural model developed to evaluate the hypothesised relationships outlined earlier. The goodness-of-fit indices indicated that the model achieved an acceptable and satisfactory fit to the observed data. Employing a maximum likelihood-based bootstrap estimation procedure, we computed the structural regression path coefficients to assess the direct effects among the latent variables within the model. The model fit summary shows that the model is a generally acceptable fit, thus RMSEA = 0.096, SRMR = 0.043 < 0.05, CMIN = 3.247 < 5, CFI = 0.928 > 0.90 and TLI = 0.909, which is greater than 0.90.
Table 5 presents the maximum likelihood estimates of the structural path coefficients, along with their corresponding bootstrapped 95% bias-corrected confidence intervals.
| TABLE 5: Structural model path beta estimates. |
Hypothesis H1a: The analysis revealed that the direct effect of PA on EI was positive and statistically significant (β = 0.388; SE = 0.167; 95% CI [0.082, 0.719]; p = 0.023). This result supports H1a, indicating that a favourable PA significantly enhances EI. Consequently, the null hypothesis is rejected.
Hypothesis H2a: The regression path coefficient for the direct effect of SN on EI was positive but not statistically significant (β = 0.258; SE = 0.182; 95% CI [−0.060, 0.660]; p = 0.103). This finding does not empirically support H2a, suggesting that SN does not significantly and directly influence EI. Therefore, the null hypothesis (H20) is accepted.
Hypothesis H3a: The direct effect of PBC on EI was found to be positive and statistically significant (β = 0.364; SE = 0.141; 95% CI [0.115, 0.669]; p = 0.004). This outcome supports H3a, confirming that higher levels of PBC significantly contribute to stronger EIs.
Discussion
This section discusses the study’s results concerning the influence of PA, SNs and PBC on EI among unemployed youth residing in a South African township. The findings are interpreted through the lens of the TPB and the existing scholarly literature, with attention given to both their theoretical contributions and their practical implications.
Personal attitude and entrepreneurial intention
The results revealed that PA had a positive and statistically significant direct influence on EI (β = 0.388; p = 0.023). This finding indicates that unemployed youth who perceive entrepreneurship favourably are more inclined to develop stronger intentions to establish their own ventures. This outcome supports the central proposition of the TPB, which asserts that a positive disposition towards a particular behaviour enhances the likelihood of intending to perform that behaviour (Ajzen 1991; Sibanda et al. 2020). The finding is also consistent with prior studies that identified PA as a crucial antecedent of EI (Liñán & Chen 2009; Urban 2010).
Similarly, Fatoki (2014) reported that South African students who regarded entrepreneurship as appealing and rewarding demonstrated higher EIs. This finding is significant in the context of unemployed township youth because it emphasises the need for interventions that cultivate positive attitudes towards entrepreneurship. These interventions could include entrepreneurship education, exposure to entrepreneurial role models and community programmes that showcase the benefits and opportunities of entrepreneurship.
Subjective norm and entrepreneurial intention
Contrary to expectations, the SN did not have a statistically significant effect on EI (β = 0.258; p = 0.103), although the norm was positively correlated. While the social pressures from family, friends and community members may influence youth in other contexts, the lack of a significant relationship in this study suggests that external social influences are less pivotal in shaping EIs among unemployed youth in the township.
This outcome is not unexpected as previous research has reported inconsistent findings regarding the influence of SNs on EI. For instance, Iakovleva et al. (2011) observed that in several developing economies, SNs exhibited either weak or statistically insignificant effects on individuals’ intentions to engage in entrepreneurship. This observation may be a result of several factors, including the socio-economic realities of the township environment, where individuals may prioritise personal agency and control over external influences when considering entrepreneurship (Sibanda et al. 2020).
The lack of significant influence from SNs could also indicate that societal expectations in this context do not strongly promote or discourage entrepreneurship. As a result, youth may rely more on their personal beliefs and perceived ability to control entrepreneurial outcomes rather than social approval or disapproval. This finding highlights a potential gap in community support structures for entrepreneurship, suggesting the need for more targeted efforts to foster a culture of entrepreneurship within township communities (Makwembere et al. 2024).
Perceived behavioural control and entrepreneurial intention
The analysis revealed that PBC exerted a positive and statistically significant direct influence on EI: β = 0.364; p = 0.004. This result, in turn, means that what is very important in developing EI among youth is their belief in their ability to perform the task, access resources and overcome challenges. This outcome is not surprising as, consistent with the TPB, people who perceive that they can do something and that they possess the necessary skills and resources for starting a business are more likely to develop EIs (Ajzen 1991). The leading role of PBC in predicting EI agrees with several other research studies across similar contexts. For instance, such studies as Krueger et al. (2000) and Fatoki (2014) reported that when people feel that they are in a position to control the entrepreneurial process and can, therefore, defeat the uncertainties related to the creation of a business, they develop a greater tendency towards entrepreneurship.
This finding represents a very important practical implication for entrepreneurship promotion efforts. In their efforts to enhance EI among unemployed township youth, policymakers and community leaders should give full attention to developing youths’ perceived control of entrepreneurial activities by providing training programmes that match the needs for development of entrepreneurial skills, mentorship, support services and resources such as startup capital and business networks (Makwembere et al. 2024). When youth in particular feel that the barriers to entrepreneurship are surmountable, they are more likely to take the first concrete steps towards entrepreneurship.
The findings affirm the TPB framework in the South African township context. The significance of PA and PBC suggests that internal motivation and confidence play essential roles in shaping EIs. The non-significance of the SN challenges assumptions about collectivist influence and points to weak entrepreneurial social cues in township settings (Iakovleva et al. 2011).
The study’s contribution lies in its contextual application of TPB, showing that control and attitudes outweigh social norms in influencing EI in disadvantaged areas.
Implications
The findings of this research add to the broader literature on EI by reaffirming the applicability of the TPB within a South African township context. The results highlight PA and PBC as key determinants of EI, whereas SN appears to play a comparatively weaker role in shaping entrepreneurial motivation among unemployed township youth.
The study provides context-specific insights into the applicability of TPB within a South African township, highlighting how socio-economic challenges may shape individuals’ perceptions of and responses to entrepreneurial opportunities. The significant role of PBC suggests that structural barriers, such as limited access to resources and skills, may be particularly salient in township environments, making self-efficacy and control crucial for EI.
Limitations and future research
The study was confined to one township and may have limited potential for generalisation to other contexts. Further research may extend the analysis into other townships and rural areas to explore what factors influence unemployment in the youths’ intention to be entrepreneurial. The study focused on a single township, limiting generalisability. Future research should consider multi-township or longitudinal approaches to assess change over time or comparative approaches across multiple provinces. The cross-sectional design precludes causal inference.
Conclusion and recommendations
In conclusion, this study underscores the critical role of PA and PBC in shaping EIs among unemployed youth in a South African township. While SN was not a significant predictor, enhancing attitudes towards entrepreneurship and empowering youth with the skills and resources they need to feel in control can significantly improve EI. These findings provide a roadmap for policymakers and community leaders aiming to cultivate entrepreneurship as a solution to youth unemployment in marginalised communities.
From a policy perspective, the findings highlight several important avenues for encouraging entrepreneurship among unemployed youth in South African townships. Educational programmes that foster positive attitudes towards entrepreneurship could be beneficial by presenting it as a viable career path. Integrating entrepreneurship education at the secondary and post-school levels may enhance these outcomes. Furthermore, establishing mentorship and incubation programmes, alongside policy reforms aimed at alleviating external constraints such as limited finance and entrepreneurial networks, could support youth entrepreneurship. Schools, community centres and training institutions may play a critical role in shaping youth perceptions and capacities for entrepreneurship.
Given the significant effect of PBC on EI, it is vital to implement initiatives that strengthen young people’s confidence in their capacity to establish and manage businesses. Interventions such as mentorship programmes, practical entrepreneurship training and workshops on business management can help enhance youths’ perceived competence and self-efficacy in entrepreneurial activities. Additionally, addressing structural constraints remains crucial. Policymakers should prioritise improving access to finance, essential resources and entrepreneurial support networks to enable aspiring young entrepreneurs to transition from intention to action.
Overall, the study concludes that EI among unemployed youth in Mdantsane Township is largely influenced by favourable PAs and a strong sense of PBC, underscoring the importance of both psychological and structural enablers in fostering youth entrepreneurship.
Acknowledgements
We thank the participants for taking part in the study.
Competing interests
The authors declare that they have no financial or personal relationships that may have inappropriately influenced them in writing this article.
CRediT authorship contribution
Obrain Tinashe Murire: Conceptualisation, Formal analysis, Methodology, Writing – original draft. Sandra Makwembere: Conceptualisation, Methodology, Writing – original draft, Writing – review & editing. Xabiso Ngabase: Data curation, Writing – original draft. Thobeka Ncanywa: Conceptualisation, Methodology, Writing – original draft, Writing – review & editing.
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.
Funding information
This research received no specific grant from any funding agency in the public, commercial or not-for-profit sectors.
Data availability
The data that support the findings of this study are available from the corresponding author, Obrain Tinashe Murire, upon reasonable request.
Disclaimer
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.
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Appendix 1
Demographic information
| TABLE 1-A1: Respondent demographic information (N = 248). |
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