From optimism to action: navigating Generation Z's technopreneurial engagement with drop shipping in South Africa

In today's postmodern era, technological optimism has become a vital lens through which societies and individuals navigate rapid digital transformation and entrepreneurial endeavours (Maziriri et al., 2025). It reflects a belief in technology's empowering capacity to enhance human agency, efficiency, and creativity (Peschl, 2024). For Generation Z, who are digital natives, such optimism not only nurtures curiosity and enjoyment but also translates into tangible behavioural intentions, such as adopting innovative business models like drop shipping (Atmaja et al., 2024). Scholars argue that technology optimism moderates the critical relationships between perceived value and satisfaction, enabling users to embrace emerging technologies, such as VR tourism or digital commerce, with greater enthusiasm (Zhu et al., 2025). In fields such as healthcare and education, optimism towards technology has been shown to strengthen trust and increase willingness to adopt digital solutions, even during crises (Bayuo, 2024; Aasvik et al., 2025). Furthermore, the philosophy of technology emphasises that optimism extends beyond mere functional utility; it reflects a worldview in which technology is an integral partner in human development rather than a disruptive threat (Bayuo, 2024). This aligns with eco-modernist perspectives that position technological innovation as a cornerstone for sustainable growth and societal resilience (Javed et al., 2025). Thus, in the context of technopreneurship and drop-shipping adoption, technological optimism is not merely an attitude but a driver of entrepreneurial intention, equipping Gen Z to view digital disruptions as opportunities for innovative participation in the global economy.

Existing international literature consistently demonstrates that technological optimism plays an important role in shaping perceptions of technology and behavioural outcomes across diverse contexts. Prior studies have shown that technological optimism enhances technology adoption intentions, strengthens perceptions of value and trust, and positively influences user engagement and behavioural responses in areas such as healthcare technologies, autonomous transportation systems, virtual reality environments, workplace technologies, and human-centred innovation practices (Atmaja et al., 2024; Aasvik et al., 2025; Manresa et al., 2024; Bayuo, 2024; Zhu et al., 2025). Collectively, these studies suggest that individuals with greater technological optimism are more likely to embrace technological innovations and translate positive perceptions into behavioural actions. Despite this growing body of international evidence, limited empirical research has examined the influence of technological optimism on Gen Z's technopreneurial behaviour in the South African context, particularly regarding engagement with drop shipping as a digital entrepreneurial model. Consequently, there remains a contextual and empirical gap that warrants investigation through a model grounded in the Theory of Planned Behaviour (TPB), Traditional Behavioural Reasoning Model (TBRM), and Hedonic Motivation Theory.

International studies have increasingly highlighted the importance of technological optimism in shaping technology adoption behaviours across diverse digital environments. Existing evidence suggests that technological optimism enhances users' trust, perceptions of value, engagement, and behavioural intentions across contexts such as healthcare technologies, autonomous transportation systems, virtual reality environments, workplace technologies, and human-centred innovation practices (Atmaja et al., 2024; Aasvik et al., 2025; Bayuo, 2024; Manresa et al., 2024; Zhu et al., 2025). However, much of this evidence is derived from Asian and Western contexts characterised by relatively advanced technological ecosystems. Consequently, the direct application of these findings to the South African context remains challenging due to the country's distinct socio-economic conditions, digital landscape, and entrepreneurial environment. Within South Africa, existing research has largely focused on technological readiness, technology acceptance, and psychological barriers associated with organisational technology adoption. Although these studies underscore the importance of factors such as optimism, trust, and readiness in facilitating digital adoption, they have not specifically examined drop shipping as a technopreneurial business model. Furthermore, while recent studies suggest that technological optimism may influence entrepreneurial intentions among Generation Z students, limited empirical evidence exists regarding its influence on attitudes, behavioural intentions, and the actual use of drop shipping as a business model within the South African context. Furthermore, the role of perceived enjoyment in strengthening the relationship between intention and use remains poorly understood. Enjoyment is a significant driver of digital engagement, and its interaction with optimism could be crucial in translating entrepreneurial intentions into tangible technopreneurial behaviours. Closing this gap is crucial for a deeper understanding of how technological optimism affects the adoption of drop shipping in South Africa.

Hence, drawing on these prevailing gaps, this paper responds to the apparent need for enhanced understanding of the relationships linking technological optimism, perceived enjoyment, attitudes, intentions, and the actual use of drop shipping among Generation Z by setting out six key research questions (RQ):

The study makes five pivotal contributions. Firstly, while existing research has explored the role of technological optimism in various contexts such as VR tourism in China (Zhu et al., 2025), telemedicine in Indonesia (Atmaja et al., 2024), autonomous shuttles in Norway (Aasvik et al., 2025), and generative AI in Spain (Manresa et al., 2024), limited attention has been given to its impact on entrepreneurial behaviours in South Africa. This paper contributes to the literature by investigating technological optimism as a determinant of attitudes, intentions, and actual use of drop shipping as a business model, thereby expanding the application of technology-related concepts in a developing-country context.

Secondly, this study responds to calls for more Africa-centred research on technology adoption and entrepreneurial behaviour (Urban and Galawe, 2020; Khoza et al., 2024; Noriega Del Valle et al., 2024). By focussing on Generation Z students in South Africa, it challenges the uncritical transferability of Western-based research findings, thus contextualising technopreneurial behaviour within a setting marked by socio-economic disparities, digital divides, and entrepreneurial necessity.

Thirdly, the study advances theory by integrating the theory of planned behaviour (TPB), the traditional behavioural reasoning model (TBRM), and hedonic motivation theory, and enriches these theories by incorporating the moderating effect of perceived enjoyment on the relationship between intention and actual use. The TPB explains behavioural intention as a function of attitudes, subjective norms, and perceived behavioural control, offering a predictive framework for intentional action (Ajzen, 1991). However, the TPB deliberately does not clarify the cognitive processes by which individuals generate and justify their beliefs about the underlying constructs. The TBRM addresses this limitation by explicitly theorising the reasons for and reasons against behaviour as central explanatory mechanisms (Westaby, 2005). These logical reasons capture individuals' justifications, values and contextual rationales, particularly in situations involving competing goals or moral trade-offs. In the current study, we integrate TBP and TBRM by positioning behavioural reasons as antecedents that inform and shape TPB's attitudinal and control beliefs. In doing so, TBRM shows the cognitive content of belief formation, while TPB explains how these beliefs are organised into motivational determinants of intention. This integration allows for a more comprehensive explanation of intentional behaviour without compromising TPB's structural parsimony. This combined framework highlights not only cognitive antecedents of entrepreneurial behaviour but also the emotional mechanisms that catalyse the translation of intention into practice, thereby deepening theoretical understanding of technopreneurship.

Fourthly, the study contributes to sectoral knowledge by focussing on drop shipping, a rapidly growing e-commerce model that is highly relevant to youth entrepreneurship in South Africa. While previous local research has explored technology acceptance in organisational settings (Khoza et al., 2024; Patel and Ragolane, 2024), few have considered how specific digital business models shape entrepreneurial outcomes among students. By situating drop shipping within the broader discourse of technopreneurship, the study offers contextual specificity and practical relevance.

Lastly, this research provides actionable insights for educators, policymakers, and practitioners. By demonstrating the role of technological optimism and perceived enjoyment in fostering entrepreneurial adoption, the study equips higher education institutions, entrepreneurship development agencies, and innovation policymakers with evidence-based strategies to nurture Gen Z technopreneurs. These findings can guide curriculum reforms, training initiatives, and digital incubation programmes to equip students with the mindset and motivation to translate intentions into viable online businesses.

The remainder of this paper is structured as follows: firstly, we examine the relevant theoretical foundations to provide a basis for the hypotheses. Next, the research design is clarified with respect to sampling and measurement issues, and thereafter, the statistical analyses of the data are presented. Next, the paper discusses its findings and provides several theoretical and managerial implications. Lastly, the limitations and future research directions are provided.

This section provides the theoretical foundation necessary for empirical research. The study is based on the theory of planned behaviour (TPB), the traditional behavioural reasoning model (TBRM), and the hedonic motivation theory, which are chosen as the most appropriate frameworks for this research and are explained in detail to justify their selection. This theoretical overview also helps in developing hypotheses for the study, which will be discussed in the following sections.

The theory of planned behaviour (TPB), proposed by Ajzen (1985), describes human actions as influenced by behavioural intentions, attitudes, and perceived control. Goh et al. (2017) describe the TPB as a rational decision-making tool that utilises three key variables: individuals' attitudes towards a behaviour, their perceptions of social influences, and their perceived control over the behaviour, to predict intentions. Raygor (2016) notes that the TPB accounts for motivational factors in specific contexts to explain why certain behaviours are enacted, while Ajzen (2015) emphasises that its goal is to provide a comprehensive framework for understanding the determinants of consumer behavioural intentions.

In this study, TPB is particularly relevant because several of its constructs are directly involved in formulating hypotheses. For instance, the research investigates whether technological optimism affects Gen Z students' attitudes toward adopting drop shipping as a business model and whether these attitudes, in turn, significantly influence their intention to engage in drop shipping. Additionally, Wong et al. (2018) highlight that the TPB's predictive power can be improved by incorporating additional variables. This approach is increasingly evident in recent research, where scholars have expanded the TPB framework by adding new constructs (Jang et al., 2015; Maichum et al., 2016; Read et al., 2013).

Although widely used to examine behavioural intentions, the TPB has been criticised for frequently neglecting domain-specific factors (Armitage and Conner, 2001; Donald et al., 2014). To address this issue, researchers have increasingly worked to extend the model by adding extra constructs (Jang et al., 2015; Maichum et al., 2016; Read et al., 2013). This study adopts this approach by including variables such as technological optimism and perceived enjoyment, alongside traditional TPB constructs such as behavioural intention, attitude towards behaviour, and actual behaviour. In doing so, the research aims to provide a more comprehensive understanding of the factors influencing Gen Z's adoption of drop shipping, while capturing the distinctive traits and entrepreneurial tendencies of this generation.

The second theory utilised in this study is the Traditional Behavioural Reasoning Model (TBRM), which offers a structured approach to understanding decision-making by examining cognitive, emotional, and situational factors (Hammond, 1996). TBRM focuses on evaluating options based on both intrinsic and extrinsic considerations and perceiving opportunities through a cognitive assessment of available information (Hammond, 1996). Applying TBRM to the adoption of drop shipping among Gen Z entrepreneurs provides valuable insights into their motivations and decision-making processes (Hammond, 1996; Westaby, 2005). This model connects cognitive and emotional factors to predict behavioural intentions and actions, offering a comprehensive view of Gen Z's engagement in technopreneurship in the digital age (Hammond, 1996).

In line with the Traditional Behavioural Reasoning Model (TBRM), this study examines how Gen Z entrepreneurs' cognitive assessments and emotional responses influence their decision to adopt drop shipping as a business model. A crucial element in this decision-making process is technological optimism, which holds that technology can yield positive outcomes and serves as a valuable tool for achieving personal and professional goals. Technological optimism has been identified as a significant driver of Gen Z's entrepreneurial endeavours, particularly in the digital realm (Maziriri et al., 2025; Vu et al., 2024). This optimistic perspective on technology motivates Gen Z individuals to adopt innovative business models, such as dropshipping, that leverage digital platforms and tools to facilitate e-commerce (Menaouer, 2021).

Furthermore, the ease of technology and Gen Z's interest in digital entrepreneurship exemplify a broader trend in which younger generations are more willing to take financial risks to establish their own businesses (Jones, 2023; Trisno, 2025). Their digital proficiency gives them a competitive edge in launching and succeeding in ventures compared with previous generations. Their optimistic view of technology not only drives their entrepreneurial aspirations but also guides their actions, motivating them to actively seek out and engage in digital business opportunities, such as drop shipping (Ardelean, 2021; Steininger, 2022). Therefore, integrating technological optimism into the TBRM framework enhances our understanding of how Gen Z entrepreneurs' positive attitudes toward technology influence their decision-making and behaviours when embracing drop shipping as a business model (Hammond, 1996; Westaby, 2005).

Hedonic Motivation Theory originates from early work in psychology and information systems that sought to explain behaviour driven by intrinsic pleasure rather than purely utilitarian outcomes. It was formally pioneered in the technology adoption literature through the Hedonic-Motivation System Adoption Model (HMSAM) developed by Lowry et al. (2013). These scholars argued that many contemporary digital systems are adopted for their enjoyment, engagement, and immersion, rather than solely for their productivity-enhancing capabilities. They conceptualised hedonic motivation as the degree of pleasure and enjoyment derived from system use, which stimulates cognitive absorption and sustained engagement. Building on this foundation, later theorists, most notably Venkatesh et al. (2012), integrated hedonic motivation into UTAUT2, defining it as the fun or pleasure associated with using technology and empirically demonstrating its strong influence on behavioural intention and actual use, particularly among younger and digitally fluent cohorts. In the post-modern digital economy, characterised by platformization, gamification, and experience-centric technologies, hedonic motivation has been extensively examined by contemporary scholars across Emerald, Elsevier, and SAGE journals, who consistently show that perceived enjoyment functions as a critical affective driver of technology adoption, continuance, and entrepreneurial engagement (Tamilmani et al., 2019; Nambisan, 2017; Shanmugavel, 2023). Recent studies further demonstrate that hedonic motivation is especially salient for Generation Z users, whose technology use is strongly shaped by experiential value, enjoyment, and emotional engagement rather than purely instrumental considerations (Foroughi et al., 2025; Thangavel and Chandra, 2024). This theory is highly relevant to the present study, which empirically examines the relationships between technological optimism, perceived enjoyment, attitudes, intentions, and the actual use of drop shipping among Generation Z. Anchored in the Theory of Planned Behaviour (TPB) and the Traditional Behavioural Reasoning Model (TBRM), the study positions perceived enjoyment as a hedonic mechanism that strengthens the translation of intention into behaviour, thereby addressing the well-documented intention–behaviour gap in digital entrepreneurship research. When combined, Hedonic Motivation Theory complements TPB's cognitive pathway from attitudes to intentions and TBRM's emphasis on reasons for and against behaviour by introducing an affective–experiential lens that explains why technologically optimistic Gen Z individuals are more likely to enact, rather than merely intend, technopreneurial behaviour such as drop shipping within the South African context.

The conceptual model of this study is based on three influential frameworks: The Theory of Planned Behaviour (TPB), the Traditional Behavioural Reasoning Model (TBRM), and hedonic motivation theory. This model illustrates how technological optimism influences attitudes toward drop shipping, which in turn affects the intention to use it. These intentions, in turn, predict the actual adoption of drop shipping. In addition, the perceived enjoyment of drop shipping serves a dual role: it directly influences attitudes and intentions, and it also moderates the relationship between intention and actual use. Essentially, when individuals perceive drop shipping as more enjoyable, the link between their intention and their adoption of drop shipping strengthens. Figure 1 illustrates the conceptual model, outlining the connections between the variables under investigation. Subsequently, the study's hypotheses will be developed in the following sections.

Technological optimism refers to an individual's belief that technological advancements can improve efficiency, create opportunities, and generate beneficial outcomes in personal and business environments (Serras et al., 2024). Existing scholarship generally suggests that individuals exhibiting high levels of technological optimism tend to develop favourable evaluations of technology-enabled innovations because they perceive technological systems as useful and capable of solving business challenges (Zhou et al., 2023). However, prior studies have largely focused on conventional technology adoption contexts, such as online banking, e-commerce systems, and mobile applications, with limited attention to digital entrepreneurial models such as drop shipping. This raises questions about whether the positive effects of technological optimism observed in technology-use settings can be directly extended to entrepreneurial contexts, where business uncertainty and risk are more pronounced.

Although studies by Venkatesh et al. (2012) and Alalwan et al. (2017) indicate that technologically optimistic individuals are more receptive to emerging digital systems due to perceived advantages such as efficiency, automation, and ease of use, these studies predominantly focus on technology acceptance behaviour rather than entrepreneurial engagement. In contrast, entrepreneurial contexts involve additional considerations such as financial uncertainty, market competition, and operational dependencies that may alter how optimism shapes attitudes. Thus, while technological optimism may encourage individuals to perceive drop shipping as a scalable and cost-effective business model due to its low barriers to entry and reliance on digital infrastructure, such positive perceptions may not necessarily translate into universally favourable attitudes.

Furthermore, prior literature presents mixed perspectives regarding the implications of technological optimism. Some scholars argue that optimism promotes stronger confidence in digital systems and lowers perceived barriers to adoption (Dwivedi et al., 2021). Conversely, excessive technological optimism may result in unrealistic expectations and an underestimation of risks associated with online business activities, including privacy concerns, supplier unreliability, and technological failures (Kim and Hall, 2019). Within the drop shipping context, where entrepreneurs depend heavily on external digital platforms and third-party suppliers, such risks may challenge the assumption that technology alone guarantees business success. Therefore, the relationship between technological optimism and attitudes towards drop shipping may be more nuanced than existing literature suggests. Given these contrasting perspectives, there remains a need to understand whether technological optimism consistently contributes to favourable attitudes toward drop shipping among Generation Z entrepreneurs. Accordingly, the following hypothesis is proposed:

Attitudes, defined as individuals' favourable or unfavourable evaluations of a particular behaviour or innovation (Claudy et al., 2015; Fishbein and Ajzen, 1975), occupy a central position within the Theory of Planned Behaviour (TPB), where they are regarded as key determinants of behavioural intentions (Fishbein and Ajzen, 1975). Existing literature generally supports the proposition that positive attitudes increase an individual's likelihood of engaging in a specific behaviour. Empirical evidence has consistently demonstrated this relationship across a range of technology-related contexts, including food delivery applications (Tandon et al., 2021), mobile payment systems (Wang et al., 2022), and educational technologies (Al-Sharhan et al., 2023). Such findings suggest that individuals who perceive technologies positively are more inclined to develop intentions to adopt or use them.

However, much of this evidence has emerged from technology adoption contexts where individuals primarily assume the role of users or consumers rather than entrepreneurs. This distinction is important because broader considerations beyond technology evaluations alone shape entrepreneurial intentions. Unlike technology adoption decisions, entrepreneurial engagement involves uncertainty, financial risks, resource constraints, and long-term commitment. Consequently, although positive attitudes may encourage behavioural intentions, their influence within entrepreneurial contexts may not be as straightforward as existing studies imply.

Within the technopreneurship literature, studies have similarly identified attitudes as important antecedents of entrepreneurial intentions. For example, Maziriri et al. (2024) reported a significant positive relationship between technopreneurial attitudes and entrepreneurial career intentions, while Soomro and Shah (2021), Nurhayati and Machmud (2019), and Oladejo et al. (2022) observed comparable patterns across different settings. Nevertheless, these studies predominantly focus on general entrepreneurial or technopreneurial intentions rather than specifically examining digital business models such as dropshipping. The distinctive characteristics of drop shipping, including reliance on online platforms, third-party suppliers, and digitally mediated transactions, may introduce contextual dynamics that alter the extent to which attitudes influence behavioural intentions.

Furthermore, previous studies have often assumed a direct and uniformly positive relationship between attitudes and intentions, with limited consideration of contextual moderators or competing influences. Positive attitudes toward drop shipping may not necessarily lead to stronger entrepreneurial intentions if individuals simultaneously perceive concerns about market saturation, supplier reliability, or business sustainability. Therefore, while prior literature provides substantial support for the attitude–intention relationship, the applicability of these findings to the drop shipping context remains underexplored. Given these observations, further investigation is required to determine whether favourable attitudes toward drop shipping significantly influence intentions to engage in this form of technopreneurship. Based on the above discussion, the following hypothesis is posited:

Understanding the relationship between intention and actual use is essential in evaluating the adoption of drop shipping as a technopreneurial business model. While limited studies have directly examined this relationship within the drop shipping context, evidence from related technology and entrepreneurship domains consistently supports the link between behavioural intention and actual behaviour. For instance, Melián-González et al. (2021) found that intentions significantly predicted technology adoption behaviour, while Kim and Hall (2019) demonstrated a positive and statistically significant relationship between behavioural intention and virtual reality use. Similarly, within online retail environments, Palmer et al. (2020) reported that stronger intentions, supported by digital capabilities and strategic planning, translated into actual implementation of e-commerce activities.

Within entrepreneurship research, intention extends beyond mere motivation and serves as an indicator of an individual's readiness and commitment to engage in entrepreneurial activities such as launching digital platforms and managing supply chains (Davidson, 2015). The Theory of Planned Behaviour proposes that behavioural intentions are immediate antecedents of actual behaviour, suggesting that individuals with stronger intentions are more likely to perform the intended action (Ajzen, 1991). However, scholars also argue that intentions alone may not always lead to behaviour due to intervening barriers such as resource constraints, technological challenges, and limited entrepreneurial capabilities. Nevertheless, in digital entrepreneurship contexts such as dropshipping, individuals with stronger intentions are likely to exhibit greater persistence and a greater willingness to overcome these challenges, increasing the probability of actual engagement with the business model. Therefore, stronger intentions toward adopting drop shipping are expected to positively influence actual use. Based on the preceding discussion, the following hypothesis is formulated:

Perceived enjoyment, defined as the extent to which engaging in an activity is perceived as pleasurable and enjoyable in its own right, has been widely recognised as an important determinant of users' attitudes towards technology adoption (Scherer et al., 2019). Existing studies consistently indicate that users who derive enjoyment from interacting with technologies such as mobile services, e-commerce platforms, and online learning systems tend to develop more favourable attitudes towards these technologies (Huang et al., 2019; Kim and Forsythe, 2021; Zhao et al., 2023). Such findings suggest that enjoyment acts as an intrinsic motivator that enhances users' evaluations and perceptions of technological systems.

The relationship between perceived enjoyment and attitudes is further supported by behavioural theories, particularly the Theory of Planned Behaviour and technology acceptance literature, which posit that positive experiences influence individuals' evaluative judgements toward a particular behaviour or technology (Ajzen, 1991; Venkatesh, 2000). However, some scholars argue that the influence of enjoyment on attitudes may vary depending on contextual factors such as technological complexity, perceived usefulness, and users' prior experience. Despite these considerations, in digital entrepreneurial contexts, intrinsic enjoyment often plays a significant role because entrepreneurial activities increasingly involve interactive digital environments that shape user experiences.

Within the context of drop shipping, perceived enjoyment may arise from the flexibility of operating an online business, interacting with digital platforms, monitoring customer engagement, and managing transactions without the burden of inventory ownership. The convenience and interactive nature of these activities may generate positive experiences that influence entrepreneurs' evaluations of the business model. Consequently, individuals who perceive greater enjoyment from engaging with drop-shipping activities are likely to develop more favourable attitudes towards adopting this technopreneurship model. Guided by the preceding theoretical and empirical evidence, the following hypothesis is formulated:

Perceived enjoyment has been widely recognised as an important determinant of individuals' intentions to adopt technological innovations (Maziriri et al., 2023). Existing literature suggests that individuals are more likely to develop intentions to use a technology when the interaction itself generates positive experiences and intrinsic satisfaction. This relationship has been consistently observed across various technological contexts, including e-commerce platforms, mobile applications, and online learning environments (Lee, 2019; Ertz et al., 2020; Kim and Hall, 2019).

Technology adoption literature further proposes that intrinsic motivational factors, such as enjoyment, influence behavioural intentions because enjoyable experiences create positive perceptions and reduce psychological resistance to using a system (Davis and Venkatesh, 1996). Empirical studies have also demonstrated that perceived enjoyment positively influences individuals' willingness to participate in online transactions and entrepreneurial activities (Chiu et al., 2021; Huang and Benyoucef, 2013). However, some scholars argue that the strength of this relationship may vary with contextual factors such as users' prior experience, perceived usefulness, and technological capabilities.

Within the context of drop shipping, perceived enjoyment may emerge from the flexibility and interactive nature of managing online business activities, including monitoring customer engagement, selecting products, customising digital storefronts, and operating without the burden of inventory ownership. Features such as user-friendly platforms, reduced start-up risk, and opportunities for experimentation may generate positive experiences that strengthen individuals' intentions to engage with the business model. Consequently, individuals who perceive drop shipping as enjoyable are more likely to develop stronger intentions to adopt it as a technopreneurial business model. Drawing upon the above arguments, the following hypothesis is advanced:

The Theory of Planned Behaviour proposes that behavioural intention is the most immediate predictor of actual behaviour (Ajzen, 1991). However, research indicates that intentions do not always translate directly into behaviour, a phenomenon commonly referred to as the intention–behaviour gap (Sheeran and Webb, 2016). Scholars argue that this gap may arise because various contextual and psychological factors influence the extent to which intended actions are eventually enacted. Consequently, researchers have increasingly examined moderating variables that strengthen or weaken the relationship between intention and actual behaviour.

One factor that may influence this relationship is perceived enjoyment, defined as the intrinsic pleasure derived from engaging in an activity independent of its functional outcomes (Davis et al., 1992; Van der Heijden, 2004). Existing studies suggest that perceived enjoyment strengthens behavioural enactment because enjoyable experiences increase intrinsic motivation, cognitive engagement, and sustained interaction with technological systems (Venkatesh et al., 2003; Yi and Hwang, 2023). Individuals who derive enjoyment from a technological activity are more likely to remain engaged and invest greater effort in translating their intentions into actual behaviour.

In the context of technopreneurship and drop shipping, perceived enjoyment may be particularly relevant given the interactive and flexible nature of digital entrepreneurial activities. Managing online storefronts, utilising automation tools, analysing customer interactions, and implementing digital marketing strategies may create enjoyable experiences for technology-oriented entrepreneurs. Such enjoyment can foster cognitive absorption and greater task involvement, thereby increasing the likelihood that intentions evolve into sustained entrepreneurial actions (Agarwal and Karahanna, 2000; Moon and Kim, 2001; Childers et al., 2001). From the perspective of innovation diffusion theory, technology adoption is influenced not only by functional benefits but also by experiential factors that shape users' engagement with technological innovations (Rogers, 2003). Therefore, higher levels of perceived enjoyment may strengthen the extent to which intentions toward drop shipping are translated into actual use behaviour. In light of the foregoing discussion, the following hypothesis is proposed:

This study is based on positivist philosophy, which holds that phenomena can be understood through the collection and analysis of quantifiable data to produce verifiable results (Dzomonda and Neneh, 2023; Saunders et al., 2019). Positivism promotes objectivity and the generalisation of findings (Bell et al., 2022; Saunders et al., 2019). A quantitative approach was used, emphasising the collection and analysis of numerical data to explore the research problem (Bell et al., 2022). A causal research design was chosen to investigate the relationships among technological optimism, attitudes, intentions, and actual drop-shipping use, with perceived enjoyment serving as a moderating variable. This approach is appropriate because it prioritises objectivity and allows insights to be derived from a structured survey through detailed statistical analysis (Taherdoost, 2022).

This study focused on Generation Z students at the University of the Western Cape in Bellville, South Africa's Western Cape Province, and the University of the Witwatersrand in Johannesburg, Gauteng Province. The selection of students aligns with standard practices in entrepreneurial research, which often involve student samples in various contexts (Neneh and Dzomonda, 2024; Gieure et al., 2020; Kong et al., 2020; Syed et al., 2020). University students were chosen because they are more likely to be interested in and engage in technopreneurial activities, such as drop shipping (Neneh and Dzomonda, 2024; Cui and Bell, 2022; Maheshwari et al., 2023). University students, particularly Generation Z, are an appropriate population for examining technopreneurial behaviour in South Africa, as they are digital natives with high exposure to and competence in technology-enabled business models such as dropshipping (Prensky, 2001; Vial, 2019). Intention-based frameworks, including the Theory of Planned Behaviour, support the use of students as subjects, given that entrepreneurial intentions formed during university years are strong predictors of subsequent entrepreneurial action (Ajzen, 1991; Krueger et al., 2000). In an emerging economy characterised by high youth unemployment, South African universities serve as key incubators for digital entrepreneurship, with many students actively engaging in low-entry online ventures while studying. Consequently, students provide a valid and contextually relevant proxy for understanding early-stage technopreneurial engagement.

The population size of Generation Z students at the aforementioned universities was crucial for probability sampling. The University of the Western Cape has approximately 23,000 students, while the University of the Witwatersrand has 40,722, for a total of 63,722 students. The researcher aimed to have 382 survey participants. The sample size was determined using the Raosoft calculator, based on an estimated total student population of approximately 60,295 across both universities. With a 5% margin of error, a 95% confidence level, and a 50% response distribution, the minimum required sample size was 382. Ultimately, data were collected from 359 participants, resulting in a response rate of 93.98%.

Given that the sampling frame of registered students at the participating universities was accessible, a probability-based approach was adopted to enhance the generalisability of the findings. Specifically, simple random sampling was employed as the primary sampling technique, ensuring that each eligible student had an equal and known probability of selection and thereby reducing systematic selection bias (Bryman, 2016; Saunders et al., 2019). This approach is widely recommended in quantitative behavioural research where population lists are available and inferential statistical analysis is intended.

In addition, quota sampling was incorporated as a complementary strategy to ensure adequate representation of the focal subpopulation central to the study, namely Generation Z. Quotas were defined using age-based criteria, targeting individuals born between 1995 and 2009 (aged 18–29), consistent with established generational classifications (Goh and Lee, 2018). The use of quota sampling alongside random selection has been endorsed in prior entrepreneurship and technology adoption studies to prevent over- or under-representation of theoretically important demographic groups while retaining the benefits of probability sampling (Hair et al., 2017; Etikan et al., 2016).

The integration of probability and non-probability sampling techniques reflects a pragmatic mixed sampling strategy that has been increasingly adopted in social science and entrepreneurship research, particularly in higher education contexts (Saunders et al., 2019; Creswell and Plano Clark, 2018). Such approaches enable researchers to balance methodological rigour with contextual and theoretical relevance, especially when investigating generational cohorts or digitally engaged populations (Liñán and Fayolle, 2015; Sarstedt et al., 2022). Accordingly, the mixed sampling strategy employed in this study ensured both representativeness and alignment with the study's theoretical focus on Generation Z technopreneurial behaviour.

Data collection was conducted via an online questionnaire, emphasising precise measurement of both the intention to use and the actual use of drop shipping. The primary survey data were collected in two phases. The first survey, covering variables related to the intention to use drop shipping, was distributed between March and April 2025. Participants provided insights into technological optimism, attitudes towards drop shipping, and their intention to use it. Subsequently, the same participants were followed up with a second questionnaire between late April and early May 2025, focussing on their actual use of drop shipping. This approach aligns with previous research (Tao, 2009; Bhattacherjee et al., 2012; Chopdar and Sivakumar, 2019) that collected data at two time points: intention at t¹ and actual use at t^2. employing this two-time-point method is essential for establishing causality (Maier et al., 2023). The following section is centred on the respondents' demographic profile.

The demographic profile of the Generation Z students who participated in this study reflects a diverse yet representative sample within the South African higher education context. Of the 359 respondents, 44% were from the University of the Western Cape and 56% from the University of the Witwatersrand, indicating broad institutional representation across the two universities. The majority of participants were aged 18–22 years, consistent with the Generation Z cohort, with the largest group being 18-year-olds (19%). The gender distribution was fairly balanced, with 47% male, 50% female, and 3% preferring not to disclose their gender. In terms of academic standing, students were distributed across all levels, with 31% in the first year, 21% in the second year, 24% in the third year, and 24% at the postgraduate level. Monthly allowances varied, with the largest groups receiving between R1,501 and R2,000 (29%) or more than R2,000 (26%), while smaller groups reported receiving less financial support. Ethnically, African students constituted the largest segment (47%), followed by Coloured (22%), Indian (16%), White (13%), and other groups (2%). The demographic characteristics of the respondents are presented in Table 1.

To facilitate data collection, the study began by adapting and validating the measurement items. Established and previously validated scales were consulted to ensure consistency and comparability with prior research (Boudreau et al., 2001). The constructs examined in this study were drawn from the extant literature and refined to align with the context of student technopreneurship. Table 2 outlines the measurement scales, corresponding items, original sources, and Cronbach's alpha coefficients for each construct. All items were measured using a five-point Likert scale ranging from strongly disagree (1) to strongly agree (5).

This study was approved by the Humanities and Social Sciences Research Ethics Committee (HSSREC) at the University of the Western Cape, South Africa (Reference Number: HS24/10/34). All participants were informed about the purpose of the research, their rights to voluntary participation, and the confidentiality policy. Informed consent was obtained from each participant prior to participation. No personal identifiers were collected, and data were used exclusively for academic purposes.

Partial Least Squares Structural Equation Modelling (PLS-SEM), implemented using SmartPLS 4 software, was employed in this study due to its suitability for analysing complex research models derived from survey data and its robustness with small-to-medium sample sizes. PLS-SEM is particularly well aligned with prediction-oriented research objectives (Sarstedt et al., 2020a, b; Shmueli et al., 2019), making it appropriate for examining the hypothesised relationships among technological optimism, perceived enjoyment, attitudes, intentions, and the actual use of drop shipping among Generation Z in an emerging economy context.

In contrast to covariance-based SEM (CB-SEM), which is primarily confirmatory and focused on theory testing and model fit, PLS-SEM emphasises maximising explained variance (R²) and predictive accuracy of endogenous constructs (Hair et al., 2022). This distinction is especially relevant for the present study, which seeks to explain and predict behavioural outcomes rather than to validate an established theory in a strictly confirmatory manner. Furthermore, PLS-SEM imposes fewer distributional assumptions, performs well with non-normal data, and is more tolerant of complex models with multiple constructs and indicators (Hair et al., 2019; Chin, 1998). Given the exploratory nature of the research context, the inclusion of multiple latent variables, and the study's focus on prediction and behavioural explanation in an emerging market setting, PLS-SEM was deemed methodologically more appropriate than CB-SEM.

Convergence validity is evaluated using factor loadings, composite reliability (CR) and average variance extracted (AVE) (Hair et al., 2019). The construct CR values are larger than 0.7, all item loadings exceed the recommended value of 0.5, and AVE values exceed the threshold value of 0.5, as shown in Table 3 (Byrne, 2013; Hair et al., 2019; Ting et al., 2019; Nunnally and Bernstein, 1994). Therefore, convergent validity was established.

In response to concerns about the high Composite Reliability (CR = 0.957) and potential item redundancy within the Intention to Use Drop Shipping construct, an inter-item correlation assessment was conducted. Inter-item correlations provide an additional means of evaluating whether scale items measure the same underlying construct while maintaining sufficient conceptual distinctiveness. According to Clark and Watson (1995), inter-item correlations ranging from 0.15 to 0.85 are generally considered acceptable, whereas excessively high correlations may indicate redundancy among indicators.

The results presented in Table 4 demonstrate that the inter-item correlations for the Intention to Use Drop Shipping construct ranged from 0.581 to 0.792. Although the correlations indicate strong relationships among the indicators, none exceeded the recommended threshold of 0.85. This suggests that while the items consistently capture the underlying concept of intention towards drop shipping, they remain sufficiently distinct and do not exhibit problematic overlap. Consequently, the high Composite Reliability value appears to reflect strong internal consistency rather than item redundancy.

The findings indicate that the construct demonstrates strong internal consistency, with no evidence of excessive item duplication. Therefore, the high reliability of the Intention to Use Drop Shipping scale can be interpreted as a robust measure of the construct rather than as problematic item redundancy.

Discriminant validity was assessed using the heterotrait and monotrait (HTMT) ratio of the correction technique on the complete data set (Henseler et al., 2015; Ting et al., 2019). As shown in Table 5, the discriminant values do not violate the threshold of 0.85 (Henseler et al., 2015), indicating no multicollinearity among the construct items.

In PLS-SEM, common method bias (CMB) is detected using a full collinearity assessment (Kock, 2015). Variance inflation factor (VIF) values should be below the 3.3 threshold (Hair et al., 2011; Kock, 2015). This is indicative that the model is free from common method bias. Any value greater than 3.3 means the model is affected by CMB. Therefore, in line with standard procedures in business research, VIF values were computed rather than reporting collinearity issues in this work. As shown in Table 3, multicollinearity was evaluated using VIFs, and the results indicated that all constructs had VIFs below 3.3 (Kock and Lynn, 2012). The outcome thus supported the notion that CMB does not seem to be a problem in the investigation.

To assess potential non-response bias, the study compared early and late respondents on key demographic variables and core constructs, following the wave analysis approach commonly recommended in survey-based behavioural research (Armstrong and Overton, 1977; Rogelberg and Stanton, 2007). The comparison revealed no statistically significant differences between early and late respondents, suggesting that non-response bias is unlikely to affect the study's results. This approach assumes that late respondents resemble non-respondents, and is widely accepted as a practical diagnostic technique when direct data from non-respondents are unavailable (Lindner et al., 2001; Saunders et al., 2019). In addition, the achieved response rate of 93.98% substantially exceeds the minimum thresholds commonly regarded as acceptable in behavioural and social science research, thereby further reducing concerns about systematic non-response effects and enhancing confidence in the representativeness and validity of the findings (Baruch and Holtom, 2008; Hair et al., 2022).

Although this study adopted a two-wave data collection approach, with predictor measures collected at T1 and actual use collected at T2, additional diagnostic procedures were conducted to address concerns about common method bias (CMB). Common method bias may arise when variance is attributable to the measurement method rather than to the constructs being measured, particularly in self-reported survey research (Podsakoff et al., 2003). Therefore, following the recommendations of Podsakoff et al. (2012), Kock (2015), and Hair et al. (2022), this study assessed CMB using both a random variable test and inner VIF scores.

First, a random marker variable test was conducted by incorporating a theoretically unrelated construct into the PLS-SEM model. Following recommendations by Podsakoff et al. (2003) and Lindell and Whitney (2001), a marker variable should be conceptually distinct from the focal constructs and should not exhibit meaningful relationships with the study variables. In this study, preference for campus recreational activities was used as the marker variable because it is theoretically unrelated to technological optimism, perceived enjoyment, attitudes towards drop shipping, and intention to use drop shipping. The results showed that the marker variable had weak and statistically non-significant effects on the endogenous constructs, namely attitudes towards the use of drop shipping (β = 0.028; t = 0.641; p = 0.522) and intention to use drop shipping (β = 0.031; t = 0.718; p = 0.473). These findings suggest that the observed relationships are not substantially influenced by common method variance.

Second, a full collinearity assessment using the inner variance inflation factor (VIF) values was conducted as an additional diagnostic test for common method bias. Unlike traditional collinearity diagnostics that focus only on predictor relationships, Kock and Lynn (2012) and Kock (2015) proposed a full collinearity VIF assessment as a robust procedure capable of simultaneously detecting vertical and lateral collinearity and identifying potential common method variance in PLS-SEM models. Hair et al. (2019, 2022) further recommend this approach because method bias frequently inflates correlations among latent variables and may subsequently distort structural relationships and path estimates. According to Kock (2015), VIF values exceeding the conservative threshold of 3.3 indicate that a model may suffer from pathological collinearity and common method bias, whereas values below this threshold suggest that CMB is unlikely to threaten model validity. Moreover, Diamantopoulos and Siguaw (2006) contend that lower VIF values provide evidence that predictor constructs maintain adequate independence and do not exhibit problematic overlap. As shown in Table 6, all inner VIF values ranged from 1.214 to 2.486, remaining well below the recommended threshold of 3.3. Therefore, the findings provide additional support for the conclusion that common method bias and multicollinearity did not significantly affect the study results.

In order to assess model fitness in SMARTPLS, the Standardised Root Mean Square Residual (SRMR) and normed fit index (NFI) are commonly used. The fitness of the proposed structural model is shown in Table 7.

According to Amoah and Jibril (2021), SRMR is a measure of absolute fit, with a lower value indicating a better fit. Model complexity is not penalised by SRMR, and a value less than 0.08 is generally considered a good fit (Amoah and Jibril, 2021). The NFI statistic evaluates the model by comparing its chi-square value to that of the null model (Hooper et al., 2008). For a good fit, the NFI value should be 0.903 or higher. Both the SRMR and the NFI in the study (Table 5) satisfy the model's fitness conditions. The SMR value of 0.074 is less than 0.08, while the NFI value of 0.906 exceeds the recommended threshold of 0.9. Furthermore, a model with a good fit is expected to have SRMR and NFI values below 0.95 (Henseler et al., 2015). All of these values (Table 5) meet the required criteria, confirming the model's goodness of fit.

The R², Q², and effect size (f²) values, as presented in Table 6, provide a comprehensive assessment of the model's explanatory power, predictive relevance, and the magnitude of predictor effects. For attitudes towards the use of drop shipping (ATUDS), the R² is 0.578, indicating that 57.8% of the variance in ATUDS is explained by technological optimism (TO). This suggests a moderate-to-substantial level of explanatory power. The R² for intention to use drop shipping (INT) is 0.631, meaning that 63.1% of the variance in intention is accounted for by ATUDS, TO, and perceived enjoyment (PE), which reflects a substantial explanatory power. Meanwhile, actual use of drop shipping (AU) has an R² of 0.462, indicating that 46.2% of its variance is explained by INT and PE, representing a moderate level of explanation.

Hair et al. (2017) recommend that researchers examine Q² to assess the structural model's predictive relevance. Predictive applicability of constructs must be positive (i.e., greater than zero) (Hair et al., 2019). The Q² values, which assess predictive relevance, are all above zero, including 0.201 for ATUDS, 0.347 for INT, and 0.255 for AU, demonstrating that the model has meaningful predictive capability for all three constructs. Additionally, the effect sizes (f²) are huge: 2.971 for ATUDS, 3.420 for INT, and 2.821 for AU. These values far exceed the threshold for a large effect (0.35), indicating that the corresponding exogenous variables have a substantial impact on their respective outcomes. Collectively, the results in Table 8 confirm the structural model's robustness, explanatory power, and predictive relevance.

A more advanced, prediction-oriented technique in PLS-SEM, PLS-Predict, was subsequently employed to evaluate the model's out-of-sample predictive performance (Chin et al., 2020; Shmueli et al., 2019). As reported in Table 9, all endogenous indicators relating to attitudes towards, intention to use, and actual use of drop shipping exhibit adequate to strong predictive relevance. In particular, the Q² predicted values for all indicators are greater than zero, indicating that the PLS model outperforms the linear benchmark model (LM) in predictive accuracy. Moreover, the root mean square error (RMSE) and mean absolute error (MAE) values associated with the PLS model are consistently lower than those of the LM across all indicators, thereby meeting the recommended criteria for assessing predictive performance in PLS-SEM (Shmueli et al., 2019; Hair et al., 2022). Collectively, these results confirm that the proposed model demonstrates strong out-of-sample predictive capability, particularly for attitudinal responses, behavioural intentions, and actual drop-shipping usage behaviour within the target population.

Effect size (f²) measures the contribution of an exogenous construct to the R² value of an endogenous variable by assessing the change in R² when the specific predictor is excluded from the model (Hair et al., 2019). According to Bliwise (2006), an f² value of less than 0.30 indicates a weak effect, values between 0.30 and 0.50 represent a moderate effect, and values greater than 0.50 indicate a strong effect. The effect size can be calculated using the formula:

Where R² is the coefficient of determination.

As shown in Table 6, the f² values for attitudes towards the use of drop shipping, intention to use drop shipping, and actual use of drop shipping are all above 0.50, indicating that the corresponding exogenous constructs have a substantial effect on their respective endogenous variables.

Figure 2 presents the structural model results, including the t-values used to test the significance of hypothesised relationships. Based on the guidelines of Chin (1998), Chinomona et al. (2010), and Nyagadza et al. (2021), a t-value greater than 1.96 indicates statistical significance at the 5% level. Accordingly, the results show that H1 (t = 2.161), H2 (t = 10.428), H3 (t = 10.185), H4 (t = 2.010) and H5(t = 7.931) are significantly supported. These findings confirm meaningful relationships among technological optimism, attitudes, intention, and actual drop shipping usage. Perceived enjoyment also significantly influences both attitudes and intention. This study yielded several key findings. All five hypotheses with a direct relationship were accepted. An overview of the hypothesis-testing results, including path coefficients, p-values, and T-values, is presented in Table 10.

Using consistent PLS bootstrapping, T-statistics and p-values were generated to determine whether the moderating variable significantly influences the relationship between the independent predictor variable (Hair et al., 2017) and the dependent outcome variable (intention to use drop shipping as a business model). The required thresholds for both T-statistics and p-values to indicate a significant relationship are that the T-value must be equal to or greater than 1.96, and the p-value must be less than 0.05 (Gye-Soo, 2016). Both the T-value and the p-value thresholds must be met simultaneously to confirm the significance of the proposed relationships. Table 11 illustrates the T-statistics and p-values of the moderated relationship.

The results for H6 indicate a positive and statistically significant moderating effect of PE on the relationship between INT and OB in the Gen Z cohort studied. This implies that PE strengthens INT's favourable influence on AU. Additionally, this finding was supported by the absence of zero in the 95% confidence interval (0.108 and 0.192, respectively). Thus, when Generation Z students perceive enjoyment in using drop shipping as a technopreneurial model, the positive influence of INT on AU becomes more pronounced. Therefore, the statistical analysis supported H6, suggesting that PE moderates the relationship between INT and AU. The significant moderating effect of perceived enjoyment on the relationship between intention to use dropshipping and actual use (H6) can be more deeply understood through the lens of hedonic motivation theory, which posits that individuals are more likely to enact behaviours that are intrinsically pleasurable, enjoyable, or emotionally rewarding (Davis et al., 1992; Venkatesh et al., 2012). While intention is traditionally viewed as the nearest determinant of behaviour in intention-based models such as the Theory of Planned Behaviour (TPB), intention alone does not guarantee enactment, particularly in contexts characterised by uncertainty, effort and delayed rewards, such as technopreneurship. Importantly. The moderating effect indicates that enjoyment does not merely increase intention as supported by H5, but changes the strength of the intention-behaviour relationship itself. This aligns with hedonic motivation theory, which argues that intrinsic motivation transforms behaviour from obligation-driven to self-reinforcing (Deci and Ryan, 2000). In this sense, enjoyment acts as a behavioural lubricant, lowering resistance to action and increasing persistence during execution phases. By demonstrating that perceived enjoyment moderates the intention-behaviour relationship, this study extends hedonic motivation theory into the domain of technopreneurship. It indicates that enjoyment is not only an antecedent of technology acceptance but also a mechanism governing behavioural enactment, offering a more nuanced understanding of how entrepreneurial intentions are realised in practice.

The impact of PE on the relationship between INT and AU was investigated in greater detail using simple slopes analysis, as depicted in Figure 3. Following Dawson's (2014) guidelines, the graph in Figure 3 shows two lines representing low and high levels of the moderator (PE). The slopes of these lines indicate how the strength of the relationship between INT and AU varies with PE. At higher levels of PE, the slope is steeper, indicating that when individuals find the system more enjoyable, the impact of intention on actual use is significantly stronger. Conversely, at lower levels of PE, the relationship is weaker, suggesting that even with strong intention, low enjoyment reduces the likelihood of actual use. This interaction supports the hypothesis that PE positively moderates the INT–AU relationship, thereby enhancing the predictive power of intention when enjoyment is high.

This study found that technological optimism is positively and statistically significantly associated with attitudes towards drop shipping among Gen Z respondents, thereby supporting H1. The standardised regression coefficient (β = 0.123; p = 0.031 [two-tailed] and the bootstrapped confidence interval [0.017–0.242] indicated a meaningful effect, suggesting that individuals with higher levels of technological optimism are more likely to express positive attitudes towards the use of drop shipping. The conclusion drawn from this empirical finding is that technological optimism significantly shapes positive attitudes toward drop shipping among Gen Z technopreneurs. In the South African context, where Gen Z students are already heavy users of digital platforms, entrepreneurship education should integrate hands-on exposure to e-commerce infrastructure, such as Shopify dashboards, suppliers' platforms, and digital advertising tools, into coursework. Past research indicates that optimism toward technology enhances openness to experimentation and lowers perceived complexity, thereby strengthening favourable entrepreneurial attitudes (Parasuraman, 2000; Autio et al., 2018). This implies the need to harness technological optimism early through digitally embedded curricula. When individuals believe that technological advancements will reduce business complexities, they are more likely to adopt digital business models such as dropshipping. The results of this research corroborate those of Niemela-Nyrhinen (2007) and Kim and Hall (2019), who assert that technological optimism significantly influences positive perceptions of digital business adoption.

The study found that attitudes towards drop shipping are positively and significantly related to the intention to use it as a business model for technopreneurship, thus supporting Hypothesis 2. The regression results were β = 0.513 (p = 0.000 [two-tailed]), with a bootstrapping confidence interval of [0.415–0.606]. A beta value above 0.5 indicates a strong effect, and a p-value of less than 0.001 signifies a highly significant relationship. In line with the TPB, which posits that attitudes towards a behaviour are among the most important predictors of behavioural intentions (Ajzen, 1991), these findings support the same conclusion. Given the confirmed link between attitude toward dropshipping and intention to use it for technopreneurship (H2), higher education institutions, such as universities, should prioritise attitude-shaping pedagogical strategies, including case-based learning featuring relatable South African Gen Z entrepreneurs and simulation-based venture creation. Evidence from entrepreneurship education research indicates that positive attitudes, rather than abstract knowledge alone, are the strongest predictors of entrepreneurial intention among students (Fayolle and Gailly, 2015; Ndofirepi, 2020). The empirical findings suggest that positive attitudes significantly influence the intention to adopt drop shipping as a business model among Gen Z technopreneurs. The findings align with those of previous researchers. For instance, Pavlou and Fygenson (2006) confirmed that favourable attitudes significantly increase entrepreneurial intention in online business settings. Furthermore, Gopi and Ramayah (2007) found that attitudes play a significant role in forming intentions among technology-driven businesses. Therefore, the acceptance of Hypothesis 2 in this study contributes to the robust body of literature that validates the importance of attitudes in shaping intentions.

Although technological optimism had a statistically significant positive effect on attitudes towards drop shipping, the relatively modest effect size (β = 0.123) warrants further consideration. While the finding confirms that optimistic perceptions regarding technology contribute to favourable attitudes, the comparatively weaker coefficient suggests that technological optimism alone may not be a dominant determinant of attitudes among Generation Z respondents. This may be explained by the characteristics of Generation Z itself, a cohort often described as digitally immersed and highly accustomed to technology use. For such individuals, technological optimism may represent a baseline expectation rather than a strong differentiating factor influencing attitudes. In other words, because many Gen Z individuals already perceive technology as an inherent aspect of their daily lives, simply being optimistic about technology may not substantially alter their evaluations of drop shipping. Instead, more immediate considerations such as perceived usefulness, entrepreneurial self-efficacy, trust, social influence, or perceived opportunities for financial independence may exert a stronger influence on the formation of attitudes towards adopting digital business models.

Furthermore, the contrast between the relatively weak technological optimism–attitude relationship (β = 0.123) and the substantially stronger attitude–intention relationship (β = 0.513) may indicate that technological optimism operates indirectly through other psychological or behavioural mechanisms not explicitly captured in the current model. Existing literature suggests that technological optimism can shape behavioural outcomes through mediating factors such as perceived ease of use, perceived usefulness, technology readiness, and entrepreneurial confidence. Studies integrating the Technology Readiness Index (TRI) and Technology Acceptance Model (TAM) have demonstrated that optimistic individuals tend to perceive technologies as more useful and easier to use, which subsequently strengthens technology acceptance and behavioural intentions (Blut et al., 2020; Khoza and Buitendach, 2024; Nigatu et al., 2024). Furthermore, evidence indicates that technology readiness positively influences entrepreneurial commitment and confidence in adopting technology-driven opportunities, thereby facilitating entrepreneurial engagement and technology-related behaviours (Farradinna et al., 2025). These findings collectively suggest that technological optimism exerts its influence indirectly through cognitive and psychological mechanisms that enhance individuals' readiness and confidence to engage with emerging technologies. Consequently, technological optimism may act more as a distal antecedent rather than a direct driver of entrepreneurial attitudes. This interpretation highlights the possibility that other unexamined pathways may explain how optimism ultimately translates into stronger entrepreneurial intentions and behaviours. Future studies may therefore benefit from incorporating additional mediating constructs to further unpack the mechanisms through which technological optimism influences drop-shipping adoption among Gen Z technopreneurs.

It was also found that there is a positive and statistically significant relationship between the intention to use drop shipping as a business model for technopreneurship and actual use of drop shipping as a business model for technopreneurship; hence, H3 was accepted. The regression results (β = 0.505; p = 0.000 [two-tailed]; bootstrapping confidence interval [0.407–0.603]) demonstrate high statistical significance. The p-value below 0.001, along with the bootstrapping confidence interval, reinforces the robustness of the finding. The statistically significant relationship between intention and actual use of dropshipping (H3) indicates that once Gen Z technopreneurs form strong intentions, they are likely to act provided enabling conditions exist. Incubation hubs should therefore move beyond motivational training toward execution-oriented support, such as assistance with supplier vetting, digital advertising optimisation, customer service automation, and returns management. This aligns with evidence that digital entrepreneurs benefit more from capability-building interventions rather than generic mentoring (Nambisan, 2017). The outcome that, as intentions to use drop shipping increase, there is a greater likelihood of actual engagement is consistent with the Theory of Planned Behaviour (Ajzen, 1991), which posits intentions as the strongest predictors of behaviour. The conclusion derived from the empirical findings is that intention plays a crucial role in predicting the actual use of drop shipping as a business model. Pavlou and Fygenson (2006) found that strong intention significantly increases the actual use within the context of online consumer behaviour. Moreover, Venkatesh et al. (2003) also emphasise that behavioural intention is a direct antecedent of actual technology use. Although intentions to use (H3), policymakers play a critical role in maintaining this conversion by reducing the friction in digital entrepreneurship. Simplified youth business registration, affordable access to digital payment systems, and clearer guidelines on consumer protection for small businesses online can reinforce the move from intention to action. Institutional support has been shown to significantly amplify youth engagement in digital entrepreneurship ecosystems in emerging economies (Sussan and Acs, 2017).

In this study, H4 was accepted, as the statistical results demonstrated a significant relationship between perceived enjoyment of drop shipping and attitudes towards its use. The path coefficient was (β = 0.103; p = 0.044 [two-tailed]; bootstrapping confidence interval [0.014–278]. Based on these results, when technopreneurs find drop shipping to be enjoyable, they are more likely to develop a favourable attitude, which then translates into actual use. This outcome aligns with the findings of Venkatesh et al. (2012) and Van der Heijden (2004), which suggest that perceived enjoyment not only enhances attitudes but also outcomes. The significant effects of perceived enjoyment on both attitudes (H4) and intention (H5) underscore that enjoyment is not incidental but central to sustained technopreneurial engagement. Universities should therefore integrate gamified learning elements, such as sales challenges, digital marketing competitions, and peer rankings, into entrepreneurship modules. Enjoyment has been shown to enhance intrinsic motivation and persistence, and to deepen engagement with technology-based learning tasks, particularly among Generation Z (Ainley and Ainley, 2011; Ratten, 2023). The empirical findings suggest a positive and significant relationship between the perceived enjoyment of drop shipping and attitudes towards its use, as well as actual use of drop shipping as a business model for technopreneurship. Enjoyment strengthens engagement and intention, ultimately leading to the actual use of the business model. Studies by Davis et al. (1992), who incorporated perceived enjoyment into the Technology Acceptance Model, and Childers et al. (2001), who found that enjoyment significantly influences consumer technology behaviour.

In this study, H5 was accepted because a positive and significant relationship was found between perceived enjoyment of drop shipping and the intention to use drop shipping as a business model for technopreneurship, leading to actual use of the model. The statistical outputs β = 0.384; p = 0.000 [two-tailed]; bootstrapping confidence interval [0.291–0.479] demonstrate a moderate to strong effect with high confidence. This finding suggests that the more technopreneurs perceive drop shipping as enjoyable or satisfying, the more likely they are to intend to adopt the business model and subsequently engage with it. These results align with the hedonic motivation theory and the TAM3, which emphasise perceived enjoyment as a critical determinant of behavioural intention in technology adoption (Venkatesh and Bala, 2008). The conclusion drawn from the empirical finding is that perceived enjoyment serves as an intrinsic motivator influencing technopreneurs' intention to adopt drop shipping as a business model. Prior research corroborates this relationship; for example, Davis et al. (1992) found that perceived enjoyment substantially influences users' intentions to adopt new technologies. Similarly, research by Childers et al. (2001) highlights that hedonic value plays a significant role in consumer engagement with technology. In conclusion, in the context of technopreneurship, Gen Z is more likely to adopt digital systems that offer engaging, enjoyable, and user-centric experiences, which underscores the significance of this hypothesis.

Moreover, H6 was accepted, demonstrating that perceived enjoyment in drop shipping positively and significantly moderates the relationship between the intention to use drop shipping as a business model for technopreneurship and actual use of the model (β = 0.149; p = 0.000 [two-tailed], with a bootstrapping confidence interval of [0.108–0.192]). The beta indicates a statistically significant effect, and the confidence interval reinforces the robustness of the moderating effect. The moderating effect of perceived enjoyment on the intention-use relationship (H6) proposes that enjoyment strengthens the likelihood that intentions translate into actual entrepreneurial behaviour. Incubation hubs should deliberately design enjoyable entrepreneurial ecosystems, including peer communities, demo days for micro-stores, and social learning platforms (for example, WhatsApp or Discord cohorts). Social and affective reinforcement has been shown to solidify entrepreneurial identity and persistence, especially among youth entrepreneurs navigating uncertain digital markets (Fauchart and Gruber, 2011; Shepherd et al., 2015). It can be concluded that perceived enjoyment strongly motivates the intention to use drop shipping as a business model, eventually leading to actual use. The results align with prior research by Venkatesh (2000) and Davis et al. (1992), which indicate that enjoyment, an intrinsic motivational factor, can positively influence the intention and actual use of drop shipping. Furthermore, the findings support integrating enjoyment into behavioural models, such as the IDT, in which enjoyment and engagement play crucial roles (Van der Heijden, 2004). Because drop shipping allows low-cost entry, incubation hubs can frame it as a safe space for experimentation, encouraging rapid testing and iteration without the stigma of failure. This is particularly relevant in South Africa, where fear of failure remains a strong deterrent to entrepreneurial action (Herrington and Kelley, 2023). Creating an environment where enjoyment coexists with disciplined experimentation can convert short-term engagement into long-term technopreneurial trajectories. The strong role of enjoyment across attitudes, intention, and behaviour (H4-H6) suggests that policy messaging that is overly focused on necessity-driven entrepreneurship may misalign with Generation Z's motivations. Policymakers should incorporate narratives emphasising creativity, autonomy, enjoyment, and digital self-expression, which have been shown to resonate with younger cohorts and enhance programme uptake (Rothenberg et al., 2019; Ratten, 2023).

Collectively, the findings of the current study indicate that technological optimism initiates positive attitudes, attitudes form intention, and intention leads to action, while enjoyment operates as both a direct driver and a catalyst that strengthens the intention-action link. Universities, incubation hubs, and policymakers each influence different stages of this pathway. Policies and interventions that ignore enjoyment risk weakening the translation of intention into actual technopreneurial behaviour among Generation Z in South Africa.

This study offers several important theoretical implications for digital entrepreneurship research, particularly in emerging-economy contexts. From a theoretical standpoint, the findings extend the Theory of Planned Behaviour (TPB) and the Traditional Behavioural Reasoning Model (TBRM) by demonstrating that both cognitive and affective mechanisms jointly shape the translation of entrepreneurial intention into actual behaviour in technology-enabled business settings. While TPB has been widely applied to explain entrepreneurial intentions, scholars have consistently highlighted its limited capacity to account for intention–behaviour gaps, especially in dynamic, experiential digital environments (Ajzen, 1991; Sheeran, 2002). By empirically showing that technological optimism influences attitudes and intentions, and that perceived enjoyment significantly strengthens the intention–behaviour relationship, this study refines TPB by incorporating Hedonic Motivation Theory as a complementary affective lens. Specifically, perceived enjoyment, conceptually grounded in Hedonic Motivation Theory, functions as a behavioural accelerator, explaining why technologically optimistic individuals are more likely to convert entrepreneurial intentions into actual technopreneurial action. This theoretical integration advances existing models by positioning enjoyment not merely as a distal motivational antecedent but as a boundary condition that amplifies behavioural enactment, thereby addressing a core limitation of intention-based frameworks. In doing so, the study responds to calls for greater incorporation of emotional and experiential constructs in technology and entrepreneurship research (Hagger and Hamilton, 2021; Venkatesh et al., 2012), while offering a more holistic explanatory framework that captures rational evaluations (TPB), behavioural reasoning processes (TBRM), and intrinsic pleasure-driven motivations (Hedonic Motivation Theory) underlying Generation Z's engagement with digital entrepreneurial activities such as drop shipping.

The findings also generate clear directions for future research. Scholars are encouraged to extend the proposed model by introducing additional mediating and moderating variables such as entrepreneurial self-efficacy, perceived platform risk, and digital ecosystem support, which have been shown to shape technology-enabled entrepreneurial behaviour (Bandura, 1997; Autio et al., 2018). Moreover, comparative and multi-group research designs could test whether the strength of technological optimism and enjoyment differs across contexts, such as between emerging and developed economies, student versus non-student youth, or necessity-versus opportunity-driven entrepreneurs. Longitudinal and experimental studies would further strengthen causal inference by examining whether interventions that increase enjoyment or technological optimism over time lead to sustained entrepreneurial behaviour, thereby addressing long-standing methodological critiques of cross-sectional entrepreneurship research (Davidsson, 2020).

From an educational perspective, the findings carry important implications for entrepreneurship curriculum design and pedagogy. The strong role of technological optimism and enjoyment suggests that traditional, theory-heavy entrepreneurship education may be insufficient to stimulate actual venture creation. Instead, entrepreneurship programmes should prioritise experiential, technology-mediated learning, including live drop-shipping projects, platform simulations, and digital marketing laboratories. Prior research shows that experiential and problem-based learning enhances entrepreneurial competence and behavioural readiness (Fayolle and Gailly, 2015; Nabi et al., 2017). By embedding gamified assessments, real-time experimentation, and iterative feedback into curricula, educators can deliberately cultivate enjoyment and confidence, thereby increasing the likelihood that students' progress from intention to action. These findings reinforce the argument that entrepreneurship education should move beyond intention formation toward behaviour-oriented learning outcomes.

For practitioners and entrepreneurship support organisations, including incubators and accelerators, the study highlights that skills training alone is insufficient to ensure the adoption of digital business models such as dropshipping. Training programmes should be designed to lower cognitive overload, provide early experiential success, and sustain enjoyment throughout the entrepreneurial journey. Research on digital entrepreneurship indicates that novice entrepreneurs are more likely to persist when platforms are perceived as user-friendly and rewarding to engage with (Nambisan, 2017; Sussan and Acs, 2017). Practitioners should therefore focus on modular training approaches, mentorship-driven experimentation, and peer-learning communities that normalise trial and error and iterative learning. Such interventions directly operationalise the study's findings by creating environments that strengthen the intention–behaviour link identified in the empirical model.

At the policy and societal level, the study provides evidence-based insights relevant to youth employment and digital inclusion strategies. Although the data were collected from two South African universities, the mechanisms identified-technological optimism, enjoyment, and behavioural translation-are not institution-specific and are likely applicable to broader youth populations in emerging economies facing high unemployment and limited formal job opportunities. Policymakers can leverage these insights by incorporating digital micro-entrepreneurship pathways, such as drop shipping, into national youth entrepreneurship and skills development strategies. Prior studies emphasise that access to digital infrastructure must be complemented by positive technology experiences and capability-building to generate meaningful employment outcomes (World Bank, 2020; OECD, 2021). By supporting university-based digital incubators, subsidising access to e-commerce platforms, and promoting user-friendly digital ecosystems, policymakers can increase the likelihood that entrepreneurship initiatives lead to real venture activity rather than symbolic participation.

Overall, this study provides a stronger bridge between theory and practice by demonstrating that fostering technopreneurship among Generation Z requires more than intention-building. It requires the deliberate design of educational, institutional, and policy environments that enhance enjoyment, reinforce technological optimism, and facilitate behavioural enactment. In doing so, the study contributes to entrepreneurship scholarship by offering a transferable, empirically grounded framework for promoting youth digital entrepreneurship in South Africa and comparable emerging economies.

Despite its contributions, this study is subject to several limitations that should be acknowledged. First, the sample comprised university students from two South African universities, which limits the generalisability of the findings beyond Generation Z students and similar higher-education contexts. Although students are an appropriate population for examining early-stage technopreneurial behaviour, future research should extend the model to non-student youth, informal entrepreneurs, and established small business owners to enhance external validity. Second, the study relied on self-reported measures of actual drop shipping use, which may be affected by recall bias or social desirability bias and may not fully capture sustained entrepreneurial engagement. Future studies could address this limitation by employing objective behavioural indicators, such as platform usage data, transaction records, or longitudinal tracking of venture activity.

Third, although data were collected at two time points to reduce common-method concerns, the relatively short interval between waves and the use of a single survey instrument may still introduce common-method variance. Future research could further mitigate this issue by adopting multi-source data, time-lagged designs over longer periods, or experimental approaches. In addition, subsequent studies may explore heterogeneity across demographic and contextual factors, including gender, income level, institutional context, and urban–rural differences, as well as compare drop shipping with alternative digital business models. Incorporating additional mediators and moderators, such as entrepreneurial self-efficacy, risk propensity, social influence, and entrepreneurial ecosystem support, and extending the analysis to cross-country emerging-market samples would further strengthen the theoretical and empirical contributions. Finally, while the quantitative approach yielded valuable insights, future research may benefit from mixed methods designs to provide richer, more nuanced understandings of technopreneurial engagement.