The entrepreneurial intention-action gap and psychological capital components: insights from social and commercial entrepreneurs Open Access

In the past decades, scholars like Adam and Fayolle (2015) have been trying to understand the entrepreneurial process, in particular how prospective entrepreneurs transition from entrepreneurial intention (EI) to entrepreneurial action (EA). EI refers to the individual’s intent to start a business in the future (Krueger, 2017), while EA refers to actions taken by an individual when making decisions under conditions of uncertainty to pursue a business opportunity (Dimov and Pistrui, 2020). As many as 69% of individuals fail to translate their EI into the action of starting their own businesses (Van Gelderen et al., 2015). This results in what is referred to as “the EIA gap” and has been investigated by several scholars examining personality traits and other contextual factors that could bridge this gap (Adam and Fayolle, 2015; Baluku et al., 2020; Lima et al., 2020; Roos and Botha, 2022; Van Gelderen et al., 2015). Baluku et al. (2020) found that the presence of a strong proactive personality and higher PsyCap result not only enhances EI but may also lead to actions to start a business. Similarly, Lima et al. (2020) suggest that the PsyCap components positively influence entrepreneurial behaviour; however, the study does not address how these components influence individuals’ transition from EI to EA. Hence, the purpose of this paper is to address this limitation by determining whether the PsyCap components (hope, optimism, resilience and self-efficacy) mediate the relationship between EI and the three phases of EA (predecisional, preactional and actional) for social and commercial entrepreneurs.

PsyCap is related to EA through effective entrepreneurial marketing (Hills et al., 2010). Morris et al. (2002) define entrepreneurial marketing as the “proactive identification and exploration of opportunities for acquiring and retaining profitable customers through innovative approaches and value creation”. Similarly, Lee and Yang (2019) and Wafeq, Al Serhan, Gleason, Dasanayaka, Houjeir and Al Sakka (2019) found that PsyCap connects an entrepreneur to its customers through effective entrepreneurial marketing strategies. Yet these PsyCap components and their influence on the EIA gap have not been determined for social and commercial entrepreneurs.

Social entrepreneurs are defined as those with the aim of solving social problems and creating sustainable solutions, whereas commercial entrepreneurs are those who intend starting their business with a profit motive (Sastre‐Castillo, Peris‐Ortiz and Danvila‐Del Valle, 2015). In addition, most of the studies exploring the two types of entrepreneurs investigated either the EI of commercial entrepreneurs (Santos et al., 2021) or the EI of social entrepreneurs (Wach, Kruse, Costa and Antonio Moriano, 2023) or focused on EA as a single construct (Ip et al., 2022; Jin, 2017; Rakotoarisoa et al., 2022) without measuring the influence of the PsyCap components in the transition from EI to the various phases of EA. Specifically, Rakotoarisoa et al. (2022) explore the influence of the PsyCap components on social entrepreneur’s intention and found support that optimism has a positive influence on social EI. On the other hand, Jin (2017) examines the influence of PsyCap on start-up entrepreneurs’ intention and found that resilience and self-efficacy influence the Chinese entrepreneurs, while Korean entrepreneurs’ EI was influenced by hope and optimism. Furthermore, Lima et al. (2020) examine the determinants of social entrepreneurial behaviour and the influence of PsyCap on entrepreneurial behaviour, respectively. Although this previous work revealed that PsyCap components play a crucial role in relation to both the EI and EA, its influence on the EIA gap for both social and commercial entrepreneurs, is undetermined. Thus, it seems that different PsyCap components influence different types of entrepreneurs as well as entrepreneurs in different cultural and country contexts. While most of the previous studies have been conducted in a Global North context, our study focused on social and commercial entrepreneurs in a Global South context. This quantitative cross-sectional study uses the mindset theory of actional phases (Gollwitzer, 2012; Gollwitzer and Keller, 2016) to demonstrate how an entrepreneur transitions through the different phases to bridge the EIA gap.

This paper develops and tests a comprehensive framework of the EIA gap, by examining the effects of the PsyCap components between the EI and the three phases of the EA which has received limited scholarly attention. Consequently, the results enhance our understanding of why some individuals with EI do not engage in EA (business start-up). The rest of the paper unfolds as follows: The theoretical foundations and hypotheses are presented, followed by the presentation of the methodology and analyses employed, and the discussion of the results. The paper concludes with the implications and recommendations for future research.

Clarification of how specific actions, undertaken under uncertain conditions, result in goal formation which ultimately leads to EA, is supported by the mindset theory of action phases. According to this theory, the course of action can be divided into four action phases: predecisional, preactional, actional and postactional (Gollwitzer, 2012; Botha, 2024). The first three phases (predecisional, preactional and actional) are identified as necessary to study EA from a process perspective (Botha, 2020; Delanoë‐Gueguen and Fayolle, 2019; Van Gelderen et al., 2015). During the predecisional phase the prospective entrepreneur adopts a deliberative mindset in which relevant information is evaluated to inform the feasibility and desirability of the potential goal to be chosen (Gollwitzer and Keller, 2016). Once a decision is made to pursue a specific goal, the prospective entrepreneur transitions from the predecisional to the preactional phase. In the preactional phase, an implemental mindset is adopted to consider strategies regarding the when, where and how to implement the actions to reach the chosen goal (Delanoë‐Gueguen and Fayolle, 2019; Gollwitzer and Keller, 2016). After the preactional phase, the prospective entrepreneur transitions to the actional phase, in which the actions aimed at achieving the chosen goal are taken.

PsyCap is a psychological core construct that draws from positive psychology. Luthans and Youssef (2004, p. 152) postulate that PsyCap “applies positively oriented human resource strengths and psychological capacities that can be measured, developed and managed for performance improvement in today’s workplace”. The four PsyCap components (self-efficacy, hope, optimism and resilience) are presented in an integrative manner within positive psychology (Nolzen, 2018), as resources critical for success achievement, especially as it relates to the entrepreneurial process. Wafeq et al. (2019) found a clear connection and resemblance between marketing functions and entrepreneurship, as both require the ability to deal with and transform challenges into opportunities. Marketing functions naturally deal with the external environment, which includes customers, suppliers, competitors and many other stakeholders. It is for this reason that Wafeq et al. (2019) discovered a strong correlation between the PsyCap components and the marketing functions, as they are all crucial components of a successful entrepreneurship endeavour. PsyCap shapes an entrepreneur’s thinking and behaviour, which in turn determines their approach to marketing. Therefore, the intersection between PsyCap and entrepreneurial marketing is crucial (Lee and Yang, 2019) and strong support that links the marketing–entrepreneurship interface (MEI) literature is provided by Karami et al. (2024) and Patra and Lenka (2024). Furthermore, Breit and Volkmann (2024) suggest that PsyCap components are key resources that influence entrepreneurs’ conception of marketing and its activities. The four PsyCap components are described as follows and enhanced through entrepreneurial marketing:

1. Self-efficacy refers to the belief that one has the capability to achieve one’s goals or realise the desired outcome (Luthans and Youssef-Morgan, 2017). Individuals with high levels of self-efficacy are more likely to persevere in their marketing decision-making and strategy implementation (Breit and Volkmann, 2024).

2. Hope refers to the determination that one will achieve one’s goal and the belief that there are several ways to achieve that goal (Hefferon and Boniwell, 2011). Individuals with high levels of hope are more likely to experiment with innovative approaches and proactive marketing strategies (Hills et al., 2010).

3. Optimism refers to a positive expectation that things will unfold in a positive manner (Luthans and Youssef-Morgan, 2017). Individuals with high levels of optimism have a positive expectation regarding their marketing outcomes, and they are more open to taking calculated risks and exploring with unconventional marketing strategies (Wafeq et al., 2019).

4. Resilience is defined as the flexibility to successfully adapt in changing and challenging situations and the ability to overcome the negative experience (Hefferon and Boniwell, 2011). Individuals with high levels of resilience are adaptable and can change their marketing strategies based on feedback received from setbacks (Morris et al., 2002).

EI has received extensive scholarly discourse over the years (Bird, 1988; Krueger, 2017) and is defined as “a self-acknowledged commitment by a person that they intend to set up a new business venture and consciously plan to do so at some point in the future” Thompson (2009, p. 676). Although EI and the predecisional phase of action share certain features, they should clearly be distinguished. Furthermore, there are contradictions in the literature regarding the occurrence of EI and predecisional action. On the one side, scholars argue that EI takes place before action occurs in the predecisional action phase. Specifically, Thompson (2009) highlights that the intent to start a business at some “point in the future” might be near, or undetermined, and even unreachable. Due to this “undetermined” element, Bird (1988) contend that EI is a guide to goal setting and planning, yet no action is taken. Furthermore, EI is considered as a goal intention (Delanoë‐Gueguen and Fayolle, 2019) whereby it is considered as a mental readiness process while predecisional action is the first stage in the Rubicon model of action which involves the pursuing of a goal (Roos and Botha, 2022) not only the “thinking” about it. During this phase, individuals consider various desires and deliberate about the ventures they might want to pursue. Delanoë‐Gueguen and Fayolle (2019) argue that individuals in the predecisional phase adopt a deliberative mindset which is characterised by the feasibility of a potential venture, therefore the action of determining the feasibility is taken. Hence, the aim of the predecisional phase is to choose among a set of preferences and turn them into goal implementation (Gollwitzer, 2012). Goal implementation takes place in the preactional and actional EA phases in which prospective entrepreneurs undertake actions aimed at achieving an intended goal (e.g. venture creation) (Gollwitzer, 2012). On the other side, scholars such as Van Gelderen et al. (2015) contend that the predecisional phase is the stage during which EI is formed and EI occurs after the predecisional phase as the result or outcome of the deliberations within this predecisional phase. Liñán et al. (2024) agree and argue that EI marks the end of the predecisional phase and the move towards subsequent action phases. Without first forming an EI within the predecisional phase, an individual cannot proceed to the planning and action stages of starting a venture (Van Gelderen et al., 2018). In this paper, our argument is not whether EI occurs before, within or after the predecisional stage but rather to determine whether the PsyCap components moderate the relationship between EI and each of the three EA stages.

Several scholars have investigated variables influencing the EI of social and commercial entrepreneurs, respectively (Bacq and Alt, 2018; Cardella et al., 2024; Fu et al., 2022; Mair and Noboa, 2006). Bacq and Alt (2018) suggest that empathy is an important element that differentiates social and commercial entrepreneurs. However, their study found that self-efficacy mediates the relationship between empathy and EI. In addition, self-efficacy has a positive influence on social entrepreneurs’ intention. These findings are supported by Cardella et al. (2024) who also found a positive relationship between self-efficacy and EI. The authors also found support for the mediation effect of self-efficacy in the relationship between empathy and social EI. Furthermore, Fu et al. (2022) found that self-efficacy significantly influences EI and partially mediates the relationship between entrepreneurial education and EI. While Mair and Noboa (2006) propose that self-efficacy enables individual’s perception of the feasibility of social venture creation which in turn influences their EI. Contradictory, previous scholars such as Ephrem et al. (2019) and Jin (2017) explored the influence of PsyCap on EI and found that PsyCap components positively influenced the prospective entrepreneur’s start-up intentions. While Urban (2020) explores the entrepreneurial alertness, self-efficacy and social entrepreneurship intention (SEI) and suggests that no relationship was established between dispositional optimism and SEI. These contradictions call for further investigating regarding the influence of the PsyCap components on EI, EA and how EI transitions to EA for both social and commercial entrepreneurs.

Several studies investigated the individual and contextual factors that influence entrepreneurs to take action (Cardon et al., 2017; Ip et al., 2022; Newman et al., 2021; Roos and Botha, 2022), with a few focusing on the PsyCap components. One such component is entrepreneurial passion which has been identified as one of the important individual factors that drives venture creation and performance outcomes (Newman et al., 2021). Specifically, Cardon et al. (2017) identified important elements of passion such as passion for people, products and services, invention and social mission. These elements and other antecedents (such as self-efficacy, entrepreneurial effort and commitment) are valuable for venture creation and performance outcomes (Cardon et al., 2017; Newman et al., 2021). Furthermore, Roos and Botha (2022) proposed that entrepreneurial passion as an antecedent of optimism. Individuals with high levels of optimism are found to be more attracted to situations with some level of uncertainty and seen to have some level of control on the outcome (such as venture creation) (Dawson, 2017). Similarly, Ip et al. (2022) found support that self-efficacy positively influence social entrepreneurial behaviour for Taiwanese respondents while they observed no relationship for Chinese respondents in their comparative study. Dorado and Ventresca (2013) provide a perspective on institutional conditions which can motivate individuals to undertake EA in the context of complex social problems (social entrepreneurship). The authors suggest that these conditions can alter individual’s decision-making logic (deliberative mindset), whether to act or not based on their appraisal of the feasibility to resolve social problems or the possibility to create unintended consequences. This view is supported by the mindset theory of action phases which suggests that during the predecisional phase individuals embark on the assessment of the feasibility and desirability of their wishes. Entrepreneurial marketing supports this EA process approach, as marketing is not treated as a standalone business function but rather integrated into every phase of EA. This will result in entrepreneurs increasing their visibility and gaining access to more opportunities as every activity that is done well can be a component of their marketing efforts (Edmondson et al., 2024).

The EIA gap is an occurrence resulting from the failure of individuals to translate their EI to EA (Van Gelderen et al., 2015). Baluku et al. (2020) examined proactive personality and PsyCap and the EIA gap. They suggest that PsyCap has a positive influence on the EI and may lead prospective entrepreneurs to taking conscious steps towards starting their businesses. Roos and Botha (2022) investigated contextual factors such as self-identity, family, formal institutions and self-efficacy and the EIA gap, which suggest that these elements are important in closing the gap. Contrasting result were found by Cui (2021) who explored how entrepreneurial behaviour is influenced by entrepreneurial education and PsyCap. He found that only self-efficacy positively influenced the entrepreneurial behaviour of college students, while the other components (hope, optimism and resilience) did not have such an effect.

The conceptual framework is proposed in Figure 1 which highlights the theory that not only supports the PsyCap components but also supports the EIA gap. Combining the definition of EI by Thompson (2009), and the assertion by Bird (1988) that EI guides goal setting (goal intention), PsyCap components, and the mindset theory of action phases, we develop the framework to bridge the EIA gap. The framework aims to explain how prospective entrepreneurs translate their EI to EA. We establish which of the PsyCap components have a mediating effect on the relationship between EI and the three EA phases. Moreover, entrepreneurship literature has found support that a positive relationship exists between PsyCap and EI (Baluku et al., 2020), and EA (Lima et al., 2020) which is enhanced by effective marketing strategies (Hills et al., 2010). In Figure 1, we illustrate that entrepreneurial marketing has been found to enhance PsyCap (Lee and Yang, 2019) and is also related to both EI and EA (Morris et al., 2002). Whereby entrepreneurial marketing proactively identifies and explores opportunities which supports the EA process approach identified in this study.

Several studies found that self-efficacy positively influences entrepreneurial behaviour (Cui, 2021; Lima et al., 2020), while Roos and Botha (2022) suggest that self-efficacy is an important factor in the relationship between entrepreneurial intention and action. Ip et al. (2022) explored the determinants of prospective social EA in a comparative study between the Chinese and Taiwanese respondents; they found that self-efficacy positively influenced social entrepreneurial behaviour from Taiwanese respondents, while no relationship was observed from the Chinese respondents. Despite these contradicting findings, self-efficacy as a psychological construct plays a crucial role not only in commercial entrepreneurship but also in social entrepreneurship (Urban, 2020). Hence, we state the following hypotheses for both commercial and social entrepreneurs:

Hope has been recognised as an essential resource necessary for individuals who are seeking to effect change in their environment and is therefore key to the entrepreneurial process (Luthans and Youssef, 2004). Jin (2017) explored how the start-up intention of prospective commercial entrepreneurs is affected by PsyCap; the findings revealed that hope positively affected the intention of start-up. This positive effect of hope was also confirmed to be present in the entrepreneurial behaviour (Lima et al., 2020). While the construct of hope in social entrepreneurship context is still new (Lingappa et al., 2022), recent studies have identified it as an important entrepreneurial resource for social entrepreneurs (Choi and Chang, 2023; Lingappa et al., 2022). In contrast, Rakotoarisoa et al. (2022) found that hope did not have a considerable effect on social entrepreneurial intention. However, we state the following hypotheses for both commercial and social entrepreneurs:

Bernoster et al. (2018) in their investigation of the association between overconfidence, optimism and entrepreneurial intention, found that there was a high association between optimism and EI and orientation. Dawson (2017) suggests that individuals who have high levels of optimism are attracted to situations that have some level of uncertainty and where the individual is seen to have some level of control on the outcome. Lima et al. (2020) also found optimism to be an important factor in the transition to the entrepreneurial action. In contrast, Urban (2020) found no relationship between optimism and social entrepreneurial intentions. However, we state the following hypotheses for both commercial and social entrepreneurs:

The findings of Chadwick and Raver (2020) as well as Roos and Botha (2022) indicate that resilience played a crucial role in contributing towards closing the EIA gap. Furthermore, these findings reveal that entrepreneurs with high levels of resilience were able to positively evaluate challenging conditions during the start-up as desirable and possible to overcome. In addition, Lima et al. (2020) also found that resilience positively influenced the EA. Therefore, the following hypotheses for both commercial and social entrepreneurs are stated:

Figure 2 graphically illustrates the hypothesised model of self-efficacy, hope, optimism and resilience as mediators in the relationship between EI and each of the three phases of EA.

The contextual importance of the study both geographical and socio-cultural is provided as it may have an influence on the population sample’s translation of their EI to EA. PsyCap has been found to have different cross-cultural implications when applied in different cultural settings (Luthans and Youssef-Morgan, 2017). South Africa is a vast country consisting of nine provinces, a diverse mix of cultures and 11 official languages. It is also considered as one of the countries with the highest rates of inequalities and unemployment (Bowmaker-Falconer and Meyer, 2022). These socio-cultural factors influence the population’s shared beliefs and attitudes, for example, their perception or attitudes towards entrepreneurship (Bushe, 2019). Previous South Africa entrepreneurship studies suggest, for example, that social entrepreneurs have a clear role to play in contributing towards resolving some of the social problems (Urban and Galawe, 2020), and the development of commercial entrepreneurs is also considered as a solution in reducing unemployment (Moos et al., 2022). Furthermore, there is a need to enhance the EA levels of women entrepreneurs considering their critical role they play in the economic growth and poverty reduction in South Africa (Botha, 2020). Similarly, Neneh (2019) emphasises the need to understand the profile of South African university students who translate their EI to EA within a short term given the potential contribution of university entrepreneurship in reducing unemployment. On the other hand, Bowmaker-Falconer and Meyer (2022) suggest that there is a favourable outlook on the health of entrepreneurial activity in South Africa as the Global Entrepreneurial Monitor (GEM) report reveals that there has been a significant increase of individuals who have perceived capabilities required for entrepreneurship. However, the authors caution that while there are individuals who recognise good business opportunities, about 53% would not pursue them due to fear of failure. The relevance of conducting this study may provide new insights in contrast to previous studies. In addition, it may provide information required in the development of strategies and policy direction which can contribute to the reduction of the above-mentioned social-economic problems. Furthermore, the discrepancy between entrepreneurship studies conducted in the Global North and Global South emphasise the importance of investigating different contexts. Most studies concerning the EIA gap are undertaken in the Global North (Van Gelderen et al., 2015) which underscores formal institutional (Cui, 2021) and systemic factors (Baluku et al., 2020). While there are limited EIA studies in the Global South, Roos and Botha (2022) highlight the critical influence of family support, social identity and interactions with formal institutions. These differences suggest that strategies must be tailored to fit the specific contextual realities of each region to bridge the EIA gap.

This study used non-proportional quota sampling to ensure that the number of respondents in each quota group (commercial and social entrepreneurs) was not proportional to the size of the target population. Control variables are used to classify the target population according to the relevant demographic characteristics (Wiid and Diggines, 2021). The two types of entrepreneurs (commercial and social) are used as a grouping variable, and gender (male and female) as a sub-group. This grouping was essential to the study as it made it easier to recruit the social entrepreneurs, as there was less respondents of this group than the commercial entrepreneur group.

The initial questionnaire of the study was piloted using a convenience sample of eight existing entrepreneurs, consisting of four social and four commercial entrepreneurs, following a collaborative participant pre-testing method (Blumberg et al., 2014). For the primary data collection, the anonymous and personalised online survey links were distributed by email to various business emails obtained through different South African business directories, LinkedIn and mobile application (WhatsApp) contacts as well as referrals from entrepreneurs themselves. In addition, paper-based drop-off-collect surveys were also distributed, mainly in the Gauteng metropolitan areas, to supplement the online data collection, but most importantly to obtain a greater representation coverage in line with the quota. Furthermore, paper-based drop-off surveys were also distributed to reach the social entrepreneur sub-sample, which are difficult to access through online processes as some organisations do not have online and internet facilities. Follow-up emails and WhatsApp messages were sent to those who were surveyed online, using personalised survey links. No incentives were provided to respondents to complete the questionnaire. A total of 430 surveys were distributed and 257 (123 online and 134 paper-based) surveys were received back, resulting in a response rate of 59%. A total of 84 online and 117 paper-based were usable; 57 surveys were excluded because of instances of extremity bias and/or item non-response error which could be due to the length of the survey. Therefore, a total of 201 usable surveys, consisting of 107 commercial and 92 social entrepreneurs, were included in this study.

The EI scale by Liñán and Chen (2009) was used in this study to measure each respondent’s perceived level of EI. This measure consists of six-item statements and a seven-point Likert scale which was labelled ranging from 1 (Strongly disagree) to 7 (Strongly agree). No scale items were reverse-scored and a high score on these statements represents a high level of EI.

This study adopted the EA scale reported by Lyu et al. (2023), which is a list of start-up activities adopted from the Panel Study Entrepreneurial Dynamics (PSED) and the Global University Entrepreneurial Spirit students’ Survey (GUESSS). The choice of these measurements was informed by their broad range and extensive application in the study of the EIA gap. This measure consists of 19-item statements and a seven-point Likert scale, which was labelled ranging from 1 (Strongly disagree) to 7 (Strongly agree) and was used to measure each respondent’s perceived level of EA. No scale items were reverse-scored, and the study followed an approach by Delanoë‐Gueguen and Fayolle (2019) and Botha (2020), who suggested that the entrepreneurial activities can be categorised into predecisional, preactional and actional phases of EA. Exploratory factor analysis was used to group the entrepreneurial activities into the three actional phases.

The PsyCap instrument as reported by Ephrem et al. (2019) was used, and the scale consists of seven-item statements for self-efficacy; six-item statements for hope; nine-item statements for optimism; and seven-item statements for resilience. A seven-point Likert scale, which was labelled ranging from 1 (Strongly disagree) to 7 (Strongly agree) was used and no scale items were reverse scored. A high score on these statements represents a high level of self-efficacy/hope/optimism/resilience.

The validity and reliability of the scales used in the study was determined using confirmatory factor analysis (CFA) as all the scales were developed and tested in previous studies (Liñán and Chen, 2009; Lyu et al., 2023; Ephrem et al., 2019).

The inferential statistical tests used in the study include Pearson’s correlation which was used to determine the relationship between the constructs. H1–H4 is tested by conducting mediation analysis, using bias-correlated bootstrap confidence intervals, which is widely recommended for inferences about the indirect effect to determine if a mediation effect exists and whether the effect is partial or full mediation. Choi et al. (2021, p. 12) suggest that “if the bootstrapped confidence interval (CI) (both bias-corrected 95% CI and percentile 95% CI) of the point estimate of the indirect effect through the proposed mediator does not include zero, the mediation effect is significant. If the direct effect exists under the premise of this mediation effect, then the intermediate variable has a partial mediation effect; if no direct effect exists, the intermediate variable plays a role of complete mediation”. The Hayes Process macro (Hayes, 2013), available in SPSS V29, was used to conduct the analysis.

The total sample consists of 201 respondents, of which 48.3% were females and 48.8% were males, while 53.2% were commercial and 45.8% were social entrepreneurs. The respondents’ level of education was spread between 30.8% that has a diploma, 28.4% completed matric (Grade 12) and 24.4% have a postgraduate degree. The highest number (33.3%) of the respondents was between the ages of 41 and 50, followed by 31% between the ages of 31 and 40 and 18.9% between the ages of 51 and 60. Most of the respondents operated their businesses in the service (41.3%) and education (20.4%) industries.

CFA was conducted to determine the reliability and validity of the study’s constructs. To evaluate the fit of the measurement model, the following fit indices were used (Kline, 2016): comparative fit index (CFI), incremental fit index (IFI), root mean square error of approximation (RMSEA) and standardised root mean square residual (SRMR). The initial CFA comprises of all eight constructs (EI, hope, resilience, optimism, self-efficacy, predecisional, preactional and actional) and 36 items. Figure 3 indicates the CFA which illustrates the covariances between all the constructs. The results indicated an inadmissible fit. After studying the item loadings and modification indices, eight items were removed and six theoretically justifiable error covariances were added. This resulted in an adequate model fit. The results are presented in Table 1 and indicate that the model was adequate as the CFI = 0.90, IFI = 0.91, RMSEA = 0.05 and SRMR = 0.07. All the model indices results were within the acceptable range, CFI and IFI were greater than 0.90, RMSEA and SRMR were less than 0.08 (Kline, 2016).

In the final measurement model, the number of items per construct were as follows: Hope consists of two items, Resilience (three items), Optimism (three items), Self-efficacy (six items), EI (four items), predecisional (two items), preactional (three items) and actional (five items). Therefore, the final measurement model consists of a total of 28 items.

Convergent and discriminant validity were subsequently established. Convergent validity was assessed using average variance extracted (AVE) and composite reliability (Hair, 2010; Fornell and Larcker, 1981; Henseler et al., 2009). AVE determines the amount of variance explained by the items representing the construct in relation to the amount of variance due to measurement error. Composite reliability (CR) is a measure of internal consistency, like Cronbach’s alpha, in scale items. The thresholds for AVE is 0.5 (Hair et al., 2017) and for CR a value of 0.6 (Fornell and Larcker (1981), is acceptable. Table 2 indicates that optimism, self-efficacy, EI, predecisional and actional have AVE values less than 0.5. All constructs have a CR value above 0.6. However, Malhotra and Dash (2011) argue that AVE is often too strict, and reliability can be established through CR alone. In addition, Hair et al. (2017), Fornell and Larcker (1981) and Kline (2016) argue that SEM model fit can still be achieved even if some constructs fall slightly below the AVE threshold of 0.5, provided that CR is acceptable and that global fit indices (e.g. CFI, RMSEA, SRMR) indicate an adequate model.

Discriminant validity measures the extent to which constructs are distinctly different from others and the Fornell and Larcker criteria for discriminant validity were used. It requires that the squared root value of AVE should be larger than the correlation between that construct with all other constructs (Fornell and Larcker, 1981). The square root of AVE is indicated in bold in Table 2. The off-diagonal elements indicate the correlation between each pair of constructs. The results indicated discriminant validity for all pairs of constructs, except for self-efficacy and hope, self-efficacy and resilience, and actional and preactional phases.

Given that AVE is a strict criterion and the low values (<0.5) for four of the constructs above, the heterotrait-monotrait (HTMT) (Voorhees et al., 2016) was calculated as an alternative discriminant validity criterion for all the pairs and are presented in Table 3. The HTMT acceptable threshold should be below 0.85 to be acceptable (Voorhees et al., 2016). The HTMT values are determined for the three pairs of constructs that did not meet the Fornell and Larcker criterion as explained in the previous section. In Table 3, the HTMT values are indicated as 0.84 (self-efficacy and hope), 0.73 (self-efficacy and resilience) and 0.79 (actional and preactional phase) for the three pairs and are all below 0.85, the acceptable threshold. Therefore, we can assume discriminant validity between all pairs of constructs as the HTMT value for all the pairs in Table 3 are below 0.85.

The descriptive statistics in Table 4 indicate the respondents’ average mean score levels relating to the constructs of the study which leaned from the level of agreement to strong agreement level. The mean scores ranged between the highest score of 6.41 for the preactional phase and the lowest score of 4.97 for the respondents’ perceived resilience.

Mediation was tested using the bias-corrected bootstrap confidence intervals method, for standardised direct and indirect effects, to determine if a mediation effect exists and whether the effect is partial or full mediation (Choi et al., 2021). Tables 5–8 present the standardised direct and indirect effects for self-efficacy, hope, optimism and resilience, respectively.

When testing H1 [self-efficacy as a mediator in the relationship between EI and (a) predecisional, (b) preactional and (c) actional phases of the EA], the results revealed that confidence intervals of the indirect effects for predecisional, preactional and actional phases do contain zero. The results for the three EA phases (−0.07 to 0.10, −0.01 to 0.20 and −0.04 to 0.08, respectively) and were not statistically significant. Thus, no mediation effect of self-efficacy exists between EI and the three action phases of the EA. Therefore, H1a, H1b and H1c are not supported.

When testing H2 [hope as a mediator in the relationship between EI and (a) predecisional, (b) preactional and (c) actional phases of the EA], the results revealed that confidence intervals of the indirect effects for all phases did not contain zero (0.01–0.14) predecisional, (0.00–0.11) preactional, and (0.00–0.09) actional phase and the effects were statistically significant. Thus, a mediation effect of hope exists between EI and the predecisional, preactional and actional phases. In addition, the confidence intervals for the direct effect did not contain zero for predecisional (0.02–0.62) and the effects were statistically significant. While the confidence intervals for the direct effect did contain zero for preactional (−0.16 to 0.16) and for actional (−0.02 to 0.29) and the effects were not statistically significant. Thus, a partial mediation effect of hope exists between EI and the predecisional phase and a full mediation effect exists between EI and preactional; and also, between EI and the actional phase; therefore, H2a, H2b and H2c are supported.

In H3 optimism is tested as a mediator in the relationship between EI and (a) predecisional, (b) preactional and (c) actional phases of the EA. The results revealed that confidence intervals of the indirect effects for predecisional, preactional and actional phases do contain zero (−0.02 to 0.04, −0.07 to 0.01 and −0.03 to 0.02, respectively). Thus, the effects were not statistically significant, and no mediation effect of optimism exists between entrepreneurial intention and the three action phases of EA. Therefore, H3a, H3b and H3c are not supported.

In H4 resilience is tested as a mediator in the relationship between EI and (a) predecisional, (b) preactional and (c) actional phases of the EA. The results revealed that confidence intervals of the indirect effects for predecisional and preactional did not contain zero (−0.14 to −0.01 and −0.17 to −0.01), respectively, and the effects were statistically significant. Thus, a mediation effect of resilience exists between EI and the predecisional phase as well as between EI and preactional phase. In addition, the confidence intervals for the direct effect do not contain zero for predecisional phase (0.02–0.62) and the effects were statistically significant. While the confidence intervals for the direct effect did contain zero for the preactional phase (−0.16 to 0.16), the effects were not statistically significant. Thus, a partial mediation effect of resilience exists between EI and the predecisional phase and a full mediation effect of resilience exists between EI and preactional phase, therefore H4a and H4b were thus supported. The results further revealed that confidence intervals of the indirect effects for actional did contain zero (−0.07 to 0.04) and the effects was not statistically significant. Thus, no mediation effect of resilience exists between EI and the actional phase.

The results support H2 represented by sub-hypotheses (H2a, H2b and H2c) and the sub-hypotheses of H4a and H4b, while the other hypotheses are not supported. H2 focused on the mediation effect of hope in the relationship between EI and EA. Specifically, H2a, H2b and H2c tested the mediation effect of hope between EI and the predecisional, preactional and actional phases, respectively. The results revealed a partial mediation effect of hope (H2a) and a full mediation effect of hope (H2b and H2c). These findings are in line with the study of Lima et al. (2020), which indicate that hope positively influenced the relationship between EI and entrepreneurial behaviour. Specifically, Hills et al. (2010) found that hope is strongly related to innovative approaches and proactive marketing strategies. Furthermore, Lee and Yang (2019), Karami et al. (2024) and Patra and Lenka (2024) confirm strong relationships between PsyCap components and the MEI literature. This study found that hope may be an important resource through the development of marketing activities that assists entrepreneurs’ transition from EI through all three of the EA phases.

Our findings further confirm H4a and H4b which focused on the mediation effect of resilience in the relationship between EI and the predecisional and preactional phase of the EA. For resilience, the results revealed a partial mediation effect (H4a) between EI and the predecisional and a full mediation effect (H4b) between EI the preactional phase. Previous studies by Lima et al. (2020) and Roos and Botha (2022) also support the findings that confirm that resilience positively influences the EA and the EIA gap. Specifically, we further draw connections with the MEI literature as Morris et al. (2002) confirm the relationship between resilience and EI through effective entrepreneurial marketing strategies. Breit and Volkmann’s (2024) recent review of literature regarding entrepreneurial marketing suggests that entrepreneurs operate in the marketplace that is complex, dynamic and uncertain. Thus, PsyCap components play a critical role in enabling entrepreneurs to cope with extreme uncertainty and adapt to sudden economic changes (Karami et al., 2024). Patra and Lenka (2024) also confirm our findings as they found that resilience is the most significant factor influencing females’ EI in adverse conditions. The establishment of hope and resilience as mediators in the relationship between EI and EA (predecisional, preactional and actional), is specifically novel and relevant for prospective entrepreneurs. While previous models enhanced our understanding of EI, this study moves beyond mere correlation by rather explaining how and which medicating psychological processes can convert EI into EA. We could not confirm the mediation effect of self-efficacy and optimism for the commercial and social entrepreneurs in South Africa. Our findings differ from the Global North studies that found that self-efficacy and optimism positively influences the EIA gap (Cui, 2021; Lima et al., 2020; Karami et al. (2024). However, in Urban’s (2020) South African study, he found no relationship between optimism and social entrepreneurial intentions. Our findings correspond with these findings which seem to be generalisable in a Global South context.

Previous research revealed that the PsyCap components positively influence entrepreneurial behaviour (Lima et al., 2020), yet the need to establish how these components influence the EIA gap, is unknown. In particular, we adopted a process-approach as we aimed to understand how the PsyCap components influence the transition from EI through the three phases of EA (predecisional, preactional and actional). The study addresses this gap, and contributes to this body of knowledge regarding the EIA gap and the individual PsyCap components. Specifically, our findings established the importance of the role of hope and resilience in the relationship between EI and EA (through the three phases), which was not confirmed in previous studies. Furthermore, this paper suggests that entrepreneurial marketing can be an important aid in enhancing the relationship between all four of the PsyCap components and EA (Morris et al., 2002; Hills et al., 2010; Wafeq et al., 2019; Breit and Volkmann, 2024).

This study makes several theoretical contributions. First, there is a growing scholarly focus on the application of the mindset theory of action phases in understanding the various phases of the entrepreneurial process. However, the theory does not consider that EI could precede goal setting (goal intention) as suggested by Bird (1988). In this paper, we provide the contradicting views regarding the occurrence of EI and the predicational action as well as a clear distinction between the two. Consequently, we contribute to both the EI literature and the mindset theory of action phases by developing and testing a conceptual framework to address this gap in the entrepreneurial process. Our proposed conceptual framework illustrates that the process commences with the prospective entrepreneur’s EI (a self-acknowledged conviction to start a business venture at some point in the future) which is followed by a predecisional phase in which an individual takes specific action of setting goal intentions by assessing the desirability and feasibility of their preferences (wishes or desires). Once the individual has decided on the goal (goal intention), he or she moves to the preactional and the actional phases of the EA. Second, by integrating the PsyCap components in the framework, the study provides other mechanism on how these resources may facilitate the translation of EI to EA. Through the mediating effect, the PsyCap components (specifically, hope and resilience) enhance the prospective entrepreneur’s mindset in making decisions and enable the individual to move from EI to the predecisional phase of the EA. Our framework supports the work conducted by Nolzen (2018) who postulates that hope and optimism enable individuals to positively assess the desirability and feasibility of their goals and come up with various strategies to achieve these goals. While resilience provides the capacity to persevere while trying to achieve these goals. Furthermore, these PsyCap components have been identified as important resources that influences individual’s approach to marketing. This study further argue for a synergistic relationship between the mediators as resilience enables individual entrepreneurs to adapt and change their marketing strategies based on feedback received from setbacks (Patra and Lenka, 2024), while hope provides the determination to achieve one’s goals by experimenting with different marketing strategies in response to a particular situation. Therefore, understanding and nurturing PsyCap alongside the implementation of entrepreneurial marketing strategies can significantly enhance an entrepreneur’s ability to build a successful and sustainable business (Hills et al., 2010; Karami et al. (2024). Third, this study responds to a call by McMullen and Dimov (2013) on time and the entrepreneurial journey, in which they concluded that the process through which new venture creation unfolds is a phenomenon that requires scholarly understanding. Welter and Scrimpshire (2021) add that “beyond the empirical case for the use of PsyCap in entrepreneurship and its unique distinction from financial capital, a case must be made for new insights that this construct may bring about…it is particularly important when understanding entrepreneurship as a process”. Therefore, the findings of the mediating effect of hope and resilience in the relationship between the EI and the EA phases provide novel insight in the South African context. This finding was also confirmed by the MEI literature (Hills et al., 2010). Most importantly, it enriches our understanding on the cross-cultural implications of the PsyCap components in different cultural settings. Previous studies on the influence of the PsyCap components revealed contrasting findings. Therefore, our findings support PsyCap literature which suggest that the PsyCap components are perceived differently in different socio-cultural settings (Luthans and Youssef-Morgan, 2017). Finally, traditionally EA is tested as a single construct, yet in this study we measure the different phases of EA to determine firstly which constructs belong to each of the three phases of EA. By doing so, we capture how different PsyCap components influence each EA phase. Secondly, as EA is not a one-time event but rather a series of actions over time, we contribute to the development of the EA construct and recognise the influence of time and context on EA. Finally, we capture the complexity of measuring EA as this process which may allow future researchers to measure different constructs in each phase of EA more accurately.

Firstly, by empirically testing the conceptual model developed in this study, hope and resilience were identified as important resources that may assist prospective entrepreneurs in transitioning from EI to EA. Since social entrepreneurs were also included in the sample, an important contribution of the study is that the findings not only indicate that commercial entrepreneurs should improve their hope and resilience PsyCap components if they wish to take EA, but also that social entrepreneurs should do the same.This finding can be used by social enterprise support organisations, government, policy makers and practitioners as these PsyCap components draw from entrepreneurial marketing by encouraging an entrepreneurial attitude that encourages innovation, taking calculated risks, and adaptability. By developing their PsyCap, entrepreneurs may become more adept at navigating market uncertainty and seizing new possibilities through strategic marketing strategies. Secondly, as PsyCap components may be developed, Luthans and Youssef-Morgan (2017) posit that “a typical PsyCap development intervention includes goal setting, generation of pathways, mental rehearsals of goal pursuit through various generated pathways, and contingency planning to overcome obstacle”. These are also several different actions that should be undertaken in the three action phases of the EA. Therefore, incorporating the development of the PsyCap components (hope and resilience) can assist academic institutions, business incubators and other organisations which have interest in entrepreneurship development to enhance their programme designs and training initiatives. Finally, the development of these PsyCap components may contribute to reducing prospective entrepreneur’s fear of failure, increase entrepreneurial activity rates and other socio-economic problems. By adopting a process-based approach when testing EA, this study can assist educators and policymakers in designing support systems such as funding, mentorship and training which are tailored to the different phases of EA.

No study is without limitations. Firstly, a cross-sectional survey method and a non-probability sampling technique were used on a sample of 201 existing commercial and social entrepreneurs. Since the population sample was extracted from a population which consists of a diverse cultural mix, it may limit the transferability of the findings in less complex contexts and cultures (contexts with few languages and cultures). The sample size limits the application of multi-group CFA. Future studies could include a larger sample through a probability sampling technique to allow cross-cultural comparison as well as data analysis through a multi-group CFA. Furthermore, larger sub-samples of social and commercial entrepreneurs could result in a comparison study between the two sub-samples to determine if different PsyCap components influence the EIA-gap. It would also be interesting if the same study could be undertaken using longitudinal data on a sample of nascent commercial and social entrepreneurs, following their entrepreneurial journey through the three EA phases to observe which of the PsyCap components would influence the EIA gap in a Global North context. The findings partially confirmed the hypotheses in this study, as only the mediating effect of hope could be established between the EI and the three phases and the mediating effect of resilience could only be established for the predecisional and preactional phases, and not for the actional phase. Therefore, the mediation effect of PsyCap components in the relationship between EI and the actional phases of EA could be explored in different settings and samples to compare the results. Another limitation is that although the entrepreneurial marketing literature supports the PsyCap components, future studies could empirically test the effect of specific entrepreneurial marketing strategies on the EIA gap.