Abstract
Orientation: Research on tourism entrepreneurship often generalises findings from developed markets, overlooking the unique internal environmental factors and socio-economic contexts in emerging destinations.
Research purpose: This research examines the key selected internal environmental factors affecting the probability of tourism business success in Mtubatuba Local Municipality, KwaZulu-Natal province in South Africa.
Motivation for the study: Tourism entrepreneurship is a scarce resource in South Africa, with a high failure rate among new entrants. Understanding success factors is crucial for fostering sustainable tourism businesses.
Research design, approach and method: A quantitative survey of 116 tourism business owners was conducted across Mtubatuba. Data integrity was ensured using IBM SPSS software (version 29), and an ordered Logit model was applied to identify and quantify internal environmental factors influencing business success.
Main findings: The findings suggest that education, experience, and certain internal environmental factors (such as family support and personal happiness) are critical predictors of success in tourism businesses.
Practical and/or managerial implications: The findings provide valuable insights for policymakers and stakeholders to support tourism entrepreneurship by enhancing education, fostering business understanding, promoting family engagement, and encouraging personal well-being.
Contribution and/or value-add: These findings have practical implications for policymakers and stakeholders within the socio-economic contexts of an emerging destination, aiming to support entrepreneurship and promote business success in the tourism industry. The study demonstrates that education, business understanding, family engagement in business, and motivation all significantly impact the probability of success in tourism entrepreneurship.
Keywords: tourism entrepreneurship; internal environmental factors; business success; emerging destinations; ordered logit model.
Introduction
To enable the tourism business to display success, various entrepreneurial success driver models are proposed. For instance, Lussier’s model (as cited in Elsafty, Abadir & Shaarawy 2020:62) identified 15 variables that predict business success or failure, including factors such as capital, record-keeping, planning, education, industry experience, staffing and financial control, among others. From the literature reviewed, it has been noted that there is little consistency in the literature to support, which variables statistically predict success versus failure (Elsafty et al. 2020; Hareebin 2020; Ndlovu & Sibanda 2023). The three most frequently mentioned variables according to Elsafty et al. (2020) are management experience and capabilities, human capital and planning (which includes the ability to identify opportunities). As emphasised by scholars (such as Hareebin 2020; Limsong et al. 2016), human capital (the knowledge, skills and abilities that entrepreneurs possess, which assist them in developing and growing their firms), social capital (the benefits entrepreneurs obtain from their social networks) and psychological capital are the most important factors for the successful development and growth of businesses. Rogerson (2020) recognises the tourism industry as a vibrant sector for economic development. Considering this, entrepreneurship in South Africa represents a limited economic driver, as it is not yet fully leveraged to contribute significantly to Gross Domestic Product (GDP) or broader economic development (Erasmus, Rudansky-Kloppers & Strydom 2019), and this includes tourism-related entrepreneurship. The situation in South Africa is exacerbated by the high failure rate of new tourism entrepreneurs coming into the entrepreneurship system, as borne out by the results of the Global Entrepreneurship Monitor (GEM 2023) report. It is necessary, therefore, to study success factors for tourism entrepreneurship in the South African context. Literature review indicates that good management is imperative for any business success (Fouad 2021), but South Africa is still facing the problem of low entrepreneurial activity (Mhlongo, Ntshangase & Ezeuduji 2024; Ntshangase & Ezeuduji 2023) and the high failure rate of new entrepreneurs coming into the entrepreneurship system (Iwu et al. 2024; Maziriri & Chivandi 2020). According to Hart, Bonner, Prashar, Ri, Levie and Mwaura (2020), potential entrepreneurs in South Africa lack the mindset and skills to become true entrepreneurs, especially at the early stage of entrepreneurial activities (ranging from start-up businesses to those established for 3–5 years).
Building on insights from tourism entrepreneurship literature, this research aims to deepen the understanding of key internal environmental factors that influence tourism business success probability, focusing on the Mtubatuba Local Municipality in KwaZulu-Natal, South Africa. Mtubatuba is situated near the iSimangaliso Wetland Park, recognised as a UNESCO World Heritage Site, and offers a unique context for examining tourism entrepreneurship in an emerging market. This study’s contribution lies in conceptualising the key selected internal factors within emerging destinations’ distinctive socioeconomic and cultural changing aspects, contrasting them with those observed in developed markets. Thus, by employing an ordered logit model for data analysis, the research provides innovative insights into the degrees of tourism entrepreneurship specific to Mtubatuba. The results of this study may also be helpful to policymakers and stakeholders aiming to support entrepreneurship and promote business success in the tourism industry. The following sections outline the key research questions and review relevant literature on the internal business environment. This study aims to address two primary questions (Qs) aligned with the research objectives:
Q1: What are the key internal environmental factors influencing the probability of tourism business success in the Mtubatuba Local Municipality, KwaZulu-Natal?
Q2: How do these factors reflect emerging destinations’ unique socioeconomic and cultural contexts compared to findings from developed markets?
The following section presents a comprehensive review of the literature.
Literature review
Using a variety of search engines, including ‘Ebscohost Discovery’, ‘ScienceDirect’, ‘JSTOR’, ‘Emerald’, ‘Google Scholar’, ‘SpringerNature’ and others (see Table 1), a scan of published studies shows that academic research on the internal predictors influencing business success is extensively reported and explored in the literature worldwide. There are data to conclude that certain key principles are important for business success. Despite the growing interest in entrepreneurship, existing research often falls short in applying robust statistical probability models to examine success factors specific to tourism entrepreneurship (Hart et al., 2020; Iwu et al. 2024). While many studies have explored general entrepreneurship success factors (Hassan & Ibrahim 2022; Lim & Tan 2022; Okeremi & Caesar 2023), these efforts typically lack a focus on tourism or rely on exploratory approaches rather than comprehensive statistical analyses. Furthermore, many studies are based on developed markets, where socioeconomic and cultural contexts differ significantly from those of emerging destinations. This creates a theoretical gap in understanding how internal environmental factors uniquely shape tourism business success in emerging economies (Fouad 2021; Lim & Tan 2022; Mensah & Agyapong 2023; Okeremi & Caesar 2023). The novelty of this study lies in conceptualising these factors within the distinctive socioeconomic and cultural dynamics of an emerging destination, contrasting them with insights from developed markets. This study recognises that the success of small-, micro- and medium-sized tourism enterprises (SMMTEs) is influenced by the trajectory of their business growth, which can vary based on factors such as market conditions, operational strategies and the unique characteristics of the local tourism context.
| TABLE 1: Worldwide academic research studies on factors influencing business success. |
Table 1 demonstrates that several researchers from around the world have looked into internal factors that contribute to business success; however, as each entrepreneur is different, it is still challenging to have standardised qualities or the same levels of business success (Iwu et al. 2024; OECD 2022, 2024; Patel & Singh 2023; Zhang & Li 2022). According to Iwu et al. (2024), entrepreneurs are culturally different from each other. Similarly, the cultural backgrounds of African and western tourism entrepreneurs are not the same (Iwu et al. 2024; Okeremi & Caesar 2023). Cultural norms have an impact on the levels of entrepreneurial activity in a nation or region, claim Zhang and Li (2022). The research has identified the key selected internal environmental factors as critical drivers of business success: entrepreneurial education, the type and degree of education, experience and family background oriented towards business, as well as the individual’s intentions to launch a business and their level of personal happiness. Many factors were found to be highly relevant to the current investigation. Within the context of tourism entrepreneurship, internal factors (such as educational background, family business experience and the main reasons for starting a business, like needing to survive or being unemployed) are critical in determining success (Mahmoud, Abou-Shouk & Fawzy 2019; Maziriri & Chivandi 2020; Montañés-Del-Río & Medina-Garrido 2020). One cannot overstate the importance of education, as it plays a major role in the financial success of those who own tourism-related businesses (Ntshangase & Ezeuduji 2023; Paudyal 2019; Yang 2021). The effectiveness of tertiary education in the hotel industry and how these characteristics support the development of highly skilled human resources in the sector were the subjects of a study conducted by Resmi and Atthaariq (2021).
The study by Resmi and Atthaariq (2021) emphasises the need for effective educational and training programmes to equip aspiring business owners with the knowledge and abilities needed to succeed in the very competitive field of tourism entrepreneurship. Moreover, having a family with a tourism-related business is a prerequisite for anyone hoping to enter the tourism entrepreneurship field (Dong, Peypoch & Zhang 2020; Yang 2021). Paudyal (2019) researched the career paths and strategies of academics in the tourism and hospitality industry. The study shed light on the importance of real-world experience in forming successful entrepreneurial activities (Dong et al. 2020; Paudyal 2019). The examination of results shows that entrepreneurs with prior business experience had a higher probability of succeeding in their entrepreneurial activities by using their knowledge (Paudyal 2019). In the tourism industry, necessity-driven entrepreneurship is common (Dong et al. 2020; Ntshangase 2022). People may start their businesses to make money when they have few possibilities for employment (O’Donnell et al. 2024). Williams, McCarthy and Davidson (2021) assert that entrepreneurs motivated by necessity frequently exhibit resilience and adaptability, qualities necessary for thriving in the unpredictable tourism sector. Prior studies indicate that even though these business owners might experience initial resource limitations (Williams et al. 2021), their tenacity might lead to the success of their businesses (O’Donnell et al. 2024). One major motivator for people to pursue entrepreneurship is unemployment (Mensah-Williams & Derera 2023).
Research by Lim et al. (2024) shows that people who start businesses out of need, such as those motivated by unemployment, typically have higher levels of success motivation. The pressing desire to get a constant income frequently drives this increased motivation (Muñoz, Álvarez & Baños 2023), which encourages people to put in more work and persevere in their entrepreneurial activities (O’Donnell et al. 2024). Recent research publications (e.g. Lim et al. 2024; Steiger et al. 2023; Su et al. 2020) have provided sufficient evidence of the association between an entrepreneur’s well-being and business performance. According to a study by Peters, Kallmuenzer and Buhalis (2019) and Su et al. (2020), business owners who uphold strong personal values and an optimistic outlook are better able to manage stress and make business-advancing judgements.
Tourism business internal success factors: Developed vs. emerging economies
Research on internal factors affecting tourism business success has received significant attention across developed and emerging economies (Mhlongo et al. 2024; Ntshangase & Ezeuduji 2023). However, the socioeconomic conditions, entrepreneurial motivations and structural challenges differ between these contexts, leading to varied findings and theoretical implications (Mensah-Williams & Derera 2023). In developed economies, internal success factors are often aligned with access to innovation, education and strategic management practices. For example, the study conducted by Utami, Dhewanto and Lestari (2023) in Indonesia highlights that leadership quality, innovation and financial access are critical drivers of tourism business success. Similarly, Yen, Tsaur and Yen (2024) found that innovation management and financial stability significantly influence tourism enterprises’ sustainability in Taiwan. These studies reflect well-established institutional frameworks that support tourism entrepreneurship through consistent access to capital, technology and skills development.
On the contrary, in emerging economies, the research underlines the influence of necessity-driven entrepreneurship (as evident in the study by Williams et al. 2021), human capital limitations (Mhlongo et al. 2024) and sociocultural dynamics on tourism business success (Ntshangase 2022). Iwu et al. (2024) demonstrate that education, experience and adaptability to informal market conditions are key factors driving entrepreneurial success in South Africa. Similar findings emerge in Egypt, where Fouad (2021) identifies financial management, employee skills and marketing effectiveness as critical, often constrained by resource scarcity and skill deficits. These studies reflect the systemic challenges of emerging markets, where tourism entrepreneurs face infrastructural shortages, high unemployment and limited formal education opportunities. We have noted that despite the academic progress in the tourism entrepreneurship field, critical research gaps persist.
Firstly, methodological constraints undermine the generalisability of findings. Many studies in both contexts (e.g. Achmad, Prambudia & Rumanti 2023; Muñoz et al. 2023) rely on self-reported measures of success, subject to biases. For instance, Achmad et al. (2023) emphasise personal happiness as a predictor of success but fail to account for contextual differences between western entrepreneurial ecosystems and emerging economies. This creates theoretical ambiguity regarding how psychological and educational factors interact with socioeconomic challenges in resource-limited contexts, like South Africa, especially in KwaZulu-Natal Province. Secondly, the influence of family business background and entrepreneurial experience reveals contrasting results. In developed economies, family businesses are often integrated with institutional support structures that promote intergenerational knowledge transfer (Chlosta et al. 2012; OECD 2022). In contrast, findings from emerging markets, such as South Africa (Ntshangase 2022), show only marginal benefits of family business heritage, constrained by weak institutional frameworks and limited mentorship opportunities (Ntshangase & Ezeuduji 2023). These inconsistencies highlight the need for context-specific examinations of entrepreneurial legacy and experience as predictors of tourism business success. Thirdly, necessity-driven entrepreneurship remains largely ignored in developed economies, where opportunity-driven motivations dominate (Williams et al. 2021). In emerging contexts, necessity entrepreneurship, stemming from unemployment or survival needs, plays a central role (Ntshangase & Ezeuduji 2020; O’Donnell et al. 2024). However, few studies explore how such motivations influence long-term success, particularly in tourism sectors characterised by seasonality and low-profit margins. The next section discusses the methodology used to get the study’s conclusions.
Research design and methods
This study designed as a survey employed a uniform data collection technique to ensure that the results could be compared within the positivist paradigm. It measured business success indicators using a quantitative survey. The study’s explanatory variables covered personal sociodemographic characteristics, categorised as internal environmental factors. This study focused on tourism-related entrepreneurs actively operating businesses, with an emphasis on SMMTEs. Small-, micro- and medium-sized tourism enterprises include formally registered, informal and non-VAT (value-added tax)-registered businesses (Ntshangase 2022). Formally registered businesses are officially recognised by regulatory authorities (Ryff & Singer 1996), while informal businesses (do not hold the required documentation like a business licence or a certificate of acceptability) operate without formal registration (Steiger et al. 2023; Williams et al. 2021). According to Tahir and Burki (2023), non-VAT registered businesses are formally recognised but generate turnovers below the VAT registration threshold. These businesses mostly include street trading, backyard manufacturing and home-based enterprises. Operating across tourism sectors such as accommodation, transport, visitor attractions, events and tourist services (Iwu et al. 2024; Okeremi & Caesar 2023), SMMTEs play a crucial role in local economic development within the study area. For this research, businesses with fewer than 200 employees were targeted, aligning with the definition of SMMEs in South Africa (Erasmus et al. 2019). Surveys targeted a mix of formal, informal and non-VAT registered tourism-related businesses, including street vendors, backyard manufacturers (e.g. handcrafters) and occasional home-based enterprises.
Sampling and data collection methods
The study employed non-probability sampling techniques to survey 116 respondents from both registered and non-registered tourism enterprises in Mtubatuba Local Municipality. To overcome the constraint of non-generalisability inherent in non-probability research like this, a sample size of 116 was considered adequate to cover a diverse array of viewpoints, thereby enhancing the study’s reliability. Through a survey-based approach, the research covered 32 registered and 84 non-registered tourism establishments. Approximately 90% of the questionnaires were distributed in St Lucia, Dukuduku, Khula Village, eMonzi, and the town of Mtubatuba (including Riverview), while 10% were distributed in rural areas like KwaBhoboza and KwaSomkhele.
A sum of 250 surveys were disseminated from ‘March to November 2023’; nevertheless, 186 surveys were completed by February 2024. Following data refinement, the investigation was left with 116 surveys for analysis. The inability to increase the sample size stemmed from challenges in engaging business owners and managers to respond to the surveys. Given the relatively limited number of tourism-focused entrepreneurs in this region compared to larger urban centres like Durban or Richards Bay in KwaZulu-Natal, South Africa (Ntshangase 2022), the scholars posited that this sample size, obtained without the use of probability sampling methodologies, sufficed for drawing inferences about the research aims. An agreement was established in specific research sites between researchers and stakeholders in the tourism sector to permit the distribution and retrieval of questionnaires on a biweekly basis (fortnightly drop-and-collect methods). In other cases, the researchers distributed surveys directly, waited for completion and assisted respondents where needed, including reading out or recording responses.
To ensure understanding among all respondents who were not proficient in English, the surveys were translated from English to isiZulu, the local vernacular language. For individuals with reading difficulties, the questionnaire was orally presented in isiZulu. Among the researchers, one is fluent in English, while the other is fluent in isiZulu. This approach aimed to mitigate issues such as inaccurate or incomplete translations, which could potentially lead to the distortion of intended nuances in the research or the alteration of a question’s original meaning. The suitability of the ordered logit model for ordinal dependent variables was acknowledged (Otekunrin et al. 2021), as it was used to detect and assess the internal factors driving entrepreneurship in the tourism sector (Otekunrin et al. 2021). Logistic regression was applied to construct the empirical model using primary data obtained from a structured questionnaire distributed to a sample of 116 purposively chosen tourism enterprises, both registered and unregistered. The adoption of the ordered logit model was essential because of the ordinal nature of the dependent variables, which assessed entrepreneurs’ success levels. As outlined by McCullagh (1980), the use of a multinomial logit model reduces estimation accuracy by disregarding the ordinal structure of the data. Nevertheless, the multinomial logit model cannot be invalidated if parameter estimates are equivalent (Hausman & McFadden 1984).
Research instrument and ethical considerations
The survey was designed based on a conceptual framework and previous empirical studies on business success (Muñoz et al. 2023; O’Donnell et al. 2024; Steiger et al. 2023; Williams et al. 2021) and includes the level of education (Ntshangase, Ezeuduji & Ayanwale 2024), years of business experience, family business background (Ntshangase & Ezeuduji 2020), entrepreneurial motivation for entering tourism-related businesses and an individual’s level of happiness. The questionnaire contained five dimensions of internal factors that may influence business success. The survey consisted of close-ended matrix questions to save respondents’ time and improve response comparability (Chawla & Sondh 2011), with each construct measured by eight items. The survey used a 5-point Likert scale (1: strongly agree to 5: strongly disagree). Approval to conduct this study was granted by the Faculty of Humanities and Social Science Research Ethics Committee at the university in 2022 (UZREC 171110-030-PGD-2022/73). In addition, the gatekeeper permission letter was granted by Mtubatuba Local Municipality. Respondents were fully informed of the study’s purpose and objectives before participation, ensuring ethical compliance and transparency throughout the data collection process.
Model specification
Within the framework of ordered logit analysis, the estimation of an inherent score involves a linear combination of independent variables and a series of threshold values. The likelihood of observing a specific outcome i is defined as the probability of the calculated linear combination, increased by a stochastic element, falling within the predetermined range of threshold values assigned to the outcome, as follows (Equation 1):
j = 1, …, J
where the error term uj follows, by assumption, a logistical distribution in ordered logit, β1…βk are the unknown slope coefficients to be estimated and x1 … xk are the corresponding explanatory variables. The unknown coefficients are estimated simultaneously with the cut-points κ1… κk–1 where κ denotes the number of possible outcomes. Noteworthy is that x0 is regarded as –∞, while xk is viewed as +∞, which is a direct generalisation of the standard two-outcome logit specification. In Equation 2 the probability of each observation is given by
where pij denotes probability and the remaining terms are as defined before. This study estimated the ordered logit model using the maximum likelihood technique whose log likelihood is given by
where wj wis an optional weight and
The study’s explanatory variables and their description are presented in Table 2. In general, they combine personal sociodemographic characteristics, defined as internal environmental factors guided by both statistical tests and empirical literature. These factors include the level of education, number of years in business (or business experience), family business background, motivation for engaging in tourism-related business and one’s level of happiness.
| TABLE 2: The study’s explanatory variables and their description. |
Table 2 lists the factors that were used to describe each and show whether they should have a positive (+) or negative (−) impact on entrepreneurial success. For example, the impact of gender on achievement can differ depending on social standards and the availability of resources (Mahmoud et al. 2019). Success is anticipated to be positively impacted by education and experience, as these factors are typically associated with greater resources, knowledge and abilities (Mahmoud et al. 2019; Montañés-Del-Río & Medina-Garrido 2020).
Ethical considerations
Ethical clearance to conduct this study was obtained from the University of Zululand Research Ethics Committee (No. UZREC 171110-030 PGD 2022/73).
Results
The study begins with a basic summarisation of probabilities for each level of business success (Table 3).
| TABLE 3: Summary statistics – probabilities of tourism business success. |
Table 3 presents summary statistics of the probabilities associated with different levels of tourism business success, ranked from ‘unsuccessful’ to ‘very successful’. The results are based on 116 observations. The results highlight that most tourism businesses in Mtubatuba Local Municipality fall into the ‘surviving’ category, with fewer achieving ‘successful’ or ‘very successful’ statuses. The wide range in the latter categories suggests the potential for growth and varying levels of achievement among tourism businesses.
The researchers countered heteroscedasticity in cross-sectional data by using an ordered logit model with resilient standard errors to evaluate the influence of environmental factors on the chance of business success. Based on lower Akaike Information Criterion (AIC) values, the ordered logit model was chosen over the ordered probit model (Bozdogan 1987). Using a general-to-specific modelling technique, we used a stepwise regression strategy to eliminate unimportant variables while preserving parsimony and preventing overfitting. Positive coefficients on explanatory variables raised the probability of higher success rankings, according to our dependent variable, a ranked binary indicator of entrepreneurial success. Table 4 showcases the ordered logistic regression results on internal factors affecting tourism-related businesses, obtained from the regression modelling and diagnostic testing.
| TABLE 4: Ordered logistic regression – internal factors affecting tourism-related businesses. |
Discussion
Education and tourism business success
Table 4 shows education as a dummy variable, with no western (or formal) education as the baseline. The treatment groups consist of respondents with primary, secondary and tertiary education levels. The coefficients for each group show how an education degree influences the likelihood of success in tourism entrepreneurship. The results demonstrate a positive association between education level and success likelihood (Baah & Rambe, 2024; Ntshangase & Ezeuduji, 2023), with coefficients significant at the 5% level for primary education and at the 10% level for secondary and tertiary education. The basic education coefficients change from 0.855 to 1.045, with odds ratios between 2.35 and 2.84. This suggests that those with a primary education are 2–3 times more likely to succeed than those without western education. Consistent with past predictions, individuals with secondary and tertiary education have a larger chance of success than those with primary education (Dlamini 2022; Sang, Alexander & Anwar 2023). Respondents with secondary education had odds ratios ranging from 4.246 to 5.859, indicating that they are up to six times more likely to succeed than those without western education. The odds ratios for tertiary education vary from 5.847 to 7.752, indicating a 6–7 times greater likelihood of success.
These findings emphasise the increased likelihood of success with higher education levels (Sang et al. 2023). Alternatively, probabilities and the lower-end cutoff score provide similar insights. In contrast, developed economies often demonstrate a more robust baseline effect of education on tourism entrepreneurship. Dlamini (2022) and Sang et al. (2023) report similar trends but highlight additional factors such as advanced technical training, access to technology and a supportive regulatory environment that complements education’s impact. In developed contexts, tertiary education often provides a greater advantage because of exposure to sophisticated business strategies and access to resources such as funding and mentorship. The odds ratios supported by Sang et al. (2023) for tertiary education (5.847–7.752) align with findings from emerging economies but often come with a greater emphasis on innovation and scalability.
For holders of tertiary qualifications, using model 1 as an example, the probability of being unsuccessful is technically the probability of 2.048 + uj ≤ –0.986 or equivalently uj ≤ –3.034, which, given knowledge of the logistic distribution (1/1+e3.034), yields 4.59%. For those with no western education, which is the baseline group, the probability of being unsuccessful is the probability that uj ≤ –0.986, which is much higher at 27.17% relative to the 4.59% observed for those with tertiary education. In other words, respondents with no western education have a higher probability of being unsuccessful (27.17%) than those with tertiary education whose probability of failure is only 4.59%. Many studies, including Dlamini (2022), support the conclusion that education improves business success. It supports Bauman and Lucy’s (2021) claim that education gives critical managerial and decision-making skills.
Experience and tourism business success
Individuals with 1–3 years of business experience form the baseline group. The positive and significant coefficients for longer experience demonstrate that experience is critical for business success. Table 4 demonstrates that respondents with 4–6 years of experience are at least twice as likely to succeed as those with 1–3 years. As one gains more experience, the effect grows stronger, as expected. The findings suggest that those with 7–9 years and 10 years or more of business experience are 2.5 times and 5 times more likely to be successful than those with 1–3 years of experience, respectively. In principle, this study confirms the key work of Becker (1964) whose thesis highlighted the dominating significance of work experience in gathering the skills and information required to successfully build a business. Furthermore, Shirima (2022) and Dlamini (2022) have recently suggested a theoretical framework emphasising the importance of business experiences for entrepreneurs as a precursor to business success. The data in Table 4 support this claim.
This study confirms that, across both contexts, the positive relationship between business experience and success likelihood remains consistent. However, in emerging economies, experience compensates for gaps in formal education (Shirima 2022), limited access to capital and weaker institutional support, making it a more critical determinant of success (Dlamini 2022). In developed economies, according to Bauman and Lucy (2021), the combination of experience with other resources such as technology, financial support and market networks further increases business success. Therefore, we advocate that while experience is universally important, its interplay with other internal factors varies significantly between developed and emerging economies.
Family business background and tourism business success
A family business background was included to capture the potential derivative component of success that may result from having a family business background. Individuals without tourism-related business owners in their family received value 1 (i.e. the treatment group), whereas those with tourism-related business owners in their family were classified as the baseline group. Researchers find evidence, notably in the last two regression variations, that persons without tourism-related business owners in their families are less likely to succeed than those with tourism-related business owners, but the effect is marginally significant. This finding is experimentally compatible with Wyrwich (2015), and it supports the theoretical notion that family business ownership heavily influences a child’s career choices, as most children tend to follow their parent’s footsteps. According to Chlosta et al. (2012), parents can be role models for children to the extent that individuals from business-oriented families tend to have higher social and human capital because of the experience, skills and knowledge required to manage a business gained through participation in family business management. The findings in Table 4 support this hypothesis, which is positive. Motivation was entered as a dummy variable, with those looking for a tourism business opportunity as the treatment group and those motivated by unemployment as the baseline. The findings demonstrate no significant difference at the 10% level, implying that opportunity-driven and necessity-driven entrepreneurs have identical success rates. This could be because both types are equally committed to success. Interestingly, individuals who are happy with their business are 2.5 times more likely to succeed, which is consistent with the positive association between happiness, morale and productivity, all of which are important determinants of business success (Baah & Rambe, 2024; Ntshangase, 2022). The findings highlight that internal business factors such as education, years of experience and family business background play a critical role in tourism business success, particularly in emerging destinations like Mtubatuba in South Africa, where limited access to resources and informal business operations are prevalent. These results align with the socioeconomic challenges and opportunities observed in emerging markets, which differ significantly from developed economies.
Theoretical implications
The results confirm the theoretical assertion that education is a crucial factor in the success of tourism-related entrepreneurs (Peters et al. 2019; Manalu, Simatupang & Novani 2024; Muñoz et al. 2023; O’Donnell et al. 2024; Steiger et al. 2023; Williams et al. 2021). This is evidenced by the positive coefficients associated with primary, secondary and tertiary education, showing that higher educational levels significantly enhance the probability of success in tourism entrepreneurship. These findings align with prior research that underscores the significance of education in providing entrepreneurs with the necessary managerial and decision-making competencies to achieve success in their enterprises (Bauman & Lucy 2021). The positive and statistically significant coefficients related to years of professional experience reinforce the theoretical framework introduced by Becker (1964), emphasising the vital role of business experience in acquiring the expertise and knowledge critical for entrepreneurial achievement.
The rising likelihood of success associated with each level of experience confirms that practical exposure contributes to an entrepreneur’s capacity to overcome complications and effectively leverage opportunities. This finding is particularly pertinent in emerging destinations, where experiential knowledge allows entrepreneurs to adapt to fluctuating market conditions, respond to diverse tourist preferences and engage with local communities effectively. According to Mensah-Williams and Derera (2023), such capabilities are vital for building sustainable tourism ventures in regions undergoing rapid development or transition. The marginally significant coefficients linked to a background in family business provide empirical support for the theory suggesting that family business ownership significantly impacts individuals’ career decisions and provides them with valuable experience, competencies and knowledge essential for managing businesses (Chlosta et al. 2012). However, in emerging destinations, the impact of family business experience may extend beyond mere knowledge transmission (Fouad 2021; Utami et al. 2023). It can foster social capital and trust within local communities, enabling entrepreneurs to establish partnerships (Achmad et al. 2023; Yen et al. 2024) and access resources that are otherwise difficult to obtain in less formalised economic environments. This suggests the importance of leveraging familial and communal networks in contexts where institutional support for entrepreneurship is limited, as stated by Iwu et al. (2024).
Beyond these traditional determinants of entrepreneurial success, the study highlights the need to consider the interplay of cultural attitudes, psychological resilience and innovation capacity, especially in emerging destinations. These factors may mediate or even amplify the effects of education and experience (Mhlongo et al. 2024; Ntshangase & Ezeuduji 2023), as entrepreneurs in such contexts often operate in environments characterised by uncertainty and rapid change. Furthermore, the findings suggest the potential for integrating context-specific entrepreneurial training programmes that blend formal education with experiential learning and mentorship tailored to the unique dynamics of emerging destinations. Such initiatives could provide a more holistic approach to fostering entrepreneurial success and sustainability. This finding underscores the transmission of entrepreneurial skills across generations within family-run enterprises.
Practical implications
Policymakers and players in tourism entrepreneurship should prioritise efforts that aim to improve entrepreneurs’ educational achievements. Investments in educational and training programmes tailored to the needs of future entrepreneurs have the potential to improve the overall competitiveness and sustainability of tourism-related businesses (Montañés-Del-Río & Medina-Garrido 2020). Tourism entrepreneurial assistance programmes should provide mentorship and experiential learning opportunities to help prospective and early-stage entrepreneurs develop practical skills and knowledge. Mentorship programmes that pair new tourism entrepreneurs with seasoned industry professionals can provide useful insights and help in navigating the challenges of running a business. Recognising the importance of a family business heritage in entrepreneurial success, efforts should be made to promote the continuation of family-owned tourism businesses (Mahmoud et al. 2019). Providing incentives for intergenerational entrepreneurship and facilitating succession planning can help to protect and use the knowledge and skills accumulated inside family businesses. Given the documented link between personal well-being and business success, tourism-related entrepreneurs and business owners should prioritise measures targeted at increasing employee satisfaction and well-being. Establishing an encouraging work environment, inspiring a good work–life balance and cultivating a positive business culture can all help to boost morale, productivity and, ultimately, business success.
Conclusion
The study demonstrates that education, business understanding, family engagement in business and motivation all have a significant impact in determining the probability of success in the sector of tourism entrepreneurship. Higher levels of education correlate positively with increased success rates, as evidenced by the comparative success of individuals with primary, secondary and tertiary education versus those without a western educational background, with the latter group having the lowest chance of success. Tertiary education has the highest probability of success. Gathered business experience is regarded as important, as success rates tend to increase in line with the number of years of experience, emphasising the need for learning through practical exposure. A family of tourism-related businesses moderately increases the likelihood of success, validating the view that family business ownership offers valuable social and human capital experience. Furthermore, the data show that there is no significant difference in success rates between persons motivated by opportunity and those motivated by necessity to pursue entrepreneurship, implying that both motivational variables might provide similar results. However, obtaining personal happiness from one’s business enterprise considerably increases the probability of success. These findings emphasise the critical importance of education and experiential learning in the dominion of entrepreneurial activities, as well as the beneficial influence of family business backgrounds and personal happiness on achieving positive entrepreneurial outcomes in the tourism industry.
Recommendations
Based on the findings of the ordered logistic regression analysis on factors affecting tourism-related businesses, several actionable recommendations can be proposed:
- Policymakers should concentrate on funding education and training initiatives that are specifically designed to help the tourism industry develop its entrepreneurship abilities, given the strong correlation that exists between educational attainment and business success. Potential initiatives could involve making business management courses, mentorship programmes and vocational training available to prospective business owners.
- As experience is a key factor of success, initiatives to encourage chances for people to obtain real-world experience in the tourism sector should be supported. Networking events, apprenticeships and internship programmes can help existing and upcoming entrepreneurs acquire new skills and transmit existing expertise.
- Policymakers should consider introducing assistance programmes for succession planning inside family-owned tourism businesses, given the inconsistent findings of family business backgrounds. To ensure success and continuity, this may entail offering tools and advice on the transfer of knowledge and skills between generations.
- More research could examine the complex dynamics of entrepreneurial motivation within the tourism industry, even while business motivation factors such as survival and unemployment did not show any significant connections with success. The establishment of specialised support services and interventions can be influenced by an understanding of the fundamental causes of entrepreneurial behaviour.
Limitations and future research
The study has a cross-sectional design that limits the ability to determine the cause-and-effect relationships between variables. More reliable proof of underlying links would come from experimental or longitudinal research designs. Undertaking long-term research to track the development of tourism-related businesses could provide important information on sustainability and the long-term factors that determine success in the industry. Longitudinal data analysis can help identify important turning points, trends and patterns in the entrepreneurial process. Analytical comparisons across cultural and geographic contexts can improve our understanding of the contextual factors affecting business success in the tourism sector. Comparative analyses can highlight unique obstacles, best practices and lessons that can be applied to encourage entrepreneurship in a range of contexts.
Acknowledgements
We would like to offer our heartfelt gratitude to everyone who helped us complete this study. We are grateful for the cooperation and participation of the tourism-related business owners and managers who graciously offered their experiences and perspectives.
Competing interests
The authors declare that they have no financial or personal relationships that may have inappropriately influenced them in writing this article.
Authors’ contributions
S.D.N. contributed to the conceptualisation of the research, carried out the investigation and was primarily responsible for drafting the original manuscript. I.O.E. provided supervision for the project, developed the methodology, conducted the analysis and validation of the findings and contributed to reviewing and editing the manuscript to ensure its accuracy and clarity.
Funding information
This research received no specific grant from any funding agency in the public, commercial or not-for-profit sectors.
Data availability
All data that support the study and findings are available in this research article and references.
Disclaimer
The views and opinions expressed in this article are those of the authors and are the product of professional research. It does not necessarily reflect the official policy or position of any affiliated institution, funder, agency or that of the publisher. The authors are responsible for this articl’s results, findings and content.
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