Culture, entrepreneurial intention and entrepreneurial ecosystems: evidence from Nelson Mandela Bay, South Africa

Abstract

Purpose

Contemporary entrepreneurial ecosystem models and frameworks advocate that culture is a criterion for entrepreneurial intention and central to entrepreneurship discourse. However, there is limited research from resource-constrained economies, such as sub-Saharan Africa and at a sub-national level. Responding to calls for bottom-up perspectives hinged on local context and heterogeneous nature, this paper aims to provide an in-depth understanding from multiple perspectives about the effect that culture and entrepreneurial intention have on the entrepreneurship process and performance in Nelson Mandela Bay, South Africa.

Design/methodology/approach

A mixed-method research design followed a sequential independent process consisting of two phases. Phase 1 included the dissemination of questionnaires to economically active participants, and 300 responses were statistically analysed. In Phase 2, 15 semi-structured interviews with influential economic development agents were conducted.

Findings

The results indicated that social legitimacy towards entrepreneurship existed and self-employment was viewed positively. However, self-employment endeavours were mainly necessity driven, and the systemic low levels of innovation, poor business competitiveness and the inability to scale were highlighted. The findings indicated that individuals venturing into business had a culture of being dependant on the government, lacking a risk appetite, fearing failure, with disparate groups suffering from a poor legacy of entrepreneurship.

Originality/value

Despite research done on the role of culture and entrepreneurial intention on entrepreneurial ecosystems, there are few case studies showing their influence at a sub-national level. This study responds to calls for studies on a sub-national level by exploring the influence that culture and entrepreneurial intention have on entrepreneurship in a resource-constrained metropole.

Citation

Boucher, S., Cullen, M. and Calitz, A.P. (2023), "Culture, entrepreneurial intention and entrepreneurial ecosystems: evidence from Nelson Mandela Bay, South Africa", Journal of Entrepreneurship in Emerging Economies, Vol. ahead-of-print No. ahead-of-print. https://doi.org/10.1108/JEEE-05-2022-0156

1. Introduction

Entrepreneurial ecosystems have become the modus operandi for future market-orientated industrial policy and value creation (Mason and Brown, 2014; Brown and Mawson, 2019). Various models, frameworks and perspectives of entrepreneurial ecosystems have accepted the presence of the entrepreneur as the central actor who operates in an environment with various conditions that legitimise the system within a range of socio-economic, institutional and informational contexts (Audretsch and Belitski, 2017; Bosma et al., 2019).

Literature on entrepreneurial ecosystems has argued that the legacy of entrepreneurship in a specific location stimulates the motivation to undertake an entrepreneurial venture and supports fast-failure (Isenberg, 2010; Feld, 2012; Spigel, 2017; Fritsch and Wyrwich, 2018; Spigel and Vinodrai, 2020). In fact, Iftikhar et al. (2020) underline the significance of culture and social practices as facilitators or hindrances for economic activity. Thus, shaping societal attitudes and influencing individual ambitions towards starting a business (Aleksandrova et al., 2019; Bowmaker-Falconer and Meyer, 2022).

In a study on Waterloo, Canada’s entrepreneurial ecosystem, Spigel and Vinodrai (2020) advocate that the region has a strong culture of trust and co-operation between entrepreneurs and community leaders. Similarly, Feld (2012) argued that Boulder’s success in Colorado, USA, was due to a culture of co-operation over competition. In the study, entrepreneurs shared knowledge and expertise while espousing failure as an opportunity. In a comparative study conducted by Kilroy (2014) on competitive cities, the author highlights how competitors in Gaziantep, Turkey, lobbied for infrastructure upgrades, which showed co-operation. Based on these examples, the potential impact of the perception of a location’s culture, which may be viewed through trust and co-operation, offers implications for a location. These implications may underscore the way the location is viewed by entrepreneurs, investors and skilled workers.

Despite the popularity of the entrepreneurial ecosystem phenomenon, research studies lack both a theoretical underpinning and have insufficient data at a sub-national level (Stam, 2015; Roundy and Fayard, 2018). Limited data at the sub-national level prevent regions from exploiting location-based infrastructure, knowledge, capabilities and specialisms to promote a regional competitive advantage (Bailey et al., 2018). Spigel et al. (2020) research paper: A manifesto for researching entrepreneurial ecosystems explain that existing data are limited to national levels, but ecosystems function on a city, city-region or regional level. The manifesto brings attention to a consensus from policymakers who underlined the importance of combining quantitative and qualitative inquiries, which can contribute to economic development policies and the entrepreneurship process (Spigel et al., 2020).

Against this background, this study provides a sub-national inquiry about the culture and entrepreneurial intentions in Nelson Mandela Bay, which is one of eight metropolitan regions in South Africa. Thus, contributing to the gap in research by addressing a real-world context by combining findings from quantitative and qualitative approaches from stakeholders in the metropole. The methodological approach provided evidence of the culture and intention in the metropole to understand its influence on the ecosystem, with attention given to the heterogeneous nature of the location and institutional context.

The methodological approach presents the interplay of the local social and cultural factors with the individual attributes of entrepreneurs in the metropole. Arguably, the integration with the qualitative expert interviews support arguments by Isenberg (2010) and Feld (2012), who explicate the importance of engaging stakeholders supporting entrepreneurship to understand the needs of entrepreneurs. In addition, this paper provides insights to policymakers who may struggle with perception bias about the social and cultural factors, which support entrepreneurial development.

The layout of the paper is as follows: firstly, in Section 2, the entrepreneurial ecosystem is conceptualised by presenting definitions, frameworks and models. Thereafter, a literature review of theories, culture, entrepreneurial intention and the type of entrepreneurialism in South Africa is provided (see Section 3–5). Thirdly, in Section 6, the methodological process that was followed is presented by discussing the mixed-method research design and the quantitative and qualitative phases. Fourthly, in Section 7, the results of each phase are presented followed by the integration of the data sets. The remainder of the paper provides a discussion, which presents the main findings, limitations and future research (Section 8). Finally, in Section 9, conclusions are provided.

2. Conceptualising the entrepreneurial ecosystem – definitions, models and frameworks

The entrepreneurial ecosystem concept dates back more than three decades (Malecki, 2018) gaining wider interest in the past few years (O’Connor et al., 2018; Stam and Van De Ven, 2019). Most definitions regarding the entrepreneurial ecosystem share the view of interacting actors and factors that reinforce entrepreneurship within a geographical boundary (Borissenko and Boschma, 2016; Roundy, 2017; Mack and Mayer, 2016; Malecki, 2018). The actors are defined by Mason and Brown (2014) as entrepreneurial actors, entrepreneurial organisations, institutions and entrepreneurial processes, which formally and informally coalesce to connect, mediate and govern the performance within the local entrepreneurial environment. These interacting actors and factors are human-constructed systems, and their diversity is the result of intentional actions, shared goals and behaviours of the actors, which induces productive economic gains (Acs et al., 2017; Stam, 2015; Stam and van de Ven, 2019).

In light of the various definitions pertaining to an entrepreneurial ecosystem, it may be broadly explained as an organised set of interdependent components (actors and factors) that enable productive entrepreneurship within a specific location (Isenberg, 2011; Stam, 2015; Acs et al., 2017; Brown and Mason, 2017; Stam and Van De Ven, 2019). The actors are seen as communities of independent actors, such as government, universities, mentors, service providers, media and large organisations (Hechavarría and Ingram, 2019). These actors play a significant role in the development of entrepreneurship in a specific location.

The definitions highlight the central role of the entrepreneur as creators of new ventures and the result of entrepreneurship may reflect both successful or failed businesses (Bosma et al., 2019). Entrepreneurs are expressed as actively seeking opportunities, and the output may be in the form of innovative start-ups, high growth start-ups and entrepreneurial employees (Stam, 2014, 2015; Bosma et al., 2019). Failed ventures may be recycled back into the ecosystem through an economy of experience lens. The economy of experience lens refers to the experience acquired by these failed entrepreneurs, who can spillover their knowledge and expertise into the system.

There are several models and frameworks of entrepreneurial ecosystems (Stam, 2015; Brown and Mason, 2017; Malecki, 2018). A key feature of entrepreneurial ecosystems is presented through their actors and factors that network within a set of preconditions with the aim of new venture creation, innovation and the development of new sectors. The models and frameworks, which informed this study were the Attributes of the Entrepreneurial Ecosystem (Spigel, 2015), Elements and Outputs of the Entrepreneurial Ecosystem (Stam and Van De Ven, 2019) and the Global Entrepreneurship Monitor (GEM) Conceptual Framework (Bosma et al., 2019).

The attributes of the entrepreneurial ecosystem model include cultural (cultural attitudes and histories of entrepreneurship), social (networks, investment capital, mentors and dealmakers and worker talent) and material (universities, support services and physical infrastructure, policies and governance and strong local markets) attributes. Spigel (2015) argues that a supportive culture and histories that advocate a positive view of entrepreneurship are crucial to developing dense networks and fostering entrepreneurial policies and programmes.

In the elements and outputs of the entrepreneurial ecosystem framework, Stam and Van de Ven (2019) suggest two layers before the output layer of productive entrepreneurship: the institutional arrangement and the resource endowment layer. The institutional arrangements layer represents foundational aspects, such as formal institutions, culture and networks. These are the preconditions that create the supportive environment that provides the foundation for entrepreneurial activity. The resource endowment layer includes factors, such as physical infrastructure, demand, intermediaries, talent, knowledge, leadership and finance.

The GEM conceptual framework guides entrepreneurial activity against a set of preconditions (Bosma et al., 2019). These preconditions include the social, cultural, political and economic context within a spatial location. In addition, the framework considers individual and societal values as moderating variables. Individual attributes describe an individual’s perception of an opportunity and the ability to act on an opportunity, while societal values focus on the shared understanding in a community that either encourages or discourages entrepreneurship.

3. Theoretical framework

3.1 Institutional theory

Institutional theory describes how the formal and informal institutions in a specific location shape the intention and motivation of individuals to undertake new ventures (Boucher et al., 2021). Formal institutions include government policies, laws and regulations that facilitate economic, social and political interactions (Bosma et al., 2018; Fritsch and Wyrwich, 2018; Fuentelsaz et al., 2019). Informal institutions include the culture, social norms, social practices and shared community values (North, 1990; Mason and Brown, 2014; Bosma et al., 2018; Tehseen and Anderson, 2020).

Formal institutions are argued to have the ability to reinforce or weaken local economic development (Fuentelsaz et al., 2019) and the institutional structures shape agencies and business dynamism within a location (Fritsch and Wyrwich, 2018; Fritsch et al., 2019). For example, South Africa suffers from low business dynamism and competitiveness because of insolvency regulation and administrative burdens, such as the onerous processes to start a business (Schwab, 2019). In contrast, the Rwandan Government has supported entrepreneurship through focused efforts, such as business friendly policies, easier tax repayments and easier access of construction permits, among others. These efforts have allowed Rwanda to improve their ranking to 38th position out of 190 countries in the world in terms of ease of doing business, and have become desirable for investors (The World Bank, 2019; Trading Economics, 2019).

The cases of developing economies, such as South Africa and Rwanda, explicate the importance of understanding how institutional structures shape agencies in the entrepreneurial ecosystem (Fritsch et al., 2019). The concept of reinforcement is linked to high quality government bureaucracy and policy, which does not restrict entrepreneurial intention. According to Porter (1990, 1998), OECD (2007) and Saeedikiya et al. (2022), businesses with onerous regulatory compliance reduce the incentive to start a business, and poor economic freedom reduces innovation capacity. In fact, the OECD (2019) argues that “red tape” is more expensive for small businesses than big businesses, which reinforces the notion that formal institutions can either aid or hinder entrepreneurial activity.

On the other hand, informal institutions are often referred to as a catalyst for entrepreneurial attitudes, risk-taking and collaboration (Fritsch and Wyrwich, 2018; Fritsch et al., 2019). In Scott’s (2008) seminal work, he categorises the informal institutions into normative and cultural-cognitive pillars. Normative refers to the societal norms and values that govern societal choices, while cultural-cognitive refers to the shared understanding among the community in a location. Entrepreneurial motivation is reflected in the normative-cognitive layer and is as a result of the acceptance of self-employment and entrepreneurship (Isenberg, 2011; Roundy, 2017; Fritsch and Wyrwich, 2018; Aleksandrova et al., 2019). The cultural-cognitive layer elevates the status of entrepreneurship (Scott, 2008) and Boucher et al. (2021) explain that societies that tolerate failure share an understanding that failure is a learning opportunity. However, certain societal structures can influence the level of entrepreneurial activity within a sub-national context.

Tucker (2010) conducted a longitudinal study of peasant-entrepreneurs in Goremo, which is located in the Cappadocia region of Turkey. He presents findings about their endogenous power that influenced entrepreneurial activity in the tourism business sector. Peasants, within the context of the study, are conceptualised by focusing on subsistence while trying to control their means of production, which is associated with guarding their societal norms (Johnson, 2004). Their level of collaboration ensured independence of the market economy and the benefits associated with economies of scope were less important when compared to their societal norms and values.

In a study by Montiel Mendez and Pelly (2021), which focused on a heterotopian context in Viall Ahumada (VA), a subspace nearby the Mexico-USA border, revealed that the space was not willing to develop rural entrepreneurial activity. Despite the opportunity for personal and economic development, an antisocial capital (poor group dynamics in support, trust or reciprocity) existed, which is referred to as deviant heterotopias. The authors indicate that VA has location-based resources; however, the extent of the antisocial capital leads to what Tucker (2010) refers to as a “limited good” attitude, which refers to a situation where no cohesiveness is present between residents. The findings underscore the power of context insofar that the question regarding how rural enterprising relates to the rural context (Gaddefors and Anderson, 2019).

Despite the general views of institutions, each region is very unique with regard to entrepreneurial behaviour, innovation capacity and new venture creation (Fritsch et al., 2019). Thus, the use of institutional theory aids as a conceptual lens to determine the institutional and social structures in Nelson Mandela Bay, South Africa.

3.2 Theory of planned behaviour

Bird (1988) explains that the ideas and intentions of entrepreneurs guide new venture creation. The argument herein is that intention, which is the initial step towards venture creation, transforms ideas into products and services. The commonly used theory to predict entrepreneurial intention, which is well supported by empirical evidence, is Ajzen’s theory of planned behaviour (TPB) (Engle et al., 2010; Moriano et al., 2012; Farrukh et al., 2018).

The TPB, which is a social-cognitive model, focuses on the individual’s attitude, subjective norms and perceived behavioural control to determine intention and behaviour (Ajzen, 1991). The theory has successfully been applied in both developing and developed country-contexts (Engle et al., 2010) and cultural variation was a distinct moderating influence in subjective norms (Moriano et al., 2012; Hassan and Shiu, 2017; Tehseen and Anderson, 2020; Fleck et al., 2021).

In light of the aforementioned, TPB is commonly associated with entrepreneurial intention studies; however, Valliere (2015) explains that studies ignore evidence of effectuation of aspirant entrepreneurs. Sarasvathy (2001) brings attention to entrepreneurs as a product of someone who had an idea and leveraged contingent opportunities (by choosing the quickest and most efficient method) to satisfy an aspiration, which emerged through economic decision-making. Thus, effectuation describes that at the founder/decision maker level, there is no form of strategic planning beforehand, such as market research or surveys to drive insights before selling a product or service, but an imagination and aspiration were present.

3.3 Resource-constraint version of the disadvantaged theory

The resource constraint version of the disadvantaged theory of entrepreneurship argues that destitute groups of society become necessity-based entrepreneurs in response to disadvantages in the labour market (Light and Karageorgis, 1994). Generally, destitute individuals respond to unemployment by becoming micro-entrepreneurs to sustain themselves, and they remain informal. This sector undertakes economic activities, but it is not subject to government regulation, taxation or protection. Thus, micro-enterprises are not growth-orientated and innovative, which relates to the economic stagnation of South Africa as seen by the gross domestic product (GDP) per capita growth (annual percentage) of −8.137% (The World Bank, 2020). Despite the inability of micro-enterprises to scale, they are reported in total entrepreneurial activity in countries and unrelated to mainstream businesses. The resource-constraint version of the disadvantaged theory is applied to understand entrepreneurial intention in South Africa as a large share of businesses operate as own-account workers within the informal sector.

4. Culture and entrepreneurial intention

Culture is argued to exert a strong role in developing entrepreneurial attitudes and behaviour within a particular context (Fritsch and Wyrwich, 2018; Fritsch, Obschonka et al., 2019; Fleck et al., 2021; Saeedikiya et al., 2022). Seminal work conducted by Krueger and Brazeal (1994) explained that a shared understanding in the community encourages or discourages entrepreneurship, insofar as it influences the perceptions and desirability thereof. This reveals that culture acts as a catalyst for risk-taking and collaboration.

Cultural and social norms in favour of self-employment usually indicate that an adequate number of entrepreneurial role models exist in a location (Fritsch and Wyrwich, 2018), thus, supporting the elevation of the social status of entrepreneurship. For instance, cities such as London and Berlin have developed an admired image for entrepreneurs in comparison to the Mediterranean which views entrepreneurship as a less favoured option (European Digital City Index, 2016). The admiration of entrepreneurship supports the tolerance of failure and generates new competencies that support entrepreneurs to become mentors or advisors and recycle their expertise and learnings (Spigel and Vinodrai, 2020).

Spigel and Vinodrai (2020) argue that an entrepreneurial culture drives entrepreneurial intention and affords resource endowments, such as entrepreneurial finance and competencies through the supporting infrastructure for new products and services (Woolley, 2017). The resource endowments are a result of the social legitimacy of entrepreneurship (Fritsch and Wyrwich, 2018; Aleksandrova et al., 2019). The social legitimacy of entrepreneurship in a location creates a demand for local goods and services (Porter, 1990). Social legitimacy may be attributed to the legacy of entrepreneurial traditions within a specific spatial location (Aleksandrova et al., 2019; Fritsch et al., 2019; Fleck et al., 2021). Ultimately, the social legitimacy of entrepreneurship spurs an innovation differential (Danish et al., 2019). An innovation differential is manifested through new product designs, processes, marketing strategies or training methods (Porter, 1990). This indicates that entrepreneurial culture creates the efficacy to create a new venture in a specific location.

Despite the benefits attributed to the social legitimacy of entrepreneurship, Woolley (2017) explains that there is no set predictor of how a location may develop an entrepreneurial culture. Furthermore, Fleck et al. (2021) argue that social legitimacy shaped by institutional systems requires educational programmes to moderate entrepreneurial activity in environments that are hostile to entrepreneurship.

National reports, such as the GEM South Africa explained that the perceptions in society, through the lens of their cultural and social context influence entrepreneurial ambitions (Bowmaker-Falconer and Meyer, 2022). For example, cultural priorities in a given location can be heterogeneous, as noticeable in the study conducted on the extent and type of entrepreneurial competencies of different ethnicities in Malaysia (Tehseen and Anderson, 2020). The study explained that ethnic differences existed between Malaysian Indians and Malaysian Chinese concerning their propensity towards entrepreneurship. The findings indicated that Malaysian Indians focused on societal values, while Malaysian Chinese were driven by a commercial view and performed better economically.

Against this background, entrepreneurial intention is catalysed by attitudes and perceptions including views of opportunities, confidence and risk-taking propensity. Given the significance and uncertainty surrounding establishing an entrepreneurial culture, both policymakers and practitioners must be careful not to develop a perception bias of the entrepreneurial culture or intention, as each location is heterogeneous with unique characteristics.

5. The type of entrepreneurship in South Africa

South Africa applies the total early-stage entrepreneurial activity (TEA) rate as a measurement for entrepreneurship. TEA is based on the active population, who are individuals between the age of 18 and 64 years who are nascent entrepreneurs and new business owners who passed the nascent stage (Bowmaker-Falconer and Herrington, 2020; The World Bank, 2021).

In 2019, South Africa’s TEA stood at 10.8%, below the average for the African region of 12.1% and TEA has not increased between 2017 and 2019. However, the current entrepreneurial activity does not show a proportionate increase in the annual GDP per capita or employment. The disproportionate relationship between South Africa’s TEA and economic performance is explained by the concentration of necessity entrepreneurs, where high TEA rates indicate poor economic growth and competitiveness (Acs et al., 2018a; Almodóvar-González et al., 2020).

In 2018, a baseline study of small businesses was performed by the small business institute in partnership with the small business project on data from 2011 to 2016. The study used business-level data from the South African Revenue Service and National Treasury’s tax data filed by formal businesses (Small Business Institute and the Small Business Project, 2019). Formal businesses are registered for tax and issue tax certificates to employees, which are submitted to the South African Revenue Service. The findings indicated that formal small, medium, and micro enterprises (SMMEs) accounted for approximately 98.5% of the formal businesses in the economy (Small Business Institute and the Small Business Project, 2019). However, their employment numbers were inverse, insofar that only 5.1% of the employment was found in micro-enterprises, 11% in small-enterprises and 12% in medium-enterprises. Therefore, employment by SMMEs accounted for 28% of total formal jobs and international trends suggest that small businesses should contribute approximately 60%–70% of jobs for an economy.

6. Research methodology

6.1 Case study context

This research study is based in Nelson Mandela Bay, which is one of eight metropolitan regions in South Africa. It is known as the economic hub in the Eastern Cape province and includes the city of Port Elizabeth and the towns of Uitenhage and Despatch (Municipalities of South Africa, 2022). Port Elizabeth and Uitenhage have recently been renamed Gqeberha and Kariega, respectively. The region has notable resources, such as two ports and a strong manufacturing and automotive sector. Yet, despite being acknowledged as the economic hub of the province and its major sectors, entrepreneurial activity is lagging in terms of innovation and market access.

The region struggles to attract investment and competent labour. In fact, it was reported that the metropole has the slowest growing labour market compared to the other metropolitan areas in South Africa (NMBM, 2021). The Nelson Mandela Bay Municipality (NMBM) Integrated Development Plan (IDP) states that the region is unattractive as a location to work and establish new ventures.

Despite national calls to promote entrepreneurship in South Africa, the IDP indicated that the cost of doing business was high compared to other cities in South Africa (NMBM, 2021). Subsequently, South Africa’s National Treasury is attempting to lower the cost of doing business in the metropole to attract business (NMBM, 2021).

Furthermore, most businesses in the region are informal and unregistered. Dobbin (2019) asserted that the number of enterprises within the micro-enterprise category accounts for approximately 87.4% of businesses operating in Nelson Mandela Bay. The concentration of total informal SMMEs in the informal sector shows disproportionate employment. In this line, the concentration of informal businesses has led to poor economic growth, which has led to a situation of high unemployment and counteracted circular entrepreneurship. The current report of unemployment rate stands at 34.7% (Kimberley, 2022) and the levels of inequality are fairly high across Nelson Mandela Bay (National Treasury, 2021). Notably, a Gini coefficient of 0.63 was reported that is indicative of high inequality (Department of Cooperative Governance and Traditional Affairs, 2020).

Other areas of concern are the political instability. In 2019, the Nelson Mandela Bay Business Chamber expressed to the Mayor and mayoral committee that political instability deterred investment (Nkosi, 2019). For instance, political infighting and lack of council resolutions have reduced the social contract with citizens, which affects enterprise promotion and innovation (Khoza, 2022). Such political infighting has caused a diaspora of inequality on citizens through municipal inefficiency and poor financial control.

The South African National Treasury outlines various priority areas as essential for job creation and economic growth. However, in 2019 and 2020, it was reported that the NMBM budget for infrastructure maintenance was underspent at 1.9% (2018–2019) and 1.6% (2019–2020) instead of the treasury regulation of 8% (Municipal Money, 2020). The presence of poor fiscal management, such as underspending on areas, which otherwise would aid with spatial equality of disparate groups, contradicts the Public Finance Management Act and hinders social progress (South African Government, 1999).

6.2 Case study strategy – mixed methods design

This study satisfies the boundaries of the case study strategy by:

• following an empirical inquiry of a complex phenomenon, such as an entrepreneurial ecosystem in a real-world context, Nelson Mandela Bay (Yin, 2014, p. 16);

• seeking perspectives using multiple data collection procedures, whereby two data collection methods are applied in a sequence (Creswell, 2015, p. 14); and

• presenting evidence through a combination of quantitative and qualitative approaches.

A mixed-method research design was used in this study and followed a sequential independent process, which was performed in two phases and independently analysed. Schoonenboom and Johnson (2017) assert that there are situations where a mixed-method design can be conducted concurrently using a dependent data analysis and sequentially following an independent data analysis. The choice of independence was because the sample for each phase was heterogeneous and to determine whether similar findings existed from Phase 1 (quantitative data) to Phase 2 (qualitative data). Therefore, the purpose of the mixed-method study was to perform triangulation, which is the point of integration.

In analysing the quantitative data, this study statistically evaluated the perceptions of culture and entrepreneurial intention that would account for entrepreneurial activity in the specific cultural and social context. By thematically analysing the data set from the semi-structured interviews, the study was able to explore perceptions of the structural aspects of the culture and entrepreneurial intention in Nelson Mandela Bay. Consistent with a sequential design, the study begins by presenting the sampling and data collection methods for each phase. It follows with the results for both phases and the procedure for connecting the data sets. Finally, it concludes with the integration of both phases at the point of integration.

Full ethics clearance was obtained for this study [H-18-BES-BS-039].

6.3 Sample and data collection: quantitative phase

The quantitative phase aimed to determine if culture and entrepreneurial intention had a positive quantitative relationship with the entrepreneurial ecosystem in Nelson Mandela Bay’s cultural and social context. Phase 1 included the dissemination of questionnaires to individuals in the categories: start-ups, micro-enterprises, small- and medium-enterprises (SMEs) and employees from big businesses, corporates and multinational enterprises (MNEs). These individuals were recruited through a convenience sampling method, and 300 responses were received. The description of the categories is presented in Table 1.

The selection of start-ups, micro-enterprises and SMEs was centred around the role of the entrepreneur as a creator of new ventures who has successful or failed businesses (Bosma et al., 2018). Individuals from large businesses, corporates or MNEs were selected as they form part of the skilled workers who are important because of their expertise. These individuals provide skills, insights and experience surrounding processes and market opportunities that are developed from employment (Spigel, 2017).

A questionnaire consisting of a biographical section and a set of statements associated with culture and entrepreneurial intention was used against a five-point Likert Scale (ranging from 1 = Totally Disagree to 5 = Totally Agree). The Cronbach Alpha coefficient (α) was used to measure the reliability of the measuring instrument, and the two factors showed good (Culture α = 0.79) and excellent (Entrepreneurial intention α = 0.84) reliability.

A combination of the delivery-and-collection and Web-based questionnaire using the university online survey tool, QuestionPro was used. The authors approached three business support institutions, namely, The Business Place, Nelson Mandela Bay Business Chamber and IHub, to distribute the survey to their database of start-ups, micro-enterprises and SMEs. Additionally, one of the authors physically attended three boot camps hosted by a local incubator, Propella in Port Elizabeth. At the boot camps, the study was first introduced followed by an explanation of the purpose, including confidentiality and anonymity. If the entrepreneurs wished to participate, the author distributed hard copies of the questionnaire and collected them once completed. Furthermore, social media platforms, such as LinkedIn and Facebook, were used to distribute the survey. Data were exported into Excel followed by coding. Incomplete records were discarded.

6.4 Sample and data collection: qualitative phase

The qualitative phase of the study consisted of economic development agents from Nelson Mandela Bay. By using the purposive sampling method, 15 semi-structured interviews were conducted. These stakeholders were identified by their role in promoting socio-economic development and the facilitation and promotion of entrepreneurs in Nelson Mandela Bay. These stakeholders form part of the leaders and role models who provide direction and oversight to ensure co-operation and competition (Feld, 2012; Stam, 2015; Stam and Van De Ven, 2019). Isenberg (2010) and Feld (2012) underscore the importance of their inclusion, as they provide insights to understand the needs of entrepreneurs.

By applying the purposive sampling method, the researchers increased the likelihood of obtaining credible information to explore perceptions of the structural aspects of the culture and entrepreneurial intention in Nelson Mandela Bay. The ideal sample size for a single case study ranges from 15 to 30 interviews; however, the number of interviews was focused on the theory of thematic saturation (Malterud et al., 2015; Vasileiou et al., 2018). Furthermore, empirical research on the adequate sample size for interviews found that the first six interviews produced the most information and 80%–92% of concepts were identified in the first ten interviews (Morgan et al., 2002). For this study, the researchers interviewed until saturation was achieved and a total of 15 interviews were conducted as the data collected gathered similar patterns to address the research objective.

Appointments were made with identified economic development agents. The participants completed an informed consent form, which detailed the purpose of the research, confidentiality, anonymity and the use of the data. Interview data were captured through audio recordings to ensure that key information was not lost. Table 2 provides descriptive information about the participants in the qualitative inquiry and pseudonyms are used because of anonymity.

7. Results

7.1 Quantitative phase

In Phase 1, the quantitative data are analysed by using descriptive and inferential data analysis techniques. The descriptive statistics, frequency distribution of factors, one sample t-test, Pearson’s correlation and simple linear regression are reported.

7.1.1 Descriptive statistics.

The biographical details of the respondents, such as category, gender, age and level of education are presented in Table 3. In terms of the categories, it was reported that 35% (n = 104) of the respondents were start-ups, 16% (n = 49) were micro-enterprises, 32% (n = 95) were SMEs and 17% (n = 52) were large businesses, corporate or MNEs. Most of the survey respondents fell into the start-up category, which may potentially indicate bias. Bias is explained because the majority of enterprises in Nelson Mandela Bay operate within the micro-enterprise category (Dobbin, 2019).

The distribution of gender was 60% (n = 181) male and 40% (n = 119) female. While more males participated in the study, the difference was deemed immaterial to the practical significance of the study. In 2020, GEM South Africa reported that men are twice as likely to become new enterprise entrepreneurs (Bosma et al., 2019).

Furthermore, the concentration of respondents falling into the age range of 26–35 (31%, n = 94) and 36–45 (26%, n = 78) corresponds with the findings from the 2019/2020 GEM South Africa report. Herein, it is reported that entrepreneurial activity is prevalent among individuals between the age range of 25–34 years and 35–44 years (Bowmaker-Falconer and Herrington, 2020). The biographical information relating to the level of education indicated 69% (n = 207) of the respondents continued their studies after having completed their matric (high school certificate). In contrast, 31% (n = 93) of the respondents had either a matric qualification or less. These results may indicate bias as the majority of enterprises in Nelson Mandela Bay operate within the micro-enterprise category (Dobbin, 2019). The sample of micro-enterprises in this study is low (16%, n = 49), and this category is characterised as being informal with low levels of education, whereby the individuals are motivated by necessity.

7.1.2 Frequency distribution of factors.

The average scores from the respondents are categorised according to the five-point Likert scale. The categories are described as Disagree, Neutral and Agree. As depicted in Table 4, from a sample of 300 respondents, more individuals had a positive perception of the Culture for the items that were measured.

The frequencies pertaining to culture presented an overall impression that a social legitimacy to entrepreneurship existed in Nelson Mandela Bay, albeit, there were diverse responses to the city’s support of female entrepreneurs (Disagree = 25%, Neutral = 39% and Agree = 36%), businesses in the city support each other (Disagree = 30%, Neutral = 28% and Agree = 42%) and the city encourages and supports innovation (Disagree = 24%, Neutral = 30% and Agree = 46%).

The entrepreneurial intention results in Table 5 revealed that respondents were ambivalent (41%, n = 122) to the statement individuals are willing to take risks and strongly agreed to the statement a fear of failure restricts people from starting their own business (79%, n = 237). The response trend to these two items echoes the results from the 2019/2020 GEM South Africa report. Herein the fear of failure was notably high at 49.8%, showing an upward trend from 2017 (Bowmaker-Falconer and Herrington, 2020).

7.1.3 One-sample t-tests: independent factors.

A one-sample t-test was performed to determine whether the population mean score of the factors for the sample, n = 300 is positive, negative or neutral. Therefore, the one-sample t-test measured whether the null hypothesis would be accepted or rejected. Despite the hypothesis presented, both relationships for entrepreneurial culture and entrepreneurial intention with the entrepreneurial ecosystem had large p-values (p-value ≥ 0.05), which meant that there was weak evidence to reject the null hypothesis (Table 6).

Thereafter, the effect size from the sample (n = 300) was performed through the Cohen’s d, which provides the practical significance for entrepreneurial culture and entrepreneurial intention. Table 7 includes the results from the one-sample t-test, mean values, degrees of freedom, where d.f. = 299, the t-values and p-value and the effect size using the Cohen’s d threshold.

Entrepreneurial intention (µ = 3.54; p > 0.0005; Cohen’s d = 0.20) had a positive mean score, no statistical significance (p > 0.0005) and small practical significance (Cohen’s d = 0.20). Entrepreneurial culture (µ = 3,29; p > 0.0005; Cohen’s d = 0.16) had a positive mean score, no statistical significance (p > 0.0005) and no practical significance.

7.1.4 Pearson’s correlation.

The correlational results for culture and entrepreneurial intention were calculated using Pearson’s r (Table 8). The Pearson’s r correlation for culture and the entrepreneurial ecosystem showed a medium positive correlation, which was statistically and practically significant, where the Pearson coefficient was |r| > = 0.300. Equally, entrepreneurial intention showed a low positive correlation with the entrepreneurial ecosystem, which were statistically and practically significant.

The predictor variables, entrepreneurial culture and entrepreneurial intention have positive correlations with the outcome variable, entrepreneurial ecosystem. The results from the correlation support the literature regarding the interdependence of the factors of an entrepreneurial ecosystem.

7.1.5 Simple linear regression.

A simple linear regression with entrepreneurial ecosystem (y) as the dependent variable and culture (x₁) and entrepreneurial intention (x2) as independent variables was conducted. The regression output in Table 9 revealed that a statistically significant relationship existed between culture and entrepreneurial ecosystem (p < 0.001). Thus, supporting the claim that the entrepreneurial ecosystem is dependent on culture. However, no statistically significant relationship existed between entrepreneurial intention and the entrepreneurial ecosystem (p > 0.05). Therefore, the integration with the data set from the qualitative phase became important in developing a comprehensive understanding of the culture and entrepreneurial intention in Nelson Mandela Bay.

7.2 Qualitative phase

A thematic analysis was used to analyse the interview data and identify patterns in the data. Braun and Clarke’s (2006) six-phase method to ensure trustworthiness of the thematic analysis was applied. Data were analysed both inductively and deductively. The deductive analysis used the theoretical frameworks, which follow the theoretical thematic analysis approach (Braun and Clarke, 2006). The analysis procedure was iterative, and an open coding schema was used to support the modification and reduction of codes. Quotations were extracted and initial codes were developed. Thereafter, a theme search was conducted once the coding theoretical saturation was achieved.

7.2.1 Theme: culture and societal norms.

Figure 1 provides the thematic map for the main theme Culture and Societal Norms and its associated sub-themes Negative View of Social Legitimacy and Culture, Positive View of Social Legitimacy and Culture and A Culture of Dependency and Entitlement.

7.2.1.1 Sub-theme: negative view of social legitimacy.

Participants were asked about their overall view of Nelson Mandela Bay’s entrepreneurial culture. Participants 9 and 11 state that the metropole does not have an entrepreneurial culture, and indicate that starting a business is necessity driven instead of opportunity driven. The extracts from discussions with Participants 9 and 11 were as follows:

I think the culture is not entrepreneurial, but it's a needs pressure from unemployment and pressure from, you know, trying to create solutions for poverty, more than focusing on creating a solid entrepreneurial culture (P9, Business Owner, line 55).

Most SMMEs are just trying to survive (P11, Business Owner, line 21).

When asked whether the city encourages entrepreneurship, Participants 10, 13 and 15 explain that no efforts have been put in place. In fact, participant 15 brings attention to the superficial way entrepreneurs in the city are acknowledged:

I think what we don’t have in this is a celebration of entrepreneurial excellence. We have the Business Chamber annual banquet and there they celebrate companies […] But we don’t go to your individual entrepreneurs and there are some brilliant, brilliant businessman in this city, people that are operating under the radar, and they’re not celebrated in my view (P10, Higher Education: University, line 19).

We do encourage strongly, but we haven’t had that culture of celebration and having role models that we can say, these are the people that we have supported and they’re doing wonderful work in the community. No, we don’t do that. So, in short no (P13, Government: Municipality, line 57).

I don’t believe they are. And also, all the entrepreneurs that comes in newspapers and social media is by a vote of friends who can sms the most, and no one really conducts a deep analysis of small businesses in the metro (P15, Business Owner, line 64).

7.2.1.2 Sub-theme: positive view of social legitimacy and culture.

Questions in the semi-structured interviews attempted to determine the social acceptance of owning a business as it elevates the entrepreneurial culture. Several participants indicated that measures to elevate its status were undertaken. The following excerpts were taken from Participants 1, 2 and 13:

There are promotions, which for example, share success stories through information communication material […] The Nelson Mandela Bay Business Chamber promotes the flow of information (P1, Not for Profit: Business Chamber, line 312).

The Nelson Mandela Bay has promoted public image for entrepreneurship. And I believe that more can be done […] individuals are encouraged to become business owners and entrepreneurs, so it definitely is […] (P2, Political Party, line 39).

Yes, they are viewed as economic drivers. So, it is held in high regard. In fact, it’s promoted rather than formal employment. Many are encouraged to startup businesses, to contribute to the local economy, create jobs and things like that (P13, Government: Municipality, line 69).

When asked about whether the local community of Nelson Mandela Bay supported local businesses, both Participants 10 and 11 felt that the support exists. The following excerpts provide the data evidence:

I think there is a general pride in our city and a general loyalty to our business in our city (P10, Higher Education: University, line 29).

I think that despite national and especially local government lack of support for SMMEs, community support in NMB is quite strong (P11, Business Owner, line 32).

7.2.1.3 Sub-theme: a culture of dependency and entitlement.

Throughout the interviews, participants expressed that the entrepreneurs in the city suffered from entitlement and dependency. These views emerged when referring to the policies, such as the Preferential Procurement Regulations and the B-BBEE Act. For example, Participant 12 stated:

The SMMEs are opportunists and have a sense of entitlement (P12, Government: Municipality, line 217).

When asked about how the policies support entrepreneurship, Participants 3 and 5 state that policies do not support entrepreneurship and qualified their views as follows:

And so, there is a dependency created by the 30% by the BEE, by the this. In other words, if I meet all these criteria, I should be getting work, so you create not only the dependency, […] So, there is entitlement around, No, but we must have, you must have, if you don’t give it, we will do this or we will do that (P3, Government Entity, line 42).

I just don’t feel that there is that culture of entrepreneurial support in anything entrepreneurs are seen as a necessary evil, you know, give them their 30% so that they can stop making a noise (P5, Incubator Manager, line 145).

7.2.2 Theme: the entrepreneurial mindset.

Figure 2 illustrates the thematic map of the main theme The Entrepreneurial Mindset and its associated sub-themes Entrepreneurial Challenges: Mindset and Knowledge and Seeking Business Opportunities.

7.2.2.1 Sub-theme: entrepreneurial challenges: mindset and knowledge.

This theme emerged naturally throughout the interviews for separate questions, and was interpreted as a codable moment after searching for themes in the interview data. The following extracts act as data evidence to support the theme.

Participant 2 was asked whether the network of entrepreneurs provides an information flow. He responded that networks exist, but businesses do not use the opportunities presented to them. As he qualified his statement, he expressed that there is a dissonance in understanding the difference between an entrepreneur and a survivalist. The following excerpt is an extract from Participant 2:

But maybe the smaller businesses need to be educated. And maybe the other thing is, as well as what I’d like to say about that, is that a small business, and sorry for repeating this, it’s not somebody who sells apples outside the hospital, that’s not a small business, that is not even a survivalist […] So, I think just the mindset must be changed and entrepreneurs must make use of the opportunity (P2, line 51).

Based on the first question of the interview regarding the entrepreneurial ecosystem, Participant 9 immediately asserted that the entrepreneurial ventures were based on unemployment and qualified her view as follows:

Now, the expectation to be given work, you know, by small businesses to fight for work opportunities, not to be able to competitively develop businesses that can get work opportunities […] it has also been infiltrated by the need for people to do an activity whilst they are not really entrepreneurial (P9, Business Owner, line 13).

Participant 10 was asked about the support given to domestic suppliers of products insofar that it aids in accessing various supply chains. In his response, he argues that businesses in Nelson Mandela Bay do not meet the basic requirements of competitive tenders and lack the requisite capabilities:

I know of the Volkswagen initiative, which was actually quite a big one. They added around 400 people, suppliers that actually were invited to actually make a pitch to them. And I think only about 40 of them actually met the requirements […] (P10, Higher Education, line 139).

During the discussion surrounding the business support services and the extent of assistance provided to access funds, Participant 15 underlines that the support exists. However, he continues by stating that there is a lack of business acumen. Participant 15 highlights, that entrepreneurs access the support services too late and lose contracts as a result:

A small business don’t have all the business acumen, respectfully said. They know they’re good at what they do, their quality is great and that’s why they started their own business. They don’t understand business that well […] (P15, Business Owner, line 376).

The interviews explicate that the potential reasons for going into self-employment are based on unemployment and explain that there is a lack of requisite skills and knowledge to compete effectively. Other issues highlighted were the mindset of entrepreneurship, which was explained as a product of historical exclusion from the mainstream economy and a lack of entrepreneurial role models between disparate groups in the city.

The views from the interviewees acknowledge that there are insufficient knowledge and skills among the city entrepreneurs. Subsequently, the lack of knowledge and skills affects location competitiveness and lowers the ability to improve the socio-economic landscape.

7.2.2.2 Sub-theme: seeking business opportunities.

Participants were asked whether they believed that the citizens of Nelson Mandela Bay search for entrepreneurial opportunities. Some participants indicated that entrepreneurs did, however, most alluded to dissonance in terms of their mindset as described in the previous sub-theme. Those who responded to this question expressed their views as follows:

So, I think that notwithstanding the challenges in municipalities, there are people who will do things. It’s the scaling up that becomes the problem (P3, Government Entity, line 211).

I believe they do in more than usual levels […] you’ve got at any given time, a group of people that are looking for entrepreneurial opportunities (P5, Incubator Manager, line 182).

If I look at the amount of staff with a side hussle, if I look at the the SPAZA shops, the informal businesses that fills Korsten […] South Africans have realised that seeking formal employment is like finding needle in a haystack. But starting your own business is the onset of putting food on the table. So definitely (P7, Private Sector: Banking, line 123).

The participants explained that individuals in Nelson Mandela Bay seek business opportunities. Both the GEM and Global Entrepreneurship Index acknowledge that South Africa ranks high in terms of opportunity perception (Acs et al., 2018b; Bosma et al., 2019; Bowmaker-Falconer and Herrington, 2020). However, the fear of failure has been reported as an obstacle to starting a business. Furthermore, as noted in the previous sub-theme, the potential reason for starting a new venture is a product of the lack of employment opportunities.

7.3 Integration of the data sets

The overall findings from the quantitative and qualitative results were compared (triangulated) using a joint display and were merged by doing a side-by-side comparison. Triangulation served to draw a comparison from the results in Phase 1 and Phase 2, such as convergence (confirmation), complementary (expansion) or divergent (discordance) insights. The joint display serves as a visual tool to determine confirmation, expansion or discordance and this technique is argued as a framework for integration (Greene, 2007, p. 143). The joint display is organised into three columns. Column 1 provides the results of the quantitative analysis; Column 2 presents the qualitative findings as general patterns and refers to quotes for data evidence; and Column 3 presents the interpretation, which provides a summary of how participants from both phases responded to the culture and entrepreneurial intention in Nelson Mandela Bay.

Confirmation and expansion provide supportive data evidence; however, discordance in the results required a re-evaluation of both data sets to ensure the inferences made were correct (Erzberger and Kelle, 2003). Discordance required the authors to determine whether the divergent findings revealed a different dimension of the phenomenon being studied. If it revealed a different dimension, an expansion with new insights was gathered (Fetters et al., 2013; Moseholm and Fetters, 2017). These insights carry complementary or supplementary insights about the phenomenon. Furthermore, to assist in clarifying any discordance, this study drew on theory to explain contradictions in the data sets (Tashakkori and Teddlie, 2008).

The meta-inference in Table 10, which is associated with the views of culture indicated that there was confirmation and discordance between the data sets. The confirmation indicates that both phases showed that there was a social legitimacy of entrepreneurship. Such confirmation can be related to the elevated status that the South African mainstream media and policymakers have placed on entrepreneurship both on national, provincial and local levels as a way to address unemployment and poverty.

However, discordance in the data sets was highlighted as well, which was supported by the resource-constraint version of the disadvantaged theory. Participants in the qualitative phase suggested that the choice of self-employment was predominantly associated with high unemployment and poverty and not because of a desire to innovate or scale. Supplementary insights are invoked insofar that necessity-driven entrepreneurs are not spurred by an entrepreneurial culture, which meant that the behaviour was motivated by the need to survive.

The meta-inference in Table 11, which is associated with the views of entrepreneurial intention indicated that there was confirmation and discordance between the data sets. The confirmation indicates that both phases showed that individuals in Nelson Mandela Bay seek out business opportunities and that a fear of failure existed. However, the intention to start a new business was predominantly associated with survival, as shown in the integration of culture with entrepreneurial intention.

Discordance in the data sets was highlighted, as well as it pertained to the risk appetite and the type of entrepreneurship. The institutional theory, in particular, the cultural-cognitive pillar and cultural variation in subjective norms in TPB were used to structure the analysis for the discordance presented, as it focuses on the shared understanding or adoption of common beliefs within a society in a specific location. Participants in the qualitative phase suggested that the poor risk tolerance was associated with the low entrepreneurial legacy, which existed between disparate groups and the type of entrepreneurship was not entrepreneurial insofar that entrepreneurs in the metropole depend on the government for contracts and are not developing innovative business models to compete effectively.

8. Discussion

The findings from the meta-inferences presented confirmatory and divergent results. Both data sets generally showed that there was support for local businesses and that citizens in Nelson Mandela Bay searched for business opportunities. Thus, explicating that social legitimacy towards entrepreneurship in Nelson Mandela Bay existed. Participants from both data sets indicated that both residents and local businesses show a shared understanding in terms of local demand. This satisfied the assertion that the social legitimacy of entrepreneurship in a location creates a demand for local goods and services (Porter, 1990; Spigel, 2015; Fritsch and Wyrwich, 2017).

Despite these findings, there was divergence present in the data sets as the qualitative data explained that a high level of self-employment in Nelson Mandela Bay was a response to unemployment, thus, necessity driven. Self-employed individuals lacked the requisite skills and knowledge to compete effectively, thus limiting innovation potential and scalability. Scalability allows businesses to move into the next size category, which allows businesses to access finance more easily. The scaling of businesses affects innovation, competition, employment and the average wage rate (Acs et al., 2018b; OECD, 2018). This may address issues, such as the low productivity rates and income inequality present in the metropole and its current Gini Coefficient.

The poor social progress can be explained by the level of self-employment in the informal sector. It has been reported that 87.4% of businesses operating in Nelson Mandela Bay operate within the micro-enterprise category (Dobbin, 2019). This indicates that a disproportionate amount of employment lies within this category. The contention is that high levels of self-employment in developing economies are disproportionate to economic growth, which may be seen by the level of unemployment and poverty. The resource-constraint version of the disadvantaged theory was used to explain the divergence between the data sets, as it related to the choice of self-employment to survive.

Another issue highlighted was the mindset of entrepreneurship. The historical exclusion of disparate groups from the mainstream economy and the low entrepreneurial legacy serves to bring supplementary insights. Generally, a history of self-employment in a location reveals entrepreneurial personalities and innovation capacity. However, this may invoke that there is a lack of entrepreneurial role models between disparate groups in the metropole and explicate why the fear of failure and low-risk tolerance is present. Applying the normative pillar of institutional theory provides the lens to understand that the norms and values within society can reduce the tolerance to undertake risks.

Although the quantitative results showed a positive average frequency and correlation between entrepreneurial intention and the entrepreneurial ecosystem, the integration with the qualitative results presented divergence. The findings from the qualitative data set highlighted that a pattern of dependency and entitlement existed among entrepreneurs. The cultural-cognitive layer of institutional theory was used as a lens to understand the divergence. Herein, the issue of dependency may be understood through the history of the economic exclusion of the majority, which subsequently led to the democratic government assuming responsibility.

8.1 Limitations and future research

This study is based on Nelson Mandela Bay, South Africa, which is one of the eight metropolitan regions in South Africa. Furthermore, this inquiry is based on a single case study, which means that the insights are limited to a location. It is, therefore, recommended that the study be repeated in a different metropolitan region to compare the findings. The replication, using a similar research design in other metropolitan regions can highlight whether the findings are unique to Nelson Mandela Bay. Notwithstanding, a granular examination may reveal differences in social, economic and institutional contexts for various sub-national locations in South Africa.

Future research should repeat the survey with a larger sample size and control certain demographic variables to determine whether any statistical or practical significant differences are evident. To support a more rigorous quantitative analysis, researchers may adopt a multistage purposeful sampling technique to select participants on the basis that many metropoles within South Africa suffer from segregated spatial designs. Following, a multistage purpose sampling technique may improve the generalisability of the quantitative findings.

8.2 Practical recommendations

Entrepreneurial ecosystems are built on a sub-national level, which means that strategic investments need to be carefully evaluated to reduce wasteful expenditure. The findings from the meta-inferences have important implications for metropolitan stakeholders and entrepreneurs.

Against this backdrop, the Mayor, municipality, councillors, economic development agents and educators should be proactive to both elevate the status of entrepreneurship and create a business climate that encourages the stimulation of innovative business models, among others. In particular, the findings are relevant to policymakers, as they reveal that local and contextually sensitive policies would support innovative entrepreneurship instead of a necessity-driven form of entrepreneurship. Contextually, in areas with complex spatial division, an engagement process with different groups, such as disparate groups may be necessary to create a broader view of entrepreneurship.

In this line, Spigel et al. (2020) argued that policy and research should be sensitive to other forms of entrepreneurs, especially in emerging economies with difficult macroeconomic factors. As evident in the ecosystem definitions, there are actors and factors that lead to productive entrepreneurship, and the institutional context shows that participatory-led approaches should be included to transfer value to the metropole. For example, a joint strategy should be present albeit the fact that formal leadership in a location rest with the municipality, economic development agents and mayors. This would encompass collaboration with the public and private stakeholders for local economic development endeavours (Isenberg, 2011).

Strategies such as educational programmes and government initiative tax breaks are suggested to reduce poor risk tolerance and the fear of failure. Chambers of Business should showcase the success stories of metropolitan entrepreneurs to stimulate role modelling. Individuals in the metropole may then consider the benefits of entrepreneurship despite their normative disposition, insofar as others have successfully translated ideas into products and services.

Entrepreneurs who have a vested interest and history in a location may act as role models or regional champions. For instance, Feldman (2014) argues that development in a location can be improved through the story of those entrepreneurs who were able to create connections and ventures. This aligns with the recycling of entrepreneurship to the extent that there is an opportunity for reinvestment of entrepreneurial expertise and know-how (Isenberg, 2011; Roundy, 2017).

Furthermore, events that bring together disparate groups who have historically been excluded from the mainstream economy should be prioritised. The utilisation of support institutions in the metropole can aid nascent entrepreneurs in the development stage in terms of infrastructure, such as space, information and access to contacts to make viable connections. The city leadership may need to engage financial institutions to assist entrepreneurs, who move from the nascent stage into the growth stage.

The metropole should further use the memorandum of understanding (MOU) with the university to stimulate dense connections that, in the medium to long term, may induce labour mobility and generate positive spillovers in learning and innovation. For instance, the MOU between the university and the municipality should be accelerated to build knowledge capacity and build innovative business models. This may support innovation and attract knowledge workers and investors.

Additionally, policies that have caused a disproportionate impact on the metropole’s progress should be addressed as contracts are surrendered to outside (more competitive) companies, which is a loss of tax revenue and job opportunities. The metropolitan leaders may need to focus efforts by using the MOU between the university and the municipality to improve the efficiency of local producers and entrepreneurs operating in important sectors, such as the tourism sector, the green economy and the blue oceans economy.

9. Conclusions

This study presented insights regarding the culture and entrepreneurial intention to promote an understanding of the type and nature of entrepreneurship in Nelson Mandela Bay, South Africa. The contributions that this study makes, which are important to understand the influence of culture and entrepreneurial intention as a predictor for entrepreneurial ecosystem development on a sub-national level. The findings provide evidence-based insights that can support decision makers within resource-constrained environments to tailor and adopt strategies to enable productive entrepreneurship.

For the ecosystem to be enabled, the inadequacies in the institutions on the local government level should be addressed by being business focused and private sector led. Consideration of the type of information and how it is communicated can improve economic decision-making among aspirant entrepreneurs. Furthermore, educational programmes need to address the knowledge requirements of the individuals without making assumptions given the institutional context.

Figures

Figure 1.

Thematic map of the view of culture and societal norms with associated sub-themes

Figure 2.

Thematic map of the view of the entrepreneurial mindset with associated sub-themes

Table 1.

Description of categories

Category	Definition
Start-up	Start-ups are classified as business in their initial stage of business
SMEs	Full-time equivalent employees of 11–50 in small enterprises and 51–250 in medium enterprises (Department of Small Business Development, 2019). The total annual turnover, indicated in millions, varies by size and sector
Micro-enterprises	Micro-enterprises are characterised as having 0–10 employees (Department of Small Business Development, 2019). The total annual turnover, indicated in millions, varies by size and sector
Large (big business and MNEs)	Large enterprises employ 250 or more people. Albeit MNEs conduct business in various countries with its subsidiaries and affiliates. MNEs possess considerable and wide human resources, finance, expertise and technology, as well as enjoy substantial competitive advantage

Source: Adopted from Department of Small Business Development (2019)

Table 2.

Descriptive information for participants in the qualitative phase

Participant and code reference	Age range (years)	Gender	Position
				Participant 1 (P1)	26–35	Male	Not for profit: business chamber
Participant 2 (P2)	56–65	Male	Political party
Participant 3 (P3)	56–65	Male	Government entity
Participant 4 (P4)	46–55	Male	Business owner
Participant 5 (P5)	36–45	Male	Incubator manager
Participant 6 (P6)	26–35	Male	Government entity
Participant 7 (P7)	36–45	Female	Private sector: banking
Participant 8 (P8)	36–45	Male	Incubator manager
Participant 9 (P9)	46–55	Female	Business owner
Participant 10 (P10)	56–65	Male	Higher education: university
Participant 11 (P11)	36–45	Male	Business owner
Participant 12 (P12)	56–65	Female	Government: municipality
Participant 13 (P13)	26–35	Female	Government: municipality
Participant 14 (P14)	18–25	Male	Higher education: university
Participant 15 (P15)	26–35	Male	Business owner

Source: Authors

Table 3.

Participant characteristics (n = 300)

Category	Start-up	Micro-enterprise, e.g. hawker	SME	Large business, corporate or MNE
	104 (35%)	49 (16%)	95 (32%)	52 (17%)
Gender	Male	Female
	181 (60%)	119 (40%)
Age	18–25	26–35	36–45	46–55	56–65	66+
	51 (17%)	94 (31%)	78 (26%)	53 (18%)	17 (6%)	7 (2%)
Level of education	Less than matric	Matric	Diploma	Degree	Postgraduate degree
	21 (7%)	72 (24%)	71 (23.7%)	71 (23.7%)	65 (21.7%)

Source: Authors

Table 4.

Frequency distribution for the independent factor, culture (n = 300)

Questionnaire statement	Disagree		Neutral		Agree
	n	%	n	%	n	%
The community supports entrepreneurship	66	22.00	64	21.33	170	56.67
Businesses in the city support each other	91	30.33	84	28.00	125	41.67
The city supports female entrepreneurship	76	25.33	117	39.00	107	35.67
Entrepreneurship is seen as a good career choice	63	21.00	54	18.00	183	61.00
The city encourages and supports innovation	73	24.33	89	29.67	138	46.00
The city supports migrant entrepreneurs	63	21.00	84	28.00	153	51.00
Successful business owners act as mentors	73	24.33	67	22.33	160	53.33

Source: Authors

Table 5.

Frequency distribution for the independent factor, entrepreneurial intention (n = 300)

Questionnaire statement	Disagree		Neutral		Agree
	n	%	n	%	n	%
The intention to develop business ideas exists	40	13.33	54	18.00	206	68.67
There is intention to start a business	29	9.67	47	15.67	224	74.67
There is intention to take over a family business	38	12.67	91	30.33	171	57.00
Individuals are willing to take risks	60	20.00	122	40.67	118	39.33
A fear of failure restricts people from starting their own business	19	6.33	44	14.67	237	79.00

Source: Authors

Table 6.

Results from the hypothesis test

Hypothesis	p-value	Accept/reject
H1. There is a relationship between entrepreneurial culture and the entrepreneurial ecosystem	≥ 0.005	Accept the null hypothesis and reject the alternative hypothesis
H2. There is a relationship between entrepreneurial intention and the entrepreneurial ecosystem	≥ 0.005	Accept the null hypothesis and reject the alternative hypothesis

Source: Authors

Table 7.

One-sample t-tests: independent factors

Factors	Descriptive statistics		One-sample t-test classification
	n	Mean	d.f.	t-value
	SD		H1	p-value	Cohen’s d	Category
Entrepreneurial intention	300	3.54	299	3.43	0.20 Small	Positive
	0.72		µ ≠ 3.40	0.001
Entrepreneurial culture	300	3.29	299	2.80	0.16 Not significant	Inconclusive

Source: Authors

Table 8.

Pearson’s r correlations of culture and entrepreneurial intention variables

	Entrepreneurial culture (p-value)	Entrepreneurial intention (p-value)
Entrepreneurial ecosystem	0.663 Medium positive correlation	0.382 Low positive correlation

Note:

Practical and statistical significance where |r| > = 0.300

Source: Authors

Table 9.

Simple linear regression

Coefficientsa
Model		Unstandardised coefficients		Standardised coefficients
		B	Sth. error	Beta	t	Sig.
1	(Constant)	1.337	0.405		3.302	0.001
	Culture	0.432	0.060	0.364	7.182	0.000
	Entrepreneurial intention	0.039	0.050	0.034	0.775	0.439

Note:

^aDependent variable: entrepreneurial ecosystem

Source: Authors

Table 10.

Joint display comparing the quantitative and qualitative findings for culture

Quantitative results (n = 300)	Qualitative results (n = 15)	Interpretation
Central tendency: M = 3.29 (SD = 0.71) (Neutral) Range on Likert scale = 1–5 Frequency distribution: 54% had a positive attitude about the culture r = 0.663 (medium positive correlation) (p < 0.001)	Most participants had a negative view of the culture and societal norms. Several of the participants qualified their statements. For example, some participants indicated that individuals go into self-employment to survive. For example, a participant refers to the choice as “needs pressure” (P9, Business Owner) Another participant explains that there are low efforts to elevate the status of entrepreneurship. For example, a participant states “…but we haven’t had that culture of celebration and having role models” (P13, Government: Municipality) Another participant explains that the entrepreneurs are opportunists and have a mindset of entitlement. For example, a participant states: “The SMMEs are opportunists and have a sense of entitlement” (P12, Government: Municipality)	Confirmation: there tends to be a social legitimacy of entrepreneurship in that the community supports local businesses. Similarly, local businesses support each other. This is supported by institutional theory Discordance: resource-constraint version of disadvantaged theory is used to structure the analysis for discordance

Source: Authors

Table 11.

Joint display comparing the quantitative and qualitative findings for entrepreneurial intention

Quantitative results (n = 300)	Qualitative results (n = 15)	Interpretation
Central tendency: M = 3.54 (SD = 0.72) (Positive) Range on Likert scale = 1–5 Frequency distribution: 62% of participants had a positive response r = 0.382 (low positive correlation) (p > 0.05)	Participants indicated that there was an intention to start new ventures. For example, participants stated:“I believe they do in more than usual levels … you’ve got at any given time, a group of people that are looking for entrepreneurial opportunities” (P5, Incubator Manager)“South Africans have realised that seeking formal employment is like finding needle in a haystack” (P7, Private Sector: Banking) Participants further indicated that there was a low risk tolerance. One participant stated: “The risk appetite is just not there” (P4, Business Owner) Several participants indicated that there was a significant dependency on the government and two participants qualified their statements as follows: “Where you find that SMMEs would want, you know, the politics of the day…” (P5, Incubator Manager)“Now, the expectation to be given work … they are not really entrepreneurial” (P9, Business Owner)	Confirmation: confirmation in data sets for seeking business opportunities and that a fear of failure exists Discordance: differences in the risk appetite and intention of individuals in Nelson Mandela Bay. Institutional theory and TBP structured the analysis and supported the supplementary insights to explain the divergence

Source: Authors