Entrepreneurial ecosystem affects organisational learning, creativity and success

Abstract

Entrepreneurship, a catalyst for advanced economies, yields widespread societal advantages through successful ventures. Amidst this, scholars and practitioners ardently contribute to a burgeoning knowledge repository, aiming to augment the triumph rate of startups. This study focalises on learning and creativity, pivotal facets for entrepreneurial accomplishment, and advances a theoretical framework elucidating the startup ecosystem’s role in organisational learning and creativity. The World Economic Forum’s (2013) model, encompassing six factors—Accessible Market, Workforce, Support System, Regulatory Framework, Education and Training, Cultural Support—comprises the entrepreneurial ecosystem examined. Our dataset, culled from surveys of 200 SME and startup founders or CEOs in Tay Ninh City, Vietnam, with at least five years of operational history, informs our study. Employing SmartPLS 3.0 and PLS-SEM methodology, empirical analysis unveils significant impacts: two ecosystem factors and organisational learning and creativity influence entrepreneurial success. Organisational learning engenders notable effects from the accessible market and workforce, while creativity draws impetus from accessible market, education and training, and support systems. Notably, organisational learning bolsters creativity within startups. These insights carry implications for catalysing regional entrepreneurship.

Keywords:

• entrepreneurial ecosystem
• entrepreneurship
• entrepreneurial success
• organisational learning
• organisational creativity

PUBLIC INTEREST STATEMENT

The advent of the fourth industrial revolution has catalysed a significant surge in the proliferation of pioneering start-up ventures, thereby facilitating the transition from a conventional economic framework to the digital economy. Consequently, the concepts of “entrepreneurship” and “innovative start-ups” have garnered considerable scholarly, policymaker, and entrepreneur attention. Entrepreneurship assumes a pivotal role in facilitating economic expansion and the metamorphosis of economies. Furthermore, a nation’s entrepreneurial spirit, particularly among its youth, serves as a barometer of its competitiveness. Vietnam, as a developing country with a socialist orientation, regards entrepreneurship as a strategic catalyst for achieving sustainable long-term economic growth. Consequently, these factors serve as the impetus behind our research endeavor, aiming to contribute to the global start-up ecosystem while fostering the sustainable development of Vietnam.

1. Introduction

Entrepreneurship has become the driving force behind any nation’s socioeconomic progress in recent decades. In which the entrepreneur plays a critical role in the economy by establishing new enterprises. Entrepreneurs have a critical role in the economy, performing specialised responsibilities such as creating jobs, increasing productivity, and developing and commercialising high-quality technologies. In fact, entrepreneurs encounter numerous problems in finding business partners and seeking assistance from personal relationships that are part of the community and culture (Giardino et al., 2015). Many national leaders have been paying close attention to the development of a dynamic and productive entrepreneurship ecosystem. Developing an effective entrepreneurial ecosystem is a regional economic development approach that focuses on developing supporting circumstances that promote long-term startup success. As a result, many nascent ecosystems around the world require a theoretical framework for building their community to grow toward a viable and sustainable ecosystem.

Entrepreneurs do not need to be experts in every field, but they must be skilled in enough areas to put together the numerous ingredients needed to build a successful business (Lazear, 2005). This demonstrates the significance of entrepreneurial education for countries. In addition, the modern economy highlights that innovation in entrepreneurship is important due to greater globalisation and technical advancement have given rise to increased company prospects, but also increased market activity and competitive pressures (McMullen & Shepherd, 2006). Creativity allows the company to take advantage of these opportunities in ways that bring a strategic advantage to the organisation. Based on the problem statement, the research question posed in this study is: To what extent do entrepreneurial ecosystem pillars (accessible market, human capital, support system, regulatory framework, education, and training, cultural support) affect organisational learning, creativity, and startup success?

Although there have been many studies on the entrepreneurial ecosystem and its correlation with re-lated variables, this study comprehensively explored the ecosystem elements by studying four specific variables, and their interrelationships with creativity, learning and success of SMEs. This study presents the interpretation of these factors individually and the correlations between the research factors in pairs and clearly analyse these correlations in comparing with previous studies. Furthermore, this research was conducted in Vietnam, a developing economy following socialist-oriented market. Therefore, the results of this study are believed to contribute to the literature of entrepreneurship topic, helping legislators and entrepreneurs in these economies have a better overview of the importance of the entrepreneurial ecosystem. This study conducted in Tay Ninh City (Vietnam) and targeted SME owners who have been operating their business in the city for at least five years and have expertise and judgment in entrepreneurship. The convenience sample will be used, and data was gathered primarily from 200 businesses around the region where entrepreneurs are available to be approached. However, the study outcome cannot reflect the entire startup circumstances in Vietnam. Hopefully, entrepreneurial players in Vietnam and developing nations with similar orientations would benefit from the strong link between the startup ecosystem, startup learning, creativity, and business success.

2. Literature review

2.1. Entrepreneurial success

The notion of entrepreneurial success has been a subject of universal interest among business academics (Baron & Henry, 2011). Previous research has identified key factors associated with entrepreneurship that contribute to entrepreneurial success, including risk-taking, personal efficiency, opportunity awareness, perseverance, and social skills (Markman & Baron, 2003). Irrespective of the scale or nature of the business, be it a startup or an established enterprise, the strategies that establish connections between the business and its ecosystem are fundamental to achieving entrepreneurial success (Henry et al., 2017). This book presents a classic definition of entrepreneurial strategy, emphasising the link between the product or service and its environment, and outlines six conditions that must be fulfilled for entrepreneurial success, encompassing consumers, competitors, technology, policy, and demographic patterns. Market share growth is a crucial goal for small and medium-sized enterprises (SMEs) (Rhee et al., 2010). Customer retention emerges as a vital tactic for maximising market share. Unger et al. (2008) support the notion that profitability and firm size are indicators of firm success, and they employ indicators of profitability, growth, and firm size to measure the success of startups in Peru and South Africa, studying the impact of human capital on corporate success (Unger et al., 2008, 2009). The operationalisation of growth is relatively subjective compared to that of size, considering variables such as the number of workers and equipment value as forecasts for annual percentage increase or decrease (Frese et al., 2007).

2.2. Organisational creativity

SMEs are facing increased pressure to generate new value in response to the global economic crisis and evolving market and societal changes. The demand for innovative products, services, and solutions, as well as the competition for talented and creative employees, has heightened global competitiveness across various sectors (McMullen & Shepherd, 2006). Startup founders are recognising the limitations of conventional approaches and strategies in addressing managerial issues and solving problems. Both emerging and established companies are striving to meet demands and achieve ambitious goals, making creativity and innovation crucial for success and growth in a competitive and dynamic environment (Fillis & Rentschler, 2010; Shalley et al., 2009).

Entrepreneurial creativity, as proposed by Fillis and Rentschler (2005), plays a role throughout the lifespan of a startup and is influenced by various factors, including individual decision-making and supportive elements. When personal ambition and engagement are fuelled by promising rewards and recognition, entrepreneurial creativity emerges. Mambula and Sawyer (2004) shed light on the performance factors of a bootstrapped startup, where the founder relied on creative skills to sustain the business. Challenges such as limited financial resources, inadequate infrastructure, competition from multinational companies, unfavourable government measures, scarcity of machinery and raw materials, as well as internal obstacles like poor preparation, insufficient leadership skills, and lack of expertise, all pose constraints.

Moreover, effective management is essential in the innovation process and is as critical as the technological creativity demonstrated by innovative technologists and scientists (Martins & Terblanche, 2003). In light of these dynamics, SMEs must embrace creativity and innovation to overcome constraints, drive growth, and achieve sustainable success in the evolving business landscape.

2.3. Organisational learning

Business activities involve the development and commercialisation of new technology, expansion into new markets, or the provision of new services through the creative utilisation of existing resources (Ireland et al., 2001). Strategic capabilities, such as learning and innovation, play a vital role in resource growth and the attainment of competitive advantage within organisations. Organisational learning focuses on the acquisition of valid insights from gathered information to enhance an organisation’s adaptive capacity (Callahan, 2003). Entrepreneurship and organisational learning are closely intertwined, where understanding organisational learning serves as a mechanism to propose, create, and introduce new concepts originating from both internal and external sources (McAdam & Galloway, 2005). Thus, a sustainable startup is an organisation capable of creating, learning, and influencing its environment.

Molina and Callahan (2009) argue that both individual and organisational learning have a positive impact on startup performance. Intrapreneurship, the practice of fostering entrepreneurial opportunities within the organisation, is considered a means to identify individuals who excel in recognising prospects and launching new ventures (Antoncic & Hisrich, 2001). According to Politis (2005), intrapreneurs require cognitive abilities to evaluate resources and effectively work with them, highlighting the significance of learning in this process. Leaders should adopt effective corporate learning strategies to cultivate an intrapreneurial culture within their organisations (Harrison & Leitch, 2005). As individuals are continuously discovered, assessed, and exploited by the organisation, these recurrent procedures are formalised, fostering an internal learning atmosphere that supports ongoing learning and innovative processes aligned with the evolving needs of startups (Lumpkin & Lichtenstein, 2005).

2.4. Entrepreneurial ecosystem

The entrepreneurial ecosystem is becoming more interested as an approach for understanding the concept of entrepreneurship at the macro aspect and business level. It consists of all the interdependent actors and factors that allow and limit entrepreneurship within a particular area. Although the ecosystem definitions and components may differ between regions and countries, entrepreneurship scholars later added and modified the startup factors to bring out the six pillars of the efficient ecosystem. The results of this study are based on a combination of The World Economic Forum and Stanford University when they surveyed 1,000 business owners worldwide to provide a better understanding of a successful ecosystem (Foster et al., 2013). This study focusses on the six factors of the start-up environment based on the eight pillars of the startup ecosystem suggested by the World Economic Forum: Accessible Market, Workforce (Human Capital), Support System, Regulatory Framework, Education and Training, and Cultural Support.

2.5. Organisational learning and entrepreneurial success

The relationship between entrepreneurship and learning is closely intertwined, as organisational learning involves implementing new ideas developed internally or acquired externally (McAdam & Galloway, 2005). An entrepreneurial organisation is capable of creating, learning, and influencing its environment. Learning plays a crucial role in the long-term success of both individuals and organisations (Franco & Haase, 2009; Keith et al., 2016). Rather than focusing on whether learning immediately leads to success, empirical studies have shifted towards examining when and why learning translates into improved performance. Organisational learning should be adaptive to meet the dynamic needs of the market, generating innovative approaches or providing the necessary knowledge to effectively meet customer demands (Levinthal & Rerup, 2006). Leveraging existing knowledge from collaborative partners and external sources is essential for enhancing business success, reducing uncertainty, and capitalising on opportunities. These two types of learning are referred to as experimental learning and acquisitive learning (Dess et al., 2003). Experimental learning, also known as incremental learning or adaptive learning, occurs within the organisation and involves generating unique information specific to the startup. Acquisitive learning, on the other hand, entails acquiring and internalising knowledge from the external environment to expand the firm’s capabilities beyond its current limitations (Morgan & Berthon, 2008). Both forms of learning have been shown to enhance organisational performance (Zhao et al., 2011). However, the boundary conditions of the learning-performance relationship have received particular attention, with the concept of “Premature Learning” proposed by Bapuji and Crossan (2004). This boundary refers to the extent and scope of an organisation’s learning experience, which directly impacts its outcomes. Insufficient learning experience may lead to the application of inappropriate generalisations to future operations, undermining efficiency. Additionally, Finkelstein and Haleblian (2002) found a U-shaped relationship between previous acquisition experience and acquisition success, suggesting that the benefits of experience diminish initially and then increase as more experience is gained. Therefore, learning from the successes and failures of others, particularly for team founders, is a critical factor contributing to entrepreneurial success.

H1:

Organisational learning directly affects entrepreneurial success.

2.6. Organisational creativity and entrepreneurial success

Understanding creativity is crucial for future economic success as it can lead to cost-effective yet valuable solutions. Creativity is considered a core competency within organisations (Palus & Horth, 2002), and the creativity of key decision makers plays a critical role in achieving future business success. Successful founders possess characteristics such as the ability to calculate risks, fearlessness in the face of failure, and a willingness to take risks (Mambula & Sawyer, 2004). Entrepreneurship comprises three fundamental elements: invention, risk-taking, and proactiveness. Innovation refers to the process by which entrepreneurs pursue new opportunities and translate ideas into profitable outcomes (Fillis & Rentschler, 2010). Risk-taking involves founders investing substantial resources in potential opportunities for success, while proactiveness emphasises tenacity, adaptability, and deviation from conventional methods (Fillis & Rentschler, 2010). Creative leadership is often viewed as more effective than traditional management techniques in navigating non-linear and unpredictable external events. The fusion of creativity and technology is crucial for the commercialisation of ideas, products, or services. Individual creativity contributes to a competitive advantage and fosters innovation within startups, while teams or groups of creative individuals amplify this advantage further (Hirst et al., 2009). Thus, fostering a creative culture is essential in startup environments. In today’s rapidly changing economies, creativity holds significant importance across commercial, scientific, and social domains. Entrepreneurial contributions to creativity can challenge traditional norms and achieve incremental or ground breaking success. Entrepreneurial innovation draws from various disciplines beyond business, emphasising the role of economics, psychology, sociology, and other subjects (Blackburn & Kovalainen, 2009). It is argued that entrepreneurial creativity research should be informed by these multidisciplinary perspectives (Fillis & Rentschler, 2005). Furthermore, it is emphasised that creative ideas need not be complex, as even simple responses can lead to entrepreneurial success in the business environment (Fillis & Rentschler, 2005).

H2:

Organisational creativity directly affects entrepreneurial success.

2.7. Organisational learning and organisational creativity

In a competitive market, founders of startups face the challenge of adapting quickly to a changing environment and employing innovation to address new and demanding scenarios. Hence, startup founders must explore and create novel approaches to drive innovation across all aspects of their business. Learning plays a vital role in problem-solving and can serve as a catalyst for making a difference. Consequently, problem-solving has been recognised as a crucial tool for fostering innovation and entrepreneurial behaviour. Creativity enables entrepreneurs to identify and leverage opportunities that enhance the competitiveness and innovativeness of their ventures (Fillis & Rentschler, 2010). This understanding has propelled the significance of creativity development and innovative capabilities, with entrepreneurship classrooms assuming an increasingly pivotal role in fostering such learning.

Intrapreneurship represents an extension of organisational learning as intrapreneurs, who are employees possessing resources such as experience, innovative thinking, a willingness to embrace change and risk, and access to business resources, challenge conventional paradigms (Honig, 2001). Founders learn through interaction with their environment to acquire knowledge (Casey, 2005). Intrapreneurs, however, need to be risk-takers who seize opportunities that arise in dynamic environments (Dutta & Crossan, 2005). Entrepreneurship necessitates an ecosystem that supports creativity and discovery, extending beyond a supportive and productive business climate (Lee et al., 2004). A robust and broad knowledge base, sophisticated business and social networks, and the ability to identify opportunities are factors that foster successful entrepreneurial behaviours (Harryson, 2008). Notably, organisations renowned for their exceptional performance, such as Rover and Whirlpool, actively seek specific resources from their environment, including new production technologies, highly skilled employees, and innovative training programs, to cultivate the skill sets required for sustained performance.

Moreover, when organisations embrace learning as a cultural component, it impacts corporate values, such as the promotion of intrapreneurial innovation (Honig, 2001). Conceptual learning is a learning strategy that fosters creativity by equipping employees with the knowledge and means to critically comprehend existing methods and situations. For instance, conceptual knowledge can be nurtured by encouraging employees to explore novel ways of working or by facilitating improvements that are not directly tied to their roles (Ubeda & Lopis, 2002).

H3:

Organisational learning directly affects organisational creativity.

2.8. Entrepreneurial ecosystem and organisational learning

According to the World Economic Forum in 2013, startups’ growth relies on market access, human capital, and funding (Foster et al., 2013). An ideal market entails supportive regulations, abundant human resources, and facilitating authorities. Factors such as the availability of human resources, government policies, R&D funding, university support, and incubators significantly influence a startup’s learning outcomes (Manimala et al., 2019). Stuart and Sorenson (2005) underscore the importance of local social networks in providing founders with access to capital sources, knowledge, finance, and personnel. Governments play a crucial role as stakeholders in facilitating market access. Implementing cooperative strategies for sharing knowledge and technology with universities in developed nations is necessary to enhance access to the host country’s knowledge resources. Additionally, this study addresses the impact of workforce quality on an organisation’s learning process. The current trend in human resource development emphasises workplace learning, where employees learn while working instead of attending formal training courses. As a result, modern HR focuses on interactive and self-learning skill sets. Startups that attract talent from various fields have an advantage in terms of employee branding, as fresher talent will be drawn to these organisations for learning purposes. Creating an ecosystem that attracts potential entrepreneurs necessitates the involvement of professional services, experienced mentors/advisers, incubators/facilitators, and networks of fellow entrepreneurs (Roundy et al., 2017). Without the support of specialists, entrepreneurs find it challenging to incorporate learning activities into their operations.

An efficient government is positively linked to a favourable entrepreneurial environment (Korosteleva & Belitski, 2017). A robust entrepreneurial ecosystem focuses on key participants such as experienced entrepreneurs, incubators, and universities. In developed ecosystems, the government collaborates with community stakeholders to establish denser networks of entrepreneurs, supportive platforms, and activities that facilitate connections among entrepreneurs. An ecosystem fosters learning within the entrepreneurial community, and the success of entrepreneurs contributes to the availability of additional resources, making it easier for entrepreneurs to develop and sustain their ventures. The presence of technological talent generated by high-quality educational institutions or access to educational services is an indicator of ecosystem maturity in terms of education and training (Berbegal‐Mirabent et al., 2012). Colleges and research centres play a crucial role in training entrepreneurs and providing networking opportunities through their knowledge of technologies that assist businesses. Successful founders often serve as mentors to their employees. Establishing an effective training system based on informal learning practices is also a cost-effective way for startups to optimise their training efforts. Furthermore, the cultural and social norms of each nation reflect its unique characteristics. The geopolitical situation influences society and creates opportunities and barriers for companies (Cukier et al., 2015). For instance, the perception of failure as a learning opportunity rather than a punishment depends on the local society’s views and attitudes towards failure. If failure is stigmatised, organisations associated with failure may struggle to utilise the knowledge and skills they have acquired to rebuild their businesses (Cardon et al., 2011). Consequently, founders must establish a culture of learning at all levels of their business.

H4:

Entrepreneurial ecosystem factors (H4a—Accessible market, H4b—Cultural support, H4c—Education and training, H4d—Regulatory framework, H4e—Support system, H4f—Workforce) directly affect organisational learning.

2.9. Entrepreneurial ecosystem and entrepreneurial success

Market access is vital for the long-term viability of entrepreneurial organisations, necessitating a supportive regulatory environment and access to human resources and auxiliary bodies. Factors such as the availability of human capital, government legislation, R&D support, academic aid, and incubators significantly influence a company’s performance (Caliendo & Kritikos, 2008). Local social networks play a crucial role in providing entrepreneurs with access to capital, expertise, funding, and human resources (Brush et al., 2019). Researchers emphasise the significance of expanding the talent pool within an ecosystem for the survival and prosperity of companies (Feld, 2020; Isenberg, 2011). Management and technological talent offer opportunities for local entrepreneurs to expand internationally, benefiting from economies of scale and a diverse pool of skills (Ghio et al., 2015; Glaeser et al., 2014; Mason & Brown, 2014). However, high labour demand and compensation in larger markets can discourage individuals from starting their own ventures, depleting the workforce in startups and small businesses (Caliendo & Kritikos, 2008).

Developed ecosystems foster entrepreneurship through government support, community networks, and platforms that provide resources and opportunities for entrepreneurs (Spigel, 2017). Strong public backing is essential for successful entrepreneurship (Baumol, 2008). Private investment organisations, such as angels and venture capitalists, offer advice and investments to startups, which can also benefit from R&D funding and government initiatives (Cukier et al., 2015). Technology serves as a catalyst for attracting highly skilled individuals to the region and acts as a proving ground for the quality of new entrepreneurial generations (Huffman & Quigley, 2002). The existing regulatory system, encompassing labour laws, tax laws, intellectual property protection, patents, and other forms of red tape, determines costs and shapes the startup business model (Cukier et al., 2015). Education level, work experience, and personal attributes contribute to an individual’s entrepreneurial spirit (Boschma & Frenken, 2009). Entrepreneurs assess the host country’s education policy to determine the quantity and quality of human resources in the startup market (Wright et al., 2007). Educational institutions play a critical role in developing talent and technology that assist businesses in surviving and growing (Huffman & Quigley, 2002). Effective educational strategies can also contribute to enhancing the identification of business opportunities and mitigating the perception of risks associated with initiating entrepreneurial ventures. By implementing such policies, individuals can be equipped with analytical methodologies and tools, such as market research and risk analysis, which enable them to reduce the uncertainty related to the various scenarios in which their envisioned entrepreneurial endeavour may be positioned. Consequently, this can alleviate their perceived risk levels when embarking on a new entrepreneurial venture (Martínez-Cañas et al., 2023).

Trust among business residents, community members, and social security is a significant element of a thriving entrepreneurship environment. Appreciation for creative ideas, methods, as well as cultural factors like race and ethnicity, contribute to a unique ecosystem where entrepreneurship becomes the norm (Caliendo & Kritikos, 2008). In the entrepreneurial context of developing countries, research has indicated that both social networks and family networks have the potential to provide informal support to entrepreneurs in rural and economically challenged regions, particularly in the form of risk-sharing. This can play a pivotal role in creating conducive conditions for their entrepreneurial success (Zhang & Zhao, 2015). Moreover, both social networks and family networks have the potential to provide informal support to entrepreneurs in rural and economically challenged regions, particularly in the form of risk-sharing. This can play a pivotal role in creating conducive conditions for their entrepreneurial success (Ruiz-Palomino & Martínez-Cañas, 2021). Thus, community cultures bolster entrepreneurial activity.

H5:

Entrepreneurial ecosystem factors (H4a—Accessible market, H4b—Cultural support, H4c—Education and training, H4d—Regulatory framework, H4e—Support system, H4f—Workforce) directly affect entrepreneurial success.

2.10. Entrepreneurial ecosystem and organisational creativity

Globalisation and technological advancements have created more commercial opportunities but also intensified market congestion and competition (McMullen & Shepherd, 2006). Startups face the crucial task of selecting the market for their innovative products. Isenberg (2010) proposes an entrepreneurial ecosystem model that incorporates factors such as supportive policies, leadership, access to unique financing, essential human resources, and business-friendly marketplaces. Human capital plays a critical role in fostering a creative culture within organisations, with recruitment, selection, and employee retention being key components (Martins & Terblanche, 2003). Beyond individual attributes like intelligence, expertise, risk-taking, curiosity, and enthusiasm, diversity in recruitment is crucial for attracting creative and innovative individuals who can contribute diversified ideas and methods (Martins & Terblanche, 2003).

Creativity is not solely influenced by individual traits but also sociologically grounded, with ecosystem stakeholders directly or indirectly impacting founders’ decision-making processes due to biases (Manimala et al., 2019). Startup ecosystems raise awareness and stimulate entrepreneurial creativity (Theodoraki & Messeghem, 2017). Ecosystem performance is seen as the interaction among individuals, organisations, and institutions, with founders overseeing the operation and development of the ecosystem. Recognitions, rewards, and access to resources such as time, information, technology, and creative individuals are important factors (Alvedalen & Boschma, 2017; Martins & Terblanche, 2003). Additionally, information technology serves as a crucial resource for supporting effective innovation. Regional entrepreneurship policies are shifting toward promoting entrepreneurship innovation, aiming to transition from an entrepreneurship policy to an entrepreneurial economy policy (Stam, 2015).

An effective regulatory framework, prioritisation of resource allocation, and government support in job creation and finance contribute to an entrepreneurial ecosystem that fosters innovative firms and influences founders’ perspectives on asset allocation, government assistance, and trust (Stenholm et al., 2013). This shift in perception leads businesses to focus on generating creative products and services rather than copying existing ideas. Research on creativity has drawn insights from psychometrics, cognitive psychology, biostereometrics, biology, and contextual studies, highlighting implications for education and training (Petrowski, 2000). The significant impact of creativity has led to proposals for the establishment of a “Creativity University” dedicated to teaching and nurturing creative art and abilities (Duderstadt, 2000). Universities and research centres play a role in supporting businesses through entrepreneurial training and networking opportunities. Start-up-friendly countries facilitate incubators and accelerators run by universities and existing firms, offering coaching and enhancement of startup approaches such as innovation, lean startup, customer development, and disciplined entrepreneurship (Aulet, 2013; Ries, 2011).

Cultural support, including broad knowledge bases, well-developed business and social networks, and the ability to identify opportunities, contributes to effective entrepreneurial behaviour (Harryson, 2008; Lee et al., 2004). The appreciation for innovative ideas and approaches creates a unique ecosystem where cultural norms foster entrepreneurship. Risk-taking is inherent to the process of ingraining innovation in organisations, societies, and communities, representing people’s willingness to invest substantial resources in prospects expected to succeed.

H6:

Entrepreneurial ecosystem factors (H4a—Accessible market, H4b—Cultural support, H4c—Education and training, H4d—Regulatory framework, H4e—Support system, H4f—Workforce) directly affect organisational creativity.

3. Methodology

3.1. Research methodology

The quantitative approach was applied for this study because it can indicate the study’s problem by highlighting patterns or simply describing the relationships between variables. Examining the validity and reliability of the measurement scales may also provide additional evidence for the findings. To test hypotheses and analyse the association between variables, statistical, empirical, and numerical methods are utilised. The Table 1 indicate four factors with measured items.

Table 1. Measurement scale

Constructs		Items	Statements
Entrepreneurial Ecosystem variables	Accessible Markets (ACMA)	ACMA1	Domestic Market – Large Companies as Customers
		ACMA2	Domestic Market – Small/Medium Companies as Customers
		ACMA3	Domestic Market – Governments as Customers
	Human Capital/Workforc (HUCA)	HUCA3	Entrepreneurial Company Experience
		HUCA4	Outsourcing Availability
		HUCA5	Access to Immigrant Workforce
	Support System (SUSY)	SUSY1	Mentors/Advisors
		SUSY2	Professional Services
		SUSY3	Incubators/Accelerators
		SUSY4	Network of Entrepreneurial Peers
	Regulatory Framework (REFRA)	REFRA1	Ease of Starting a Business
		REFRA2	Tax Incentives
		REFRA3	Business-Friendly Legislation/Policies
	Education and Training (EDUTRA)	EDUTRA2	Available Workforce with University Education
		EDUTRA3	Entrepreneur-Specific Training
		EDUTRA4	Universities Promoting a Culture of Respect for Entrepreneurship
		EDUTRA5	Role of Universities in Idea-Formation for New Companies
		EDUTRA6	Role of Universities in Providing Graduates for SMEs
	Cultural Support (CUSUP)	CUSUP2	Preference for Self-Employment
		CUSUP3	Success Stories/Role Models
		CUSUP4	Research Culture
		CUSUP5	Positive Image of Entrepreneurship
Organisational Learning (ENLE)		ENLE1	Acquiring much new and relevant knowledge
		ENLE2	Acquiring critical capacities and skills
		ENLE3	Influencing of new knowledge on improvements
		ENLE4	their organisations were learning organisations
Organisational Creativity (ENRE)		ENRE1	Adaptability to the changing environment
		ENRE2	New initiatives in planning
		ENRE3	New initiatives in control system
		ENRE4	New initiatives with integrated apparatus
Entrepreneurial Success (ENSU)		ENSU1	Market share
		ENSU2	Increase in sales.
		ENSU3	Increase in profitability
		ENSU4	Increase in earnings
		ENSU5	Sustainable grow
		ENSU6	Exceeding business goals

Source: Adapted from World Economic Forum (2013), Akgün et al. (2008); Ellinger et al. (2002); Hormiga et al. (2011).

3.2. Sampling and data collection

There were a total of 5,839 small and medium-sized businesses in Tay Ninh Province in 2021 (Nhi, 2022), according to the Department of Planning and Investment of Tay Ninh Province, making up 96.49% of all businesses in the region. The owners or CEOs of SMEs and startups in Tay Ninh City (Vietnam) who have run their own businesses for at least five years were chosen to be the target population of this study, as mentioned in Table 2. The questionnaire was sent indirectly to 400 business owners in the city via official email. A total of 219 responses were collected, equivalent to a response rate of 55%. After removing unreliable data, 200 responses were expected to serve the research purpose. Stratified sampling was used to collect the responses. According to Heckler (2005), the Exploration Factors Analysis (EFA) has the lowest subject-to-item scale of any case at 5:1. In this study, a 5:1 ratio would be reached to ensure unwavering consistency and validity.

Table 2. Demographic data

Demographic Categories		Frequency	Percentage (%)
Gender	Male	119	59.5
	Female	81	40.5
Age	18–24	6	3.0
	25–34	61	30.5
	35–44	80	40.0
	45–54	49	24.5
	Above 55	4	2.0
Education level	High School	22	11.0
	College	47	23.5
	University	99	49.5
	Postgraduate	32	16.0
Income	Less than 1 billion VND	48	24.0
	2–3 billion VND	72	36.0
	4–5 billion VND	40	20.0
	More than 5 billion VND	40	20.0
Age of firms	Less than 1 year	43	21.5
	2–3 years	78	39.0
	4–5 years	39	19.5
	5 years	1	0.5
	More than 6 years	39	19.5
Fields	Industry	57	28.5
	Trading and Service	72	36.0
	High Technology	9	4.5
	Real Estate/Construction	18	9.0
	Others	44	22.0
Firms size (number of employees)	Less than 10 employees	92	46.0
	11–20 employees	54	27.0
	21–40 employees	31	15.5
	More than 40 employees	23	11.5

Source: Author owns calculation.

3.3. Measurement of variable

The survey form was used because it helps the researcher to contact a wide range of individuals and gather data on a range of questions in a short period (Jankowicz, 2005). The questionnaires were composed in both English and Vietnamese to alleviate respondents’ confusion and failure to understand the survey. All steps were based on a five-point Likert scale of 1 to 5, indicating strongly disagreed, disagreed, neutral, agreed, and strongly agreed. Hence, conclusions can be drawn based on empirical evidence, which leads to the reliability and objectiveness of the findings.

3.4. Analytical procedure

The partial least squares structural equation model (PLS-SEM) was used to analyse the results. Before any factual investigation, the data would be coded, digitised, and screened for missing values. The SmartPLS 3.0 program was used to view the statistical results. When using PLS-SEM in a multivariate analysis methodology, a full evaluation of the final finding (model assessment) is required. Examining the measurement model and the structured model are typically the first two phases in PLS-SEM. The measurement model’s validity and reliability were tested in the first step. The aim of this step was to ensure that if the meaning indicates that a variable is not accurate or trustworthy, the researcher would not be able to use it to analyse systemic interactions. After the values have been qualified, the structural model estimates were examined.

4. Results and discussion

4.1. Measurement model

Factor loadings equal to or greater than 0.7 yield desirable effects (Nenkov et al., 2008). Accordingly, the selected items in each variable met the necessary reliability by a factor greater than 0.7 (the values range from 0.704 to 0.903), except ENSU5 (0.684). The findings of the average variance extracted (AVE) have been successfully used to determine convergent and discriminatory validity. Therefore, the AVE statistic is the criterion for measuring the model’s convergent validity and the average sum of variation in the predictor variables that it can explain. (AVE) readings should be higher than 0.5 (0.5), according to Fornell and Larcker (1981). Table 4 shows that the AVE of all variables in this study exceeded the criterion by more than 0.5, with values ranging from 0.580 to 0.754.

Table 4. Fornell-Larcker criterion analysis

	ACMA	CUSUP	EDUTRA	ENSU	ENRE	ENLE	REFRA	SUSY	HUCA
ACMA	0.779
CUSUP	0.377	0.818
EDUTRA	0.465	0.606	0.790
ENSU	0.443	0.284	0.381	0.779
ENRE	0.542	0.422	0.578	0.563	0.761
ENLE	0.550	0.426	0.482	0.505	0.576	0.795
REFRA	0.382	0.598	0.591	0.366	0.438	0.439	0.869
SUSY	0.486	0.486	0.642	0.532	0.613	0.504	0.553	0.769
HUCA	0.339	0.314	0.526	0.464	0.403	0.433	0.319	0.538	0.802

Source: Author own calculation, based on SmartPLS 3.0 program.

Fornell-Larcker Criteria Analysis is routinely used to test the discriminant validity of the model. By using the square root of AVE to see if it has more variance in its dimensions than any other construct (Hair et al., 2014). For example, the Regulatory Framework (REFRA) AVE is estimated to be 0.754. (From Table 4). As a result, its square root is 0.869. The result is greater than the correlation values in the REFRA column (0.553 and 0.319) and greater than the correlation values in the REFRA row (0.366 to 0.598). Similarly, as seen in Tables 3, the latent variables in other variables yield the same output.

Table 3. Internal consistency

	Cronbach’s Alpha	Composite Reliability	AVE
ENLE	0.805	0.872	0.632
ENRE	0.759	0.846	0.580
ENSU	0.870	0.902	0.607
ACMA	0.678	0.815	0.596
HUCA	0.722	0.844	0.643
SUSY	0.770	0.851	0.588
EDUTRA	0.849	0.892	0.623
REFRA	0.837	0.902	0.754
CUSUP	0.836	0.888	0.667

Source: Author own calculation, based on SmartPLS 3.0 program.

Therefore, the independent and dependent variables in this met the criteria of the measurement model by employing outstanding statistics for evaluating reliability and validity (Outer loadings, Composite reliability (CR), Average variance extracted (AVE), and Fornell-Larcker Criterion Analysis.

4.2. Structural model result

The next stage is to use bootstrapping, as hypothesised in H1 and H2, the positive influence of organisational learning and creativity on entrepreneurial success is confirmed. Additionally, analogous outcomes are obtained in the context of H3. Furthermore, all the calculated path coefficients corresponding to H1, H2, and H3 are statistically significant. The empirical analysis lends support to hypotheses H1, H2, and H3 by demonstrating the existence of significance levels with P-values below 0.05. Consequently, the findings underscore the interdependence between organisational learning, creativity, and entrepreneurial success, which cannot be disentangled (refer to Table 5).

Table 5. Path coefficient and hypotheses testing result

Hypothesises	Direct Effects Model		Path Coefficients	P-value	Results
H1	Organisational Learning -> Entrepreneurial Success		0.158	0.043	Supported
H2	Organisational Creativity -> Entrepreneurial Success		0.304	0.000	Supported
H3	Organisational Learning -> Organisational Creativity		0.249	0.001	Supported
H4	Entrepreneurial Ecosystem -> Organisational Learning	H4a - Accessible Markets	0.342	0.000	Supported
		H4b - Cultural Support	0.100	0.288	Rejected
		H4c - Education and Training	0.034	0.727	Rejected
		H4d - Regulatory Framework	0.111	0.228	Rejected
		H4e - Support System	0.112	0.155	Rejected
		H4f - Workforce	0.172	0.006	Supported
H5	Entrepreneurial Ecosystem -> Entrepreneurial Success	H5a - Accessible Markets	0.091	0.227	Rejected
		H5b - Cultural Support	−0.062	0.410	Rejected
		H5c - Education and Training	−0.165	0.102	Rejected
		H5d - Regulatory Framework	0.081	0.309	Rejected
		H5e - Support System	0.194	0.035	Supported
		H5f - Workforce	0.218	0.001	Supported
H6	Entrepreneurial Ecosystem -> Organisational Creativity	H6a - Accessible Markets	0.181	0.003	Supported
		H6b - Cultural Support	−0.005	0.951	Rejected
		H6c - Education and Training	0.217	0.024	Supported
		H6d - Regulatory Framework	−0.016	0.826	Rejected
		H6e - Support System	0.283	0.001	Supported
		H6f - Workforce	−0.024	0.729	Rejected

Source: Author owns calculation, based on SmartPLS 3.0 program.

Notably, concerning hypotheses H4, H5, and H6, most of the variables within the entrepreneurial ecosystem exhibit insignificant impacts on the dimensions of learning, success, and creativity due to P-values exceeding 0.05. Nevertheless, certain hypotheses yield meaningful insights, unravelling the intricate relationships between the entrepreneurial ecosystem and organisational learning. Notably, H4a (accessible market, β = 0.342, p < 0.05) and H4f (workforce, human capital, β = 0.218, p < 0.05) manifest a significant influence. Similarly, within H5, support system (H5e, β = 0.194, p < 0.05) and workforce (H5f, β = 0.218, p < 0.05) emerge as prominent catalysts of entrepreneurial success. These factors act as direct contributors to business success and crucial precursors thereof, underscoring their inseparable nature (see Table 5).

Turning to hypothesis H6, three path coefficients—H6a, H6c, and H6e—attain significance levels below 0.05, in contrast to cultural support, regulatory framework, and human capital (H6b, H6d, and H6f), which fail to elicit a noteworthy impact on organisational creativity, evidenced by P-values surpassing 0.05. For the results of path coefficients for the research model, see Figure 1.

Figure 1. Result of research framework.

Source: Author owns conception, based on research question.

5. Discussion

In conclusion, the outcomes of this study confirm the significant effects of H1, H2, and H3, underscoring a substantial connection between the entrepreneurial success, organisational creativity, and learning. Additionally, while H4, H5, and H6 exhibit a partial impact, the comprehensive analysis underscores the intricate interplay of ecosystem variables with organisational learning, creativity and business success. These findings contribute to a more nuanced understanding of the relationships within the studied framework, shedding light on the multifaceted nature of factors influencing entrepreneurial success. The research outcomes significantly contribute to the existing entrepreneurship literature by shedding light on the pivotal roles played by ecosystem components such as accessible markets, educational initiatives, training programs, and the presence of entrepreneurial talent (human capital) in driving entrepreneurship’s expansion across diverse societal sectors. These factors not only positively impact business success but also influence organisational learning and creativity.

The study establishes a positive correlation between learning and creativity within the business context, underscoring the need for educational practices that foster innovation. Furthermore, it emphasises the positive link between organisational learning, creativity, and entrepreneurial success. Building education systems and policies that promote innovation becomes crucial in ensuring the success of startups. The study recognises the importance of ecosystem practices in creating a supportive startup environment, mitigating the risk of venture failure by influencing factors of learning and creativity. These insights highlight the significance of ecosystem dynamics in society’s entrepreneurial landscape.

The study’s emphasis on both statistically significant and non-significant variables preserves its academic and practical value. By encompassing a wide range of variables, the research provides a nuanced understanding of the intricate interplay within the entrepreneurial realm. The research also underscores the necessity for future investigations to explore the indirect roles that certain non-significant variables might play in shaping the broader entrepreneurial ecosystem dynamics.

The research findings offer practical implications for policymakers, educators, and entrepreneurs seeking to foster a vibrant and innovative entrepreneurial landscape. This study highlight that the accessible market factor exerts a stronger influence on startup learning compared to human capital. That suggests that lawmakers and national leaders should focus on developing the accessible market factor if they intent to increase learning in their entrepreneur community. This point is meaningful for Vietnam’s policymakers and other countries pursuing a socialist-oriented market economy. The nature of this type of economy is hierarchical and bureaucratic, and the red tap appears as a barrier to the growth of the business sector. Thus, continuous innovation in economic policy becomes a strategic imperative, directly impacting enterprise creativity, learning, and ultimately business success. Besides, building a social networking that providing founders with access to capital sources such as knowledge, finance, and personnel is necessary for an effective ecosystem (Stuart & Sorenson, 2005). More specifically, strategies for sharing knowledge and technology with universities in developed countries should be considered and implemented. It is possible to consider giving a long-term strategy to improve the quality of human resources locally instead of outsourcing human resources abroad with high costs. Moreover, understanding the significance of social networks and family networks in rural and economically challenging environments, governments and entrepreneurial support organizations can formulate tailored policies and programs to offer localized assistance. This may encompass supporting social and family networks to mitigate risks and create favourable conditions for enterprises. In terms of organisational creativity, the study empirically establishes the positive impact of accessible markets, support systems, and education and training on entrepreneurial innovation within the startup ecosystem. Notably, the support system emerges as the most influential factor on startup creativity, followed by education and training, and accessible markets. A critical relationship exists between market incubation founders’ perceptions (including training, business support, financial and technical assistance, resources and equipment, networking and mentorship, and aftercare programs) and their understanding of the services offered by incubators (Meru & Struwig, 2011). Therefore, authorities should actively promote this symbiotic relationship to stimulate innovative entrepreneurship.

In addition, the study also highlights the importance of learning factors in enhancing innovation with-in entrepreneurial community. As such, the national leaders should consider more on education in the community. To be more specific, potential entrepreneurs’ creative thinking is formed through a professional and formal education and training process, particularly higher education courses such as Bachelor of Eco-nomics or MBA programs that can integrate entrepreneurship. Previous studies have also agreed on the value of education in the startup ecosystem, with successful entrepreneurs serving as coaches to aspiring entrepreneurs (Berbegal‐Mirabent et al., 2012; Ries, 2011). Incubators and accelerators are run by universities and existing businesses that use agile methodologies, lean startup, customer development, and disciplined entrepreneurship to train and guide startups (Blank, 2020). These training programs and entrepreneurial support policies not only aid individuals in more effectively identifying business opportunities but also serve to mitigate uncertainty and risks associated with entrepreneurship. This prompts a consideration of optimizing the training process within the entrepreneurial domain. By blending experiential “learning by doing” with a challenging and growth-oriented learning environment, we can foster the emergence of future generations of innovative, self-assured entrepreneurs better equipped to confront the challenges of entrepreneurship. In Vietnam, entrepreneurial competitions, seminars, workshops, and the sharing of experiences among successful entrepreneurs are already prevalent, particularly in business universities. Leveraging the knowledge of experienced predecessors enables young entrepreneurs to mitigate the risk of business failure. Importantly, this research underscores the pivotal role of organisational learning and creativity in entrepreneurial success. Consequently, policymakers, governors, and ecosystem founders must recognise that creativity plays a fundamental role in determining startup success, particularly in a rapidly changing business landscape characterised by increasing uncertainty. To foster an environment conducive to innovative startup ideas, it is imperative to loosen bureaucratic barriers, evaluate student achievements based on creativity, encourage risk-taking among founders, and leverage knowledge from partners and public sources to enhance current knowledge utilisation.

Conclusions

The study aims to identify the important determinants of the Entrepreneurial Ecosystem, and startup learning and innovation since these variables relate to business success in the context of Vietnam (Tay Ninh City). Research data collected from 200 SMEs was used to test the research model. This study’s findings reveal empirical evidence to support numerous theories, allowing for a better understanding of the ecosystem’s effects on organisational learning, innovation, and entrepreneurial success (Caliendo & Kritikos, 2008; Stuart & Sorenson, 2005; Theodoraki & Messeghem, 2017). The findings of this study underscore the significance of several environmental variables, namely the Accessible Market, Human Capital, Support System, and Education & Training, in shaping ENLE (Entrepreneurial Ecosystem), ENRE (Entrepreneurial Learning), and ENSU (Entrepreneurial Success). The observed positive and multiple correlations highlight the need for careful consideration of these ecosystem aspects and the formulation of management-level recommendations. Policymakers, university executives, incubator entities, and entrepreneurs worldwide can effectively practice entrepreneurship by focusing on these variables.

Notably, within the Vietnamese market context, the accessible market and support system variables emerge as the most influential factors affecting the learning and innovation capabilities of enterprises. In order to bridge the gap between business owners and government support, it is imperative for the government to continually innovate its management practices in the business sector. By doing so, they can create an environment that fosters closer collaboration and mutual understanding. This finding aligns with previous research and contributes to the existing entrepreneurship literature, particularly within the context of Vietnam—a developing Southeast Asian country that follows a socialist-oriented market economy. Furthermore, this study establishes a connection between the main findings of the research and suggestive phenomena/processes within the Vietnamese economy. By highlighting the importance of accessible markets and support systems, the study sheds light on the challenges faced by businesses and offers insights into how policymakers can address these challenges through innovative economic policies and initiatives. This connection underscores the relevance and applicability of the research findings to the specific economic context of Vietnam, and it encourages further exploration of these connections to foster entrepreneurship and economic development.

However, the main limitation should be considered while interpreting the findings of this study. With the 200 responses collected from small enterprises in Tay Ninh (Vietnam), the results are subject to generalisation issues. Despite having practical recommendations and meaningful data, this study mainly describes the circumstances in Vietnam—a developing Southeast Asian country that follow a socialist-oriented market economy. This paper paves the way for further research. First, the use of a probability sample to reproduce this study is possible to expand this issue. In this respect, it enables a population similar to Vietnam to generalise the conclusions of the field. Second, ecosystem variables should be generated in other nations, particularly in socialist-oriented market economies to have a deeper understanding. This study can be extended by the later author to include strategic variables in the research framework. In order to obtain deeper insight into the impact of the ecosystem on the relationship entre entrepreneurship variables and start-up success, all four characteristics of the entrepreneurial ecosystem should thus be covered by the research model.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Notes on contributors

Khuong Ngoc Mai

Mai Ngoc Khuong (PhD) is a Lecturer and Researcher of School of Business Administration, International University, Vietnam National University, Ho Chi Minh city. He has Bachelor degree in tourism and hospitality management, Master of Science degree in leisure, tourism and environment at Wageningen University, The Netherlands, and PhD in development management at School of Public Administration of the National Institute of Development Administration (NIDA), Bangkok, Thailand. His research areas of interest are organizational behaviour, entrepreneurship, leadership, and tourism. Nguyen Thanh Van is an MBA candidate studying at the Swinburne University of Technology, Australia. Van holds a Bachelor’s Degree in Human Resources and Business Management from West of England University, Bristol. Van was a student in the Business Administration program at International University, Vietnam National University, Ho Chi Minh City, Vietnam. His research interest includes topics about entrepreneurship and strategic management.