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Abstract

This article examines how high-performing digital entrepreneurship enables wealth generation or perpetuates inequalities. We integrate and extend entrepreneurship and sociology of (transnational) education scholarship to investigate how socio-economic background affects the likelihood of entrepreneurs building high-growth, digital businesses. Specifically, we address whether Vietnam’s transition from industrialization (1986) to post-industrialization (since 2009) broadens entrepreneurial opportunities or concentrates them among the country’s (upper) middle class. Our findings reveal digital entrepreneurs are five times more likely to have tertiary education from costly destinations like the United States, United Kingdom, or Australia, and three times more likely to have worked in English-speaking countries, than the entrepreneurs who built physically oriented businesses during the industrialization era. These findings suggest that the advance of Vietnam’s digital economy reinforces socio-economic divides, as digital entrepreneurship opportunities increasingly depend on access to (upper) middle-class backgrounds that can afford elite transnational education.

Keywords

Development entrepreneurship post-industrial growth social inclusion Vietnam

Introduction

Industrialization can drive significant annual economic growth, with income levels increasing as a result. However, economic growth can also fuel growing inequality, so that some members of society benefit significantly while others’ incomes stagnate. As an illustration, The Economist (2024) recently reported that the average annual growth rate of Asia’s middle class has declined since 2014. This slowing of the middle class’s growth in this dynamic region, which has expanded its activities and footprint in digital and knowledge-intensive activities, raises questions about how inclusive the growth has been. On the other hand, Vietnam’s strong economic growth rates since the 1990s have been accompanied by a steady Gini coefficient, suggesting that the country’s levels of inequality have remained relatively low. The slow growth of middle class raises questions about how inclusive the country’s recent post-industrialization has been.

In this article, we examine an aspect of this relationship between post-industrialization and social inclusion, by focussing on access to high-growth entrepreneurship as a means of wealth creation. By ‘access to’ we draw on sociological theory that expects that different backgrounds contribute to one’s ability to gain a type of employment (here, digital entrepreneurship). We integrate and extend entrepreneurship and sociology of (transnational) education scholarship to investigate how socio-economic background affects the likelihood of entrepreneurs building high-growth, digital businesses. We ask: how does post-industrialization shape individual’s ability to engage in wealth-generating entrepreneurship? Does the expanse of digital economy activities in an emerging economy create broader opportunities for wealth generation through high-growth entrepreneurship? We are interested in understanding whether digitally oriented entrepreneurship is primarily available to the existing middle class, or a mechanism for social mobility. In answering these questions, we offer a novel insight into the relationship between post-industrialization and social inclusion in emerging economies.

Entrepreneurship offers the potential for transformative social mobility, as the establishing of ventures that achieve high equity valuations can generate significant wealth for the founders (Alvarez and Barney, 2014. By founders we refer to the individuals who establish the company, and therefore have significant (initial) equity stakes in the business. However, research highlights that access to entrepreneurship is often shaped by social class. Lower socio-economic status can limit access to social capital – defined as ‘resources available to people through their social connections’ – which in turn restricts access to high-growth entrepreneurship opportunities (Kim and Aldrich, 2005: 93). Human capital, which is defined as the education, skills, and experience of individuals (see Becker, 1993), can play a critical role in shaping an ability to perform in complex sectors such as information and communication technologies (Marvel, 2013; Unger et al., 2011). The human and social capital needed to thrive in the digital economy may be most accessible to those from higher socio-economic backgrounds (Brandle and Kuckertz, 2023). If only a privileged subset of society has access to these pathways, high-growth entrepreneurship may serve to exacerbate inequality rather than act as a lever for social mobility (Bruton et al., 2021; Frid et al., 2016; Packard and Bylund, 2018). This unequal access to digital entrepreneurship may be accentuated when examining the emerging economy context. The requisite advanced digital skills, English-language proficiency, and global networks are often acquired through transnational education and work experiences in the West. This raises critical questions about who has the resources and opportunities to access wealth-generating activities – an arena for affecting social inclusion – particularly as economies transition from industrialization to post-industrialization.

To address these questions, we integrate entrepreneurship theory (De Massis et al., 2018; Lechner and Pervaiz, 2021) with research on social inclusion and social mobility (Aerts and Van Mol, 2023; Audretsch et al., 2013; Sorensen and Sharkey, 2014). We understand entrepreneurship as the identification, evaluation, and exploitation of opportunities (Shane and Venkataraman, 2000) and conceive of entrepreneurial capabilities as the competences, resources, and skills that enable individuals to perform effectively in dynamic environments (Teece et al., 1997). High-performing entrepreneurship refers to the founders of businesses that achieve significant equity market valuations. Following the World Bank’s definition, social inclusion is ‘the process of improving the terms on which individuals and groups take part in society’ by enhancing their abilities and access to opportunities. Here, we focus on wealth generation through high-growth entrepreneurship, examining the human and social capital endowments of founders that succeed in post-industrial, digitally oriented sectors.

Our focus on who in an emerging economy has the human and social capital necessary to participate in wealth-generating entrepreneurial activities provides insight into how post-industrialization processes shape the contours of social inclusion. Entrepreneurship research points to studying at elite (national) universities, such as MIT and Stanford University, as crucial institutions for (Americans) accumulating the skills and social connections that high-growth entrepreneurs need to build high-technology businesses (see Roberts, 1991). Research on the capabilities of digital entrepreneurs in emerging entrepreneurial ecosystems, like China, India, and Taiwan, have often taken a transnational perspective, examining how studying at elite Western universities, especially in the United States, contributes to the capabilities of digital entrepreneurs (Batjargal, 2007; Kenney et al., 2013). Rather than place-based experience, such as studying at a leading local university, this research suggests that attendance at an American university may be a crucial factor in one’s ability to build a digital business (Klingler-Vidra et al., 2021). While this research finds that digital entrepreneurs – in the first or second cohort of an emerging ecosystem – tend to study at elite American universities, it does not examine the socio-economic dimensions shaping individual’s ability to undertake expensive transnational education.

This is our point of departure: we bring in research on the sociology of education, which underscores that elite education, including transnational education, is primarily accessible to individuals from higher socio-economic backgrounds (Ballatore and Ferede, 2013; Netz and Finger, 2016). Sociology of education research has primarily explored the socio-economic determinants within the European and US context; it explores how socio-economic backgrounds shape the returns of tertiary education. In its focus on transnational education, it examines how the pursuit of transnational education in the form of a semester or year abroad, often in lower-cost destinations (e.g. students from the United States going abroad to South America) signifies status. We extend this scholarship by conceptualizing the relationship between socio-economic background and transnational education in an emerging economy setting. The key differences being the significant differential in average income and the cost of completing full degrees abroad in (significantly more) expensive destinations with a strong foreign language requirement. By focussing on this reverse direction of travel, we offer insight into an accentuated setting in which the socio-economic requirements for studying abroad are relatively high. We also extend transnational sociology of education by connecting it with access to career outcomes in the form of the digital entrepreneurship.

Vietnam provides a compelling case for examining the intersection of post-industrialization and social inclusion. Since the doi moi reforms in 1986, which legally permitted private sector activity, Vietnam has experienced rapid industrialization and economic growth (Angelino et al., 2020). By 2009, Vietnam had achieved lower middle-income status, reflecting its movement up global value chains towards more digitally oriented activities. Industrialization helped fuel robust economic growth, along with nearly equally high rates of expansion of the middle class. Since 2014, however, its middle class has only grown by 3%, half the rate of growth in the preceding decades (The Economist, 2024). Given this trajectory, we analyse the human and social capital of Vietnam’s high-performing entrepreneurs across the industrialization (from 1986) to post-industrialization (from 2009) periods to understand how the shift is affecting the basis (e.g. transnational experience in English-speaking countries) by which individuals have access to wealth-generating digital entrepreneurship activities. Simply, we are interested in whether graduates of local universities, such as Vietnam National University, with work experience in Hanoi or Ho Chi Minh City, are founding the countries’ high-performing digital start-ups, or one needs to be a returnee from an English-speaking university, with work experience in the West, to perform in this post-industrialization context.

Our analysis reveals that after 2010, founders were five times more likely to study in one of the world’s most-expensive destinations for tertiary education (the United States, United Kingdom, Canada and Australia). Vietnam’s post-industrial entrepreneurs are significantly more likely to have transnational experience, especially education in these expensive destinations, than their industrial counterparts. This reflects the importance of the human and social capital gained through transnational experiences – particularly English proficiency, digital know-how, and venture capital and high-technology networks – for succeeding in the digital economy. However, these opportunities are concentrated among urban, middle-class families with the financial resources and social connections to support transnational education and skill development. This suggests that while Vietnam’s middle class has expanded since 1990, access to high-performing digital entrepreneurship remains restricted to a privileged subset of society. Whereas previous research shows that place-based political connections were essential to entrepreneurial performance in industrialization settings (Ngo and Ha, 2024; Pham and Talavera, 2018), our findings point to entrepreneurial opportunity being restricted to those emanating from affluent families in the post-industrialization context.

Our findings suggest that post-industrialization in Vietnam has not necessarily expanded social inclusion. High-performing entrepreneurship in the digital economy is largely accessible to those with the financial and social capital needed to pursue transnational education and experiences. This marks a shift from the industrialization phase, where place-based experience political connections played a dominant role in determining access to high-growth entrepreneurial opportunities. In the post-industrial era, the upper middle class – often families with wealth accumulated during the industrialization period – have the requisite human and social capital needed to access to digital entrepreneurship. In this way, post-industrialization in Vietnam does not represent a straightforward expansion of opportunities but rather a reconfiguration of barriers, where access to wealth generation depends on one’s ability to accumulate transnational experience in English-speaking countries.

The paper proceeds as follows. The next section develops the theoretical framework. We then provide the historical context for the study, across Vietnam’s industrialization, from the doi moi reforms (1987–2008), to the post-industrialization digital push (beginning in 2008). Data and methods are then detailed, centring on the location (transnational or place-based) of educational and work experiences of two temporal cohorts of high-performing founders. Then our regression findings are presented, on the location of human and social capital accumulation likely to enable high-performing Vietnamese founders across what we operationalize as the country’s industrialization (1987–2007) and post-industrialization (2008–2020) periods. Lastly, we discuss how our findings update the existing knowledge on post-industrial development, entrepreneurial performance, and social inclusion. We conclude with a discussion of the theoretical contributions of the article and outline areas for further research.

Theoretical framework

Post-industrial development, social inclusion and digital entrepreneurship

The relationship between industrialization and development has been a central theme in economic scholarship. Seminal work, such as that of Gerschenkron (1962), emphasize how late industrializers leverage state-led investments and technological adoption to accelerate growth. Industrialization shifts economies from agrarian to manufacturing-based systems, generating employment, improving infrastructure, and fostering urbanization. These processes can be critical to alleviating poverty and laying the groundwork for economic advancement.

However, industrialization has also been found to introduce new structural inequalities. Early industrial economies often prioritize capital-intensive sectors like steel, oil, and heavy machinery. These sectors require significant financial resources and technical expertise, limiting access to opportunities for those without the money and knowledge. Political connections, bureaucratic know-how, and localized social capital become critical in determining who can participate in and benefit from industrialization opportunities (Li et al., 2008; Ngo and Ha, 2024; Pham and Talavera, 2018; Siegel, 2007; Westlund and Bolton, 2003). While these factors enable rapid economic growth, they also create disparities in wealth and opportunity. Piketty et al. (2006) and Kopczuk and Saez (2004) demonstrate that economic gains are often concentrated among elites, while opportunities for wider society’s social mobility diminishes. In Goldin and Katz’s (2008) account of the relationship between education, technology and equality, found that the widespread provision of education in 20th-century America initially led to a reduction in inequality.

In this setting, entrepreneurship has been framed as both a driver of and a response to inequality. On the one hand, it provides pathways for individuals to overcome systemic barriers and achieve economic mobility (McMullen et al., 2021). On the other, access to entrepreneurial opportunities – particularly high-growth ventures – is often constrained by socio-economic background (Kish-Gephart and Campbell, 2015). Research has shown that individuals from lower socio-economic backgrounds face significant barriers, including diminished self-efficacy and limited access to human and social capital (Audretsch et al., 2013). Studies have shown, though, that social class origins are not, alone, responsible for entrepreneurial intent or ability. For instance, perceptions of upward mobility can influence entrepreneurial intent, with individuals who perceive themselves as having risen above their childhood socio-economic status exhibiting greater motivation to pursue entrepreneurship (Brandle and Kuckertz, 2023).

As economies transition towards post-industrialization – which we define as the shift from an economy centred on goods to one dominated by services and innovation, emphasizing the accelerating role of information and communication technologies in this transformation (Gill, 1996:3) – the determinants of access to entrepreneurial opportunity shifts. Chetty et al. (2017) show how social mobility in the United States declined as the economy shifted towards technology and services, with education and global connections increasingly determining access to opportunities. The post-industrial context, dominated by technology and services, places a premium on specialized human capital, such as technical skills and digital expertise, as well as transnational social capital, including personal networks with leading firms and investors as well as English-language proficiency (Klingler-Vidra et al., 2021). These shifts can exacerbate inequality by favouring those who already possess the financial and educational resources necessary to acquire these capabilities. Unlike industrial economies, where growth often included large-scale labour participation, post-industrial economies reward individuals with specialized digital skills and global networks.

In post-industrial economies, human capital specific to digital technologies – such as IT proficiency and familiarity with global market practices – has become essential. Social capital, defined as the relationships and networks that facilitate access to resources and opportunities (Coleman, 1988; Putnam, 2000), is equally important, particularly in the form of transnational connections. These forms of capital are disproportionately available to individuals from higher socio-economic backgrounds, reinforcing disparities in entrepreneurial intent and success. Social capital, particularly transnational networks, further enhances the performance of post-industrial entrepreneurs. Digital entrepreneurs with transnational experience often act as connectors, linking resources and opportunities across borders (Leitch et al., 2013; Klingler-Vidra and Liu, 2020). This comprises a form of what Burt (1997) describes as the ‘structural holes’ across networks that helps boost capabilities.

Sociology of transnational education and digital entrepreneurship

Transnational education, while a valuable pathway for acquiring the skills and connections necessary for post-industrial entrepreneurship, is available primarily to individuals with the ‘right’ socio-economic backgrounds. Sociology of education research shows that socio-economic backgrounds are a strong determinant of transnational education rates. Individuals from higher socio-economic backgrounds are likely to have the economic (e.g. financial ability), cultural (e.g. prior transnational experience), human (e.g. foreign language skills), and social capital (e.g. networks that are knowledgeable about, and encouraging about, overseas studying) that foster both the intent and ability to study abroad. Studying abroad for a semester or academic year can serve as a mechanism for students from higher socio-economic backgrounds to ‘mark their distinction’ (Ballatore and Ferede, 2013). In this way, studying abroad is predominantly available to individuals coming from higher socio-economic backgrounds who are entrenching their position (Bourdieu, 1986; Bourdieu and Passerson, 1990; Netz and Finger 2016). Less research has focused on the completion of full degrees abroad, which is the most expensive, and exclusive, option (Aerts and Van Mol, 2023).

While sociology of education research has offered substantial insights into the determinants of studying abroad rates by socio-economic (and gendered) means, much of the scholarship has examined Western students – from the United States or Europe – going overseas. The reverse flow – from an emerging economy to the West – is marked by key differences. First, the length of the transnational education experience is typically greater. Rather than studying abroad for one term, it involves completing full degrees abroad. This comes at a larger cost. The average level of income in an emerging economy is lower, and the cost of studying in the Western context is amongst the world’s most expensive. The exclusionary socio-economic tendency that has already been acknowledged for completing full degrees abroad is accentuated. Only the upper middle class and above are likely able to undertake such an expensive transnational education experience. Second, the language requirements are greater. Rather than options to enhance one’s second language skills while abroad, for emerging economy students to study in an English-speaking country, they need to already have a strong command of the language. This also augurs for upper middle-class families having the ability to procure extra-curricular tutoring to develop these English-language abilities.

In the post-industrial setting, the integration of Vietnam into the global tech ecosystem has amplified the value of transnational experience in English-speaking, expensive destinations. Research has shown that entrepreneurs with transnational education possess a competitive edge when starting a high-technology business, as the nature of digital business benefits from the accumulation of the human and social capital that affords (Batjargal, 2007; Kenney et al., 2013). English-language proficiency, digital expertise (e.g. computer programming and knowledge of platform business models), and access to venture capital and technology industry networks are critical to establishing and scaling a technology-oriented start-up (Klingler-Vidra et al., 2021). The reasons being that engaging with venture capitalists, prospective customers, and recruiting talent all benefit from human capital in the form of English-language skills and technological and business model know-how as well as social capital in terms of social networks with prospective investors, corporate partners and talent. Our expectation is that studying at leading national universities in Vietnam, even though they are top within the country, is unlikely to help would-be founders accumulate the skills and network needed to build highly valued digital start-ups. In contrast, capabilities in physically oriented industrial activities (e.g. coffee and light manufacturing) benefitted from place-based knowledge and connections, and so high-performing entrepreneurs during the industrialization phase were more likely to have place-based education and experience.

Table 1 summarizes our expectations for the human and social capital that entrepreneurial founders likely need to access high-growth entrepreneurship in industrialization and post-industrialization contexts. The third row delineates how, in order to accumulate this human and social capital for physical or digital entrepreneurship, they will differently benefit from place-based or transnational experience (extending insights from existing studies on the determinants of entrepreneurial performance in Vietnam, including (Huong and Le, 2019; Nguyen and Nordman, 2018; Nguyen and Rose, 2009; Pham, 2023; Vuong et al., 2020)).

Table 1.

Location for human and social Capital Endowment Expectations for Access to High-performing entrepreneurship Across industrialization Process.

	Industrialization: Manufacturing-based industrial activity	Post-industrialization: Digitally oriented post-industrial activity
Human capital	Knowledge of domestic bureaucracy and market to secure finance and permits	Foreign language fluency and knowledge of digital business models and equity-financing domain
Social capital	Domestic connections; to local political, finance, and industry	Connections to equity investors, high-tech talent, and collaborators
Location needed to accumulate requisite capital	Place-based; home country	Transnational; English-speaking countries

In summary, we expect that the accumulation of transnationally derived – especially in high-cost, English-speaking countries – human and social capital is most accessible to individuals in emerging economies with significant financial resources. Relative to American or European students’ ability to study abroad, our expectation is that only individuals from upper middle class or above socio-economic backgrounds have the capital accumulation needed to complete a full degree abroad. Vietnam’s middle class, which earns about US$7728 a year as of 2023, accounts for approximately one-tenth of the population (Nguyen, 2020a) – hardly enough to afford the costs of overseas tuition fees and living in Western countries. As such, despite the potential for the digital economy to reduce inequality, the rise of post-industrialization may reinforce pathways to wealth generation amongst individuals from higher socio-economic backgrounds. In the next section, we expand on the Vietnamese industrialization and post-industrialization contexts to further situate the study in the empirical context.

Vietnam’s path to post-industrialization

Vietnam’s contemporary industrialization commenced in 1986 on the heels of the doi moi reforms. Doi moi was essentially the abandonment of a planned economy in favour of a free market but with state regulation and macro planning (Fforde and Vylder, 1996; Vu, 2010). It also opened the Vietnamese economy to international trade and investment, including allowing foreign firms to operate in Vietnam (Goscha, 2017).

Given the concurrent persistence and loosening of the state and state-owned enterprises, some analysts have asserted that throughout this era Vietnam can be depicted as pursuing ‘liberalization without neoliberalism’ and ‘development without a developmental state’ (Masina, 2010: 14). Others have spoken of the ‘ad hoc’ and ‘incoherent’ Vietnamese developmental state (Malesky and London, 2014) that simply ‘transmuted’ liberal practices (Yeo and Painter, 2011). In this period, Vietnam’s socialist market economy saw the advance of its light industries, notably textiles, chemicals and rubber, food and beverages, wood and paper, and electrical and electronic equipment. By 2004, these industries amounted to 84.9% of total industrial output (General Statistics Office, 2006). Over 20 years of the doi moi era, Vietnam underwent an industrial growth process that transformed its economic activity from being overwhelmingly small-scale agriculture to being nearly 50% derived from light industry, with diverse ownership and extensive manufacturing.

Reforms led to an ‘explosion’ of private businesses, as the number of new registrations rose from 14,500 over 9 years from 1990 to 1999 (Le, 2018), to 14,457 in 2000 alone (Hakkala and Kokko, 2007). Meanwhile, existing firms grew in scale and scope, employing thousands of workers and operating in capital-intensive industries such as construction, automobiles, and metal works. Many of these doi moi era firms have become household names nationwide, such as Hoa Binh (construction and real estate), Hoa Phat (steel and furniture), ACB (banking), FPT (telecom), THACO (automobile manufacturing and trading), Hoang Anh Gia Lai (furniture, agriculture, investment, and football), and Trung Nguyen (coffee and manufacturing). Given the light industry focus and the relatively low internationalization (Le, 2002) in this this period, we conceive it as Vietnam’s first wave or phase of industrialization.

The post-industrialization era can be demarcated around the time the country obtained lower middle-income status, as its GDP per capita reached US$1109 in 2009 (Ohno, 2009). Around the same time, Vietnam’s digital technology activities, especially in the ICT sector, grew as a share of economic activity (Dan Tri, 2014). On the policy side, Vietnamese leaders clearly demonstrated a political push for the development of digital technologies and economy (Politburo, 2014). The Science and Technology Law, passed in 2000 and revised in 2013, and the High-Tech Law, passed in 2008, created a legal framework for science and technology to qualify as a separate business category. This designation affects not only digitally oriented firms but also firms that ‘produce and commercialize products [or] provide services in science and technology […] resulting from scientific research and technology development’ (Article 58, Science and Technology Law). These laws were accompanied by a national programme for innovative start-ups, dubbed Project 844. Venture capital policies – and markets – also advanced in the years following the global financial crisis through a range of enabling funding mechanisms and tax treatments to encourage investments in digital technology start-ups (Klingler-Vidra, 2014).

There has not been a retreat of goods manufacturing in Vietnam. But rather, there has been a layering in of digitally based activities and firms, striving to enter global industries such as real estate, finance, and logistics through digital platforms. In this sense, post-industrialization is a new type of activity, rather than de-industrialization in which manufacturing declines or stalls. Some firms founded in this era include KMS (software development), Tiki (e-commerce), and Ivi Group (medtech). This period also saw Vietnam’s first unicorn, VNG, by achieving a value of more than $1B in 2014 (Huong, 2014). Thus, we can demarcate the onset of Vietnam’s more digital, globally oriented phase as it ascended to lower middle-income status. We identify 2008 as this key inflection point, as digital policies and global ambitions became more mainstream. Following a spate of science and technology policies being passed from 2000, the High-technology Law was passed in 2008 and in 2011 saw the creation of the National Agency for Technology Entrepreneurship and Commercialization Development (NATEC) (Klingler-Vidra and Wade, 2020: 721). The digital economy and spread of information technology infrastructure across the country, saw marked increases from 2012 onwards (Nguyen, 2020b).

Table 2 summarizes how we distinguish between Vietnam’s two industrial eras and the attributes of their high-performing businesses in each phase.

Table 2.

Vietnam’s industrialization Phases and High-performing Business Characteristics.

Industrial era	Years	Industrial policy orientation	Main economic activities of high-performing businesses
Doi moi industrialization	1987–2009	Abandon planned economy for a socialist market economy	Light industry firms (e.g. coffee, steel, electronics, and furniture) and services (e.g. finance and real estate)
Digital-orientation post-industrialization	2010–2020	Develop services industry and digital economy	Digitally oriented businesses disrupting different industry verticals (e.g. commerce and logistics)

We expect that founders of businesses in these two industrialization phases benefit from different human and social capital accumulation, particularly with respect to the place-based or transnational nature of their experience.

Data and methods

We study the relationship between social inclusion and (post)industrialization processes through the lens of access to socio-economic determinants of access to high-performing entrepreneurship. As shown in Section 3, the Vietnamese industrialization began in 1986 with the doi moi (‘renovation’ or ‘restoration’) reforms, which allowed private enterprise for the first time in the post-colonial era. The second period, which we operationalize as the onset of post-industrialization in the Vietnamese context, emerged around 2008 when the country pushed towards higher value-added activities, achieved lower middle-income status, and integrated into the global economy via its accession to the World Trade Organization. Another indicator, endogenous to our data, was the changing sectoral focus of high-performing entrepreneurs towards information and communications technologies, beginning in 2009, with the diffusion of the smart phone and cheap internet. This inflection point better reflects the evolution towards digital, globally integrated industrial activity in Vietnam. Rather than de-industrialization and the collapse of manufacturing, this addition of an expanding digital economy layers in the Vietnamese context.

Consistent with best practice in entrepreneurship literature, we used publicly traded market capitalization (‘market cap’) as the measure for high-performing firms from the doi moi era (see Klingler-Vidra et al., 2021, 2022). We accessed the Investing.com database to obtain the details of companies listed on the Ho Chi Minh City Stock Exchange.¹ This search yielded 314 companies with a market cap of over 0.5 trillion VND (approximately US$20 million). This threshold ensured that we obtained at least one company in each of Investing.com’s industry categories.² We analysed companies to code whether they were privately established or state backed. As a result of this coding, we filtered out 219 companies established by or owned by the state. We did this to ensure that our sample included only privately founded firms because we aimed to analyse the human and social capital endowments of the entrepreneurs. We further refined the sample by removing foreign-owned companies or subsidiaries of other firms. This filter led to the removal of two foreign-owned companies (Interfood Shareholding and VNS Security) and one domestic subsidiary (Viet Dragon). In addition, we identified two companies that were in the same conglomerate and thus counted as one (Vinhomes and Vincom Retail were both part of Vingroup). Ultimately, after applying these filters, we identified a sample of 80 high-performing, doi moi era businesses that were privately founded and independent (see the online appendix for the full list of firms).

We operationalized high-performing companies in the post-industrialization context as those established from 2008 onwards and focused on digital businesses. To source company data for this digital company sample, we searched two database providers – Crunchbase³ and PitchBook – for their Vietnam-headquartered companies. We use these start-up-centric data providers to operationalize digital economy by focussing on the following industry groups: Apps, Artificial Intelligence, Business Information Systems, Data and Analytics, Design, Gaming, Information Technology, Internet Services, Media and Entertainment, Messaging and Telecommunications, Mobile, Platforms, Software, and Video.⁴ The Crunchbase database query produced a list of 3673 companies headquartered in Vietnam in November 2021, while PitchBook listed 2843 companies. We used the Crunchbase dataset given its wider coverage. To identify the highest performers among this digital firm cohort, we sorted the list of companies in terms of their ability to raise private equity funding. Of the companies in the Crunchbase database, 212 had their total equity funding details.⁵ We set the threshold for being considered a high-performing company in this sample at US$100,000 in equity funding. This filter resulted in 110 companies.

We exported data from Crunchbase for each of the 110 digitally oriented companies, including their company description, founding date, headquarters location, and industry categories. We added the company-level information to the results of our own searches (in English and Vietnamese) of the company websites and of recent news regarding each company’s activities (through Google search). This information helped us to triangulate the data and to identify that these companies are Vietnamese and that they are independent, are trading actively and were privately founded.⁶ For example, we found that GATe Technology is a multinational subsidiary; therefore, we removed it. Four companies were filtered out as they were deemed ineligible because (a) their websites and social media accounts were either not updated for more than a year or had been taken down (e.g. OnOnPay last updated their Facebook page in November 2018, and their website was not accessible through searches in either English or Vietnamese); (b) news was found about them failing, being defunct or even being scam companies (e.g. Modern Tech); or (c) no information could be found about them through extensive online searches in either language (e.g. Dificat). Finally, we filtered out companies that were founded prior to 2008, as the industrialization cohort needed to be established from 2008 onwards. After applying these filters, we were left with a list of 52 Vietnam-headquartered companies that offer digital technology-based products or services, are currently operating, are independently owned and were founded in or after 2008.

Once the two temporally determined cohorts were established, we identified the founders of each firm. This practice is in line with entrepreneurial capabilities research, which studies the attributes of the individuals who comprise the top management team (Jin et al., 2017). The founding team is the focus because they have the largest equity stake in the business, so stand to reap the greatest wealth generation potential as the company’s equity valuation increases. Employees who join the company later tend to receive smaller equity stakes, and thus stand to earn less from the company’s ‘exit’ (when it goes public on the stock market or is acquired). The names of the founders of most companies were specified in the Investing.com and Crunchbase databases, but several were not. In these cases, we took three steps to identify the founders: (1) examining the company website to see if the founder’s name is specified in the history, overview, or team sections; (2) for the doi moi companies, checking VietStock.com, a domestic database of publicly traded companies; and (3) if the first two steps were inconclusive, conducting Google searches. If, after all these steps, we could not find the names of the founder(s), we removed the company from our sample. On this basis, three companies were removed from the digitally oriented sample and 11 from the doi moi list. Ultimately, we retained 69 doi moi era companies and 49 digitally oriented companies. A full list of these companies and their founders can be found in the online appendix.

As several firms have more than one founder, the total number of founders of these high-performing companies was 143 (76 from the doi moi era and 67 from the digitally enabled era). We collected and coded biographical details for each of these 143 founders. We used this list of founders to create our dependent variable, Technology Founder. This variable takes two values: 1 = technology founder and 0 = doi moi era founder. These data were gathered through a variety of sources, in English and Vietnamese, including alumni/alumna news/reports from the founders’ universities, LinkedIn, media coverage, public speeches, and Wikipedia.

To evaluate the human and social capital of each of the founders, we coded the location of work experience and university education (consistent with the methods employed by Kenney et al., 2013; Batjargal, 2007). We detailed up to four previous work experiences, beginning with the job the founders held immediately before establishing the company and their prior work experiences. This gave us insight into the country location of their professional experience; place-based in Vietnam or transnational, especially in English-speaking countries. We also coded university experience for each founder’s university degree at the bachelor’s, master’s, MBA and PhD levels, according to the university name and location (city and country). The doi moi cohort is primarily expected to study in the Vietnamese context setting, whereas transnational education in English-speaking countries is expected among the post-industrialization cohort.

One of the central points of focus in this analysis of socio-economic backgrounds and access to transnational education is the costs incurred by founders for studying abroad. Tuition fees and living costs in English-speaking countries are amongst the highest in the world. QS reported that as of 2022, the most-expensive countries to study in are the United States, New Zealand, Australia, Canada and the United Kingdom. The top of the list, the US, had minimum yearly fees of more than US$ 25,000 while the UK, the fifth most expensive, would cost nearly US$ 12,000. In the context of Vietnam’s lower middle-income economy, in which GDP per capita was below US$ 1000 until 2008, only students from high socio-economic backgrounds, or students on generous government scholarships, could afford to study overseas (see Goh et al., 2021; Kiet, 2023). To operationalize the set of most-expensive countries for completing transnational education, we used a composite ranking that integrates four different rankings, each offering insights into the financial aspects of studying in various countries. The rankings include data from HSBC (2014), Times Higher Education (THE, 2023), QS (2022), and US News and World Report (2023). Points were assigned based on each country’s position in these rankings (e.g. Rank 1 = 10 points, Rank 2 = 9 points, and so on), and scores were summed across all lists to produce an aggregated ranking. This approach ensures that countries consistently recognized for high costs across various dimensions receive higher scores. The full overview of the most-expensive destination determination is provided in the Appendix. Table 3 below summarizes the final top 10 countries based on this composite ranking. Note that many of the overseas study destinations for our founders, including Vietnam but also places like Austria and Russia, do not make into our Higher Education Expense Index.

Table 3.

Ranking of the Most Expensive University Destinations With Higher Education Expense Index (Top 4 in bold).

Country	Higer education expense index
United States	38
United Kingdom	29
Australia	25
Canada	24
Singapore	21
New Zealand	12
Hong Kong	10
Spain	8
France	7
Switzerland	7

Statistical analysis further underscores an important distinction between the top four countries and the rest in the composite ranking. The mean score of the top countries (United States, United Kingdom, Australia, and Canada) is 29.0, significantly higher (i.e. more than one standard deviation) than the mean score of 10.83 for the remaining countries.⁷ These results highlight that the top four countries are outliers in terms of the costs associated with studying abroad, reinforcing their categorization as exceptionally expensive destinations for tertiary studies.

Empirical analysis

Over time, founders of Vietnam’s high-performing businesses have increasingly studied in the most expensive, and English-language speaking, countries. The stacked bar chart in Figure 1 illustrates the cumulative number of founders studying in the ‘Top 4’ most-expensive university destinations (United States, United Kingdom, Australia, and Canada) over time, disaggregated by degree level. Each colour represents a specific degree level, including Bachelor’s (BA), Master’s (MA), MBA, and PhD, showing their respective contributions to the overall total. The chart highlights a clear upward trend in the number of students attending these prestigious destinations, particularly after 2010, marked by a sharp and sustained increase in the cumulative totals. Advanced degrees such as PhD (purple) have a smaller but consistent representation throughout the period, while there has been a marked increase in the number of Bachelors and MBAs obtained in the expensive, English-speaking countries.

Figure 1.

Cumulative top 4 most-expensive university destinations over time.

To examine the likelihood of studying in one of the ‘Top 4’ most-expensive university destinations (United States, United Kingdom, Australia, and Canada), which is an opportunity primarily available to the country’s concentrated upper middle class, we conducted a logistic regression analysis. The binary dependent variable (Top 4) indicates whether a founder studied in a ‘Top 4’ destination (1 = yes, 0 = no). The analysis included two key components: a comparison of odds before and after 2010, and a year-on-year analysis of the trend over time.

First, we created a binary independent variable (Post-2010) to identify whether the observation occurred after 2010 (1 = after 2010, 0 = 2010 or earlier). The results showed that the odds of studying in a ‘Top 4’ destination were significantly higher after 2010, with an odds ratio of 5.57 (95% CI: 2.46–13.65). This indicates that founders were over five times more likely to study in these destinations after 2010. Second, we examined year-on-year changes by treating the year as a continuous predictor in a separate logistic regression model. The analysis revealed that the odds of studying in a ‘Top 4’ destination increased by an average of 15.5% per year (odds ratio = 1.155, 95% CI: 1.088–1.243). This year-on-year growth demonstrates a gradual yet compounding increase in the likelihood of studying in these destinations, with the odds nearly quadrupling over a decade in Figure 2.

Figure 2.

Predicted probabilities of founders studying at one of the top four most-expensive countries for tertiary education.

While not illustrated in the above figure, it is notable that among the industrialization era founders, a sub-group studied in the Soviet Union, typically in the 1980s (Hoang, 2020). This group includes Pham Nhat Vuong, founder of the real estate-led conglomerate Vingroup and Vietnam’s first billionaire (in US dollar terms), and Nguyen Dang Quang, founder of the consumer goods and resources giant Masan Group. Chesnokov (2011) noted that these founders, owing to the geopolitics of the time, migrated to the Soviet Union – likely enabled by their political connections – for education (or work) and engaged in commercial activity there. As a result of which they developed experience and relationships that further fostered their political capital back in Vietnam. Since the decline of the Soviet Union and changing geopolitical dynamics, especially following then-President Clinton’s visit to Vietnam in 2000, there was a marked decline in the number of founders who studied in the former Soviet bloc.

Next, we examine the previous job destinations of all the founders in our dataset. Here we are particularly interested in whether founders had job experience in English-speaking countries. These countries are conducive to developing social networks with venture capitalists. We count English-speaking countries as those with English as one of its official languages. From the countries in our dataset, this includes the United States, United Kingdom, Australia, Hong Kong, and Singapore. This reveals that prior to 2010, most founders (86.98%) gained work experience in Vietnam, indicating a strong preference for domestic employment. In contrast, after 2010, the share of founders working only in Vietnam declined to 71.96%, highlighting a shift towards the accumulation of more transnational work experience. English-speaking countries saw some notable patterns. Before 2010, only 10.29% of founders had work experience in English-speaking countries, including the United States (5.33%). After 2010, this share slightly increased, with growing representation from Singapore (5.61%), Australia (3.74%), and the United Kingdom (3.74%). While Vietnamese entrepreneurs could have obtained sponsored permits and visas to enable their work experience in these countries, our expectation is that much of this work experience was enabled by post-study work visas.

We explore work experience patterns among founders over time by conducting a logistic regression analysis. As above, we use year as a continuous predictor to model the likelihood of founders having worked in English-speaking countries. The predicted probabilities derived from the model, visualized in Figure 3, illustrate a steady year-on-year increase in the likelihood of such work experience. The blue line represents the predicted probabilities, while the vertical dashed line in 2010 highlights a shift in this trend, underscoring the growing importance of English-speaking environments in founders’ career trajectories over time.

Figure 3.

Predicted probabilities of founders having work experience in English-speaking countries.

The logistic regression analysis reveals a significant year-on-year increase in the likelihood of founders working in English-speaking countries as post-industrialization activities grow. The odds of working in such countries increase by approximately 8.3% per year (odds ratio = 1.083, 95% CI: [1.038, 1.140]), indicating a steady upward trend over time. Additionally, the post-2010 period shows a substantial shift, with founders being 3.59 times more likely to work in English-speaking countries compared to the period before 2010 (odds ratio = 3.59, 95% CI: [1.68, 7.96]). Both results are statistically significant, underscoring a marked and accelerating probability for high-performing entrepreneurs working in English-speaking environments in the years following 2010.

Our approach to investigating social inclusion concerning wealth generation across different developmental periods has limitations. Firstly, there are other factors that shape the direction of transnational experience. We have acknowledged changing geopolitical contexts and its likely impact on whether high-flyers study in English-speaking countries or the post-Soviet Union. But we have not fully accounted for how this shapes the desire – not only the means – to study in different parts of the world. We mitigate this concern somewhat by engaging with previous research that tests for both directions, finding that the magnitude of the United States path is greater than the previous Soviet Union pathways (Klingler-Vidra et al., 2021). The third limitation is that our sample size is modest, as we analysed the highest-performing entrepreneurs rather than the wider entrepreneurial ecosystem in Vietnam. Finally, we used transnational education as a proxy for socio-economic background. Given the relatively modest scholarships for Vietnamese students to complete overseas degrees, we contend that transnational education is a good proxy for high socio-economic background. However, we acknowledge that this is not always the case, as 10% of students are funded by scholarship.

Discussion and conclusion

Our first research question is: how does post-industrialization, driven by the expansion of the digital economy, shape opportunities for wealth-generating high-growth entrepreneurship? We answered the question by exploring the human and social capital of Vietnam’s high-performing entrepreneurs across its industrialization and post-industrialization contexts, with a focus on the role of transnational experience in English-speaking countries versus place-based experience. We find that Vietnam’s digital founders are approximately five times more likely to have studied in expensive, English-speaking countries and 3.59 times more likely to have worked in such countries compared to traditional founders. Pursuing pathways like a Bachelor’s degree abroad requires substantial financial resources and English-language skills. This suggests that upper middle-class backgrounds, characterized by access to English-language education and the ability to afford high tuition fees and living costs, are increasingly crucial for building high-performing businesses in Vietnam’s post-industrial digital economy. Consequently, even excellent students from lower socio-economic backgrounds who earn a place at a leading national university may be excluded from this post-industrial wealth generation opportunity. To use an expression that is popular in Vietnam, this reliance on family resources in Vietnam’s post-industrialization is ‘same same but different’ to the barriers of its industrialization era, where local political connections were essential. Our second research question asked whether the expanse of digital economy activities in an emerging economy create broader opportunities for wealth generation through high-growth entrepreneurship. We find that while the basis of elite access to high-performing entrepreneurship is shifting in Vietnam, the advance of the digital economy is not necessarily offering an expanse of social inclusion.

This article makes a theoretical contribution by integrating and extending the sociology of education and entrepreneurship scholarship to examine social inclusion in terms of digital entrepreneurs’ transnationally accumulated human and social capital in post-industrialization settings. We contribute to entrepreneurial capabilities research by bringing in the socio-economic determinants of transnational experience, an activity that has been identified as a determinant of human and social capital accumulation for digital entrepreneurs in emerging ecosystems (Batjargal, 2007; Foster, 2023; Kenney et al., 2013; Klingler-Vidra et al., 2022). We do this by extending sociology of education research to address a reverse flow of transnational education, focussing on individuals from a non-Western, emerging economy who pursue full-degree programmes in English-speaking countries. The sociology of (transnational) education literature has primarily centred on European and US contexts, exploring access to elite national institutions or participation in transnational education through short-term study abroad experiences, often in lower-cost destinations. In contrast, this article conceptualizes transnational education in an emerging economy where inequality is greater, the middle class is smaller, and the ability to finance full-degree programmes abroad – typically in expensive destinations with high foreign language requirements – is restricted to a privileged few. In addition, the article extends existing theories to explore how transnational education shapes access to digital entrepreneurship opportunities. It argues that the digital economy demands advanced skills, global networks, and English proficiency, often acquired through transnational experiences. This raises critical questions about how the rise of the digital economy reinforces socio-economic status rather than acts as a lever for social mobility via wealth-generating entrepreneurship as economies transition to post-industrialization.

As Vietnam has developed, expanded its digital activities and integrated into global value chains, transnational education has gained importance for shaping access to high-performing entrepreneurship. This tells a different story in terms of the inclusive nature of Vietnam’s economic growth since the doi moi reforms. Opportunities to generate (significant) wealth appear to be increasingly accessible to the country’s middle class, rather than increasingly available to individuals coming from a wide range of socio-economic backgrounds. Vietnam’s post-industrialization may accentuate the country’s inequality, as less than 10% of the population may have the ability to build high-performing digital businesses.

This trend towards transnational experience as the path for digital entrepreneurs in an emerging ecosystem has similarities with observations elsewhere, where initial entrepreneur cohorts leveraged local education and work experience to establish high-performing industrial firms, followed by a subsequent cohort, often comprised of returnees, focussing on technologically oriented businesses (Kenney et al., 2013). This is not to say that transnational experience will remain essential, though. Klingler-Vidra et al., (2022) find that China’s unicorn founders increasingly possess place-based human and social capital, coming from top universities in Coastal cities. This suggests that, as Vietnam’s economy develops and its universities move up global league tables, there may also be a similar reversal in favour of place-based experience, likely around attendance at leading universities in Hanoi and Ho Chi Minh City. The virtuous relationship between local universities and growing entrepreneurial ecosystem will take time to foment in Vietnam, similar to how this evolved over the course of two decades towards place-based experience in China.

Future research could expand the sample to encompass broader sets of companies from both industrialization and post-industrialization eras, such as all publicly traded companies or Vietnamese firms that have secured VC funding, to provide deeper insights into social inclusion across society, beyond merely examining access to the highest-performing cohort. Future research could employ surveys of entrepreneurs to ascertain their socio-economic background (as in Brandle and Kuckertz, 2023), confirm scholarship status, or extend data to childhood location, primary or secondary school, or parental education or occupation. In addition, research can further explore other attributes, such as gender, ethnicity, and urban/rural, for their interaction in shaping both transnational experience as well as entrepreneurial performance.

Supplemental Material

Supplemental Material - Post-industrialization and social inclusion: Elite access to high-performing entrepreneurship in Vietnam

Supplemental Material for Post-industrialization and social inclusion: Elite access to high-performing entrepreneurship in Vietnam by Robyn Klingler-Vidra, Adam William Chalmers, and Ba Linh Tran in Journal of Competition & Change.

Footnotes

Acknowledgements

Comments provided by the inclusive industrial growth workshops organised by the special issue editors, Nahee Kang and Shaohua Zhan, were essential to shaping the paper. The paper also benefited from constructive comments and suggestions from the editor, guest editors and anonymous reviewers.

Declaration of conflicting interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This research benefitted from an Economic and Social Research Council Impact Acceleration Account research grant, which was administered by King’s College London in 2020, which shaped our thinking about the intersection of innovative entrepreneurship and social inclusion.

ORCID iD

Robyn Klingler-Vidra

Supplemental Material

Supplemental material for this article is available online.

Notes

Appendix

The lists were selected because they provide diverse perspectives on the costs associated with studying abroad. The rankings can be accessed here: HSBC (2014): https://www.statista.com/chart/3673/where-foreign-students-face-the-highest-university-fees/; THE (2023): https://www.timeshighereducation.com/student/news/best-value-countries-study-abroad; QS (2022): https://www.topuniversities.com/where-to-study/europe/united-kingdom/uk-fifth-most-expensive-study-destination-world; US News and World Report (2023): https://www.usnews.com/news/best-countries/best-countries-to-study-abroad. Each list focuses on a unique aspect of expense or value, offering a comprehensive and balanced approach:

1. HSBC (2014): This ranking considers the overall cost of studying abroad, including tuition fees, living expenses, and additional costs.

2. THE (2023): The Times Higher Education (THE) list focuses on the best-value countries for studying abroad. By inversing their ranking (beginning with the lowest-ranked country), we highlight countries perceived as offering the worst-value for money.

3. QS (2022): QS’s ranking of the most-expensive countries is based on finder.com data, emphasizing tuition costs and associated student expenses.

4. US News and World Report (2023): This list adds a global reputation dimension by evaluating the perceived quality of education in various countries, including affordability.

Together, these lists provide a comprehensive dataset by integrating both cost and value dimensions, ensuring a nuanced view of the most-expensive study destinations. Table A1.

The Higher Education Expense Index.

#	HSBC ranking of most-expensive destinations for foreign students (2014) (link)	The best-value countries to study abroad (2023) (link) **We use an inverse of the ranking; beginning with the lowest-ranked country (e.g. the worst-value) (link)	QS ranking of most-expensive countries to study (based upon finder.com data) (2022) (link)	US News and World Report (2023) (link)
1	United States	Singapore	United States	United States
2	Australia	Canada	New Zealand	United Kingdom
3	United Kingdom	United States	Australia	Spain
4	Singapore	Switzerland	Canada	France
5	Canada	United Kingdom	United Kingdom	Italy
6	Hong Kong	Egypt	Hong Kong	Japan
7	Indonesia	Australia	Singapore	Australia
8	China	New Zealand	Israel	Brazil
9	Taiwan	Greece	Lebanon	Canada
10	Malaysia	Turkey	Cuba	Turkey
11		Spain		Germany
12		Brazil		Portugal
13		Ireland		Greece
14		Italy		Netherlands
15		Japan		Egypt
16		Netherlands		Mexico
17		France		Switzerland
18		Thailand		Thailand
19		Mexico		United Arab Emirates
20		Germany		Singapore
21				New Zealand
22				India
23				China
24				Sweden
25				Belgium

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