VIETNAM – THE NETHERLANDS PROGRAMME FOR M.A IN DEVELOPMENT ECONOMICS THE EFFECT OF SOCIAL CAPITAL ON INNOVATION OF SMALL AND MEDIUM-SIZED ENTERPRISES IN VIETNAM BY HOANG DUY KHOA MAST
INTRODUCTION
Problem statement
Vietnam launched its Đổi Mới economic reforms in 1986, but the transition progressed slowly until 2000, particularly after the Asian financial crisis With increasing international economic integration, reform has shifted toward a stronger private sector and private enterprise growth Vietnam has achieved remarkable outcomes, including steady economic growth, rapid expansion of foreign trade and investment, and a substantial reduction in poverty The pivotal role of small and medium-sized enterprises (SMEs) remains clear Data from the General Statistics Office show that formal SMEs numbered 286,468 in 2012, accounting for 98.34% of all firms, contributing about 40% of GDP and providing 51% of the national employment each year, thereby underpinning sustainable economic development.
However, the Vietnamese SMEs also have to struggle many obstacles The total number of newly established firms had decreased sharply from 83.600 to 77.500 between
From 2010 to 2012, there was an upward trend in firm exits, with the number of disbanded and non-operating firms rising by 11.9% in 2012 to 60,700 companies In response to this trend, many developing countries are enacting policies to strengthen small and medium-sized enterprises (SMEs) and boost their performance The central question is how to stimulate SME development by improving performance Research shows that productivity growth can be driven by innovation, which creates competitive advantages and serves as a key source of productivity gains.
There are a lot of theoretical and empirical studies such as Brüderl (1998), Maskell, P
Scholars such as the 2000 studies, Molina-Morales (2010), and Stam et al (2014) have emphasized the decisive role of technological factors in driving economic outcomes and the determinants of innovation, while social capital has only recently begun to attract sustained attention The most famous case study cited in this literature is the Putnam–Nanni analysis, which illustrates how these dynamics play out in real-world settings.
According to Lanzetti (1993), social capital is an essential resource for firms, rooted in cooperation among individuals Individual social capital can influence a firm’s innovation, as captured by indicators that reflect networks, trust, and social ties Through social capital, firms gain the capabilities to integrate resources and to generate and share knowledge, driving improvement and performance Networks connect people to collaborate and solve problems collectively, enabling coordinated action and more effective outcomes.
This study analyzes the social capital of enterprise owners and managers and its relationship to innovation, focusing on Vietnam’s SMEs Although only a limited number of studies have confirmed that social capital influences innovation, particularly among Vietnamese SMEs, this research identifies several key components that affect SME innovation Using survey data from Vietnamese SMEs collected in 2013, the study highlights how social capital shapes innovation outcomes and suggests practical implications for boosting SME performance The qualitative results illuminate different potential factors driving innovation and offer recommendations for the development of SMEs in Vietnam Enterprises can reference these findings to support their product innovation strategies.
Research objectives
This study investigates the role of social capital in driving product innovation activities within Vietnamese SMEs and identifies the key factors that significantly influence their innovation outcomes By understanding these drivers, SME owners and managers can tailor strategic decisions to secure competitive advantages in both domestic and global markets Moreover, policymakers can target influential industry elements to design policy interventions that effectively support sector-specific innovation.
Research questions
For how to increase the productivity of SMEs in Vietnam, we will deal with these following questions:
- Does social capital affect innovation of SMEs in the case of Vietnam?
- How does social capital affect innovation?
- What should policy makers do to promote the probabilities of innovation?
Scope of the study
Vietnam's SMEs Survey, financed by the Royal Embassy of Denmark in Vietnam (Danida) under the Business Sector Programme Support (BSPS), has been conducted six times, with the latest round spanning 2007–2013 The survey is organized jointly by three institutions: the Central Institute for Economic Management (CIEM) of the Ministry of Planning and Investment (MPI); the Institute of Labor Science and Social Affairs (ILSSA) of the Ministry of Labour, Invalids and Social Affairs (MoLISA); and the Development Economics Research Group (DERG) of the University of Copenhagen.
structure of the study
Chapter 2 presents the literature review, surveying key theories and summarizing findings from empirical studies It introduces the concepts of innovation, social capital, and related designators, and analyzes their effects on innovation The chapter also assesses the need for innovation in small and medium-sized enterprises (SMEs).
Chapter 3 will be focused on explaining our methodology and data This part will content the Econometric model that we conducted and more details about the data that we used in this paper
Chapter 4 will illustrate the results that we found through in our research The variables description and descriptive statistic will be stated at the opening of this chapter which help us to understand clearly about all variables and statistics The rest of the chapter is used to describe the regression result and marginal effects
Chapter 5 is for the conclusion and policy implication All of this research will be reviewed, analyzed the advantages and disadvantages of our methodology and
9 recommendation for the future researches This chapter will also suggest the policies for policy makers and for enterprises when they want to increase the rate of innovating product.
LITERATURE REVIEW
Innovation
Over the last four decades, the concept of innovation has evolved into what is known as knowledge-based innovation, a view articulated by Hyvarinen This approach identifies several sources of knowledge-based innovation: knowledge derived from science; knowledge derived from market needs; knowledge generated by linkages among actors in markets; knowledge produced by technological networks; and knowledge rooted in social networks.
Innovation includes both internal and external activities across a firm, aimed at creating new products, improving existing products, and enhancing processes, governance, and marketing The most familiar form is research and development (R&D), a core operation in any business These innovation activities are crucial for the life of SMEs, with technology applied in a broader sense than product development alone Innovation can be classified into five types—product, process, marketing, organizational, and social innovations—yet this discussion concentrates on product innovation as the primary research focus.
Product innovation is defined as the development of new products, changes in design of established products or use new technology in the manufacture of established products
Firms gain numerous advantages from innovation, including inventing new products, improving product quality, enhancing technical features, and adding new components or functions to existing offerings, which drives growth, expansion, and a competitive advantage In small businesses, the impact of individual ideas is especially significant, as a person or a group often initiates new product concepts and makes buying decisions As Drucker (1985) noted, timing and the entrepreneur’s relationship to the surrounding environment shape opportunities for innovation.
While substantial studies have been investigating and providing proofs of relationship between countries’ export and their innovation activities at macro level (Greenhalgh,
Although micro-level research on the correlation between innovation and export performance has been relatively sparse, a substantial body of evidence indicates a significant positive impact of innovation on export performance Innovation is typically measured by R&D expenditure or the number of innovations, and numerous studies have shown that higher levels of innovation activity enhance export performance.
Innovation is defined as “implemented technologically new products and processes and significant technological improvements in products and processes” (Becheikh et al.,
2006) According to their perceptions, (technical) innovation refers to either a technologically new product/process or an existing product/process which are experienced a substantially technological advancement
Product innovation, including both new products and modifications to existing ones, contrasts with process innovation, which seeks to boost productivity and reduce production costs While product innovation can yield a competitive advantage, process innovations primarily enhance efficiency and cost-effectiveness Following Utterback and Abernathy (1975) and Cassiman and Martínez-Ros (2004), we can hypothesize that product and process innovations affect export performance in different ways In practice, these two types are often linked because newly developed or modified products frequently require new production technologies, linking design and manufacturing capabilities.
Innovation is a fundamental driver of quality, influencing firm performance and productivity To respond to changing market conditions, firms must acquire new knowledge and continually modify their products and processes At the same time, innovation serves as a strategic tool for entrepreneurs, turning change into opportunities to create new or redesigned businesses and services (OECD, 2005).
Innovation is measured through both input-oriented and output-oriented approaches The input-oriented approach uses R&D expenditure as a proxy for innovative activity, but it tends to overestimate innovation because many R&D efforts are aborted and do not lead to new or improved products or processes By contrast, output-oriented measurements rely on patent data, counts of innovations, and firm-based surveys to capture actual results However, patents often reflect invention rather than successful, market-ready innovation The innovation-count method is considered an object-based approach that aggregates innovation data from diverse sources—such as announcements of new products or processes, patent databases, journals, and other records (Becheikh et al., 2006).
Reguia (2014) has showed some advantages of product innovation:
Growth and expansion hinge on securing a sustainable competitive advantage by differentiating your product with a clear, compelling unique value proposition Through targeted research into customer needs and competitive gaps, firms can sharpen how their offering stands out from rivals, boosting attractiveness and market relevance By consistently leveraging product innovation, small firms can accelerate business development, gain a competitive edge, and attract customers who view their product as uniquely superior.
Brand switching occurs when strong product innovation convinces customers to move from rival brands The launch of the iPhone illustrates this in action, as mobile phone users shifted away from Nokia, Motorola, and Sony to embrace Apple’s new features, user experience, and ecosystem For brands operating in a competitive market, effective product innovation and clear differentiators are key to attracting customers from rivals and expanding market share.
Besides, product innovation not only take advantages but also many drawbacks:
First, innovation involves high costs and a high risk of failure When a firm pursues product innovation, it invests substantial capital and resources into the development process, and returns can be uncertain and may take a long time to materialize.
- Second, lost connect with others partners: the firms change the way operate, and the relationships between the business including customers, suppliers and counterpart will break down too
2.1.3 Importance of innovation in entrepreneurship
According to Yeniyurt (2014), the evolving needs of communities require industry leaders to continually adapt in order to maintain a healthy economy Both small and large businesses play crucial roles in supporting economic stability and growth by responding to changing demand and opportunities.
13 economy survive the changing times In other words, it is necessary for a business to be productive, innovative and ingenious
Innovation in entrepreneurship hinges on developing new products, enhancing existing offerings, and improving manufacturing processes To meet evolving customer needs and stay competitive, businesses should continuously expand their product lines and services, seeking opportunities to make their offerings better through innovation By pursuing ongoing product development and process improvements, firms can boost quality, deliver greater value, and strengthen their competitive advantage and growth trajectory.
For small businesses, innovation is the most critical driver of success, outweighing other factors By embracing innovative practices, small firms can compete with larger companies through cost-effective pricing while maintaining high quality Innovation also motivates employees to generate practical ideas that benefit the organization, creating a cycle of value creation and sustainable growth.
Today, the global economy has evolved into a knowledge-based system, moving from agricultural roots through the post-industrial and mass-production eras into a knowledge economy driven by technology and knowledge technology This transformation enables the creation of educational and innovative products and services that deliver higher returns for businesses, especially in export markets It is characterized by continuous technological innovation and intensified global competition to develop new products and processes.
The production–possibility frontier (PPF) illustrates the importance of innovation by showing the trade‑offs a economy faces when allocating resources between two goods A PPF is a graphical representation of the feasible combinations of two products that can be produced with a fixed set of resources and current technology In the diagram, points A, B, C, and D represent production options on the frontier, where increasing output of product X requires sacrificing some output of product Y With technological progress, the PPF shifts outward to the right, making a new point like E attainable and signaling that more of both goods can be produced.
Social capital
Social capital is the network of relationships that functions as intangible assets for both firms and individuals At the individual level, it represents one’s relationships with others and the resources these relationships can unlock Portes (1998) defines social capital as consisting of two elements: the network of relationships that allows individuals to access resources possessed by their associates, and the quantity and quality of the resources available within that network Adler & Kwon (2000) examine social capital at the micro level, emphasizing how networks shape the resource base accessible to actors.
There are 21 distinct types of relationships, and definitions vary depending on whether we focus on the relationships themselves, the structure that links them, or the type of ties between people Definitions can shift when we consider information relationships, personal relationships, or economic relationships, illustrating how context shapes classification By examining both the qualitative aspects of who is involved and the structural aspects of how connections are organized, we can build a clear framework for understanding relational systems across different domains, from information networks to interpersonal bonds and economic exchanges.
In conclusion, Social capital can be measure by:
Network size shapes entrepreneurial performance by expanding social relations and strengthening connectivity, which leads to greater access to information and other resources In this view, each individual contact becomes a gateway to a wider network of indirect connections, amplifying information flow and resource opportunities (Ahuja, 2000).
Network based: Membership of organizations, engagement in volunteer activities, conversations with other parents
Networks and Norms Separately: political efficacy, generalized trust, trust in government, and optimism
Social capital accumulates from an individual's network of formal and informal ties with others (Burt, 1992) Nahapiet and Ghoshal (1998) define social capital as the value that an organization derives from the connections its members bring when they join, highlighting how these networks generate organizational value.
Social capital manifested through business networking can drive long-term performance Dyer and Singh (1998) show that firm networking can generate a sustainable competitive advantage by creating relationship-specific assets, transferring tacit knowledge, and providing complementary resources and governance mechanisms As a result, business networking has the potential to boost super-normal profits Watson (2007) highlights a link between networks and the survival and growth prospects of SMEs: survival and growth rates rise as firms accumulate an optimal number of relationships, but decline when networks become congested.
Stam et al (2014) examined the role of entrepreneurs’ personal networks in small firm performance by conducting a meta-analysis of 59 empirical studies They assess multiple dimensions of social capital, including network size, strong ties (relationships with family, friends, and other close contacts that provide access to resources), weak ties (connections to distant businesses and acquaintances), structural holes (the extent to which an entrepreneur's contacts are interconnected), and network diversity The meta-analysis reveals a positive relationship between social capital and firm performance, indicating that richer networks and more diverse connections tend to enhance outcomes for small firms.
Based on a study of 1,700 new business ventures Germany, Bruderl and Preisendorfer
A 1998 empirical test of the network success hypothesis shows that social capital enhances the success of start-up firms The study distinguishes network effects into strong ties and weak ties Although human capital does not affect the amount of social capital, it significantly influences the success of new businesses In addition, the stock of human capital plays an important role in improving productivity and increasing salaries It also serves as a source to motivate and boost employees’ responsibility while enabling expenditures in R&D Consequently, firms will be better positioned to achieve their objectives Thus, Richardson suggests that firms can achieve their objectives more easily.
(1972) has also indicated that the innovation requires the use of both different skills and knowledge that would be attained in the process by the application of social capital.
Relationship between social capital and innovation
Firms increasingly invest in social capital because it boosts innovation Through collaborative learning, social capital enhances information flow and knowledge sharing, reduces uncertainty, and lowers transaction costs, thereby easing collaboration among firms A key impact is that higher levels of social capital can further reduce transaction costs (Maskell, 2001; Landry et al., 2002), accelerating innovative activities Different forms of social capital collectively influence the pace and outcome of innovation.
Extensive prior evidence confirms the effectiveness of this process Moreover, growing social capital—particularly through increased participation and stronger relational assets—raises the likelihood of innovation.
Recent research emphasizes a positive relationship between social capital and the innovation process, while some studies also report negative effects (Dasgupta, 2000) The social networks surrounding firms and their geographic context influence innovation, indicating that proximity and connectivity matter for inventive activity (Molina-Morales, 2010) The role of social capital is examined across dimensions such as trust, social interactions, shared vision, and the involvement of local institutions in product and process innovation Overall, findings suggest that social capital indicators can reveal a firm's level of innovation activity to a meaningful degree.
Within social network theories of innovation, relational tools outweigh technical tools as sources of competitive advantage (Lengrand and Chatrie, 1999) Relational capabilities can operate across both internal and external firm boundaries, whereas technical tools mainly add value externally by adopting new communications technologies and information For small firms, limited resources often prevent significant in-house innovation, making external sources essential They typically seek and connect with partners and suppliers to gather information and cultivate close, collaborative relationships Consequently, firms must continually strengthen their internal and external ties to stay competitive.
Firms with a large stock of social capital tend to secure more reliable information, reduce misbehavior, and enable members to share tacit knowledge, making negotiations smoother The value and knowledge of a business are produced by integrating relationships with mutual trust and credibility across firms, linking relational ties to inter-firm credit This social capital framework enhances information flow, collaboration, and coordination, ultimately improving negotiation outcomes and driving sustainable performance.
Social capital enhances a firm's ability to innovate, and this advantage widens as specialization increases and globalization accelerates With deeper specialization and expanding global networks, inter-firm connections strengthen, boosting collaboration, knowledge exchange, and ultimately innovative performance (Maskell, 1999).
Actually, a firm may not need to apply any particular type of innovation at every stage of its life cycle Depending on strategic goals, it might favor one form of innovation over another, or opt to pursue both types to harness their complementary benefits.
As stated above, the innovation is very important and they will always need make research carefully before deciding which type of innovation will be suitable for the firm
Social relationships and trust among employees positively influence product innovation (Tsai and Huang, 2008) A higher belief in others appears to boost innovation Subramaniam and Youndt (2005) show that idea exchange and mutual understanding among staff stimulate product innovation, with greater interaction speeding the flow of new technological information and insights Le Bas et al (1998) further indicate that these activities foster trustworthy, efficient communication channels across organizational boundaries Nahapiet and Ghoshal (1998) argue that a common language enhances access to individuals and their knowledge Moreover, shared beliefs, reciprocal respect, and aligned perceptions among staff foster learning and innovation (Wu et al., 2008) Consequently, employee interactions accelerate product innovations.
Despite substantial effort, this study has not resolved the endogeneity among variables The literature suggests that competition in international markets drives exporting firms to innovate to maintain competitiveness, and that exporting firms may learn by exporting as they are exposed to a richer source of knowledge, expertise, and technology often unavailable in the home market.
Based on literature review, this paper shows this conceptual framework:
METHODOLOGY AND DATA
Multinominal logit model
The Multinomial Logit Model (MNL) analyzes the relationship between a categorical dependent variable with multiple outcomes and a set of explanatory variables It estimates the probabilities of each possible outcome given the explanatory variables, enabling the prediction of how likely different results are By modeling these probabilities, the MNL helps researchers assess how changes in the predictors affect each category, facilitating interpretation and inference about the associations in the data.
According to Fabra and Schmidheiny (2007), the occurrence of an alternative j for individual i in the multinomial logit is:
Let J denote the number of discrete alternatives, indexed by j = 1, 2, , J This framework typically applies in contexts involving a decision maker, such as an individual, a household, or a firm The multinomial logit model assumes that the decision maker chooses from a set of alternatives, and that the available choices can differ across individuals For example, a customer may choose among the states of a loan account.
“default”, “prepayment”, “active” Or the choice of financing: “internal finance”, “bank loan”, “share issue”, “bond issue” Or firms choose from different technologies
Probability of occurrence of each alternative:
And the probability that an individual n chooses alternative j is:
� =1 𝑒 𝑥 � 𝛽 � The odds ratio (𝑃 �� /𝑃 �� ) of the multinomial logit model depends log-linearly on � � : log (
𝑃 � � ) = � ′ (𝛽 − 𝛽 ) Multinomial logit model is estimated by maximizing the log-likelihood function:
Avermaete (2004) applied a multinomial logit model to analyze product and process innovation in small food-manufacturing firms The study included 177 firms, classified into four groups: non-innovative firms with no new or improved production; traditional firms that do not invest in R&D but implement improvements to their products or processes; follower firms that engage in R&D and have at least one product or process innovation; and leader firms that conduct R&D and have at least one innovation in their product or process.
In this study, the multinomial logit model can be viewed as simultaneously estimating binary logits for all pairwise comparisons among the dependent categories The aim is to distinguish between two categories: improvement of existing products and applying a new process The independent variables are included in the model specification.
- Social capital: Network participation, network size, assistance
- Firm factors: firm age, export labor force, competitive
- Characteristics of owner/manager of enterprises: gender, age, education, high school
The choice probability equations can be specified as follows:
Pr (innovations) = f(GENDER, AGE, FIRMAGE, HIGH SCHOOL, EXPORT,
NETWORK SIZE, ASSISTANCE, LABOR FORCE, NETWORK PARTICIPATION,
Data and variables
According to Vietnam Government Decree 90/2001/ND-CP, a SME is “a business establishment with registered capital of no more than Vietnam dong (VND) 10 billion
(equivalent to USD 630,000) or with a workforce of no more than 300 regular employees”
SMEs can be categorized into micro enterprises (fewer than 10 workers), small enterprises (10–49 workers), and medium enterprises (50–299 workers), though precise classification remains challenging due to overlapping scales of capital and production activities A CIEM survey based on 2011 data shows that micro enterprises account for the largest share—about 70 percent—and include many household businesses, while only about 6 percent are medium enterprises; altogether, SMEs make up 97 percent of all enterprises and provide roughly 50 percent of total employment Evidence from multiple studies indicates that productivity in the private sector SMEs is lower than that of state-owned enterprises and foreign-invested firms SMEs face a range of constraints, including limited access to finance, land, and technology; difficulties attracting high-quality labor; competitive pressures and higher transaction costs; and, in particular, a deficit in R&D and innovation activities.
Vietnamese SMEs are not focusing on developing new products or applying any form of innovation, instead concentrating primarily on improving product quality (Phi, 2013) This narrow emphasis undermines their ability to build sustainable competitive advantages in a dynamic market To improve survival and growth, Vietnamese SMEs should embrace innovation and strengthen networks that enable knowledge sharing and collaboration, driving differentiation and long-term competitiveness.
An assessment based on 2,800 observations was conducted among small and medium-sized private enterprises in Vietnam The survey covers ten provinces, including Ho Chi Minh City, Hanoi, Hai Phong, Ha Tay, Quang Nam, Phu Tho, Nghe An, Khanh Hoa, Lam Dong, and Long An Data were collected through four questionnaires: Main (firm level), Employee (sub-sample), Economic Accounts, and Exit The sample is categorized by ownership forms, including officially registered households, private firms, cooperatives, limited liability companies, and joint-stock enterprises, with family-owned businesses accounting for about two-thirds of the enterprises in the dataset.
The 2013 SMEs Survey Report covers a broad set of topics essential to understanding small and medium-sized enterprises, including the impact of the international economic crisis, enterprise growth and dynamics, bureaucracy, informality and informal payments, and investment and access to finance It also analyzes production, technology and labour productivity, employment, environment, and the structure of trade and sales Together, these themes illuminate how SMEs navigate policy environments, efficiency drivers, and market conditions to compete and grow.
Source: 2013 Vietnam SME survey data
According to the table, the total number of firms increased slightly, rising from 2,419 in 2011 to 2,461 in 2013 However, changes vary by legal form, with private/sole proprietorships, limited liability companies, and joint-stock companies all rising between 2011 and 2013, while household enterprises and partnerships/collectives/cooperatives declined For example, household enterprises decreased from 1,571 in 2011 to 1,553 in 2013, whereas the number of limited liability companies grew from 498 to 546.
Table 5: Distinguish firm by size
Source: 2013 Vietnam SME survey data
Micro-sized firms, defined as having fewer than 10 employees, form the majority of firms From 2011 to 2013, micro firms declined from 1,763 to 1,660, while small firms increased from 566 to 614, and medium-sized firms rose from 132 to 145.
Figure 4: The 2013 SMEs’ survey sample by location
HCMC Nghe An Ha Tay Ha Noi Phu Tho Hai Quang Long An Khanh Lam
Source: 2013 Vietnam SME survey data
To ensure objective data collection, the survey was conducted across Vietnam's regions from the North to the South The majority of samples were collected in Ho Chi Minh City (24%), followed by Nghe An and Ha Tay (14%), Ha Noi (11%), and Phu Tho (10%) Other locations, including Hai Phong, Quang Nam, Long An, Khanh Hoa, and Lam Dong, had fewer samples than the top regions, yet each still contributed at least three samples.
Figure 5: The 2013 SMEs’ survey sample by sector
Source: 2013 Vietnam SME survey data
According to the survey results, the Food & Beverages sector accounted for 31% of the sample, making it the leading field The Fabricated Metal sector was second with 17%, followed by Wood at 10%, Furniture at 8%, and Rubber and Plastic and Apparel each at 5% The remaining sectors are minority shares, as described in the table above.
Table 6: Differences between large enterprises and SMEs
Indicators Large enterprises Small and Medium enterprises
Assets Over 10 billion VND Smaller 10 billion VND
Labor force Over 300 employees Smaller 300 employees
Connecting to institutes and outsiders
Depending on different level of board
Creative and adapt to market fluctuation
Lack of bureaucracy Depending on the head of enterprises of management
Difficult to go bankrupt Fierce competition - difficult to survive
Innovation Incremental innovations Radical innovation
Having many phases and incurring various fees Simple and economical
According to Greenhalgh and Rogers (2010), the innovation is defined as the applying new ideas to products, processes, or other firm’s activities that lead to increase valuable of products There are two differences definition of innovation which are production innovation and process innovation In the object and scope of the study, this paper just concentrate to examine the product innovation This is the introduction of a new product, improve the quality or redesign of old goods, services If firms introduce nothing since the last survey or in the period two years before, applying new process had a value =0, and if they succeeded in applying at least new process, its value =1 Besides it could be reinforce in an existing product as well as improvement of existing products It means if firm deliver the major improvements or changed specification of existing products since the last survey or in the period two years before the survey they had value =1, and other had value
Social capital: According to Putnam (1993), social networks based all the relationships as well as the social networks are making the business more convenience, then effect on firm performance Based on the SMEs’ survey, this research divided the effect of social capital in four aspects First, the network participation is dummy variable which equal 1 is joint 1 or more than one network and 0 in the other cases Second, network size: total regular contact is categories in 4 group: business people in the same line of business and in different lines of business, bank officials, and mass organizations Last, number of assistants: total times received assist in issues related to the business operation
The effect of the roles of owner/manager’s characteristics on innovation is Mascitelli
Small and medium-sized enterprises (SMEs) often rely on the owner/manager to directly engage with major clients, making the owner’s decisions a key driver of innovation Previous studies show that entrepreneurial age is negatively related to innovation, while long tenure and extensive experience emerge as important indicators of innovative capability Younger owner/managers tend to have stronger incentives to innovate, whereas age can influence the propensity to adopt new ideas Gender is another characteristic of SMEs that can affect innovation activities, typically modeled as a dummy variable equal to 1 for male and 0 for female The analysis suggests that male owner/managers are expected to have greater incentives to apply innovation than their female counterparts.
Firm age represents the survival capability of a firm in the face of financial difficulties and intense competition A positive relationship between firm age and performance is expected, as older firms tend to endure adverse conditions better than younger ones Consequently, innovation can enable established firms to outperform younger entrants by leveraging accumulated knowledge, resources, and adaptability (Girma et al., 2008).
Knowledge and experience are needed for innovation, a claim supported by numerous studies, including Romijn and Albaladejo (2002) They hypothesize that a manager or owner with postgraduate education is more eager to innovate, implying a positive association between higher education and innovative activity The model also includes a high school dummy variable, equal to 1 if the owner/manager has completed high school and 0 otherwise, to account for the influence of basic educational attainment on innovation propensity.
There is substantial debate about the influence of firm size on innovation Some researchers report a positive relationship, arguing that firms with larger budgets can sponsor innovative activities (Frits, 1989) Large firms also have opportunities to strengthen their competitive advantage through takeovers, mergers, and acquisitions, as well as access to larger markets Conversely, Martinez-Ros (1999) argues that small firms, with flatter hierarchies, can respond quickly to market changes In this study, firm size is measured by the number of employees to examine its link to innovation.
Using the labor force as a proxy for firm size captures the impact of human capital on firm performance While the contribution of an individual worker may be small, the accumulated influence of the workforce is substantial, especially in developing new products through idea generation, development, testing, and market exploration The skills and knowledge of employees are valuable for specific firms, shaping competitive advantage For instance, prior research has shown that organizing employees into teams can yield higher success rates (Sandberg, 1986).
EMPIRICAL RESULTS
Descriptive statistics
Table 7: Number of observations with improve existing product and new process
Source: 2013 Vietnam SME survey data
Across 2,341 observations, 409 relate to improving existing products, while 155 involve applying new processes, representing 16.64% and 6.4% of the total sample, respectively The accompanying table shows a sharp decline in efforts to improve existing products.
Table 7 illustrates that most firms do not apply innovation, with 1,866 firms not innovating To stay competitive, 324 enterprises apply only product improvement and do not create a new process, 70 enterprises develop new processes but do not improve the product, and 85 firms use both product improvement and new processes This pattern also reflects the situation in economies with a large agricultural sector, where about three-quarters of the workforce is employed in an agricultural-based economy like Vietnam.
Table 8: Interaction between improve existing product and new process
Descriptive statistics of 2341 observations are summarized in Table 9 below
Table 9: Descriptive statistics of the continuous variable
Variable Mean Std Dev Min Max
Regarding “age” variable, the average age of owner/manager is 46.5 The youngest owner/manager is just 19 years old And the oldest owner/manager is 94 years old
Regarding “firm age” variable, the average business lifetime is 15 years old Up to
2013, 2 years is the newest years of enterprises, and 76 is the oldest enterprises in this survey
Firm size, measured by the labor force (the number of employees), averages about 15 employees per firm The observed range runs from a minimum of 1 to a maximum of 1,700 employees The data indicate a tendency for firms to expand their size, as shown by 2011’s maximum observed labor force of roughly 500 employees, signaling growth potential within the sample.
In the network size variable, the maximum number of regular contacts a firm maintains is 1,437, while the average is 37 For the human capital variable, the average number of contacts that assist firm operations in 2012 is 203, with a maximum of 9,073.
Table 10: Descriptive statistics of the continuous variable of the dummy variable
Dummy variable Frequency of 0 Frequency of 1
Male owner-managers account for 60% of firms, while female owner-managers represent 40% The accompanying table shows that only 6.4% of firms export their products By contrast, the domestic market is highly competitive, with 87.76% of respondents reporting hard competition in their field.
Among owner-managers, formal education levels are relatively low Just over 23% have completed high school, while only 18% hold a university degree.
The “network participation” show that just 8.27% firms is member of one or more business associations.
Regression Results
There are nine out of ten determinants having significant impacts on improving product activity except the assistance variable The summary of regression results is presented in Table below:
Table 11: Multinomial logistic result innovation=1 (Improve product =1, new process = 0) innovation=2 (Improve product =0, new process = 1) innovation=3(Improve product =1, new process = 1) gender 0.269** -0.184 0.508**
Figures in parentheses are Wald statistics *** Significant at 1%, ** significant at 5%, * significant at 10% Source: Author’s calculation
There is a positive relationship between gender and improvements in product activity, particularly when firms implement both types of innovation The findings indicate that male owners/managers adopt innovation at a higher rate than female owners/managers.
Age of the owner/manager has a negative impact on applying new processes, suggesting that older entrepreneurs tend to have lower levels of innovation activity within their firms, a finding consistent with prior research (Mascitelli, 2000; Fontes & Coombs, 1996) In small firms, the owner's age is a key and significant factor shaping operations Younger owner/managers tend to be more enthusiastic and quicker to adopt new ideas, with longer commitment horizons that heighten their incentives to innovate Conversely, older owners may possess greater knowledge and experience The concluding insight is that the combination of commitment time and enthusiasm largely determines the extent of product improvement in these enterprises.
Product innovation probability is negatively related to firm age, with the likelihood of innovating declining as a firm’s life grows The findings show that as a firm's age increases, the probability of product innovation decreases Consistent with this pattern, younger firms are more inclined to innovate, while the oldest firms are less motivated to innovate than new entrants.
Evidence suggests that high school education lowers the probability of firm-level innovation when firms apply both types of innovation Moreover, several prior studies do not show a positive relationship between the educational level of the owner or manager and innovation.
(Diederenet al.; Romijn & Albaladejo, 2002) So the conclusion about the owner/manager finished high school would reduce the innovation’s probability may not correctly
Export activity is also have the positively affect innovation The research of Braga &
Willmore (1991) provides evidence consistent with this conclusion: firms that conduct business with overseas partners have stronger incentives to innovate than firms that trade solely in domestic markets International exposure motivates innovation, implying that global market engagement leads to greater investments in new products and processes than domestic-only firms.
The number of employees has just the positive affect on the firm which use improvement and apply new process This is coincidence with the expected sign table The
Schumpeter (1942) and Martinez-Ros (1999) argue that larger firms with abundant financial and human resources invest more in innovation activities, so a bigger workforce raises a firm's incentive to improve products and processes However, small firms face limited options for expanding scale, making mergers and acquisitions a common strategic path to growth and access to resources These findings illustrate how firm size shapes innovation incentives and strategic choices, with large firms leveraging their resource advantages to drive product development while smaller firms often pursue consolidation to achieve scale.
Competitive level have the positive relationship with product improvement Fritz
(1989) is also prove that in the severe competition environment, firms need more incentive to innovate for survival But this is not the unique solutions for firms to overcome difficult
They may reducing price and creating more promotions events
Commented [KH6]: Nguoc với kì vọng
Numerous studies show that social capital plays a significant role in the innovation process Network participation positively influences product improvement, with members of business associations often receiving stronger support than non-members This support encompasses not only financial backing but also valuable relationships with other members, which can spur collaboration and knowledge sharing In Vietnam, the government exerts influence over most formal business networks for political reasons, so when new laws or regulations are introduced, network members frequently gain political benefits that translate into competitive advantages for their firms.
Expanding network size drives more substantial progress than simply increasing interaction intensity; in network support, the quality of engagements—such as high-value interactions and timely actions within daily operations—trumps sheer quantity, as frequent but low-value contacts contribute less to overall effectiveness.
Network size has a positive effect on adopting new processes For small firms with limited resources, leveraging external information and capital becomes essential By expanding their networks and leveraging relationships and social ties, these firms can reduce costs and access critical resources They rely on direct contact and ongoing connections with partners, suppliers, and customers, and they often receive support from business associations to obtain the assistance needed to implement innovative processes.
The adoption of the new process among firms is low, driven by two main factors First, customers typically require only a standard, general product that meets their needs, so there is little demand for innovative solutions Second, many firms lack the resources and the right kind of innovative capabilities to implement the new process.
Marginal effects
After estimation, the marginal effect of an independent variable is shown as a predicted function For dummy variables, the marginal effect corresponds to the discrete change in the probability that the outcome switches from 0 to 1 when the explanatory variable increases by one unit, holding all other variables constant For continuous variables, the marginal effect is the instantaneous rate of change, measuring how the dependent variable changes with a one-unit increase in the independent variable.
When no new process is applied and firms just apply product improvement, if the owner/manager is male, the product improvement will increase by 3.4%
Age influences innovation: data show that when the owner or manager is older than a certain threshold, the probability of engaging in innovation activities declines by 0.05 percentage points Younger leaders, meanwhile, are more motivated to innovate, but they may lack the skills or experience needed to manage all operational issues effectively.
Competition is strongly correlated with innovation activities, yielding significant results When competition exists, the probability of applying innovation increases by 7.5% for product-only improvements, and the probability of achieving both types of product innovation rises by 2.3% The probability increases by 1.2% if only a new process is applied This finding is a key topic for policymakers: fostering competitive environments can boost firms' adoption of product and process innovations.
43 innovation through by the increasing competitive in the market There are many way to solve this problem The government could reduce the monopoly, reduce the support
Rising employee counts are linked to greater product improvement Adding one employee yields a 0.02% boost in product improvement, so hiring 100 more employees could boost product improvement by about 2% This effect is more feasible for larger firms, whereas small firms with fewer than 500 employees often find it difficult to scale their workforce rapidly.
Export activities, when paired with product improvements, can increase performance by 9%, providing a strong incentive for firms to engage in export As firms gain experience in the global market, they develop a competitive advantage in foreign markets.
Joining a business association significantly boosts firm innovation, increasing the adoption of product improvement by 14.8% and raising innovation by nearly 4% when both types of innovation are pursued, as captured by the network participation variable This indicates that network participation is a key driver for firms seeking to innovate their products, making membership in business associations a valuable strategy for product innovation and competitive advantage.
CONCLUSION AND RECOMMENDATIONS
Main finding
Several studies have highlighted the role of social capital in driving SME innovation in transition economies, and this paper reinforces the link between social capital and product innovation Beyond social capital, factors such as gender, firm age, high-school graduation, labor force size, export activity, and the level of competition significantly influence product improvement The findings also show that owner or manager characteristics affect the extent of innovation within firms Together, these results underscore how social, demographic, and organizational attributes shape product innovation in SMEs operating in transition economies.
Among three variables, social capital and network participation have significant effects on product innovation, with entrepreneurs earning more benefits from active network participation and association membership enhancing innovation as members are more likely to engage in business, assist each other, and receive updates on new business-related regulations While larger networks and frequent support can help firms overcome difficulties, the precise impact of the level of assistance on SME performance remains unclear, which helps explain why business associations are not yet popular in Vietnam The positive link between network size—the number of regular contacts—and innovation underscores the value of social networks, and a larger relationship network tends to be more profitable, though the extent of benefits from network assistance is not quantified Vietnamese government policy should invest in establishing and developing business networks to directly support enterprises in daily operations and long-term strategy.
Empirical evidence indicates that gender, age, export activity, firm size, and competitive orientation positively influence a firm’s innovation behavior In practice, owner and manager characteristics are key drivers of SME development, and founders need to accumulate knowledge and experience to effectively lead their enterprises.
Additionally, recruitment activity is necessary for expanding and boosting their business The major element for innovation is export activities.
Recommendations
This study underscores the impact of innovation on a firm's development and offers policy options for policymakers, grounded in the firm's business network and the key determinants of innovation It argues that effective policy must be informed by network structure, collaboration patterns, and the drivers that enable innovative activity, and it proposes concrete measures to strengthen knowledge exchange, access to finance, and capability building across business networks By aligning policy design with network dynamics and innovation determinants, these recommendations aim to boost firm performance, promote sustainable growth, and enhance competitive advantage.
Ministry of Industry and Trade (MIT) should actively support the formation and operation of industry-specific business associations These associations expand firms' networks by connecting producers with suppliers, facilitating information sharing, and organizing marketplaces, trade fairs, and collaborative workspaces Such networking and knowledge-sharing platforms help enterprises gain experience and learn new techniques to improve their products and competitiveness.
Secondly, Vietnam Trade Promotion Agency should motivate export activities to Vietnamese enterprises Besides, they should have trade policies which promote local producers to export their own products
Governments should curb monopolies and foster a competitive market by enabling open access for firms to enter and compete When barriers to entry are lowered and competition is strengthened, firms are incentivized to develop better products and services to gain market share A well-regulated, open market benefits consumers through lower prices, more choices, and ongoing innovation, driving overall economic growth.
This study faces limitations stemming from data scarcity, which prevented the dependent variables from adequately capturing both the quality and quantity of firm innovation The literature review suggests that several additional factors can influence innovation, but these variables were not fully captured in the SMEs survey used for this research.
Current work cannot directly measure endogeneity among variables because it stems from competition in international markets that compels exporting firms to innovate to stay competitive, and from the learning-by-exporting effect whereby exporters access a richer knowledge base, expertise, and technology not typically available in the home market To advance this topic, future research should develop new methodological approaches that address endogeneity and more clearly identify the causal impact of exporting on firm innovation.
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CORRELATION MATRIX gender age firmage highschool export lf netsize Assit competitive netpar gender 1 age 0.1978*** 1 firmage 0.0679*** 0.3389*** 1 highschool 0.0513* 0.0832*** 0.1301*** 1 export -0.0339 -0.0662*** -0.0283 -0.1137*** 1 lf -0.0941*** -0.0789*** -0.0225 -0.1306*** 0.26*** 1 netsize -0.0936*** -0.0945*** *-0.0441* -0.0715*** 0.071*** 0.1146*** 1
REGRESSION RESULT OF MULTINORMINAL LOGIT MODEL innova Coef Std Err z P>z [95% Conf Interval]
1 gender 0.2691743 0.132897 2.03 0.043 0.008701 0.529648 age -0.0024213 0.006226 -0.39 0.697 -0.01463 0.009783 firmage -0.0053309 0.0069296 -0.77 0.442 -0.01891 0.008251 asset 7.15e-08 3.89e-08 1.84 0.066 -4.67E-09 1.48E-07 highschool -.2251087 0.1599585 -1.41 0.159 -0.53862 0.088404 export 6317541 0.2240837 2.82 0.005 0.192558 1.07095 netsize -0.0006331 0.0015791 -0.4 0.688 -0.00373 0.002462
2 gender -0.1840318 0.2606479 -0.71 0.48 -0.69489 0.326829 age -0.0315283 0.0130479 -2.42 0.016 -0.0571 -0.00595 firmage 0.0131797 0.0121837 1.08 0.279 -0.0107 0.037059 asset 1.45e-07 5.00e-08 2.89 0.004 4.66E-08 2.42E-07 highschool -0.1084574 0.3177411 -0.34 0.733 -0.73122 0.514304 export -0.3252307 0.5951888 -0.55 0.585 -1.49178 0.841318 netsize 0.0036808 0.0013571 2.71 0.007 0.001021 0.006341
MARGINAL EFFECTS IN CASE: FIRM HAS IMPROVED PRODUCT AND NO NEW PROCESS y= Pr(innova==1) (predict,p,outcome(1))
=0.13052326 variable dy/dx Std Err z P>z [ 95% C.I ] X gender 0 0274107 0.01432 1.91 0.056 -0.00066 0.055476 0.606515 age -0.0001946 0.0007 -0.28 0.781 -0.00157 0.001178 46.1629 Firm age -0.0005354 0.00078 -0.68 0.493 -0.00207 0.000997 15.5911 high school -0.0229019 0.01657 -1.38 0.167 -0.05539 0.009582 0.237891 export 0 0896283 0.03583 2.5 0.012 0.019405 0.159852 0.061723 Network size -0.0000617 0.00017 -0.36 0.72 -0.0004 0.000275 38.0527
Assistance 0 0.00001 0.11 0.912 -2.7E-05 0.00003 199.976 lf 0.0001332 0.00016 0.85 0.395 -0.00017 0.00044 15.5778 network participation 0.1722748 0.03475 4.96 0 0.10416 0.24039 0.082726 competitive 0.0807157 0.01673 4.83 0 0.047935 0.113496 0.884269 (*) dy/dx is for discrete change of dummy variable from 0 to 1
MARGINAL EFFECTS IN CASE: FIRM HAS NEW PROCESS AND NO
IMPROVED PRODUCT y= Pr(innova==2) (predict,p,outcome(2))
=0.02640289 variable dy/dx Std Err z P>z [ 95% C.I ] X gender -0.0071119 0.00698 -1.02 0.308 -0.02079 0.006561 0.606515 age -0.0008707 0.00032 -2.73 0.006 -0.0015 -0.00025 46.1629 Firm age 0.0004132 0.00031 1.35 0.176 -0.00019 0.001011 15.5911 high school -0.0021848 0.00775 -0.28 0.778 -0.01738 0.013006 0.237891 export -0.0081842 0.01096 -0.75 0.455 -0.02967 0.013301 0.061723 Network size 0.000091 0.00003 2.66 0.008 0.000024 0.000158 38.0527
Assistance 0 0 0.45 0.655 -7.00E-06 0.000011 199.976 lf -0.0000488 0.00011 -0.45 0.652 -0.00026 0.000164 15.5778 network participation 0.0190165 0.01538 1.24 0.216 -0.01113 0.049164 0.082726 competitive 0.0145224 0.00787 1.84 0.065 -0.00091 0.029956 0.884269 (*) dy/dx is for discrete change of dummy variable from 0 to 1