UNIVERSITY OF ECONOMICS HO CHI MINH CITY VIETNAM INSTITUTE OF SOCIAL STUDIES THE HAGUE THE NETHERLANDS VIETNAM –NETHERLAND PROGRAMME FOR MA IN DEVELOPMENT ECONOMICS THE ROLE OF FAMILY INVOLVEMENT IN A[.]
INTRODUCTION
Problem statement
Family involvement significantly influences firm performance, a topic widely debated in academic research While many scholars distinguish between family and non-family business outcomes, inconsistent findings often result from variations in defining family firms, performance metrics, and sample selection Despite these discrepancies, the ongoing debate highlights the importance of understanding how “family effect” and “family involvement” impact productivity and overall firm success.
Small and medium-sized enterprises (SMEs) play a vital role in Vietnam's economic growth and integration into the developing economy, garnering increasing attention from economists Studies such as CIEM (2010) analyze the characteristics of Vietnamese SMEs, government policies, and the business environment, highlighting their importance Research by Nguyen Ngoc Anh et al (2008) emphasizes the critical role of innovation in enhancing SME export performance Additionally, Le Van Khoa (2006) addresses environmental pollution issues caused by SMEs in Ho Chi Minh City In 2009, family firms constituted over 60% of Vietnamese SMEs, yet there is a notable lack of research examining the differences between family and non-family firms, specifically regarding the impact of family ownership on firm productivity in Vietnam.
In this paper, we consider how the family ownership impacts to the firm productivity in Vietnam, making it different to the non-family ones
The Cobb-Douglas production function is commonly used to compare firm output between family and non-family businesses, as seen in studies by Bosworth and Londes (2002), Barth et al (2005), and Martikainen (2009), which indicate an ambiguous relationship To interpret these differences, Barbera and Moores (2011) argued that assuming homogeneous factor elasticity can lead to varied results; they emphasized that the two main production factors—labor and capital—contribute differently to output.
Research objectives
This study investigates how differences between family and non-family firms in utilizing labor and capital impact SME output and total factor productivity (TFP) It also examines other key determinants influencing SME performance and offers practical recommendations for firms seeking to enhance their productivity and growth.
This study tries to answer whether the family involvement has any impacts on the performance of the small and medium sized enterprises for the case of Vietnam.
Scope of study and data
This study utilizes the Cobb-Douglas production function combined with OLS and panel data analysis to identify key factors influencing firm output Panel data effectively addresses heterogeneity issues and controls for omitted variables across individual firms The dataset includes over 2,000 small and medium enterprises (SMEs) from surveys conducted in 2005, 2007, and 2009 by the World Institute for Development Economics Research, the University of Copenhagen, and Vietnamese government agencies It provides comprehensive information on the characteristics of Vietnam’s business environment and SME operations.
Thesis structure
Following the introduction, this paper is structured to provide a comprehensive understanding of firm performance differences Chapter Two reviews relevant literature and empirical studies explaining variations between family and non-family firms Chapter Three details the research methodology employed for analysis Chapter Four presents descriptive statistics and key findings from the data Finally, the conclusion offers insights and practical recommendations based on the study’s results.
LITERATURE REVIEW
What is family business?
Recent researchers have paid much attention on the difference in performance between family and non-family firm such as Gallo, (1995); McConaughy et al., (1999); Westhead et al.,
The definition of a family business remains a subject of ongoing debate among researchers While there is consensus that family involvement distinguishes these firms from others (Miller & Rice, 1967), the specific criteria used to define a family business vary across studies (Westhead et al., 1998) According to Chrisman et al (2003b), the effort to develop a clear and consistent definition of family businesses is still underway.
Various definitions of family firms exist based on different methodological approaches Shanker et al (1996) distinguish between a narrow definition focused on daily business operations and a broader one encompassing strategic decision-making Astrachan et al (2002) measure the influence of family on the firm using factors such as experience, power, and culture Some scholars, like Davis et al (1989) and Shanker et al (1996), emphasize the essence of family influence on decision-making The term “familiness” was first introduced by Habbershon et al (1997) to describe the unique resources stemming from family involvement in the business system, family, or individual behaviors Habbershon et al (2003) further elaborated on this concept, highlighting its role in shaping family firm dynamics.
“familiness” can bring competitive advantage to the family firm
According to Chrisman et al (1999, 2003b), the most common definition of family business in empirical research emphasizes two key components: ownership and management or business succession Family firms are typically characterized by ownership concentrated within a single family and/or significant influence over management processes (Gallo & Svenn, 1991; Holland & Oliver, 1992) However, there is no consensus on a single definition of a family business, as variations in management, control, and ownership lead to different interpretations Moreover, Chua, Chrisman, and Sharma (1999) argue that definitions focusing solely on ownership and management do not capture the core essence of family businesses, which include the firm’s vision and the family’s intent to shape and pursue that vision across generations.
Since disadvantage of the definition regarding to the ownership and management, the other dimension is added based on the behavior perspective (Litz 1997; Daily and Dolliger
1993) According to Chua, Chrisman & Sharma (1999) confirms that the behavior dimension is more useful, give more clearly definition and better than ownership and management basement
Chua et al (1999) define a family business as a company governed and managed with the primary goal of shaping and pursuing a shared vision maintained by the dominant family coalition This approach ensures that the business is operated in a way that is potentially sustainable across multiple generations.
The primary difference between family and non-family firms lies in their behavior, which influences how they utilize inputs such as labor and capital (Martikainen et al., 2009; Moore, 2011) Firm performance depends on the efficiency of resource utilization, with family involvement impacting input contributions to output (Steers, 1982) To analyze these inputs’ contributions, the Cobb-Douglas production function is frequently employed, though Moore (2011) critiques the previous assumption of homogeneous input contributions used in earlier studies (Wall, 1998; Bosworth & Loudes, 2002; Barth et al., 20XX).
The 2005 study presents controversial results, prompting researchers to assume that the elasticity of labor and capital with respect to total output differ, as suggested by Martikainen et al (2009) This divergence in assumptions highlights the complexity of understanding factor contributions to economic output and emphasizes the importance of considering differential elasticities in productivity analyses.
5 differences in using resources between two types of firms, the next section will explain the reasons by reviewing some related researches.
Differences between family and non-family businesses
Family businesses are driven by unique family goals rooted in "familiness" or "family involvement," as defined by Habbershon et al (1999, 2003b), emphasizing the importance of family influence in decision-making According to Demsetz and Lehn (1985), these firms typically prioritize long-term objectives, such as successful succession and intergenerational transfer, over short-term gains Family owners often value family goals more highly than financial objectives, distinguishing them from non-family firms (Lee et al., 1996), with non-pecuniary motivations playing a significant role in their decisions (Stanforth et al., 1999) Nicholas Kachaner et al (2012) highlighted that family businesses focus on non-financial targets like building corporate culture, investing in employee development, and ensuring business continuity during challenging times Additionally, family firms face distinct challenges related to family dynamics, which influence resource utilization differently compared to non-family organizations (Lester et al., 2006).
Family involvement in family businesses offers a unique competitive advantage that is difficult for others to replicate This advantage primarily stems from the strategic combination of family and business resources, enhancing resource acquisition and overall business performance According to research by Aldrich et al (2003) and Stewart, the integration of family dynamics with business operations creates a distinctive value proposition, enabling family firms to secure more favorable resources and sustain long-term success.
Family firm capital, encompassing human, social, survivability, patient, and governance structures, differs from non-family businesses in its origin, purpose, and utilization (Sirmon et al., 2003) Additionally, family firms benefit from rapid information flow among members, enhancing their ability to identify and capitalize on opportunities more effectively (Barney et al., 2003).
Previous research indicates that family businesses tend to use fewer capital resources compared to non-family firms, often avoiding risky investments and missing potential opportunities They typically resist external debt and maintain a strong independence from credit institutions, as noted in studies by Anderson et al (2003) and Villalonga and Amit (2006) Data from Kachaner et al (2012) reveal that the debt proportion in family businesses is approximately 37% of total capital, which is lower than that of non-family firms.
Between 2001 and 2009, 47% of non-family businesses experienced significant changes, highlighting the cautious approach of family firms during both good and bad economic periods Family businesses tend to carefully manage expenditures and investments, prioritizing financial stability and risk aversion They generally avoid pursuing large projects that fall outside their core competencies, favoring sustainable and systematic growth over risky investments This conservative investment attitude is supported by research from Gersick et al (1997), Cabrera-Suárez et al (2001), Zahra (2005), and Morck et al.
Family firms tend to prioritize long-term investments, emphasizing stability and sustained growth (Le Breton-Miller et al., 2006) However, research indicates that family businesses are generally less innovative compared to non-family firms, potentially due to their conservative approach to risk and preservation of family legacy (Gomez-Mejia et al., 2003).
Family businesses tend to be more labor-intensive than their non-family counterparts, leveraging their advantages in workforce utilization These firms often invest more in developing and training their employees, resulting in a more effective and dedicated workforce According to Nicolas Kachaner et al., family firms are generally better at investing in workforce development and training, which enhances their overall productivity and competitiveness.
Family businesses invest more in employee training, spending an average of €885 per employee annually—over €336 more than non-family firms—facilitating the development of valuable skills, knowledge, and flexibility across different roles (2012; Becker, 1974; Fiengener et al., 1996) Additionally, a positive working environment and strong family culture enhance employee efficiency and overall productivity within these enterprises (Tagiuri & Dais, 1996; Ward, 1988) However, wages in family businesses are often lower compared to other labor-intensive companies, which can impact employee compensation (Levering & Moskowitz, 1993).
The differences in resource utilization—specifically labor and capital—between family and non-family firms significantly influence their performance Understanding these distinctions helps to explain variations in overall firm success, with family firms often leveraging their unique resource management strategies to achieve competitive advantages The next section will explore and compare the performance differences between these two types of firms, highlighting how resource allocation impacts their effectiveness and growth potential.
The performance of family and non-family firms
Family businesses tend to perform better in the long term compared to other business types, prioritizing stability over short-term gains (Kachaner et al., 2012) Their risk-averse nature often leads them to avoid aggressive expansion during periods of economic growth, resulting in comparatively weaker performance in good economic times but stronger results during crises (Kachaner et al., 2012) This operational approach, reflecting their goals and resource utilization, causes significant differences in short- and long-term outcomes, with family firms maintaining stable performance over time—such as a consistent return on equity of about 13% to 14% Conversely, non-family businesses experience more fluctuation, with their average returns varying dramatically and closely following global GDP growth rates Additionally, research indicates that regional differences influence the performance disparities between family and non-family firms.
Figure 2.1: The long-term view of family-business performance
Bosworth and Loundes (2002) used the data of 4354 small and medium enterprises from Australia in order to analyze the discretionary investment, innovation, productivity and
Research indicates that family businesses tend to underperform in productivity and profitability compared to non-family firms While family firms invest more in tangible assets, there is no significant difference in R&D, intangible assets, or employee training levels between the two types of companies Additionally, studies show no notable difference in innovation performance between family and non-family firms.
According to Barth et al (2005), the management regime significantly impacts the lower productivity of family firms compared to non-family firms, with a productivity gap of approximately 10% When family firms hire managers from outside the family, their productivity aligns closely with that of non-family firms The productivity gap increases to around 14%, reaching 15-16% when analyzing only the sub-sample of family firms This study is based on data from 438 firms collected through a firm-level survey associated with Norwegian Business and Industry.
A 2009 study by CIEM analyzed 2,520 small and medium enterprises in Vietnam to identify key determinants of labor productivity The research found that larger firms tend to have higher labor productivity, with firms based in Ho Chi Minh City outperforming those in other provinces Household or family-owned businesses are significantly less productive compared to private firms Although the adoption of new technology initially shows a positive impact on labor productivity, its significance diminishes in panel-data estimations, indicating a less consistent effect.
Martikainen et al (2009) found that family firms in the S&P 500, comprising 159 manufacturing companies, exhibit higher productivity compared to non-family firms Their study highlights that there are no significant differences in production technologies between the two types of firms The research suggests that the superior efficiency of family firms driving higher input utilization results in greater overall output and better performance than non-family firms.
F Barbera, K Moores (2011) utilized the data of more than 4500 businesses that are the Australian small and medium-sized enterprise for the year 1995-1995 in order to find out the difference between family and non-family firm on the total factor productivity (TFP) and contribution of inputs to total output Basing on the Cobb-Douglas and assuming that elasticity
A study reveals that the contribution of labor input to total output is significantly higher in family firms compared to non-family firms, while the contribution of capital is notably lower in family firms Despite these differing input contributions, there are no significant differences in total factor productivity (TFP) between family and non-family firms when accounting for input heterogeneity.
Galve-Górriz and Salas-Fumás (2011) examined the performance and behavior differences between family and non-family firms in Spain's non-regulated stock market from 1990 to 2004 They found that family firms tend to be smaller and exhibit lower average asset growth, yet are less capital-intensive and demonstrate higher total factor productivity compared to non-family firms The study also revealed no significant differences in profitability and financial policies between the two types of firms The authors highlighted the importance of productive efficiency as a key factor in understanding how ownership influences firm performance.
Table 2.1: Summary of Empirical Review on the performance difference between family firms and their counterparts
Author Variable and Methodology Data set Result
Panel data with random effects to estimate the productivity and profitability; panel probit for estimate the innovation and discretionary investment
Dependent variable: the productivity (proxy by the value added), the profitability (proxy by the economic value profit), the dummy variables for innovation and
4354 small and medium enterprises from Australia conducted by Australian Bureau of Statistics’ “Business Longitudinal” for the year 1994-1995 and 1997-1998
The non-family firms have the superior performance in the productivity and profitability significantly than the family ones
The family firms are found to invest more in the tangible assets
There are no significance in the innovation difference between family and non- family businesses
Independent variable: labor and capital, some characteristics of the firm and of the industries
Assuming that factor elasticities are homogenous for both family and non- family firm
-Cobb-Douglas production function, OLS and 2SLS model to estimate the effect of the management on productivity
Independent variable: dummy variables for family owned firm and manager regime, labor, capital, listed firm, industry
-Probit-model, OLS and 2SLS to analyze the choice of family versus professional manager
-Assuming that factor elasticities are homogenous for both family and non- family firm
Data from the survey in 1996 of 438 firms associated with the Confederation of Norwegian Business and Industry
The non-family owner firms have superior productivity than the family ones that is explained by the management regime
The productivity of the family firm with the hired manager from outside the owner family and the non-family firm is not different
However, the family with the manager from the owner family is less productive
-OLS and balance panel-data
Dependent variable: real revenue per full-time employee (regular and casual employees) and real value added per full-time employee
Independent variable: the number of labor, dummy variables for location, new technology used, ownership, sector
-2520 small and medium enterprise enterprises of Vietnam for the year
The productivity of the family firm is less than the private firm significantly but except for the partnership/collective/coopera tive enterprises
The more firm size increases, the more labor productivity increases
The firm located in the Ho Chi Minh city has the labor productivity higher than other provinces
There are no significant impact of new technology to the real revenue in the panel data
Cobb-Douglas production function, OLS and ML estimate
Dependent variable: the net annual sale
Independent variables: the number of employees; the net annual property, plant and equipment; and the dummy binary variable for family involvement
The elasticity of input to output is tested for difference between family and non-
500 firms of Anderson and Reeb
(2003) contain the information of 159 manufacturing firms of family and non- family ones
The elasticity of inputs to output between family and non-family firm are not different
The production technologies between family and non- family firms are invariant Comparing to the non-family firms, the family firms are more productive significantly
12 family firm and found to be equal
Cobb-Douglas production function, OLS, 2SLS and panel data with random effects
Dependent variable: the value added
Independent variable: labor, capital and dummy variable for family involvement
Assuming that the factors’ elasticity is heterogeneous between family and non- family firm
The Australian small and medium-sized enterprises for the year 1995-1998 of more than 4500 enterprises
Allowing for the heterogeneous of factors’ elasticity between family and non-family firm, there are no differences in TFP
Comparing to the non-family firm, the contribution to output of family labor is more and of family capital is less
Cobb- Douglas production function, OLS
Dependent variable: Value added per labor
Independent variables: capital per labor, labor, dummy variable for family involvement
Assuming the heterogeneity of the input factor elasticity between two types of firm
The family and non- family firms of non regulated firms in the Spanish stock market for the period 1990-2002/2004
Family firms tend to have higher Total Factor Productivity (TFP) compared to non-family firms, even when accounting for the heterogeneity of factors' elasticity However, the contribution of capital to output is relatively lower in family firms, indicating a different approach to resource utilization compared to their non-family counterparts.
After review some concerning studies, it suggests us some following hypothesis:
H1: Ceteris paribus, the contribution to output of labor factor in family firms is higher than in non-family firms
H2: Ceteris paribus, the contribution to output of capital factor in family firms is lower than in non-family firms
H3: Ceteris paribus, there are no difference in the total factor productivity between in the family and non-family firms
Family businesses play a vital role in the economy, particularly in developing countries, despite performance variations between different types of businesses across nations Their significance underscores the need to understand their contributions, strengths, and challenges The next section will focus on highlighting the importance of family firms in driving economic growth and stability.
The importance of the family firm
Family businesses play a vital role in the economy and society, especially in developing countries European studies, such as the European Family Businesses (EFB) report (2012), highlight their long-term performance, community contributions, stability due to low debt and risk aversion, and their capacity to create jobs These firms contribute approximately 60-90% of non-state GDP, generate 50-80% of private sector employment, and constitute about 70-90% of all businesses worldwide The PwC Family Business Survey (2012) emphasizes that family firms are a resilient and essential component of the global economy, significantly supporting economic growth and recovery, with their performance poised to improve further with increased government support.
Family businesses in developing countries predominantly operate within the informal sector, utilizing simple and labor-intensive technologies (Michael P Todaro & Stephen C Smith, 2012) Workers in this sector often have limited access to education, skills training, and improved living and working conditions, along with insufficient financial capital Consequently, productivity levels in informal enterprises tend to be lower compared to the formal sector Despite these challenges, the informal sector remains a vital component of the developing economy, providing livelihoods and economic activity.
14 developing countries, generating more than half of the employment for the population in urban areas
The informal sector plays a crucial role in the economic development of developing countries by generating surplus income that supports urban growth, despite receiving less policy support than the formal sector It is less capital-intensive, addressing the capital shortages common in developing economies, and contributes to human resource development through low-cost education and skill training Additionally, the informal sector utilizes resources more efficiently and exhibits a greater capacity to adopt technology Importantly, since many poor populations work within this sector, promoting its growth helps ensure that economic benefits are more equitably distributed to alleviate poverty.
2.5 Other determinants of a typical firm’s performance
Several factors beyond family involvement significantly influence a firm's performance, with location being particularly crucial Raspe and van Oort (2011) highlighted that knowledge externalities and proximity impact firm location decisions and their subsequent performance, especially emphasizing the benefits of urban areas with high concentrations of universities and R&D institutions Andersson, Lửửf, and Martin (2011) found that firm labor productivity is positively affected by location size and agglomeration, supporting the idea of beneficial learning effects Mellander and Florida (2012) emphasized the importance of the geographic distribution of human capital, noting that factors such as the presence of universities, diverse services, and social tolerance critically influence this distribution Additionally, Sahin et al (2010) demonstrated that urban locations with multicultural entrepreneurial environments positively impact firm performance.
Exporting significantly impacts firm performance by providing firms with gains and returns from trade, as initially introduced by Krugman (1980), who highlighted that exports help firms gain competitive advantages through the concept of “learning by exporting.” Building on Krugman’s work, Bernard and Jensen (1995) further confirmed that exporting enhances firm productivity and competitiveness, contributing to overall improved performance.
Export firms demonstrate higher productivity compared to non-export firms, highlighting the positive impact of exporting on firm performance Numerous studies, including those by Baldwin and Gu, support this finding, emphasizing that engaging in export activities can significantly enhance a company's overall performance and competitiveness.
Research by Blalock and Gerler (2004), Yasar and Rejesus (2005), and Yang (2008) highlights the significant impact of exporting on firm performance Specifically, Yong Yang (2008) emphasizes that the positive effects of exporting are more pronounced in small and medium-sized enterprises compared to larger firms These findings underscore the importance of export activities for the growth and competitiveness of smaller firms in the global market.
Research indicates that the demographic characteristics of management and board members significantly influence firm performance For instance, Bilimoria and Piderit (1994a) highlight the impact of directors' ages, while Bond, Glouharova, and Harrigan (2010) and Singh (2007) emphasize the importance of the educational level of board members Additionally, gender and gender ratios within the board also affect company outcomes, as demonstrated by studies from Adams and Ferreria (2009), Westphal and Stern (2007), and Nielsen and Huse (2010).
This article proposes a conceptual framework (Figure 2.2) based on previous research, analyzing how family involvement influences key inputs like labor and capital and their impact on total output Key factors such as location, export activity, machinery usage, age, and gender are also considered to understand variations in productivity The framework highlights differences in the contribution of labor and capital and overall productivity between family and non-family businesses The subsequent sections will present the results of econometric estimates derived from this framework.
Location, Export, age, gender, etc…
Conceptual framework
Based on a thorough review of previous research, a conceptual framework is proposed (see Figure 2.2) This study analyzes the impact of family involvement on two key inputs—labor and capital—and their effect on total output In addition to labor and capital, other factors such as location, export activity, machinery utilization, age, and gender are considered to understand their influence on productivity The framework highlights differences in how labor and capital contribute to total output and productivity between family and non-family businesses The subsequent sections will present the results of the econometric estimates based on this framework.
Location, Export, age, gender, etc…
RESEARCH METHODOLOGY
The development of Domestic Private sector and Small and Medium Enterprises in Vietnam
Since the implementation of Doi Moi in 1986, Vietnam transitioned from a centralized economy to a vibrant market economy This reform led to a significant structural shift in the types of companies operating within the country, characterized by a dramatic reduction in the state sector and a substantial rise in the non-governmental sector As evidenced in Table 3.1, the proportion of the state sector decreased by approximately 8.5 times, reflecting the profound economic transformation driven by Doi Moi policies.
Non-governmental companies experienced significant and continuous growth, increasing from approximately 82% in 2000 to over 95% in 2008 Meanwhile, the share of non-governmental sectors rose steadily, reflecting a strong upward trend Conversely, government sector contribution decreased from 13.62% to just over 1.60% The foreign investment sector maintained a relatively stable presence, accounting for about 3% throughout the years.
Table 3.1: Number and ownership structure of Vietnamese enterprises 2000-2008
-Non-state enterprise (%) 82.78 85.75 87.81 89.60 91.55 93.11 93.96 94.57 95.67 -Foreign investment enterprise (%) 3.61 3.89 3.67 3.67 3.44 3.27 3.21 3.18 2.74
The introduction of the Enterprise Law in 2000 has significantly contributed to the development of non-governmental firms by creating advantageous conditions for the non-state sector's growth According to Vo Tri Thanh and Nguyen Tu Anh (2006), this law has improved the business and investment environment and established a more transparent legal framework to foster better relations between businesses and the government The private sector primarily consists of small and medium enterprises, which play a vital role in its expansion, as evidenced by data from Tables 3.2 and 3.3 Overall, the rapid growth of this sector is largely driven by the success of small and medium-sized enterprises.
Between 2000 and 2008, the number of SMEs grew approximately fivefold, with the SME ratio exceeding 97% in non-state enterprises and about 95% across all enterprises The data indicates a significant shift in ownership structures, as shown in Table 3.2, with the state sector’s share declining to around 50% across all business types Foreign-invested SMEs now constitute approximately 75% of total SMEs, reflecting the sector’s substantial presence Over the years, there has been a remarkable transformation in the SME landscape, highlighted in Table 3.3, which details the ownership proportions The trend shows a dramatic decline in the state sector—over ten times smaller—while the non-state sector has expanded rapidly, increasing by more than 1.1 times Meanwhile, foreign-invested businesses maintain a modest share of around 2.5%, underscoring the growing dominance of non-state ownership in the SME sector.
Table 3.2: Vietnamese SMEs’ share in different ownership types
-State enterprise (%) 85.57 82.63 79.27 75.52 70.50 65.86 62.52 59.47 55.52 -Non-state enterprise (%) 99.57 99.50 99.37 99.21 99.08 98.92 98.78 97.94 97.64 -Foreign investment enterprise (%) 73.18 76.83 77.38 77.62 78.04 77.93 77.13 76.62 74.48
-State enterprise 61.75 58.06 55.32 52.49 52.16 53.60 53.75 54.52 54.49 -Non-state enterprise 97.69 97.73 97.72 97.66 97.92 98.00 98.06 98.10 98.39 -Foreign investment enterprise 74.10 77.72 74.31 73.31 73.70 74.11 74.27 74.98 76.50
Table 3.3: The number and ownership structure of Vietnamese Small and Medium
-Non-state enterprise 85.22 88.07 90.09 91.81 93.59 94.92 95.63 96.08 96.96 -Foreign investment enterprise 2.73 3.09 2.93 2.94 2.77 2.63 2.55 2.53 2.11
-Non-state enterprise 87.95 90.26 92.02 93.36 94.57 95.43 95.94 96.25 96.95 -Foreign investment enterprise 2.91 3.26 2.92 2.87 2.67 2.54 2.48 2.48 2.16
See appendix 1 to understand how Vietnam government classifies the micro, small, medium and large enterprises based on the “Criteria for a small and medium enterprise, according to the
Decree No 56/2009/ND-CP dated 30 June 2009 of the Government”
Small and medium enterprises (SMEs) have played a crucial role in Vietnam's economic growth, contributing to stability and sustainability According to Harvie (2004, 2007), private sector SMEs drive job creation, attract significant foreign direct investment (FDI), boost exports, and effectively utilize personal and social resources Additionally, SMEs support rural and regional development, underpinning the country's overall economic progress Recent performance and characteristics of Vietnamese SMEs reflect these vital contributions to the national economy.
The recent performance of Small and Medium Enterprises in Vietnam
Small and medium enterprises (SMEs) play a vital role in Vietnam’s economy by creating jobs, increasing income, and promoting social development, which helps reduce poverty According to Cao Si Kiem (2012), SMEs generate over half a million new jobs annually, employing approximately 51% of the workforce and contributing around 40% to the national GDP Over the past decade, taxes and fees paid by private SMEs to the government have increased by 18.4 times, highlighting their significant economic impact.
Recent SMEs in Vietnam have yet to achieve high efficiency, particularly amidst the impact of the global crisis, with over two-thirds of surveyed enterprises experiencing adverse effects The crisis's impacts are primarily temporary, but the overall business environment is deteriorating, leading many firms to face financial difficulties and struggle to access credit from financial institutions Labor productivity tends to increase with firm size and is higher in urban areas compared to rural regions Additionally, numerous business activities negatively affect the environment, and there is a general low level of legal knowledge and environmental awareness among entrepreneurs According to the CIEM (2010) report, while Vietnamese businesses were relatively prepared for the financial crisis, they face structural challenges that need to be addressed to align with the country's Socioeconomic Development Strategy for the next decade.
Cao Si Kiem (2012) pointed out some weaknesses of small and medium enterprises of Vietnam Firstly, small and medium enterprises still do not have access to the support programs
Many Vietnamese SMEs face significant challenges in accessing government support and resources, primarily due to enterprise resource constraints, inadequate preparation, misaligned priority sectors, and complex procedures Additionally, obtaining business loans is often difficult because of lending process obstacles, low or unsuitable collateral options, and high interest rates SMEs also encounter hurdles in securing production space, characterized by complex procedures, lack of transparent information, and unofficial costs Furthermore, Vietnamese SMEs outside the global manufacturing supply chain struggle to develop industry support and often find it challenging to become providers of services and inputs for foreign companies and large state-owned enterprises.
According to Prime Minister Decision No 1231/QĐ-TTg dated September 7, 2012, approving the SME development plan for 2011–2015, the Vietnamese government supports small and medium enterprises through eight key solutions These include improving the legal framework for market entry, operations, and exit; enhancing access to finance and credit while increasing capital efficiency; supporting technological innovation and the adoption of new technologies; developing human resources with an emphasis on managerial capacity building; fostering industry clusters and expanding land access; providing information to support market expansion; establishing organizational systems to facilitate SME growth; and implementing a comprehensive plan to oversee SME development.
Sources of data
This research analyzes Vietnamese SMEs using biannual survey data collected from 10 key provinces—Hanoi, Phu Tho, Ha Tay, Hai Phong, Nghe An, Quang Nam, Khanh Hoa, Lam Dong, Ho Chi Minh City, and Long An—by the World Institute for Development Economics Research, the University of Copenhagen, and Vietnamese government agencies The dataset, comprising over 2,000 SMEs, provides comprehensive insights into the characteristics of Vietnam’s business environment and SME performance for the years 2005, 2007, and 2009.
Based on survey data, the number of firms was 2,800 in 2005, decreasing to 2,600 in both 2007 and 2009 For our balanced panel data analysis, we selected 1,748 firms that participated consistently across all three surveys and provided complete information This ensures a reliable and comprehensive dataset for accurate research insights.
Household or family firms in Vietnam, as identified in surveys, include both registered and non-registered businesses under the Enterprise Law Non-family firms encompass private companies, collectives, partnerships, and joint-stock companies The classification of firm size in the SMEs survey follows the World Bank standards, where micro firms have 1 to 9 employees, small firms employ 10 to 49 employees, and medium firms consist of 50 to 299 employees.
Research methodology
This paper employs the concept of Total Factor Productivity (TFP) to assess firm productivity, following the approach of Palia and Lichtenberg (1999) TFP offers the advantage of measuring both labor and non-labor productivity, providing a comprehensive view of firm efficiency It is defined as the ratio of output to the weighted sum of all inputs used in the business, capturing the overall efficiency of resource utilization The TFP measure can also be reformulated to better analyze productivity dynamics within firms.
The Cobb-Douglas production function models the relationship between inputs and output, where A represents Total Factor Productivity (TFP), and Y is the actual output The function f(L, K) = L^α K^β captures how labor (L) and capital (K) contribute to production through weighted exponents α and β, reflecting their respective elasticities This formulation emphasizes that output depends on the combined weighted inputs of labor and capital, with TFP (A) serving as a measure of technological progress and efficiency in the production process.
Substitute it into the two sides of the equation 1 and taking logarithms we get
A production function is commonly utilized to assess the contribution of input factors to overall output, enabling analysis of how labor and capital influence total output, total factor productivity, and the impact of family involvement This approach aligns with studies by Wall (1998), Bosworth and Loundes (2002), Barth et al (2005), and Barbera and Moores (2011) To facilitate this analysis, Equation (2) is rewritten accordingly.
Ln(Yi) = Ln(Aij) +α ln(Li) + β ln(Ki) (3)
Where i present to the firm ith firm,
Y is the homogenous total output of ith firm
L is the homogenous labor input of ith firm
K is the homogenous capital input of ith firm
A is the total factor productivity α, β are the unknown parameters that can be estimated if we have the data of output and the inputs
Barbera and K Moores (2011) highlight that in equation (3), the contributions of labor and capital are homogeneous, with differences in family versus non-family firm involvement captured by the intercept parameter j They note that family involvement impacts the contributions of labor and capital to total output, indicating that these contributions differ between family and non-family firms Consequently, the study proposes a modified equation to better reflect these distinctions.
Ln(Yi) = Ln(Aij) +αj ln(Li) + βj ln(Ki) +λXi +ei (4)
According to Barbera and Moores (2011), the contribution of labor and capital varies across different firms, as indicated by the parameter j This heterogeneity is used to differentiate between family and non-family firms by analyzing the estimates of αj and βj Additionally, various control variables Xi are incorporated to account for other factors influencing input utilization, providing a comprehensive understanding of how family ownership impacts resource allocation.
In the Cobb-Douglas production function, Y represents total physical output; however, SME surveys often lack data on actual output Based on the works of Kenneth Arrow (1974), Barth et al (2005), and F Barbera and K Moores (2011), “value added” is calculated as the production or manufactured output value minus total indirect costs and the value of raw materials used This measure of value added is collected from economic accounts at the end of the surveyed year, providing a vital indicator for economic analysis.
Variable treatment
In equations 3 and 4, Y represents total output; however, the SME survey does not include data on total output Therefore, we use Value Added (VA) as a proxy, which is a reliable alternative The Value-Added information is calculated and available in the Economic Account section, ensuring accurate analysis despite the absence of total output data.
In a recent survey of SMEs, the VA (Value Added) is defined as the difference between the total value of production or manufactured output, the total indirect costs, and the value of raw materials used This measurement provides a clear indicator of the economic contribution of small and medium-sized enterprises by highlighting the net value created through their production processes.
Arrow (1974) and Sato (1976) highlight that using the Value-Added approach allows for effective observation and analysis of both tangible and intangible output and factor inputs This method provides a comprehensive view of economic performance by capturing all contributions to value creation Additionally, economic accounts based on this approach are statistically calculated and summarized at the end of each year, facilitating accurate assessment of economic growth and productivity.
Labor input and capital input
The total labor force at the end of the year serves as a proxy for the labor factor, including both full-time, part-time, and casual workers, as specified in survey question 73 This figure provides a comprehensive measure of the available workforce For the capital factor, we utilize the combined value of physical and financial assets held at year's end, as reported in the Economic Return, offering a complete indicator of capital resources.
Account part of SME survey Labor and capital inputs are expected to be positive significantly with the total output
Research by Martikainen et al (2009) and F Barbera and K Moores (2011) demonstrates that family involvement positively influences overall productivity, with studies using the Cobb-Douglas production function revealing that family firms tend to achieve higher total factor productivity (TFP) compared to non-family firms This evidence suggests that family-owned businesses are generally more productive and efficient.
This study defines family involvement in SMEs based on data from question 12 of the survey, which inquires about the firm's ownership and legal status Family firms are identified when the legal status registered with the government is classified as a household establishment or business Conversely, non-family firms include private or sole proprietorship entities This classification helps to distinguish between family-owned and non-family-owned small and medium-sized enterprises for analysis.
This study examines various types of business structures, including partnerships, collectives or cooperatives, limited liability companies, joint-stock companies with and without state capital, joint ventures with foreign capital, and state enterprises at both central and local levels A dummy variable is employed, assigned a value of 1 if the firm is family-owned and 0 otherwise, to capture family involvement It is hypothesized that family involvement positively influences total output, suggesting that family-owned firms may have a competitive advantage in productivity and performance.
Family labour and family capital
F Barbera, K Moores (2011) stated that the there is the difference in the contribution of labor and capital to the total output between two types of firm Two dummy variables- family labor and family capital- that show the difference between capital and labor contribution in the two types of businesses, are created by multiplying the dummy variable "family involvement" to two variables "labor input and capital input." Family labor is expected to be positively correlated with output, and family capital is expected to be negatively correlated with output
To control heterogeneity among firms, we include control variables such as location, machinery usage level, year, exports, respondent's sex, and age Location is captured using eight dummy variables representing nine surveyed provinces—Ho Chi Minh City, Ha Noi, Phu Tho, Ha Tay, Hai Phong, Nghe An, Khanh Hoa, Quang Nam, Lam Dong, and Long An—highlighting regional differences Firms in Ho Chi Minh City are anticipated to be more productive compared to those in other provinces, reflecting regional economic disparities.
We incorporate dummy variables for specific industry sectors, including apparel, fabricated goods, textiles, and furniture Firms operating within Vietnam’s traditional industries—such as apparel, textiles, and furniture—are generally expected to demonstrate higher productivity levels This approach enhances the accuracy of our analysis by accounting for sector-specific differences that influence firm performance.
The firm's operating year, calculated as the surveyed year minus the beginning year, is expected to be negatively correlated with output, indicating that older firms may exhibit lower productivity The export variable, which indicates whether a firm engages in exporting by assigning a value of 1 for exporters and 0 for non-exporters, suggests that export-oriented firms are generally associated with higher productivity levels compared to non-export firms.
Table 3.4 below presents summary of the variables used in the regression models, definitions, units and expected signs
Table 3.4: Variables used in the Production Function
The independent Variables Labor The total number of labor at the end of the year persons +
Capital The total of physical and financial asset Million
Family_involvement Dummy variable equals 1 if the firm is the family firm, equals to 0 if others
F_Labour The number of labor that family firm uses that equal to Family_involvement multiply by Labor persons +
F_Capital The capital that family firm uses that equal to Family_involvement multiply by Capital
No_year The number of operational year equals to the existing years minus to the starting year
Export The firm exports or not, dummy variable equals to 1 if export, equals to 0 if not
This chapter compares the performance of two types of enterprises, beginning with descriptive statistics to provide an overview of the data It employs both Ordinary Least Squares (OLS) and panel data analysis methods to examine the impact of family involvement on total output The findings offer valuable insights into how family involvement influences enterprise performance, leading to targeted recommendations presented in Chapter V.
Figure 4.1 illustrates the probability distribution of labor, capital, and value-added variables over the years, showing relatively consistent patterns across the period Table 4.1 provides descriptive statistics for the overall sample, including sub-samples of family and non-family firms, highlighting that family businesses constitute approximately 70% of the total Despite their predominance, non-family businesses tend to be larger in terms of key variables; their value added exceeds that of family firms by more than 10 times, capital by approximately 7 to 8 times, and labor by over 7 times.
Non-family businesses consistently outperform family businesses in size, based on labor, capital, and value-added metrics On average, non-family enterprises employ about 35 workers, compared to just 6 in family businesses, with employment levels remaining relatively stable over the years However, both business types experienced a sharp 50% decline in capital and value-added in 2009, indicating a significant downturn Notably, there are substantial differences in labor and capital utilization between family and non-family businesses, raising questions about how these disparities influence each business type’s overall output value.
Table 4.2 shows the relationship of the variables in the Cobb-Douglas function as labor, capital and value added Looking through the years, two important variables that labor and
The relationship between labor and capital inputs and overall output is positively correlated Figure 4.2 provides insights and hypotheses regarding how these inputs influence output over time The analysis reveals notable differences in how capital and labor impact output between family and non-family firms across the years To better understand these variations, more detailed regression estimates are applied in the subsequent sections.
Figure 4.1: The probability density function histogram of variables through years of
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Figure 4.2: The scatter-plot of log value add on variables of family and non-family firms through years
Family labor year 2005 Non-family labor year 2005
Family capital year 2005 Non-family capital 2005
Family Labor year 2007 Non-family Labor year 2007
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Family capital year 2007 Non-family capital 2007
Family Labor year 2009 Non-family Labor year 2009
Family capital year 2009 Non-family capital 2009