INTRODUCTION
Research objectives
Investigate the impact of internationalization degree on Vietnam manufacturing firms’ performances.
Estimate how organizational slacks affect the relationship between internationalization and firm performance.
Research questions
This study is expected to clarify the three main research questions as follows:
1 Does higher internalization degree lead to higher Vietnam manufacturing firms’ performances?
2 Does higher level of high-discretion slack have a positive effect on internationalization-performance relationship in Vietnam manufacturing firms?
3 Does higher level of low-discretion slack have a positive effect on internationalization-performance relationship in Vietnam manufacturing firms?
Research Methodology
This study performs a quantitative analysis of unbalanced panel data from 45,491 Vietnamese manufacturing firms across various industries between 2007 and 2012 The use of panel data enhances reliability over time Both fixed-effect and random-effect models are employed to analyze the data, and the Hausman test is conducted to determine the suitability of the fixed-effect versus random-effect model.
Organization of the Study
This paper consists of five chapters Chapter 1 - Introduction outlines the practical and academic challenges along with the research objectives Chapter 2 - Literature Review provides a comprehensive theoretical and empirical background, focusing on the definition of internationalization, organizational slack resources, the link between internationalization and firm performance, empirical findings, and variable measurement Chapter 3 - Research Methodology details the methods, calculations, and data used for quantitative analysis based on the conceptual framework.
Chapter 4 presents the testing results and a comprehensive discussion of these findings The study concludes in Chapter 5 with recommendations aimed at policymakers, offering insights derived from the research.
LITERATURE REVIEW
Theoretical review
Johanson & Vahlne (1977) defined internationalization as a multi-stage process that the firms make the incremental efforts to strengthen their market involvement and gradually achieve the commitments from foreign consumers
Firms' internationalization process occurs through two incremental channels (Johanson & Vahlne, 1977; Westhead et al., 2001; Contractor et al., 2003) The first channel involves international firms (IFs) facilitating the entry of their products and services into foreign markets, such as initiating exports to specific countries or establishing export channels The second channel encompasses the expansion of operations abroad, which includes developing sales subsidiaries and outsourcing production to favorable locations within host countries (Westhead et al., 2001).
Aulakh et al (2000) highlighted that export activities are crucial for many international firms (IFs) from developing countries, as they seek to overcome the challenges posed by limited domestic markets Consequently, exports represent the most effective strategy for expanding market nature and size while minimizing costs (Johanson).
In addition, Aulakh et al (2000) also assumed that those firms almost continue to be in the early stage of internationalization process and less likely
Firms from emerging economies often enter international markets by leveraging their comparative advantages in production and exporting their goods to other countries.
2000) Therefore, most of these emerging firms consider export as their key internationalization strategy and their export performance as performance of the entire internationalization process.
Assaf et al (2012) highlighted that international firms (IFs) tend to be more confident and proactive in executing suitable internationalization strategies within similar business environments, aligning with the findings of Aulakh et al (2000).
Initial success will encourage international firms (IFs) to broaden their internationalization strategies to target diverse markets and customers Exporters with robust capabilities and stable consumption markets may opt to outsource production through foreign direct investment (FDI) (Westhead et al., 2001) This transition from export to FDI represents a strategic move to achieve economies of scope and scale while also benefiting from risk diversification (Assaf et al., 2012; Cave, 1971; Lessard, 1976).
Internationalization strategies for firms typically begin with the development of market knowledge and exploration (Contractor et al, 2003) This foundational understanding influences their decision to export Enhanced market knowledge plays a crucial role in either encouraging or deterring firms from internationalizing, and it is essential for the success of international firms once they enter the global market (Westhead et al, 2001).
The internationalization process is typically gradual, driven by enhanced market knowledge By understanding the characteristics, preferences, and cultures of target foreign markets, firms can tailor their products and services to meet diverse standardized requirements while gaining valuable international experience for future growth For instance, companies can modify product packaging, trends, and flavors to align with specific languages and cultural nuances.
Leveraging Information and Communication Technology (ICT) allows firms to create user interfaces and websites that adhere to international standards and support multiple languages, catering to a global audience This enhancement in market knowledge empowers international firms to effectively introduce and sell their products or services worldwide.
II.1.2.The degree of internationalization and firm performance
The question whether higher degree of internationalization will lead to a certain higher level of firm performance is a very controversial issue until now
Decades of research have raised more questions than answers regarding the involvement of international firms (IFs) in the global market (Glauum & Oesterle, 2007) This topic remains particularly appealing to the international business community Previous empirical studies have provided a solid foundation for further research, supported by established theoretical frameworks There are compelling arguments on both sides regarding the impact of internationalization.
Internationalization is a key strategy for firms seeking growth and competitive advantage, particularly in the face of a limited domestic market This approach allows companies to expand their market reach with minimal costs while benefiting from global opportunities, including economies of scale, effective price discrimination, and access to more affordable resources.
Many argue that internationalization negatively impacts firm performance Eriksson et al (1997) highlight several challenges faced by international firms, including intense competition, high transaction costs, market volatility, and cultural diversity While the market size for international firms may significantly increase, the rise in strong competitors and the complexity of varying standards and regulations can create substantial burdens for these firms in the short term (Bobillo et al., 2010).
In a more comprehensive view, Contractor et al (2003) fully described the internationalization process with a new three-stage theory of internationalization including three separating stages with different impacts on performance.
Figure 4: Three-stage theory (S-shaped) of international expansion (Contractor et al, 2003)
The early stage of internationalization focuses on initial market exploration to support export activities (Johanson & Vahlne, 1977) During this phase, new internationalized firms familiarize themselves with foreign markets by examining cultural characteristics, languages, habits, and tastes before exporting their products and services However, firms face various legal and market barriers, along with learning costs to acquire essential entry and market information, which are referred to as "the liability of foreignness" (Contractor et al., 2003).
Internationalization poses significant risks for firms due to high uncertainties and limited economies of scale in the initial phase (Westhead et al., 2001) Despite these challenges, Johanson and Vahlne (1977) noted that companies are often willing to invest in acquiring market knowledge and international experience to enhance their foreign commitments Consequently, early-stage internationalization can adversely impact firm performance, although this effect varies based on factors such as financial capacity, human capital, management expertise, and the adaptability of each enterprise in the global market (Johanson & Vahlne, 1990; Westhead et al., 2001; Contractor et al., 2003).
In the mid-stage of internationalization, International Firms (IFs) begin to experience initial gains as they expand globally As they progress, these firms effectively absorb the benefits of their global expansion, with increased revenues outweighing the costs of learning (Contractor et al., 2003) At this stage, IFs acquire sufficient market knowledge and enhance their ability to implement exporting strategies more efficiently.
Up to this point, most of firms reach the economies of scale and can apply price discrimination strategy for different markets (Hutchinson et al,
After achieving initial success, firms often become more ambitious in their internationalization efforts Typically, they begin expanding operations abroad through foreign direct investment (FDI) or outsourcing, as they gain access to more affordable local resources, including materials and labor.
2012) It is obvious that internationalization offers a good chance to seek new potential markets and expand their growth Thus, in stage 2, internationalization is believed to lead to higher firm performance.
Empirical review
II.2.1.Internationalization and firm performance
Research on global expansion has employed diverse methodologies and variables, yielding controversial findings The primary focus has been on whether internationalization enhances or hinders the performance of international firms (IFs) However, this inquiry raises additional questions, as existing studies often overlook moderating effects that can directly and indirectly impact the relationship between degree of internationalization (DOI) and firm performance.
Recent studies have explored the relationship between various moderating factors, such as internal and external competitive advantages (Bobillo et al., 2010) and organizational slacks alongside attainment discrepancies from a firm's behavioral perspective (Lin, Liu & Cheng, 2011).
As most of initial studies on multinational corporations, Riahi-Belkaoui
In 1998, a study examined the impact of internationalization on the performance of 100 American manufacturing and service firms from 1987 to 1993 Utilizing a piecewise linear regression model, the research accounted for variations in the slope of internationalization across specific thresholds The degree of internationalization (DOI) was measured by the ratio of foreign sales to total sales, categorized into three levels: DOI1 (0-14%), DOI2 (14-47%), and DOI3 (above 47%) Additionally, the analysis controlled for firm size, represented by the logarithm of assets.
PERFORMANCE = a1 + a2DOI1i+ a3DOI2i+ a4DOI3i+a51Ai+ui
This study found an S-shaped relationship between DOI and firm performance which is consistent to the theory of Contractor et al, 2003
The study indicates that firm performance initially increases, then peaks, and ultimately declines as internationalization progresses This challenges the notion that "more multi-nationality is better," suggesting that companies must identify their optimal level of international engagement.
Bobillo et al (2010) identified an S-shaped relationship between international diversification and firm performance, influenced by internal and external capabilities, similar to findings by Riahi-Belkaoui (1998) Utilizing the Worldscope database, which includes financial statements from over 1,500 manufacturing firms across five EU countries from 1991 to 2001, the study analyzed more than 15,000 observations The fixed effect analysis was deemed the most suitable model following the Hausman test The regression model incorporated the degree of internationalization (measured as the ratio of foreign sales to total sales), along with control variables such as firm size (logarithm of total employees) and ownership (insider shareholdings) Additionally, the research explored the impact of internationalization on performance through quadratic and cubic regression models across three distinct stages.
ROAit= β0+ β1DOIit+ β2DOIit 2+ β3DOIit 3+ β4SIZEit+ β5OWNERSHIPit
In their conclusion, Bobillo et al (2010) found that the firm performance varies in different directions as the internationalization degree moves upward
The initial negative impact on performance can stem from increased transaction costs, a more complex governance structure, and the urgent need for market knowledge and technology However, the performance trend related to the Degree of Internationalization (DOI) is influenced by both internal and external factors at the firm and country levels Successful internationalization strategies depend on firms leveraging their capabilities in alignment with favorable institutional factors, such as the financial system and labor market of their country.
In 2008, Pangarkar conducted a study on the impact of internationalization on the performance of listed SMEs in Singapore, utilizing the OLS method He analyzed the lagged value of internationalization from 2013 to predict firm performance in 2004, focusing on internationalization as measured by the ratio of foreign sales to total sales The research was based on 94 completed questionnaires collected through a Likert scale survey conducted in the mid-2000s.
2005 The control variables such as firm size, capabilities, host market attractiveness are added to the regression equation as follow:
PERFORMANCET = β0 + β1DOIT-1 + β2SIZEit + β3CAPABILITIES + β4HOST_MARKET_ATTRACTIVENESS + εit
The study revealed a positive linear relationship between DOI and firm performance, highlighting that firms in Singapore and developing countries like Vietnam, Thailand, and India are more motivated to engage in international markets due to limited local opportunities However, a key challenge remains in fostering cooperation among these firms to overcome shared obstacles and enhance their capabilities.
Lin, Liu, and Cheng (2011) conducted a study in Taiwan from 2000 to 2005, examining the moderating effects of organizational slacks and attainment discrepancy on firm behavior Their research also considered several control variables, including firm size, firm age, insider shareholding, diversification, and R&D intensity.
Firm performance = β0+ β 1 Internationalization+ β2firm_size + β3firm_age + β4Insider_Shareholding+ β5Diversification + β6R&D_ratio + β7High_discretion_slack + β8Low_discretion_slack + β9Attainment_discrepancy β 10 High_discretion_slack*Internationalization + β 11 Low_discretion_slack*Internationalization+ ε
The study revealed that internationalization has a negative impact on firm performance, and no significant S-shaped relationship was identified Notably, the influence of internationalization on performance is amplified for firms that possess higher levels of organizational slack in both forms.
II.2.2.Organizational slacks, internationalization and firm performance
Tan (2003) conducted the empirical studies on the longitudinal data set of more than 17,000 large and medium state-owned enterprises in China from
Between 1995 and 1996, a study was conducted to examine the impact of slacks on the performance of international firms (IFs) To establish a causal relationship between slack and internationalization performance, a lagged model was utilized, with lagged Return on Assets (ROA) serving as a predictor The research reviewed various classifications of slacks based on specific research objectives, ultimately selecting capital depreciation funds and retained earnings as two primary sources of slacks in Chinese internationalizing firms.
The study by Lin, Liu, and Cheng (2011) utilized Return on Assets (ROA) as a performance proxy, incorporating firm size and age as control variables The findings revealed that increased levels of slacks enhance firm performance The authors explained that when firms have ample slacks, they are more inclined to invest in higher-risk markets, which are anticipated to yield greater returns.
Moreover, by higher level of slack resources, they also have more capabilities to manage the risks and maintain their competitiveness in the long-run survival (Tan, 2003).
To explore the relationship between slack and internationalization performance, Daniel et al (2004) performed a meta-analysis of 80 samples from 66 studies conducted between 1991 and 2000 The analysis revealed that slacks are classified in various ways, with the most prevalent classifications being available, recoverable, and potential slacks.
The debate over whether slacks should be viewed as a resource that positively influences performance or as a sign of inefficiency that negatively affects performance has been ongoing Recent research indicates that different types of slacks have varying impacts on performance Daniel et al (2004) conducted a study that calculated the mean correlation and variance from combined studies to explore the relationship between slack and performance Their findings highlighted the significant role of organizational slacks in enhancing firm performance by addressing both internal and external challenges.
Lin, Liu, and Cheng (2011) explored how organizational slacks influence a firm's internationalization performance They defined slack resources from a firm behavior perspective, emphasizing their flexibility for use, and utilized financial indicators for estimation, following George (2005) The study calculated high-discretion slack using the current assets to current liabilities ratio and low-discretion slack through the equity to debt ratio.
Data and Sample
The study analyzes a dataset of Vietnamese enterprises collected by the General Statistics Office (GSO) over a six-year period from 2007 to 2012 Each year, the GSO conducts a survey to gather data from all existing firms and agencies This dataset includes observations from unlisted firms across diverse industries, including food processing, textiles and garments, stationery, construction materials, high-tech, and utilities such as water and electricity supply.
The enterprise data analyzed for 2011 and 2012 included indicators recorded twice a year, at the beginning (January 1) and the end (December 31), with the study utilizing the end-of-year indicators for estimations Additionally, due to the unavailability of export volume data from 2007 to 2010, it was estimated by dividing the export-tax expenses by a 10% export tax rate.
The study focuses exclusively on Vietnamese manufacturing firms, excluding 100% foreign-invested companies and cooperatives from the testing model To ensure a representative sample, appropriate manufacturing firms were meticulously filtered, retaining only those with the “nganh_kd” code ranging from 10*-33* Additionally, the dataset was refined by removing duplicates based on the unique identifier (madn + macs + nganh_kd + year) and the year.
The outliers are also eliminated to improve the reliability of the coefficients The panel data is initially balanced in term of id and years
However, after removing duplicates and eliminating outliers, the processed data becomes unbalanced in term of year Thus, the final sample includes
59770 observations which belong to 45491 unlisted manufacturing firms over the six-year period from 2007 to 2012
There are many measures of firm performance from the empirical studies such as cost efficiency index (Assaf, Josiassen, Ratchford & Barros,
2012), the composite index of ROA and ROS (Pangarkar, 2008), the composite index of accounting value (ROA) and market value (EPS) (Tsai, 2014)
In this study, performance is evaluated using return on assets (ROA), which is widely recognized as a key indicator in numerous empirical research studies (Riahi-Belkaoui, 1998; Lin, Liu & Cheng, 2011; Lin & Liu, 2012; Hsu, Chen & ).
Cheng, 2013; Tan, 2003) Although it is a single measure, Hsu, Chen & Cheng
In 2013, it was highlighted that Return on Assets (ROA) serves as a key indicator of the effectiveness of internationalization strategies, demonstrating their contribution to economies of scope and scale (Kim, Hwang, & Burgers, 1989).
Lin, Liu, and Cheng (2011) developed a composite indicator for internationalization, incorporating three key metrics: (1) internationalization performance, defined as the ratio of foreign sales to total sales; (2) internationalization structure, represented by the ratio of foreign assets to total assets; and (3) internationalization geographic dispersion, measured by the number of countries in which a firm has subsidiaries Their analysis focused on Taiwanese high-tech firms that outsourced production and engaged in foreign direct investment (FDI), making their composite indicator particularly relevant and effective for this context.
However, the case of Vietnam manufacturing firms is quite different because the firms here almost focus on export activities via commercial agents
Due to the unavailability of data for estimating the internationalization structure and dispersion, this study measures the degree of internationalization of Vietnamese IFs using the single metric of foreign sales to total sales (FS/TS), consistent with previous empirical research (Tsai, 2013; Riahi-Bekaoui, 1998; Chiao, Yang & Yu, 2006; Bobillo et al., 2010).
III.2.3.Organizational slacks – the moderating variables
Lin, Liu, and Cheng (2011) defined high-discretion slack as the ratio of current assets to current liabilities, while low-discretion slack is represented by the equity to debt ratio This study utilizes these proxies due to their availability in the dataset and their ability to reflect idle firm resources, distinct from necessary operational resources These measures are commonly employed to assess high-discretion and low-discretion slacks (Lin & Liu, 2012; Hambrick et al., 1996; Dailey, 1995) Both types of slacks positively influence internationalization performance (Lin, Liu & Cheng, 2011).
Firm size is a widely recognized indicator that is significantly linked to firm performance Consequently, many prior studies incorporate firm size as a control variable in their performance-testing models.
(Contractor, Kundu & Hsu, 2003; Lin, Liu & Cheng, 2011; Hsu, Chen &
Cheng, 2013; Assaf, Josiassen, Ratchford, & Barros, 2012; Ciravegna, Majano,
& Zhan, 2013; Pangarkar, 2008) These studies found a positive relationship between firm size and performance
Larger firms are often perceived to possess greater capabilities and access to a wider range of resources Many previous studies utilize the logarithm of sales as a key metric for firm size, as it effectively indicates the level of a firm's inputs and overall capabilities.
(Tsai, 2013; Lin, Liu, & Cheng, 2011; Pangarkar, 2008; Assaf, Josiassen, Ratchford & Barros, 2012, Hsu, Chen & Cheng, 2013)
Another popular control variable for firm performance is firm age
Coad, Segarra, and Teruel (2010) discovered that a firm's longevity is positively correlated with its capabilities Older firms experience significant enhancements in profitability, productivity, and research and development efforts.
Therefore, firm age is expected to have a positive relationship with firm performance Firm age is calculated as the numbers of years since the firm’s foundation year (Lin, Liu & Cheng, 2011).
According to Tarutė and Gatautis (2014), the use of Information and Communication Technology (ICT) can significantly enhance the competitive advantages of small and medium-sized enterprises (SMEs) and improve their overall performance through both direct and indirect means ICT serves as a versatile tool applicable across various aspects of a business, including communication, marketing, research and development, and management By leveraging ICT effectively, enterprises can pave the way for a brighter future and better performance in the context of globalization Consequently, a positive relationship between ICT usage and firm performance is anticipated.
There is currently no standardized index for measuring ICT usage, leading most empirical studies to rely on Likert scales from custom questionnaires to assess ICT adoption within organizations This study evaluates ICT use among firms using indicators from the enterprises survey, which include (1) Internet connection, (2) websites, (3) online purchases, (4) receiving online orders, and (5) ICT software use Each of these ICT items is assigned a score of 1 point, with a maximum possible score of 5 points if a firm meets all five criteria.
Learning capability serves as a control variable in this study, acknowledging that employee quality, particularly their knowledge and understanding, significantly influences firm performance According to Tsai (2013), employees with higher qualifications, such as master's or PhD degrees, demonstrate a greater ability to adapt to changes and achieve superior performance Therefore, the ratio of master's or PhD employees to the total workforce is utilized to assess learning capacity.
Research and development (R&D) offers a significant source of innovations on from gradual to dramatic change to enhance firm performance
Research and development (R&D) activities are crucial for maintaining a firm's competitiveness by generating new products or enhancing existing ones, ultimately leading to improved consumer satisfaction (O’Sullivan and Dooley, 2008) These activities play a significant role in stimulating demand and boosting revenues for businesses.
Analytical approach
The study utilized a sample from over 300,000 Vietnamese firms annually, filtering out repeated manufacturing firms to create a comprehensive panel data set covering a six-year period from 2007.
Panel data, as defined by Murray (2005), consists of cross-sectional indicators from the same individual or entity—such as a country, region, firm, or consumer—observed over multiple time periods This data can be categorized as balanced, where each entity is observed for the same duration, or unbalanced, where the observation periods vary among entities.
In his econometric guidance document, Greene (2008) highlights several reasons for the popularity of panel data (longitudinal data) in testing models Firstly, panel data enables researchers to observe firm behaviors and trends over time Secondly, it combines time-series and cross-sectional observations, providing more information and variability, which helps eliminate collinearity between variables, increases degrees of freedom, and enhances estimation reliability Thirdly, analyzing repeated cross-sectional firm observations allows for a better understanding of how cross-sectional indicators change annually Lastly, panel data effectively uncovers and measures unobserved impacts that traditional cross-sectional or time-series data cannot capture.
To test the three main hypotheses, the study employed the fixed effect and random effect models, which are the two most popular methods for analyzing panel data Additionally, quadratic and cubic forms of DOI were incorporated to examine its curvilinear impact on performance across three distinct phases, as outlined in the first hypothesis (Green, 2008) The research primarily investigates how high-discretion and low-discretion slack moderate the relationship between internationalization and performance According to Aiken & West (1991), a third variable (Z) serves as a moderating variable when it has significant relationships with both the dependent variable (Y) and the explanatory variable (X), influencing the effect of X on Y As illustrated in figure 8, the impact of X on Y can vary based on the level of Z, either enhancing or diminishing the relationship.
Figure 8: Illustration of moderating variable
Fixed effect model assumes that there are the possible correlations between time-invariant differences across entities and the explanatory variables
The fixed effect model (FEM), as noted by Greene (2008), effectively controls for differences among predictors, allowing for the estimation of net effects on the dependent variable However, a significant limitation of FEM is its inability to measure time-invariant factors, such as gender and race, since it incorporates dummy variables into the intercept.
Another limitation is that there are many variables generated in the model which may lead to lower degree of freedom and higher possibility of multi- collinearity in the model
The random effects model assumes that random variations across entities are uncorrelated with the explanatory variables, allowing it to measure the influence of time-invariant variables However, it does not adequately address the bias from omitted variables Given the presence of omitted variables in this analysis, the fixed effects model is the preferred choice to effectively control for this bias.
The Hausman test is utilized to determine the suitability of either the fixed effect model (FEM) or the random effect model (REM) by testing the null hypothesis that their estimations are equivalent A p-value below 0.05 indicates the rejection of the null hypothesis, suggesting the use of FEM Additionally, the ordinary least squares (OLS) model undergoes tests for omitted variables, multicollinearity, and heteroskedasticity to address potential biases in estimations Any identified issues are promptly corrected to enhance the reliability of the regression coefficients (Green, 2008).
As figure 6, the model depicts three main hypotheses that the study aimed to investigate
The first hypothesis (H1) is internationalization has an S-shaped relationship with firm performance.
The second hypothesis (H2) is that high discretion slacks positively affect the relationship between internationalization and performance
The third hypothesis (H3) is that low discretion slacks positively affect the relationship between internationalization and performance.
Besides, the control variables of firm size, firm age, ICT use, learning capability, R&D intensity and ownership types are added to eliminate the problems of omitted variables.
The performance model can be expressed as a function of various factors, including DOI, firm size, firm age, ICT use, learning capabilities, R&D intensity, ownership structure, and different levels of discretionary slack Specifically, the equation incorporates both high and low discretionary slack in relation to internationalization, along with dummy variables for corporation, family, and government ownership The model is represented as: \$$\text{Performance} = \beta_0 + \beta_1 \text{DOI} + \beta_2 \text{DOI}^2 + \beta_3 \text{DOI}^3 + \beta_4 \text{firm\_size} + \beta_5 \text{firm\_age} + \beta_6 \text{ICTuse} + \beta_7 \text{learning\_capabilities} + \beta_8 \text{R\&D\_intensity} + \beta_9 \text{ownership} + \beta_{10} \text{high\_discretion\_slack} + \beta_{11} \text{low\_discretion\_slack} + \beta_{12} D_{\text{corporation}} + \beta_{13} D_{\text{family}} + \beta_{14} D_{\text{government}} + \beta_{15} \text{high\_discretion\_slack} \times \text{Internationalization} + \beta_{16} \text{low\_discretion\_slack} \times \text{internationalization} + \epsilon\$$
Firm size (+) High-discretion slack (+) Low-discretion slack (+) Firm age (+)
Learning capacity (+) R&D intensity (+) ICT use (+) Ownership types
FINDINGS
Due to the significant number of missing values in the data for ICT use, firm age, learning capacity, and R&D intensity, which is only available for two years within a six-year timeframe, STATA indicated insufficient observations when these control variables were included in the testing model Consequently, these explanatory variables were excluded from the model despite the Ramsey RESET test revealing potential omitted variables at a 1% significance level As a result, the testing model comprises the dependent variable, independent variable, moderating variables, and the remaining control variables, as outlined in Table 2.
Firm performance can be measured by the return on assets (ROA) in a specific year Internationalization is assessed through the ratio of foreign sales to total sales (FS/TS) High-discretion slack is determined by the ratio of current assets to current liabilities The interaction between internationalization and high-discretion slack is represented by the product of DOI and high-discretion slack.
Low-discretion slack The equity-to-debt ratio (E/D) DOI _ Low-discretion slack DOI multiplies with Low_discretion slack
Firm size The logarithm of sales in a given year
Joint Stock ownership Dummy = 0 or 1 if (Ownership type’s code = 1|2|3|4|5|13 as defined in the enterprise survey)
Private ownership Dummy = 0 or 1 if (Ownership type’s code = 7|8|9|14 as defined in the enterprise survey)
Joint Stock Ownership Dummy = 0 or 1 if (Ownership type’s code = 10|11 as defined in the enterprise survey)
Table 3 presents descriptive statistics, including mean, standard deviation, and correlations among variables, highlighting significant variability among firms' scales and financial indicators The average return on assets (ROA) for 45,491 firms is modest at 0.2%, with a high standard deviation of 10.3%, indicating diverse performance across various manufacturing industries The foreign sales to total sales ratio (DOI) is relatively low at 5.4%, as exports account for only about one-twentieth of total sales, reflecting that many firms operate locally with no foreign sales, while others generate substantial foreign revenue The mean firm size, calculated as the logarithm of total revenue, is 9.004, the highest among the variables Additionally, the average current assets to current liabilities ratio and the average equity-to-debt ratio are favorable for Vietnamese manufacturing firms, standing at 1.47 and 1.27, respectively, suggesting that equity and current assets effectively offset debt and liabilities The moderating variables DOI*high_slack and DOI*low_slack average 2.8% and 3.5%, respectively.
Table 3 reveals significant correlations among all variables, indicating that the degree of internationalization at three levels (DOI, DOI 2, and DOI 3) negatively correlates with firm performance, with coefficients of -0.0121, -0.0174, and -0.0192, respectively In contrast, high-discretion slack shows a negative correlation with firm performance at -3.8%, while low-discretion slack positively correlates with performance at 11.7% The strongest positive correlations are observed between DOI and high-discretion slack, as well as DOI and low-discretion slack, due to their moderating effects Additionally, the table confirms the absence of multicollinearity among predictors, except for the expected collinearity among DOI, DOI 2, and DOI 3, as all correlation coefficients remain below 0.8.
Table 3: Descriptive statistic and correlations
Variable Mean Std Dev ROA DOI DOI 2 DOI 3 firm_size high_slack low_slack
To examine the impact of international integration at various stages, Bobillo et al (2010) incorporated quadratic and cubic forms of the Degree of Internationalization (DOI) into their model This approach aimed to determine the presence of an S-shaped relationship between DOI and performance Despite the findings indicating significant multicollinearity, with a mean Variance Inflation Factor (VIF) greater than 5, Green's analysis provides valuable insights.
In 2008, it was proposed that multicollinearity can be disregarded when dealing with quadratic and cubic models Additionally, prior to incorporating DOI 2 and DOI 3, the Variance Inflation Factor (VIF) test indicated no significant multicollinearity, with a mean VIF of 2.56 The study also addressed the identified heteroskedasticity by employing robust methods.
The study performed a fixed effect analysis on four models with similar variables to facilitate comparisons, as shown in Table 4 The regression results indicate that the coefficients across the models are consistently aligned, with only minor variations Notably, the R-squared value increases with the addition of more variables The first model, which includes DOI, DOI², DOI³, and firm size, was previously examined by Riahi-Belkaoui in 1998 The second model, developed by Bobillo et al in 2010, incorporated the same variables along with ownership type The third model, proposed by Lin, Liu, and Cheng in 2011, focused on the moderating effect of slacks on the internationalization-performance relationship, while neglecting the non-linear relationship between DOI and performance by including slack variables and their interaction factors.
The fourth model is the most comprehensive, demonstrating an S-shaped relationship between internationalization and performance, with coefficients of β1=-0.2711 (p F = 0.0000 reject Ho: the model does have missing variables at the 1% level.
DOI_lowslack 1.65 0.60763 DOI_highslack 1.62 0.61846 high_slack 1.23 0.81494 low_slack 1.15 0.87088
White's test for Ho: homoskedasticity against Ha : unrestricted heteroskedasticity chi2(52) = 2670.26 Prob > chi2 = 0.0000 Cameron & Trivedi's decomposition of IM-testSource
Reject Ho, correct by using “robust”
Fixed-effects (within) regression Number of obs = 59770
R-sq: within = 0.0473 Obs per group: min = 1 between = 0.0408 avg = 1.3 overall = 0.0496 max = 6
ROA Coef Std Err t P>t [95% Conf Interval]
DOI 3 -0.3389 0.1224 -2.7700 0.0060 -0.5788 -0.0990 firm_size 0.0348 0.0015 23.4200 0.0000 0.0319 0.0377 high_slack 0.0011 0.0005 2.3000 0.0210 0.0002 0.0020 low_slack 0.0073 0.0007 10.3300 0.0000 0.0059 0.0087
Rho 0.6439 (fraction of variance due to u_i)
Random-effects GLS regression Number of obs = 59770
Group variable: id Number of groups = 45491
R-sq: within = 0.0230 Obs per group: min = 1 between = 0.0660 avg = 1.3 overall = 0.0715 max = 6
Wald chi2(8) = 3806.19 corr(u_i, X) = 0 (assumed) Prob > chi2 = 0.0000
ROA Coef Std Err z P>z [95% Conf.Interval]
DOI 3 -0.3127 0.0766 -4.0800 0.0000 -0.4627 -0.1626 high_slack 0.0027 0.0002 11.5100 0.0000 0.0023 0.0032 low_slack 0.0084 0.0003 30.2000 0.0000 0.0079 0.0090
_cons -0.1224 0.0024 -51.7900 0.0000 -0.1270 -0.1177 sigma_u 0.0586 sigma_e 0.0815 rho 34109104 (fraction of variance due to u_i)
(b) (B) (b-B) sqrt(diag(V_b-V_B)) fixed random Difference S.E.
DOI3 -0.3388983 -0.31268 -0.02622 0.0954745 firm_size 0.0348118 0.012637 0.022175 0.0014664 high_slack 0.0010646 0.002728 -0.00166 0.0003975 low_slack 0.0072813 0.008447 -0.00117 0.0006468