Understanding the determinants of international market entry is critical for the growth and survival of small and medium-sized enterprises (SMEs) in emerging economies. This research examines the key internal and external factors driving the export entry decisions of Vietnamese SMEs.
To evaluate these dynamics, this research analyzes a three-wave longitudinal panel dataset comprising 7,502 observations from 2,500 Vietnamese SMEs across survey years 2011, 2013 and 2015, complemented by an independent post-COVID cross-sectional dataset from 2023 (N = 599) as a robustness check. The study employs advanced econometric techniques, specifically linear probability models (LPM), logit and probit models incorporating random effects models, to rigorously account for unobserved firm heterogeneity.
Government support and internationally recognized quality certifications are significantly and positively associated with SMEs’ entry into foreign markets. Furthermore, global integration – achieved through importing materials, securing foreign ownership and serving as foreign subcontractors – exhibits a strong correlation with export participation. Internally, export decisions are strongly predicted by having a license to operate overseas and a higher proportion of professional and female employees.
These results imply that Vietnamese SMEs can strategically enhance their global competitiveness by diversifying their workforce, pursuing international certifications and proactively embedding themselves within global supply chains.
1. Introduction
In Vietnam, small and medium-sized enterprises (SMEs) are central to the nation’s economic growth and are regarded as the pillar of Vietnam’s economic progress. As a rapidly emerging economy driven by strong export-led growth, SMEs play a crucial role in economic development, contributing nearly 40% of GDP and 50% of employment (GSO, 2023). Despite these pivotal contributions, Vietnamese SMEs face significant challenges in entering international trade, including limited access to finance, regulatory constraints and competition from larger firms. In reality, the benefits of Vietnam’s growing international trade are disproportionately accrued by large domestic firms and the foreign sector. For instance, in 2023, the foreign-invested sector recorded a substantial trade surplus of USD 49.74 billion, while the domestic economy recorded a significant deficit of USD 21.74 billion (GSO, 2023).
This study identifies crucial factors, such as government support, a higher percentage of female employees and international quality certifications, that are strongly linked to a company’s decision to enter a foreign market. Additionally, international engagement, such as holding an overseas operating license, foreign ownership, subcontracting for foreign firms and importing foreign materials, plays a critical role. These results imply that Vietnamese SMEs can strategically enhance their global competitiveness by diversifying their workforce, pursuing international certifications and proactively embedding themselves within global supply chains.
This study makes its theoretical and empirical contributions in four key ways: First, it focuses on the initial decision to export by including LPM, probit and logit models with random effects (RE), setting it apart from prior research on post-entry expansion. Second, it extends global value chain (GVC) research by examining how foreign ownership, subcontracting, and imported raw materials facilitate market entry. Third, it integrates institutional theory, GVC perspective and resource-based view (RBV) into a unified empirical framework. Lastly, using a three-wave longitudinal panel dataset (2011–2015, N = 7,502) and validating findings with an independent post-COVID 2023 dataset (N = 599), it accounts for unobserved firm heterogeneity through RE.
2. Literature review
The literature concerning SME internationalization is extensive, yet often fragmented. This review systematically organizes the key determinants of export entry by Vietnamese SMEs within three core theoretical paradigms: the institutional theory, the GVC perspective and the RBV.
2.1 The institutional theory
From 2000 to the present, empirical research has shown that companies involved in exporting activities are more effective than those concentrating solely on the domestic market. According to Indris and Primiana (2015), external factors such as government policies and subsidies are intended to help businesses grow working capital, maintain and expand production and business activities, and attract more workers. Charoenrat and Harvie (2012) identify government intervention as a primary determinant of export propensity. By providing a combination of financial subsidies (credit and tax incentives) and operational support (technical training and tariff reductions), the state effectively mitigates the sunk costs of market entry, creating a highly favorable environment for SMEs’ expansion into global markets.
Bangwayo-Skeete and Moore (2015) indicate that adopting internationally recognized quality certifications enables firms in developing nations to enter foreign markets. Several studies demonstrate the macroeconomic benefits of ISO certification, particularly in its capacity to bolster trade volumes for developing nations (Clougherty and Grajek, 2008; Prakash and Potoski, 2006). Beyond mere compliance, the acquisition of foreign licenses represents a strategic alignment with host-country institutions, thereby reducing asymmetric trade barriers and streamlining the trajectory for international growth (Cao and Prakash, 2010). The adoption of such certifications significantly increases a firm’s likelihood of entering foreign markets. Furthermore, Calof and Beamish (1995) affirm that greater access to export infrastructure directly facilitates a firm’s decision to enter the global market. Senik et al. (2014) establish that firm resources encompass physical, organizational and relational assets, as well as access to export infrastructure, which are critical for engaging in international activities. Ho and Nguyen (2024) find that access to land, the transparency of local authorities, informal charges and local labor policies influence the internationalization of Vietnamese manufacturing SMEs.
2.2 The global value chains
The GVC framework analyzes how firms, particularly SMEs, gain a competitive advantage and access foreign markets by integrating into international production and supply networks, often through strategic relationships with multinational corporations (MNCs). Several empirical studies establish a positive correlation between foreign ownership and firms’ export propensity (Greenaway et al., 2007, 2014; Jongwanich and Kohpaiboon, 2008; Danh et al., 2014; Zhu et al., 2019; Nguyen et al., 2023). In detail, Greenaway et al. (2007) found that foreign ownership had a positive effect on export firm involvement for 9,292 UK manufacturing companies between 1993 and 2003. In addition, Jongwanich and Kohpaiboon (2008) found that foreign ownership has a significantly positive impact on firm export participation among Thai manufacturing enterprises.
The research also showed that foreign-owned firms can cover sunk costs and enter foreign markets more easily than domestically owned firms. Zhu et al. (2019) demonstrate that international construction enterprises must strategically subcontract portions of contracts to local firms to secure a competitive edge in the global market. Danh et al. (2014) establish a robust, positive association between a firm’s export propensity and its strategic reliance on imported raw materials, reinforcing the significance of backward linkages in international trade. Nguyen et al. (2023) examine the determinants of GVC integration within the Vietnamese industrial landscape. Their empirical evidence demonstrates that technological capability exerts the most profound positive impact on GVC participation, followed by foreign direct investment (FDI) and firm scale. Conversely, firm age fails to achieve statistical significance, suggesting that organizational experience is not a primary driver of internationalization in this context.
2.3 The resource-based view
The RBV asserts that competitive advantages are derived from valuable, rare, inimitable and non-substitutable internal resources, which drive superior performance in international markets. From this perspective, several scholars observe that professional workers significantly increase a firm’s likelihood of entering the export market (Dueñas-Caparas, 2006; Hiep and Ohta, 2007; Charoenrat and Harvie, 2012; Amornkitvikai et al., 2012). In detail, they found that the more skilled the factory staff is, the more successful the factory is in the export market. Dueñas-Caparas (2006) found that while high-skilled labor positively affects export performance in the Philippine food processing industry, this effect was not statistically significant in the electronics and garment sectors. Hiep and Ohta (2007) also found that innovation positively influences the probability of exporting. Furthermore, research by Amornkitvikai et al. (2012) underscores that female labor is a pivotal determinant of the export strategies of Bangladesh’s apparel industry. Danh et al. (2014) confirm that leaders’ educational attainment in exporting firms is significantly higher than the average for Vietnamese SMEs.
Recent research has highlighted the other factors that determine the export participation of private manufacturing SMEs in Vietnam (Deng and Zhang, 2018; Tuan, 2020; Doan et al., 2020; Ho and Nguyen, 2024). For example, Deng and Zhang (2018) demonstrate that while institutional quality promotes overseas sales growth, it is negatively associated with SMEs’ initial propensity to expand abroad. Doan et al. (2020) examine the impact of cash-in-advance (CIA) payment terms on the export propensity of Vietnamese firms navigating financial and institutional frictions. The authors demonstrate that the CIA acts as a critical liquidity-enhancing mechanism for institutionally constrained firms, particularly among SMEs and those facing severe credit rationing.
Despite increasing scholarly interest, research specifically addressing the internationalization of Vietnamese firms remains limited. Prior studies often lacked robust theoretical frameworks, relying instead on descriptive analyses, and frequently utilized outdated cross-sectional datasets, thereby failing to capture current trends or address complex causal relationships. Some papers do not apply any quantitative analysis model in the research. Few studies examine how Vietnamese SMEs align internationalization with environmental and social responsibility trends; however, the role of women-led SMEs in internationalization remains underexplored. The existing literature on Vietnamese SME internationalization relies on outdated datasets, thereby limiting its ability to capture recent trends (Thai, 2008; Danh et al., 2014). Other studies neglect the empirical drivers governing the initial pivot toward international markets (Thai and Chong, 2013). A growing body of literature, exemplified by the work of Danh et al. (2014), has increasingly focused on the empirical determinants governing the internationalization decisions of Vietnamese SMEs. But this study only focuses on SMEs in Vietnam’s two major cities, Ho Chi Minh City and Hanoi. In addition, the cross-sectional data used in this study are from 2009 and do not reflect the current reality of Vietnamese SMEs’ participation in internationalization. Similarly, Ha and Nguyen (2021) investigate determinants of green innovation within the manufacturing sector; there remains a distinct empirical void regarding the specific factors that catalyze the decision to participate in international markets.
This research complements existing literature by empirically validating established determinants using a longitudinal dataset that reflects recent economic shifts in Vietnam, thereby enhancing the academic landscape with the following contributions:
First, the study extends previous work by moving beyond isolated correlations to synthesize three major theoretical frameworks: the institutional theory, the GVC perspective and the RBV. This research utilizes a panel dataset spanning from 2011 to 2015. By including 2023 data, the study confirms that some determinants, such as government support and internationally recognized quality certification, are significantly and positively associated with SMEs’ entry into foreign markets.
Second, the empirical findings provide a nuanced characterization of the GVC positioning of Vietnamese SMEs. By identifying subcontracting for foreign firms and the importation of foreign materials as significant export drivers, this study reveals that these enterprises primarily occupy the mid-stream manufacturing and assembly stages of the GVC. This position underscores the critical role of SMEs as vital intermediaries in the global supply network.
Third, resource-based internal assets such as the share of females in total workers remain robust drivers of export entry despite recent global disruptions like the COVID-19 pandemic.
Fourth, the research extends existing qualitative or fragmented studies by applying a triangulated econometric framework (LPM, logit, probit and RE). This methodological rigor allows for a more precise comparison of the relative impact of different factors, such as the notably high marginal effect of gender-specific labor dynamics compared to general institutional support.
Finally, the study specifically addresses a gap in recent literature, which often focuses on the growth of existing exporters (intensive margin) by re-centering the analysis on the initial decision to enter the market (extensive margin). This provides policymakers with updated evidence on how to trigger the first-time internationalization of SMEs in the current economic climate.
3. Methodology
3.1 Empirical model
Our analysis rigorously evaluates key factors driving export success, including government support, the share of female labor in export firms, the proportion of professional employees, internationally recognized certifications, licenses to operate abroad, foreign ownership structures, subcontracting status, workforce education, material imports and access to export infrastructure.
Following a literature review (Hiep and Ohta, 2007; Jongwanich and Kohpaiboon, 2008; Senik et al., 2014; Danh et al., 2014; Quang and Quyen, 2024). The equations for the export entry decisions of all firms are identified as follows:
In this study, the dependent variable is defined as the firm’s decision to start exporting, representing the strategic transition of an enterprise from domestic operations to global market participation. Following the definition established by Hiep and Ohta (2007), a firm is classified as an exporter if its export sales constitute at least 10% of its total annual revenue. The 10% rate used in the previous studies, even by the World Bank, is similarly used to classify non-exporters and exporters. We also describe the specific variables and sign expectations in Table 1.
Variable description
| Theoretical dimension | Variables | Description | Expected sign |
|---|---|---|---|
| Dependent variable: export | = 1 if the firm is an exporter, otherwise 0 | ||
| Institutional theory | Supfromgov | = 1 if the firm receives financial support from government, otherwise 0 | + |
| Interregcer | = 1 if the firm has an internationally recognized quality certification, otherwise 0 | + | |
| Licopsea | = 1 if the firm has a license to operate abroad, otherwise 0 | + | |
| Easytoexportinfr | = 1 if export infrastructure is favorable; 0 otherwise | + | |
| Global value chain | Forownership | = 1 if the firm has ownership from a foreign partner, otherwise 0 | + |
| Subcont | = 1 if the firm is a subcontractor, otherwise 0 | + | |
| Importmaterial | = 1 if the firm imports raw materials/inputs directly from abroad, otherwise 0 | + | |
| Resource-based view | Female_share | The share of females in total workers (%) | +, − |
| Profshare | Professional share of workers (%) | + | |
| Education | The number of leaders has a university degree or above | + | |
| Training | = 1 if the firm provides or organizes training programs for its employees and 0 otherwise | + | |
| Theoretical dimension | Variables | Description | Expected sign |
|---|---|---|---|
| Dependent variable: export | = 1 if the firm is an exporter, otherwise 0 | ||
| Institutional theory | Supfromgov | = 1 if the firm receives financial support from government, otherwise 0 | + |
| Interregcer | = 1 if the firm has an internationally recognized quality certification, otherwise 0 | + | |
| Licopsea | = 1 if the firm has a license to operate abroad, otherwise 0 | + | |
| Easytoexportinfr | = 1 if export infrastructure is favorable; 0 otherwise | + | |
| Global value chain | Forownership | = 1 if the firm has ownership from a foreign partner, otherwise 0 | + |
| Subcont | = 1 if the firm is a subcontractor, otherwise 0 | + | |
| Importmaterial | = 1 if the firm imports raw materials/inputs directly from abroad, otherwise 0 | + | |
| Resource-based view | Female_share | The share of females in total workers (%) | +, − |
| Profshare | Professional share of workers (%) | + | |
| Education | The number of leaders has a university degree or above | + | |
| Training | = 1 if the firm provides or organizes training programs for its employees and 0 otherwise | + | |
3.2 Data
The core empirical analysis utilizes a three-wave longitudinal panel dataset from the United Nations University World Institute for Development Economics Research (UNU-WIDER) covering 2011, 2013 and 2015. This panel comprises 7,502 total observations across 2,500 unique manufacturing SMEs. To evaluate the post-COVID enduring validity of these determinants, we utilize an independent cross-sectional dataset from the 2023 World Bank Enterprise Survey (N = 599) as a post-hoc robustness check.
3.3 Econometric strategy
First, three models, including LPM, logit and probit, are used, combined with a cross-sectional dataset of 7,502 observations from 2,500 firms, spanning three survey waves (2011, 2013 and 2015) from UNU-WIDER, to assess the impact of factors influencing the export participation decisions of Vietnamese SMEs. LPM serves as a baseline benchmark, while probit and logit models are employed to properly account for the non-linear, binary nature of the dependent variable.
Second, to address the limitations of prior cross-sectional studies, we combined panel data from 2011, 2013 and 2015 using fixed effects (FE) and RE techniques. The choice of RE was supported by a Hausman test (p-value = 0.85), which did not reject the null hypothesis. This approach also allows for estimating important time-invariant firm attributes.
Finally, to ensure the data’s up-to-date nature after the COVID-19 pandemic and to verify the robustness of previous results, the study re-applied 2023 data (N = 599) from the World Bank, combining it with advanced econometric techniques, specifically the LPM, probit and logit models, to check robustness.
4. Results and discussion
4.1 Descriptive statistics
Table 2 illustrates the descriptive statistics of the variables, such as observations, the mean, max, min and standard deviation, in which the mean value ranges between 0 and 0.5. The majority of variables used in this research are dummy variables.
Descriptive statistics
| Variables | N | Minimum | Maximum | Mean | Std. deviation |
|---|---|---|---|---|---|
| Dependent variable: export | 7,502 | 0 | 1 | 0.064 | 0.244 |
| Independent variables: | |||||
| Supfromgov | 7,502 | 0 | 1 | 0.103 | 0.303 |
| Female share | 7,502 | 0 | 1 | 0.380 | 0.262 |
| Profshare | 7,502 | 0 | 0.77 | 0.033 | 0.070 |
| Interregcer | 7,502 | 0 | 1 | 0.060 | 0.250 |
| Licopsea | 7,502 | 0 | 1 | 0.020 | 0.139 |
| Forownership | 7,502 | 0 | 1 | 0.092 | 0.289 |
| Subcont | 7,502 | 0 | 1 | 0.100 | 0.300 |
| Importmaterial | 7,502 | 0 | 1 | 0.032 | 0.177 |
| Education | 7,502 | 0 | 68 | 0.170 | 2.20 |
| Training | 7,502 | 0 | 1 | 0.087 | 0.281 |
| Easytoinfrastr | 7,502 | 0 | 1 | 0.430 | 0.495 |
| Variables | N | Minimum | Maximum | Mean | Std. deviation |
|---|---|---|---|---|---|
| Dependent variable: export | 7,502 | 0 | 1 | 0.064 | 0.244 |
| Independent variables: | |||||
| Supfromgov | 7,502 | 0 | 1 | 0.103 | 0.303 |
| Female share | 7,502 | 0 | 1 | 0.380 | 0.262 |
| Profshare | 7,502 | 0 | 0.77 | 0.033 | 0.070 |
| Interregcer | 7,502 | 0 | 1 | 0.060 | 0.250 |
| Licopsea | 7,502 | 0 | 1 | 0.020 | 0.139 |
| Forownership | 7,502 | 0 | 1 | 0.092 | 0.289 |
| Subcont | 7,502 | 0 | 1 | 0.100 | 0.300 |
| Importmaterial | 7,502 | 0 | 1 | 0.032 | 0.177 |
| Education | 7,502 | 0 | 68 | 0.170 | 2.20 |
| Training | 7,502 | 0 | 1 | 0.087 | 0.281 |
| Easytoinfrastr | 7,502 | 0 | 1 | 0.430 | 0.495 |
Table 3 presents the correlation matrix for the variables under study. The absence of significant multicollinearity among the explanatory variables confirms the structural integrity of our regression model, ensuring that the resulting estimates are both unbiased and statistically efficient.
Correlation between independent variables
| Variables | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | 11 |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 1. Supfromgov | 1 | ||||||||||
| 2. Female share | 0.016 | 1 | |||||||||
| 3. Profshare | 0.060 | 0.007 | 1 | ||||||||
| 4. Interregcer | 0.095 | 0.050 | 0.251 | 1 | |||||||
| 5. Licopsea | 0.024 | 0.004 | 0.136 | 0.163 | 1 | ||||||
| 6. Forownership | 0.058 | 0.003 | 0.249 | 0.221 | 0.137 | 1 | |||||
| 7. Subcont | 0.044 | −0.064 | 0.035 | 0.048 | 0.011 | 0.031 | 1 | ||||
| 8. Importmaterial | 0.039 | 0.031 | 0.222 | 0.337 | 0.185 | 0.166 | 0.021 | 1 | |||
| 9. Education | 0.055 | −0.009 | 0.072 | 0.122 | 0.053 | 0.050 | 0.045 | 0.018 | 1 | ||
| 10. Training | 0.054 | 0.054 | 0.058 | 0.099 | 0.048 | 0.070 | 0.025 | 0.009 | 0.095 | 1 | |
| 11. Easytoinfrastr | 0.023 | −0.063 | 0.116 | 0.070 | 0.009 | 0.107 | 0.015 | 0.027 | 0.025 | −0.003 | 1 |
| Variables | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | 11 |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 1. Supfromgov | 1 | ||||||||||
| 2. Female share | 0.016 | 1 | |||||||||
| 3. Profshare | 0.060 | 0.007 | 1 | ||||||||
| 4. Interregcer | 0.095 | 0.050 | 0.251 | 1 | |||||||
| 5. Licopsea | 0.024 | 0.004 | 0.136 | 0.163 | 1 | ||||||
| 6. Forownership | 0.058 | 0.003 | 0.249 | 0.221 | 0.137 | 1 | |||||
| 7. Subcont | 0.044 | −0.064 | 0.035 | 0.048 | 0.011 | 0.031 | 1 | ||||
| 8. Importmaterial | 0.039 | 0.031 | 0.222 | 0.337 | 0.185 | 0.166 | 0.021 | 1 | |||
| 9. Education | 0.055 | −0.009 | 0.072 | 0.122 | 0.053 | 0.050 | 0.045 | 0.018 | 1 | ||
| 10. Training | 0.054 | 0.054 | 0.058 | 0.099 | 0.048 | 0.070 | 0.025 | 0.009 | 0.095 | 1 | |
| 11. Easytoinfrastr | 0.023 | −0.063 | 0.116 | 0.070 | 0.009 | 0.107 | 0.015 | 0.027 | 0.025 | −0.003 | 1 |
4.2 The analysis results from cross-sectional data for the period 2011–2015
The literature shows that the LPM presents critical limitations: it can yield predicted probabilities outside the [0,1] range, imposes constant marginal effects and inherently suffers from heteroscedasticity due to non-constant variance. Consequently, this research employs probit and logistic regression models to rigorously estimate marginal effects and identify key determinants influencing Vietnamese firms’ participation in international markets.
Based on the analysis, results are presented in Table 4. The empirical analysis yields several key insights. Our analysis shows that government support (Supfromgov) is a key driver of internationalization, with strong statistical significance in both logit and probit models from 2013–2015. These results provide compelling empirical validation that State-led financial interventions are significantly and positively associated with export participation, serving as a strong predictor of an SME’s transition into international markets, effectively lowering entry barriers and substantially augmenting the export propensity of Vietnamese SMEs in strict accordance with established trade theories. During the 2011–2015 period, the Vietnamese government implemented various policies to support and encourage SMEs, especially in the export sector. Acting as an exporter was likely seen as a strategic move that helped these SMEs access support packages related to finance, market information and training from both the government and their larger partner companies. Government financial support is a significant predictor that reduces entry barriers. This directly complements the institutional quality arguments made by Ho and Nguyen (2024).
Analysis results by cross-sectional data for the period 2011–2015
| Variables | 2011 | 2013 | 2015 | ||||||
|---|---|---|---|---|---|---|---|---|---|
| LPM | Logit model | Probit model | LPM | Logit model | Probit model | LPM | Logit model | Probit model | |
| Supfromgov | 0.008 | 0.050 | 0.031 | 0.066*** | 0.976*** | 0.500*** | 0.062*** | 0.806*** | 0.417*** |
| Female_share | 0.098*** | 2.063*** | 0.988*** | 0.089*** | 2.19*** | 1.013*** | 0.103*** | 2.14*** | 0.981*** |
| Profshare | 0.034 | 1.383 | 0.935** | −0.015 | 1.029 | 0.722 | 0.114 | 2.291** | 1.249*** |
| Interregcer | 0.287*** | 2.209*** | 1.195*** | 0.250*** | 2.169*** | 1.130*** | 0.090*** | 0.545*** | 0.335** |
| Licopsea | −0.020 | −0.554 | −0.394 | 0.254*** | 1.532*** | 0.838*** | 0.259*** | 1.626*** | 0.878*** |
| Forownership | 0.059*** | 0.766*** | 0.382*** | 0.016 | 0.363 | 0.179 | 0.104*** | 1.195*** | 0.635*** |
| Subcont | 0.027* | 0.507** | 0.235* | 0.039** | 0.641** | 0.344** | 0.038** | 0.572** | 0.285** |
| Importmaterial | 0.215*** | 1.430*** | 0.780*** | 0.178*** | 1.264*** | 0.697*** | 0.173*** | 1.045*** | 0.573*** |
| Education | 0.001*** | 0.023* | 0.013* | 0.001** | 0.007 | 0.004 | 0.000 | −0.000 | 0.000 |
| Training | −0.019 | −0.391 | −0.230** | −0.001 | −0.077 | −0.007 | 0.106*** | 0.106*** | 0.524*** |
| Easytoinfrastr | −0.001 | 0.043 | −0.003 | −0.015** | −0.396** | −0.205** | 0.013 | 0.316* | 0.154* |
| Constant | 0.005 | −4.270*** | −2.265*** | −0.009 | −4.555*** | −2.40*** | −0.021** | −4.549** | −2.41*** |
| R2/Pseudo R2 | 0.183 | 0.221 | 0.223 | 0.225 | 0.275 | 0.278 | 0.165 | 0.206 | 0.211 |
| Observations | 2,507 | 2,507 | 2,507 | 2,532 | 2,532 | 2,532 | 2,542 | 2,542 | 2,542 |
| Variables | 2011 | 2013 | 2015 | ||||||
|---|---|---|---|---|---|---|---|---|---|
| LPM | Logit model | Probit model | LPM | Logit model | Probit model | LPM | Logit model | Probit model | |
| Supfromgov | 0.008 | 0.050 | 0.031 | 0.066*** | 0.976*** | 0.500*** | 0.062*** | 0.806*** | 0.417*** |
| Female_share | 0.098*** | 2.063*** | 0.988*** | 0.089*** | 2.19*** | 1.013*** | 0.103*** | 2.14*** | 0.981*** |
| Profshare | 0.034 | 1.383 | 0.935** | −0.015 | 1.029 | 0.722 | 0.114 | 2.291** | 1.249*** |
| Interregcer | 0.287*** | 2.209*** | 1.195*** | 0.250*** | 2.169*** | 1.130*** | 0.090*** | 0.545*** | 0.335** |
| Licopsea | −0.020 | −0.554 | −0.394 | 0.254*** | 1.532*** | 0.838*** | 0.259*** | 1.626*** | 0.878*** |
| Forownership | 0.059*** | 0.766*** | 0.382*** | 0.016 | 0.363 | 0.179 | 0.104*** | 1.195*** | 0.635*** |
| Subcont | 0.027* | 0.507** | 0.235* | 0.039** | 0.641** | 0.344** | 0.038** | 0.572** | 0.285** |
| Importmaterial | 0.215*** | 1.430*** | 0.780*** | 0.178*** | 1.264*** | 0.697*** | 0.173*** | 1.045*** | 0.573*** |
| Education | 0.001*** | 0.023* | 0.013* | 0.001** | 0.007 | 0.004 | 0.000 | −0.000 | 0.000 |
| Training | −0.019 | −0.391 | −0.230** | −0.001 | −0.077 | −0.007 | 0.106*** | 0.106*** | 0.524*** |
| Easytoinfrastr | −0.001 | 0.043 | −0.003 | −0.015** | −0.396** | −0.205** | 0.013 | 0.316* | 0.154* |
| Constant | 0.005 | −4.270*** | −2.265*** | −0.009 | −4.555*** | −2.40*** | −0.021** | −4.549** | −2.41*** |
| R2/Pseudo R2 | 0.183 | 0.221 | 0.223 | 0.225 | 0.275 | 0.278 | 0.165 | 0.206 | 0.211 |
| Observations | 2,507 | 2,507 | 2,507 | 2,532 | 2,532 | 2,532 | 2,542 | 2,542 | 2,542 |
Note(s): *, ** and *** indicate that the coefficients are statistically significant at the 10%, 5% and 1% level
Second, a higher share of female production workers significantly increases the likelihood of SME internationalization, as evidenced by the robust positive coefficient on Female_share. This finding reflects Vietnam’s export architecture, where labor-intensive, female-dominated sectors, particularly textiles and footwear, serve as the primary drivers of global market entry. It also extends the GVC analysis by Nguyen et al. (2023), which primarily emphasizes macro-level industry factors such as assembly and production capacity, by identifying the proportion of female labor as a critical firm-level determinant of export propensity. It suggests that in the Vietnamese “processing economy”, gender-specific labor traits (precision and cost-efficiency) are core competitive advantages, a detail often overlooked in broader studies.
Thirdly, international quality certification (Interreges) emerges as a critical determinant of market entry. Possession of ISO certification serves as a potent institutional signal, effectively mitigating information asymmetries and lowering the entry barriers for Vietnamese SMEs compared to their non-certified counterparts. This extends existing studies (Prakash and Potoski, 2006) by highlighting the importance of ISO 14001 as a signal for international trade. Furthermore, it emphasizes that as a transition economy matures, formal institutional signals become more important than informal networks or internal training programs.
Fourthly, the consideration involves foreign subcontracting; the increased statistical significance of the subcontractor variable from 2011 to 2015 reflects two key dynamics: To meet the stringent demands of larger partner companies, Vietnamese SMEs acting as subcontractors were compelled to upgrade their technology and production processes, thereby enhancing their capacity to export either directly or indirectly. Furthermore, the varying level of significance across different years can be attributed to model dynamics; as other factors, such as foreign ownership or international certification, became less dominant, the unique role of a subcontractor in the export process became more apparent. This suggests that the influence of different variables on exporting can shift based on the prevailing economic context. This extends existing studies (Thai and Chong, 2013) by providing a roadmap of how Vietnamese SMEs actually “learn to export”, not through formal education or training (which it found insignificant in later analyses) but through operational integration with foreign partners.
Fifthly, the analysis of the material import variable for Vietnamese SMEs reveals a growing positive correlation with exporting, particularly from 2011 to 2015. The growing positive association between importing materials and exporting among Vietnamese SMEs is a key indicator of the country’s deepening integration into global supply chains. This shift reflects Vietnam’s evolving role from a primarily agricultural economy to a “processing economy”. As Vietnam attracted significant FDI and engaged in more Free Trade Agreements, MNCs established production bases in the country. These companies often require their local partners and subcontractors to use specific imported materials to maintain global quality and consistency standards. Consequently, for a firm to become a successful exporter, importing specialized inputs became a prerequisite, transforming a non-significant factor in 2011 into a defining characteristic of exporting firms by 2013 and 2015.
Sixthly, some coefficients of other factors are inconsistent when regressed on different years’ data. While foreign ownership (Forownership) was a significant positive factor in 2011 and 2015, its effect was not significant in 2013, indicating a complex and changing relationship over time. In contrast, having a license to operate abroad (Licopsea) was not a significant predictor of exporting in 2011 but became a strong and consistent positive predictor in both 2013 and 2015. This shift highlights the growing importance of formal market access credentials in later periods. “License to operate abroad” became a necessary and powerful signal of credibility and compliance. This credential serves as a stamp of approval, demonstrating that a firm has met the legal and regulatory requirements to conduct business internationally. This is especially true for sectors with strict standards, such as food, pharmaceuticals or high-tech goods. The significant positive correlation in later years underscores that official credentials, not just internal capabilities, became a key determinant of export success.
Conversely, several variables did not consistently show a positive relationship with a firm’s export status. Specifically, factors such as the professional share of workers, education and easy access to infrastructure for export failed to demonstrate a consistent, driving role in promoting exports within some mode. In detail, the influence of professional workers was unstable across the years covered by the cross-sectional analysis. In 2013, the variable was not statistically significant across all models (LPM, logit and probit). In contrast, in 2015, the variable showed very strong significance, particularly in the probit model. The positive and statistically significant influence of education was strong in 2011. However, this effect significantly diminished over time, becoming statistically insignificant across all models by 2015. Finally, the firm has easy access to infrastructure for export. In detail, easy access to infrastructure shows a negative and significant relationship with exporting in 2013. The effect is also negative but non-significant in the 2011 LPM and probit models. In 2015, the LPM model shows a negative and significant coefficient. This suggests that firms with seemingly “easy” access to export infrastructure may not be more likely to export, or perhaps, this variable captures other complexities not immediately apparent. This requires further studies using other data, such as panel data or the latest figures in recent times, to reach a general conclusion.
4.3 The analysis results from panel data for the period 2011–2015
Table 5 presents the results of the panel data analysis across three time periods: 2011, 2013 and 2015. These findings were used to reassess the validity of the earlier cross-sectional results (Table 4), enabling a more comprehensive evaluation through panel data. Furthermore, while LPM was considered, its limitations in analyzing binary outcome variables rendered it inferior to the logit and probit models. Consequently, the analysis prioritizes the results derived from the latter two models. Furthermore, the Hausman test results yielded a p-value of 0.85, indicating that the RE model is more suitable than the FE model; therefore, we used the RE model for the analysis.
Panel random effects regression results (UNU-WIDER, 2011–2015)
| Variables | Random effect with cluster robust | Marginal effect at mean | ||
|---|---|---|---|---|
| Logit model (i) | Probit model (ii) | Logit model (iii) | Probit model (iv) | |
| Supfromgov | 0.539*** | 0.284*** | 0.020*** | 0.024*** |
| Female_share | 2.078*** | 0.971*** | 0.079*** | 0.085*** |
| Profshare | 1.722*** | 0.980*** | 0.076*** | 0.097*** |
| Interregcer | 1.857*** | 0.986*** | 0.071*** | 0.087*** |
| Licopsea | 1.235*** | 0.629*** | 0.052*** | 0.061*** |
| Forownership | 0.898*** | 0.464*** | 0.035*** | 0.042*** |
| Subcont | 0.596*** | 0.294*** | 0.023*** | 0.026*** |
| Importmaterial | 1.407*** | 0.755*** | 0.004*** | 0.005*** |
| Education | −0.005 | −0.001 | −0.000 | −0.000 |
| Training | 0.177 | 0.073 | 0.008 | 0.008 |
| Easytoinfrastr | −0.031 | −0.026 | −0.000 | −0.001 |
| Constant | −4.522 | −2.360 | – | – |
| Wald χ2 | 443.14*** | 467.34*** | – | – |
| Observations | 7,502 | 7,502 | 7,502 | 7,502 |
| N_unique_firms | 2,500 | 2,500 | 2,500 | 2,500 |
| Clustering level | Firm level | Firm level | Firm level | Firm level |
| Hausman test: p-value (χ2, 10) | 0.85 | |||
| Variables | Random effect with cluster robust | Marginal effect at mean | ||
|---|---|---|---|---|
| Logit model (i) | Probit model (ii) | Logit model (iii) | Probit model (iv) | |
| Supfromgov | 0.539*** | 0.284*** | 0.020*** | 0.024*** |
| Female_share | 2.078*** | 0.971*** | 0.079*** | 0.085*** |
| Profshare | 1.722*** | 0.980*** | 0.076*** | 0.097*** |
| Interregcer | 1.857*** | 0.986*** | 0.071*** | 0.087*** |
| Licopsea | 1.235*** | 0.629*** | 0.052*** | 0.061*** |
| Forownership | 0.898*** | 0.464*** | 0.035*** | 0.042*** |
| Subcont | 0.596*** | 0.294*** | 0.023*** | 0.026*** |
| Importmaterial | 1.407*** | 0.755*** | 0.004*** | 0.005*** |
| Education | −0.005 | −0.001 | −0.000 | −0.000 |
| Training | 0.177 | 0.073 | 0.008 | 0.008 |
| Easytoinfrastr | −0.031 | −0.026 | −0.000 | −0.001 |
| Constant | −4.522 | −2.360 | – | – |
| Wald χ2 | 443.14*** | 467.34*** | – | – |
| Observations | 7,502 | 7,502 | 7,502 | 7,502 |
| N_unique_firms | 2,500 | 2,500 | 2,500 | 2,500 |
| Clustering level | Firm level | Firm level | Firm level | Firm level |
| Hausman test: p-value (χ2, 10) | 0.85 | |||
Note(s): *** indicate that the coefficients are statistically significant at the 1% level
The regression results reveal that the following variables are statistically significant at the 1% level and exhibit a positive influence on the international market participation decisions of Vietnamese SMEs: government financial support, proportion of female workers in the workforce, share of professional workers, possession of internationally recognized quality certifications, holding an overseas operating license, foreign ownership participation, subcontracting relationships with foreign firms and sourcing of imported materials from foreign markets.
Regarding the categorical variables, the marginal effects quantify the discrete change in the predicted probability p(y = (1/x)) as the independent variable shifts from 0 to 1, ceteris paribus. Across the Vietnamese manufacturing SME sample, the marginal effects derived from the logit and probit specifications exhibit a high degree of stability and magnitude. Consequently, based on the empirical results in Table 5, the following conclusions are established.
The marginal effects at the mean, estimated by the logit and probit models, reveal that government financial support increases the predicted probability of successful export market entry by 2.0% points (logit) and 2.4% points (probit), respectively, for SMEs receiving such assistance compared to those that do not. Similarly, a one-unit increase in the proportion of professional laborers within a firm raises the probability of export participation by 7.6% points (logit) and 9.7% points (probit). Furthermore, possession of internationally recognized quality certifications is associated with an 8.0% point (logit) and 8.7% points (probit) increase in the likelihood of export success relative to firms lacking such certifications. Licensed Vietnamese SMEs have a 5.2% point higher predicted probability of entering export markets under the logit model and 6.1% points higher under the probit model compared to unlicensed firms. Furthermore, the marginal effects at the mean for foreign ownership are estimated at 0.035 (logit) and 0.042 (probit), suggesting that foreign-owned SMEs exhibit a 3.5% and 4.2% point greater likelihood of successful export market entry compared to their domestically owned counterparts, respectively. The marginal effects estimated from both logit and probit models indicate that serving as a subcontractor for foreign firms has a statistically significant positive effect on export market entry. Specifically, subcontracting status increases the probability of export participation by 2.3% points (logit) and 2.6% points (probit) relative to non-subcontracting firms, respectively. Furthermore, if an enterprise imports raw materials from the foreign market, the probability of participating in the international market of this firm will also increase, but the probability level will not increase significantly according to the estimation of the logit and probit models.
Nonetheless, the coefficients for three factors lack statistical significance in the panel data model: education, training programs and ease of access to export infrastructure, although the second is statistically significant in the cross-sectional model. These results suggest that they do not affect Vietnamese SMEs’ decisions to participate in international markets.
4.4 Post-COVID robustness check (2023 World Bank data)
While the 2011–2015 panel data serve as our core empirical framework, the 2023 cross-sectional data act as a post-COVID robustness check to assess the enduring relevance of these determinants. To validate the robustness of the logit and probit model results obtained from the 2011–2015 dataset, this study incorporates updated 2023 World Bank data. Three variables, including training programs, leader education level and export infrastructure accessibility, were excluded from the updated model due to their statistical insignificance in the initial analysis period (2011–2015). Potential multicollinearity concerns between the training variable and the professional workforce share further supported this exclusion decision. Additionally, two other variables, government financial support (Supfromgov) and overseas operating licenses (Licopsea), were omitted from the 2023 model due to data unavailability.
To ensure our empirical findings remain relevant in the post-pandemic economic landscape, we re-estimate the empirical model using the 2023 World Bank Enterprise Survey (N = 599). The results in Table 6 confirm that the coefficients and signs across the three models (LPM, logit and probit) are consistent; therefore, we use a probit model to check for robustness. Specifically, female labor share (Female_share, β = 0.008***), international quality certifications (Interregcer, β = 0.359***), foreign ownership participation (Forownership, β = 0.673***), foreign subcontracting (Subcont, β = 0.326***) and the sourcing of imported materials from foreign markets (Importmaterial, β = 0.938***) remain robust, significant predictors of export participation.
Cross-sectional robustness check (World Bank Enterprise Survey, 2023)
| Variables | LPM | Logit model | Probit model |
|---|---|---|---|
| Female_share | 0.002*** | 0.014*** | 0.008*** |
| Profshare | 0.0001 | 0.004 | 0.002 |
| Interregcer | 0.102*** | 0.626*** | 0.359*** |
| Forownership | 0.231*** | 1.131*** | 0.673*** |
| Subcont | 0.190*** | 0.605*** | 0.326*** |
| Importmaterial | 0.290*** | 1.635*** | 0.938*** |
| Constant | −0.024 | −3.060*** | −1.742*** |
| Observations | 599 | 599 | 599 |
| R2/Pseudo R2 | 0.259 | 0.225 | 0.223 |
| Variables | LPM | Logit model | Probit model |
|---|---|---|---|
| Female_share | 0.002*** | 0.014*** | 0.008*** |
| Profshare | 0.0001 | 0.004 | 0.002 |
| Interregcer | 0.102*** | 0.626*** | 0.359*** |
| Forownership | 0.231*** | 1.131*** | 0.673*** |
| Subcont | 0.190*** | 0.605*** | 0.326*** |
| Importmaterial | 0.290*** | 1.635*** | 0.938*** |
| Constant | −0.024 | −3.060*** | −1.742*** |
| Observations | 599 | 599 | 599 |
| R2/Pseudo R2 | 0.259 | 0.225 | 0.223 |
Note(s): *** indicate that the coefficients are statistically significant at the 1% level
5. Conclusions
This study investigates factors that motivate the export entry decision of Vietnamese SMEs. To achieve the research objectives, the study applies advanced econometric techniques, specifically LPM, probit and logit models incorporating RE to account for unobserved firm heterogeneity. Based on these robust empirical estimations, we derive several critical conclusions:
Estimates derived from both the longitudinal panel and cross-sectional data (2011–2015) reveal a high degree of coefficient stability. Several factors significantly influence Vietnamese SMEs’ entry into international markets, with very high statistical significance at the 1% level, including: government financial support, proportion of female workers, possession of overseas operating licenses, foreign ownership participation, subcontracting relationships with foreign firms and importation of foreign materials. However, due to data unavailability within the 2023 World Bank Enterprise Survey, the impact of government financial support and overseas operating licenses could not be empirically validated for this specific period.
In contrast, training programs, leader education levels and export infrastructure accessibility show no statistically significant effects on internationalization decisions.
5.1 Suggestions for Vietnamese SMEs
Based on the statistically observed associations in this study, as well as inferential mechanisms from the broader literature, we propose the following strategic mandates for Vietnamese SMEs. First, enterprises must proactively leverage institutional support frameworks provided by the State and communal organizations. SMEs should move beyond passive awareness to establish internal policy-monitoring mechanisms that ensure they capitalize on all available trade-facilitation incentives and export subsidies. Through this support, Vietnamese SMEs themselves can develop sustainably and adapt to the requirements of the new context. They actively seek and apply for government financial assistance programs (e.g. export promotion funds, low-interest loans or grants); these solutions can help SMEs enhance their global competitiveness.
Secondly, the results suggest that Vietnamese SMEs must prioritize gender diversity to optimize their workforce. In labor-intensive sectors such as footwear, apparel and electronics, where female participation is a hallmark of the comparative advantage, enterprises should institutionalize gender-inclusive recruitment and professional development. By facilitating leadership pathways and specialized technical training for female employees, firms can more effectively leverage domestic human capital to bolster their export-oriented competitiveness.
Thirdly, given that the share of professional labor exhibits a strong positive association with export success, Vietnamese SMEs must prioritize human capital accumulation. This requires a shift toward aggressive upskilling programs and the cultivation of strategic institutional alliances with universities and vocational centers. By co-developing curricula and recruitment pipelines, SMEs can secure the specialized talent pools necessary to navigate the complexities of international trade.
Fourth, the analysis identifies overseas operating licenses as a critical prerequisite for internationalization. Consequently, Vietnamese SMEs aiming for global expansion must proactively secure the necessary certifications and ensure rigorous compliance with foreign regulatory frameworks to mitigate entry risks. Seek legal and consulting support to navigate international business registration processes efficiently.
Fifth, exploring subcontracting opportunities with MNCs to integrate into global supply chains is crucial. Improve product/service quality and compliance with international standards to become a reliable supplier. Besides, importing materials from well-established foreign suppliers also enhances export abilities, suggesting that SMEs should establish reliable global supply chains. Explore free trade agreements (such as RCEP and CPTPP) to reduce import costs and improve the global competitiveness of SMEs. Collaborate with foreign partners through joint ventures, investments or strategic alliances to gain access to global markets. Participate in foreign investment promotion programs, trade fairs and B2B matchmaking events.
Finally, SMEs should focus on targeted training (e.g. export procedures, e-commerce and digital trade skills) rather than general programs. Rather than focusing exclusively on physical infrastructure, SMEs should optimize logistical efficiency by forging strategic partnerships with specialized export service providers.
5.2 Limitations of the study
Firstly, this research has focused on identifying factors that motivate the export entry decision of Vietnamese SMEs. Identifying suitable indicators for this analysis proved challenging due to inherent data scarcity in the SME sector. Furthermore, data collection was complicated by the lack of standardized metrics and the operational disruptions caused by the COVID-19 pandemic, which temporarily obscured the transparent evaluation of firm-level dynamics in Vietnam.
Secondly, the research’s title was so narrow that the authors could not conduct the empirical investigation in a specific place. Hence, this study mainly used secondary data obtained from available data sources, such as UNU-WIDER and World Bank; so it might not have taken a detailed view.
As a final limitation, this study also ignores the self-selection or learning-by-export hypotheses. According to this view, only firms with productivity levels high enough to cover the substantial fixed “sunk costs” associated with entering foreign markets, such as transport costs, establishing distribution channels or meeting regulatory standards, can profitably participate in international trade. Further, ignoring the potential for endogeneity, the potentially endogenous independent variables are ISO certification or government support.
5.3 Future research directions
While existing research provides valuable insights into Vietnamese SMEs’ internationalization, gaps remain in theoretical depth, methodological diversity and coverage of emerging trends. Future studies should adopt some approaches to address potential endogeneity and self-selection bias, such as instrumental variables or Heckman selection models. Future research should focus on the growing importance of digital capabilities and e-commerce adoption in facilitating international market entry for Vietnamese SMEs. Additionally, the role of trade agreements has been highlighted as crucial in reducing barriers to internationalization, such as RCEP and CPTPP. Scholars have also noted the increasing significance of sustainability and environmental considerations in entry decisions, as global markets become more environmentally conscious. Furthermore, the COVID-19 pandemic has introduced new challenges and opportunities, reshaping the determinants affecting entry decisions. Factors, such as supply chain resilience, digital readiness and adaptability to sudden market changes, have gained prominence in future literature.
The authors express our sincere gratitude to Trang Thanh Nguyen (Department of Information and Service Management, Aalto University, Espoo, Finland; email: trang.th.nguyen@aalto.fi; carolnguyen2094@gmail.com) for helping with providing the necessary documents during the study period.

