The impact of Green Logistics Performance on Vietnam’s exports to the European Union

Abstract

This study employs a gravity model to investigate the impact of green logistics performance on Vietnam’s export flows to 27 European partner countries over the period 2010 – 2022. A Green Logistics Performance Index (GLPI) is constructed based on the Logistics Performance Index (LPI), augmented with environmental indicators and weighted using the entropy method to capture the multidimensional nature of green logistics. The gravity model is estimated using the Poisson Pseudo Maximum Likelihood (PPML) estimator to account for heteroskedasticity and the presence of zero trade flows in panel trade data. The empirical results indicate that improvements in Vietnam’s green logistics performance exert a positive effect on exports to the European Union with a one-period lag, suggesting that investments in green logistics infrastructure and practices generate trade benefits over time rather than producing immediate impacts. Overall, the findings underscore the critical role of green logistics in strengthening Vietnam’s export competitiveness in markets characterized by increasingly stringent environmental regulations.

Keyword: Green Logistics Performance Index, Vietnam’s export, European Union, EVFTA.

1. Introduction

In the context of globalization and increasingly deeper economic integration, international trade continues to be one of the main driver of global economic growth. Recently, the trend toward “greening” trade has become increasingly prominent as countries and major economic blocs, particularly the European Union (EU), have implemented a series of environmental policies linked to international trade activities.

For Vietnam, the EU is a key trading partner, particularly since the EU-Vietnam Free Trade Agreement (EVFTA) entered into force in 2020. However, the EU’s stringent quality and sustainability requirements require Vietnam to continuously adapt to evolving supply chain structures and green trade regulations to maintain and expand its market share. In response, Vietnam has issued a national strategy to 2035, with a vision to 2050, promoting digital technologies, transport optimization, environmentally friendly vehicles, and green infrastructure connectivity.

However, green logistics adoption remains limited, largely due to the dominance of small and medium-sized enterprises with financial constraints, outdated technology, and uneven awareness (Quang Huy Ngo, 2022). From this context, it is evident that examining the impact of green logistics practices on Vietnam’s international trade with the EU is both theoretically and practically significant. This study investigates how green logistics influences export and import activities under the EU’s stringent environmental and sustainability standards, while clarifying its role in enhancing trade efficiency. The findings provide a basis for policymakers and businesses to develop appropriate transition strategies and strengthen Vietnam’s competitiveness in the global green economy

2. Literature review

2.1 Logistics Performance and Green Logistics Performance

The World Bank developed the Logistics Performance Index (LPI) to provide a standardized measure of countries’ logistics performance, evaluating logistics systems based on six components: infrastructure quality, customs efficiency, shipment arrangement, logistics service competence, tracking and tracing, and timeliness.

Extending this concept, green logistics performance incorporates environmental considerations, such as energy consumption, emissions, and resource efficiency, into the assessment of logistics system. At the country level, green logistics performance reflects the ability to facilitate international trade through effective logistics infrastructure and services, while simultaneously controlling emissions and resource use associated with logistics activities (Wang et al., 2018; Ahmad et al., 2024). With the increasing importance of environmental regulations in international trade, especially in developed markets such as the EU, green logistics performance has been recognized as an important factor influencing trade competitiveness and market access (Fan et al., 2022; Huong et al., 2024). Therefore, combining environmental factors into logistics performance provides a more comprehensive and realistic assessment of logistics capability in the global trade system.

2.2. Theories

This study synthesizes various theoretical perspectives to establish a comprehensive theoretical framework. From the RBV perspective, valuable logistics capabilities enhance export competitiveness by reducing time, uncertainty, and coordination costs (Barney, 1991). The NRBV further argues that environmentally oriented capabilities, such as sustainable logistics, create competitive advantages by lowering costs and enhancing legitimacy in environmentally sensitive markets (Hart, 1995). Complementing the RBV-NRBV perspective, the gravity model explains the economic mechanism linking GLPI to export flows. Bilateral trade is negatively associated with trade costs, including transportation, time, and compliance costs (Anderson & van Wincoop, 2003). Improvements in GLPI reduce these costs by enhancing logistics efficiency and mitigating environmental-related barriers, thereby lowering trade resistance and increasing export volumes, particularly in sustainability-driven markets such as the EU.

2.3 Previous studies

Prior studies have examined the relationship between green logistics, and international trade. Wang et al. (2018) using data from 113 countries within an augmented gravity model, reveal that the LPI scores of both exporting and importing countries are positively associated with trade volume. Notably, for trade flows between different pairs, the green logistics performance of importing countries has a different impact on the export volume of exporting countries. In a study of Fan et al. (2022), a Green Logistics Performance Index (GLPI) was constructed via entropy weighting approach. Using an extended gravity model, the results demonstrate that higher levels of green logistics performance in partner countries promote China’s export activity, while greater intensities of CO2 and N2O emissions exert negative effects. Yingfei et al. (2021) highlight that infrastructure and green logistics performance enhance services trade and environment; besides that, service quality and company performance are also important mediators in improving services trade in China. Recently, the study of Ahmad et al. (2025) presents a conceptual model showing the relationship between green logistics performance and sustainable development, identifies carbon emissions, energy consumption, and waste production as key indicators of green logistics success.

However, as green logistics is prominently adpoted in developed countries, emperical research of emerging economies like Vietnam remains limited. Moreover, the interaction between green logistics performance and trade agreements – EVFTA, has not been sufficiently explored. Besides, there is a lack of research on the implementation of green logistics within stringent regulatory environments such as the European Union. Therefore, this study will address these gaps by developing a GLPI for Vietnam, examining its impact on exports to the EU and providing recommendations at both firm and national levels.

3. Methodology

3.1 Research model

Tinbergen (1962) was one of the first researchers to utilize the gravity equation for analyzing the factors impact on international trade flow. Three fundamental determinants of trade include market size, GDP and transportation costs, which have been defined as the geographical distance between two countries. Accumulating from previous studies, the basic gravity equation can be identified as:  

EX = 0 + 1GDPit + 2GDPjt + 3POPit + 4POPjt + 5DISij + Ɛ (1)

Formula (1) can be transformed to the Log-Log model–specific  types of OLS model, which allow to generate linearity in parameters: 

LnEXvn-eu = 0 + 1LnGDPvn + 2LnGDPeu + 3LnPOPvn + 4LnPOPeu +

5LnDISvn-eu + Ɛ  (2)

During that time researching the impact of GLPI on export volume from Viet Nam to Eu, a new Free Trade Agreement (FTA)–European Viet Nam Free Trade Agreement (EVFTA) came into effect. Therefore, based on the previous studies and aims of our study, our research has added four new variables: Trade Openness (OPEN), Exchange Rate Policy (EP), Green Logistics Performance Index (GLPI) and EVFTA. New equations of gravity model can be represented as: 

LnEXvn-eu = 0 + 1LnGDPvn + 2LnGDPeu + 3LnPOPvn + 4LnPOPeu + 5LnDISvn-eu + 6LnOPENeu + 7Ln7EPvn-eu +8LnGLPIvn + 9LnEVFTAvn-eu + Ɛ

3.2 Hypothesis

Green logistics has been mentioned in various academic reports and researches to emphasize the integration of environmental factors into logistics performance. Utilizing GLPI helps countries to overcome trade barriers, serves as a competitive advantage in international markets to meet the standards of developed markets and improve foreign trades (Lai & Wong, 2011). Moreover, the structure and specific provisions of trade agreements shape how GLPI affects trade flows, implying that differentiated green logistics strategies for exports and imports are essential to enhance trade performance (Tran, 2024). Improving efficiency in green logistics enhances service quality and operational efficiency at the firm level, which strengthens overall national economic efficiency (Yingfei et al., 2021). Therefore, this research proposes the hypothesis:

H1: Green Logistics Performance has a positive impact on exports from Viet Nam to the EU.

3.3 Model building process/Data processing

The dataset used in this study is compiled from the World Bank (WB), the World Integrated Trade Solution (WITS), and the World Trade Organization (WTO). The secondary data are structured as a panel covering 27 EU member countries over the period from 2010 to 2022, yielding a total of 351 country–year observations prior to data processing. Regarding data processing, five missing observations in the export variable were removed from the regression analysis. The LPI exhibits missing values for several years; therefore, linear interpolation was applied to obtain a complete time series for the period 2010–2022. The GLPI is constructed by integrating the conventional LPI with a Green Index that captures environmental sustainability. The Green Index is developed based on four environmental indicators, including CO₂ emissions, CH₄ emissions, N₂O emissions, and fossil fuel consumption.

These indicators are first standardized and then weighted using the entropy method to reflect the relative information content and variability of each component. Subsequently, both the LPI and the Green Index are normalized and combined using entropy-based weights to construct the GLPI, which reflects both logistics efficiency and environmental performance.

To ensure consistency with the gravity model framework and to facilitate elasticity-based interpretation, key variables including exports, GDP, population, trade openness, and geographical distance are transformed into natural logarithms. After data cleaning and interpolation, the final sample consists of 346 observations. The empirical analysis begins with the estimation of a baseline gravity model using Ordinary Least Squares (OLS). The model is then estimated using panel data techniques, including Fixed Effects (FE) and Random Effects (RE) specifications, followed by a Hausman test to determine the appropriate estimator.

In addition, the Poisson Pseudo Maximum Likelihood (PPML) estimator is applied to address heteroskedasticity, which is prevalent in trade data, and to avoid potential bias arising from log-linearization of the dependent variable. The PPML approach allows for consistent estimation in the presence of zero trade flows and heteroskedastic errors, making it particularly suitable for bilateral trade analysis. While OLS and FE estimations are primarily used as robustness checks, PPML is considered the preferred specification for interpreting the main empirical results.

4. Results and Discussion

4.1 Descriptive Statistics

Table 1 reports the descriptive statistics of the variables used in the model: 

Table 1. Descriptive Statistics of Variables in the Model

The mean value of the logarithm of exports (ln_ex) is 12.53 with a standard deviation of 1.77, indicating substantial variation in Vietnam’s export scale across EU trading partners. Economic size variables, including Vietnam’s GDP (ln_gdp_vn), EU GDP (ln_gdp_eu), and EU population (ln_pop_eu), exhibit relatively large dispersion, while Vietnam’s population (ln_pop_vn) remains nearly constant over the study period. The geographical distance variable (ln_dis) shows low variability, suggesting limited differences in distance between Vietnam and EU partner countries. The EVFTA dummy variable has a mean value of 0.23, indicating that approximately 23% of the observations belong to the post-EVFTA period.

4.2. Regression Results

Estimating multiple models allows for comparison of coefficient stability and robustness checks. OLS and FE serve as benchmark specifications, while PPML is employed to address heteroskedasticity and better accommodate the characteristics of bilateral trade data: 

Table 2. Regression Results of the Gravity Model

Standard errors in parentheses 

* p<0.1, ** p<0.05, *** p<0.01 

The estimation results indicate that Vietnam’s economic size plays a central role in shaping export flows to the EU. Vietnam’s population has a positive and highly significant effect at the 1% level across all model specifications. Vietnam’s GDP is not statistically significant in the OLS model but becomes significant in the FE and PPML estimations. In contrast, the effects of EU-side variables appear less stable across models. In the OLS specification, EU GDP is statistically significant with a negative sign, indicating potential specification bias when unobserved factors are not adequately controlled.

The EU population is also statistically significant in this model. However, once fixed effects and the PPML estimator are applied, these variables lose statistical significance and, in some cases, change sign. This finding suggests that demand-side effects from EU partners may be absorbed by country- or time-specific unobserved characteristics.

Regarding the key variable of interest, Vietnam’s green logistics performance index (GLPI) exhibits a positive and statistically significant effect only in the PPML model, while remaining insignificant in the OLS and FE estimations. Trade openness is statistically significant only in the OLS model and becomes insignificant in more stringent specifications, suggesting that its observed effect may reflect underlying factors that are not fully controlled for in simpler models.

The EVFTA dummy variable is statistically significant only in the PPML model and carries a negative sign, indicating that, during the study period, the agreement has not yet generated a clear export-promoting effect. This outcome may reflect policy implementation lags or short-term adjustment costs, providing a basis for further discussion in the subsequent section.

4.3. Model Selection and Robustness

Based on the characteristics of trade data and the estimation results, this study selects the Poisson Pseudo Maximum Likelihood (PPML) model as the preferred specification for interpreting the impact of green logistics on trade between Vietnam and the EU. OLS and FE models are employed as robustness checks. Comparing the signs and statistical significance of coefficients across models shows that core variables, particularly Vietnam’s economic size and green logistics performance, exhibit relatively consistent effects when appropriate specifications are applied. Differences observed for other variables reflect the influence of unobserved heterogeneity and alternative data treatments. Overall, the relative consistency across models strengthens the credibility of the findings and confirms the suitability of the PPML estimator for gravity model analysis of international trade.

EX= -175.900 + 0.0133Ln_GDP_vn + 0.012Ln_GDP_eu + 11.086Ln_POP_vn – 0.905Ln_POP_eu + 1.800Ln.GLPI_vn  – 0.012Ln_trade – 0.265Evfta. 

The PPML results indicate that Vietnam’s GDP has a positive and statistically significant effect at the 1% level, with a coefficient of 0.0133, implying that a 1% increase in Vietnam’s GDP is associated with an approximately 1.33% increase in exports to the EU. Vietnam’s population also exhibits a strong and statistically significant positive effect, reflecting the role of domestic supply capacity in promoting exports.

In contrast, EU GDP and population are not statistically significant, suggesting that demand-side factors in partner countries do not primarily drive variations in Vietnam’s exports during the study period.

Notably, the one-period lag of the green logistics performance index (GLPI_(t−1)) exhibits a large and statistically significant positive coefficient, indicating that improvements in green logistics performance take time to translate into higher export flows. Specifically, a 1% improvement in GLPI in the previous period is associated with an approximately 1.8% increase in Vietnam’s exports to the EU in the current period, highlighting the dynamic and persistent role of green logistics in facilitating trade.

5. Conclusion

By integrating the LPI and environmental indicators to develop the GLPI and applying the gravity model, this study highlights the role of green logistics for a stringent environmental standards market. Through PPML estimation, the results indicate that Vietnam’s green logistics performance significantly influences their exports flow to the EU. The improvement in GLPI is associated with the higher export value, which suggests that green logistics performance takes time to convert into trade benefits, highlighting the persistent reflection of green logistics in facilitating trade. Besides, domestic indicators such as Vietnam’s GDP and population also contribute positively to the export, while similar variables of partner countries are not statistically significant.

This can be explained that export activities are driven by the supply side logistics performance and capabilities rather than the demand side. Furthermore, despite the difference in population size and GDP of EU countries, these variations have limited explanatory power in the context of Vietnam’s exports due to high degree of economic integration and relative income levels within EU. Regarding the EVFTA policy, this dummy variable is statistically negative, implying that this trade agreement has not made immediate effects on exports yet during the study period.

Overall, these results propose recommendations for logistics companies, exporters and policy makers to enhance international trade with EU countries as well as entering the global supply chain. First, considering the significance of green logistics performance, firms can invest in green and sustainable logistics systems to improve their competitive advantage, expand the opportunities to access the market with strict regulations and high standards. In particular, firms are encouraged to adopt green or low-emission vehicles for transportation, digitize the tracking systems, implement recycled packaging, and monitor emissions. For exporting companies, they should prioritize the production and supply chain transparency to adhere to the EU’s environmental laws.

Moreover, exporters can comply with EU sustainability regulations such as traceability requirements by obtaining environmental and logistics-related certifications: ISO 14001 (Environmental Management Systems), EN 16258 (GHG emission calculation for transport services). Regarding the policies, policy makers are recommended to maximize the EVFTA benefits through different actions: negotiating non-tariff barriers faced by exporters, together with reforming domestic green standards to harmonize with international ones. At the same time, Vietnamese governments can place greater emphasis on environmental upgrading within the logistics systems.

This requires closer coordination between trade and environmental policies. It can be achieved by investment in green transport infrastructure, low-emission logistics hubs, and energy-efficient ports, or promoting the adoption of electric vehicles. In a long term perspective, the government can support these firms through tax incentives for green vehicles or preferential credit for logistics firms and manufacturers investing in low-emissions technologies.

Despite the study’s contribution, this study has limitations and gaps that open avenues for future research. The data set of the LPI has values missing for certain years, which is addressed by utilizing linear interpolation; this can cause imperfect capture in annual logistics quality. Moreover, as the time period ends in 2022, it only reflects initial years of EVFTA, future studies can continue analyzing extended timeframes for the  effect EVFTA made in long terms. Finally, more measures of the EU’s environmental policies, regulations in international trade can be incorporated to explore the relationship between green logistics and export activities.

References

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Tác động của hiệu quảlogistics xanh đến xuất khẩu của Việt Nam sang Liên minh Châu Âu

PGS.TS Nguyễn Thị Phương Thu¹

Đỗ Thị Phương Anh²

Phan Thị Hiền²

Hàn Thanh Huyền²

Phan Thị Hiền Anh²

¹Khoa Kế hoạch và Phát triển, Đại học Kinh tế Quốc dân

²Đại học Kinh tế Quốc dân

 

Tóm tắt:

Nghiên cứu này sử dụng mô hình trọng lực để phân tích tác động của hiệu quả logistics xanh đối với hoạt động xuất khẩu của Việt Nam sang 27 quốc gia đối tác châu Âu (EU-27) trong giai đoạn 2010 – 2022. Chỉ số Hiệu quả Logistics Xanh (Green Logistics Performance Index, GLPI) được xây dựng dựa trên Chỉ số Hiệu quả Logistics (Logistics Performance Index, LPI), kết hợp bổ sung các chỉ tiêu môi trường và được xác định trọng số bằng phương pháp entropy nhằm phản ánh tính đa chiều của logistics xanh. Mô hình trọng lực được ước lượng bằng phương pháp Poisson Pseudo Maximum Likelihood (PPML) nhằm xử lý hiện tượng phương sai thay đổi và sự tồn tại của các giá trị thương mại bằng 0 trong dữ liệu bảng thương mại. Kết quả thực nghiệm cho thấy việc cải thiện hiệu quả logistics xanh của Việt Nam có tác động tích cực đến xuất khẩu sang EU-27 với độ trễ một kỳ, hàm ý rằng các khoản đầu tư vào cơ sở hạ tầng và thực hành logistics xanh mang lại lợi ích thương mại theo thời gian thay vì tạo ra tác động tức thì. Nhìn chung, các phát hiện của nghiên cứu nhấn mạnh vai trò quan trọng của logistics xanh trong việc nâng cao năng lực cạnh tranh xuất khẩu của Việt Nam tại các thị trường có yêu cầu ngày càng nghiêm ngặt về môi trường.

[Tạp chí Công Thương – Các kết quả nghiên cứu khoa học và ứng dụng công nghệ, Số 4/2026]