Introduction

In the context of 'globalization', China and the countries along the “Belt and Road” Initiative have ushered in a high-speed development stage of comprehensive cooperation (Khan et al. 2022a), working together to promote a higher level of trade facilitation development trend and promote the further expansion of trade scale (Khan et al. 2022b). The proportion of the trade scale between China and the “Belt and Road” initiative countries in China’s overall foreign trade continues to grow (Mena et al. 2022), reaching 34.7% by 2022. The trade between China and the “Belt and Road” initiative countries is mainly concentrated in Southeast Asia, focusing on West Asia and South Asia (Qin 2022). From an overall perspective, in 2022, China’s trade with ASEAN accounted for 50.3% of the trade of the “Belt and Road” initiative countries. And the trade imbalance between China and the “Belt and Road” initiative countries is becoming more and more serious (Wang and Liu 2022).

Since 2007, the World Bank has published the “Logistics Performance Index Report” every two years to measure the level of logistics in countries worldwide with the LPI (Hausman et al. 2013). The progress of the logistics industry drives the development of manufacturing, finance, and other industries, promotes the coordinated development of upstream and downstream enterprises, and promotes the formation of a complete industrial chain and supply chain (Göçer et al. 2022). The logistics performance of the “Belt and Road” initiative countries has become an important factor in promoting import and export between China and the “Belt and Road” initiative countries (Pan et al. 2022). With the continuous advancement of the 'economic integration' process, logistics connects the needs of trade between countries, is an essential guarantee for the smooth operation of the supply chain (Yang 2023), and plays a vital role in the country’s economic development (Yingfei et al. 2022). Therefore, the research on the relationship between international logistics performance and the development of import and export trade has certain practical significance.

Due to the incalculable impact of the 2008 financial crisis on the world economy, this paper selects 2011–2022 as the time interval for research to avoid the effect on the accuracy of empirical results. Combined with data availability, taking 61 countries along the Belt and Road Initiative as an example, this paper profoundly analyzes the relationship between international logistics performance and national import and export trade. It systematically analyzes the impact of different indicators of international logistics performance on international trade import and export and more accurately controls the adjustment direction of resource allocation to provide some reference value for the implementation of the “Belt and Road” initiative of China and provide some reference for the balance of national logistics system and trade relations.

Compared with previous studies, the innovation of this paper is mainly reflected in the following aspects: Firstly, the interaction mechanism between international logistics performance and import and export trade is analyzed. This paper analyzes the interaction mechanism between international logistics performance and import and export trade through previous data collection. Secondly, the fixed effect model is used to test the impact of the improvement of the logistics performance level of the countries along the “Belt and Road” on the trade volume, and to explore the impact of international logistics performance on the import and export of countries of different sizes and the differences. Thirdly, the relationship between international logistics performance and import and export trade is tested by using the methods of 'eliminating outlier samples', 'reducing sample interval', 'shrinking tail processing' and 'lagging one period of explained variables', and the conclusions are summarized, and specific and feasible development suggestions are put forward.

The research contributions of this paper can be summarized as follows: Firstly, it further enriches the research on international logistics performance and import and export trade. The research of related fields is mainly related to the relationship between logistics performance and export. This paper takes import and export as the research object, which has a specific reference value for the overall development of the country and the region. Secondly, this paper not only explores the relationship between international logistics performance and import and export trade but also divides different countries according to their scale and explores the various impacts on countries of different scales, which provides a specific reference for the direction of national logistics and trade investment. Thirdly, this paper discusses the relationship between international logistics performance and the development of import and export trade, and puts forward specific suggestions to promote the improvement of international logistics performance and trade volume, which helps provide some reference value for the development of related fields.

The section 2 reviews the literature on logistics performance and international trade, and provides some theoretical support for the article. Section 3 explains the construction of the gravity model data sources, the variables, and the division of the national scale. In section 4, descriptive statistics, LPI comprehensive index regression, and LPI sub-index regression are used, and systematic analysis is carried out according to the results of empirical data. Section 5 conducts a robustness test. Section 6 summarizes the conclusions and puts forward specific suggestions based on the empirical analysis.

Literature review

Logistics performance is the key to supporting trade growth and the main factor determining a country’s economic growth (Cui et al. 2022). Bhukiya and Patel (2023) and Huong et al. (2024) believed that logistics performance promotes international trade. Barakat et al. (2023) demonstrated that the improvement of logistics performance helps to increase national trade openness and reduce trade costs. Jayathilaka et al. (2022) analyzed the impact of gross domestic product (GDP) and LPI on international trade based on 142 countries, and verified the positive role of LPI in promoting international trade, which is more significant in Asia, Europe and Oceania. Çelebi (2019) believes that logistics performance will promote the development of trade, and the efficiency of logistics system is an important factor affecting bilateral trade. Based on the sample data of 10 countries along the China-Europe Express from 2015 to 2019, Zhong and Zhou (2022) demonstrated that the improvement of international logistics performance has promoted the increase of import and export trade in Guangdong Province. Liu (2022) selected the data of 12 provinces and regions in western China from 2015 to 2020 to explore the impact of cross-border logistics performance on the competitiveness of cross-border agricultural products trade, and found that the development of cross-border logistics is conducive to improving the development of cross-border agricultural products trade in western China. The above research shows that: in the context of economic integration, the development of international logistics performance has promoted the improvement of the international trade environment and improved the convenience of international trade. There is a positive correlation between international logistics performance and international trade.

Import and export trade has a certain feedback effect on the development of logistics industry (Yang 2010). Guo (2018) used the panel data of 31 provinces in China from 1997 to 2016 to empirically test the role of import and export trade in promoting the development of the logistics industry, and the impact of exports on the development of the logistics industry is significantly greater than the role of imports. At the same time, due to differences in geographical location and resource endowments, only imports in the central and eastern regions of China promote the development of the logistics industry, and the western region is not significant. Zhan et al. (2019) found that the scale effect, export efficiency effect and export structure effect of export trade in the core area of the “Belt and Road” have promoted the development of the logistics industry. Wang and Wang (2021) found that the trade in the core area of “Belt and Road” can promote the growth and agglomeration of the logistics industry, and the export scale effect is the main factor to promote the growth of the logistics industry. The expansion of international trade scale, the improvement of trade efficiency and the improvement of trade structure have also promoted the improvement of international logistics performance. Based on the co-integration model of time series data from 1989 to 2012, Wang (2015) found that there is a co-integration relationship between logistics development and energy consumption, foreign trade and urbanization level, and this co-integration relationship has a long stability. Yang et al. (2019) found that the logistics development between China and ASEAN countries is the reason that affects the development of each other’s trade through the Granger causality test. Guo et al. (2018) studied the development of China’s logistics industry and foreign trade in the past 40 years of reform and opening up, and found that there is a long-term and stable coordinated development relationship between the two. In order to promote the sustainable development of the two, it can be achieved by optimizing the business environment, promoting the support of the coordinated development of modern logistics and foreign trade, improving the quality of logistics infrastructure and customs operation efficiency, and accelerating the informatization and standardization of logistics industry.

There are some differences in the impact of international logistics performance on countries with different income levels, different trade facilitation levels, and different population sizes (Fan and Yu 2015). See et al. (2024) found that countries with higher income levels have better logistics performance. Çelebi (2019) believes that income level is an important factor in the impact of logistics performance on trade volume. Trade facilitation will have different effects according to per capita income level, and low-income economies with higher logistics level will gain more benefits than high-income economies. Compared with the increase of logistics level in low-income countries, the increase of trade volume will be promoted, and the import volume of middle and high-income countries will benefit more from the improvement of logistics performance. Kumari and Bharti (2021) studied the impact of country size on trade and logistics performance based on population size, and found that the degree of LPI to improve related trade growth is the highest in medium-sized countries, followed by small-scale countries. Among the sub-indicators of LPI, cargo tracking ability and timeliness have the greatest impact on the trade of small-scale countries, and the convenience and timeliness of arranging international freight transportation have the greatest impact on medium-sized countries.

In summary, with the deepening of the globalization of the supply chain and industrial chain, import and export trade are moving towards lower cost and higher efficiency. International logistics performance and import and export trade promote each other and jointly drive national economic development. The impact of international performance on the trade of different countries has certain differences. However, there are still few studies on the impact of logistics performance on the trade of countries of different sizes. Therefore, this paper divides the “Belt and Road” initiative countries according to population size, further explores the impact of international logistics performance on import and export trade, and provides a reference for the development of the “Belt and Road” initiative countries and the trade between nations.

Data selection and model construction

In order to improve the trade level of the “Belt and Road” initiative countries, this paper studies the impact of international logistics performance of the “Belt and Road” initiative countries on China’s import and export trade, constructs an extended gravity model, and introduces the LPI into the model. At the same time, according to the population size, the countries along the “Belt and Road” are divided into three categories: large, medium and small, to explore the impact of international logistics performance on the import and export of countries of different sizes and the differences.

Data processing and variable setting

This study takes 2011–2022 as the time interval of the study. The data mainly come from the World Bank WDI database. In view of the fact that the data published by the World Bank has been updated to 2022, but there are missing data in individual years, such as LPI, since the World Bank releases the logistics performance index every two years, in order to ensure the continuity of the data, the missing data of this part is filled by linear prediction using stata15 software. In order to avoid the impact of unit differences between indicators on the experimental results, the gross national product of the “Belt and Road” initiative countries, China’s imports and exports to the “Belt and Road” initiative countries, the distance from the “Belt and Road” initiative countries, China’s gross national product, the comprehensive index of international logistics performance, the score of cargo tracking ability, the score of logistics serviceability, the score of international freight transportation that is easy to arrange competitive prices, the score of customs clearance process efficiency, the score of the expected time of goods to reach the consignee frequency and the score of transportation-related infrastructure quality are standardized by stata15. Variables are set as follows:

Explained variable: China’s trade volume with the “Belt and Road” initiative countries (billions of dollars).

Explanatory variable: international logistics performance of the “Belt and Road” initiative countries. Sub-indicators: goods tracking ability score, logistics serviceability score, easy-to-arrange price competitive international freight score, customs clearance process efficiency score, goods expected time to reach the consignee frequency score, and transportation-related infrastructure quality score.

Control variables: distance from the “Belt and Road” initiative countries (kilometers), gross national product of the “Belt and Road” initiative countries (billions of dollars), gross national product of China (billions of dollars), the ratio of total imports and exports of goods and services to GDP of the sample countries, whether it is adjacent to China, and whether it has joined the WTO.

Data sources and processing instructions

According to the model setting and variable definition, the variable name, economic implications, variable value, data source and expected impact on trade volume of international logistics performance and its sub-indicators and control variables on trade volume is shown in Table 1. If the expected impact on trade volume is positive, it is expressed as '+', and vice versa.

Table 1 The variable setting in the empirical model.
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Since the fixed effect model is used for regression analysis while controlling the year and time, all variables should change with time. This paper uses the product of the distance between China and the “Belt and Road” initiative countries and the Brent crude oil price of the year to represent the distance, so that the distance can change with time, which enhances the feasibility of the model. There are 65 countries and regions along the “Belt and Road” marked by the 'China Belt and Road Network'. However, due to the lack of data in Brunei, Timor-Leste, Palestine and other countries, combined with the availability of data, this study selects the “Belt and Road” initiative countries: 40 countries in Asia, 20 countries in Europe and one country in Africa, a total of 61 countries from 2011 to 2022 sample data for empirical research.

According to the average population data of the “Belt and Road” initiative countries from 2011 to 2022, the countries with the top 25% of the population are classified as large-scale countries, the latter 25% are classified as small-scale countries, and 25–75% are classified as medium-scale countries. The specific division results are shown in Table 2.

Table 2 Division of country size.
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Model construction

The gravitational model is derived from the law of universal gravitation proposed by the British physicist Newton. It was originally used to explain the interaction between objects and was later cited in the field of international trade. It is used to measure the relationship between the trade volume between the two countries and their economic scale (Zhong and Zhou 2022). The formula can be expressed as:

$${{TRADE}}_{{ij}}=\alpha \frac{{X}_{i}{X}_{j}}{{{DIS}}_{{ij}}}$$
(1)

Formula (1) is transformed into logarithmic form and the random error term can be expressed as:

$${\mathrm{ln}}{{TRADE}}_{{ij}}={\beta }_{0}+{\beta }_{1}{\mathrm{ln}}{X}_{i}+{\beta }_{2}{\mathrm{ln}}{X}_{j}+{\beta }_{3}{\mathrm{ln}}{DIS}_{{ij}}+\varepsilon$$
(2)

The above equation \({{TRADE}}_{{ij}}\) represents the trade volume between country i and country j, \({X}_{i}\) and \({X}_{j}\) represent the economic aggregate of country i and country j respectively, \({{DIS}}_{{ij}}\) represents the geographical distance between the two economies of country i and country j, \({\beta }_{0}\) represents the parameters to be estimated in the model, and ε represents the random error term of the model.

In the gravity model setting in the field of international trade, the trade volume between the two countries is negatively correlated with the distance between the two countries, and positively correlated with the total economic volume of the two countries. On the basis of the basic gravity model, combined with the existing research, the international logistics performance index released by the World Bank is introduced into the gravity model, and the control variables are added to expand the model. The control variables include: DIS, GDPJ, GDPC, OPEN, BORDER and WTO, in which OPEN is an endogenous variable, BORDER and WTO are dummy variables.

The extended gravity model can be expressed as follows:

$$\begin{array}{c}{\mathrm{ln}}{TRADE}={\beta }_{0}+{\beta }_{1}{\mathrm{ln}}{LPI}+{\beta }_{2}{\mathrm{ln}}{DIS}+{\beta }_{3}{\mathrm{ln}}{GDPJ}+{\beta }_{4}{\mathrm{ln}}{GDPC}\\ +{\beta }_{5}{OPEN}+{\beta }_{6}{BORDER}+{\beta }_{7}{WTO}+\varepsilon \end{array}$$
(3)

Each sub-index of LPI as an alternative index of LPI into the extended gravity model can be expressed as:

$$\begin{array}{l}{\mathrm{ln}}{TRADE}={\beta }_{0}+{\beta }_{1}{\mathrm{ln}}{TRACE}+{\beta }_{2}{\mathrm{ln}}{DIS}+{\beta }_{3}{\mathrm{ln}}{GDPJ}\\\qquad\qquad\qquad+\,{\beta }_{4}{\mathrm{ln}}{GDPC} +{\beta }_{5}{OPEN}\\\qquad\qquad\qquad+\,{\beta }_{6}{BORDER}+{\beta }_{7}{WTO}+\varepsilon \end{array}$$
(4)
$$\begin{array}{l}{\mathrm{ln}}{TRADE}={\beta }_{0}+{\beta }_{1}{\mathrm{ln}}\,{SERVICE}+{\beta }_{2}{\mathrm{ln}}{DIS}+{\beta }_{3}{\mathrm{ln}}{GDPJ}\\\qquad\qquad\qquad+\,{\beta }_{4}{\mathrm{ln}}{GDPC} +{\beta }_{5}{OPEN}+{\beta }_{6}{BORDER}\\\qquad\qquad\qquad+\,{\beta }_{7}{WTO}+\varepsilon \end{array}$$
(5)
$$\begin{array}{l}{\mathrm{ln}}{TRADE}={\beta }_{0}+{\beta }_{1}{\mathrm{ln}}\,{SHIPMENTS}+{\beta }_{2}{\mathrm{ln}}{DIS}+{\beta }_{3}{\mathrm{ln}}{GDPJ}\\\qquad\qquad\qquad+\,{\beta }_{4}{\mathrm{ln}}{GDPC}+{\beta }_{5}{OPEN}\\\qquad\qquad\qquad+\,{\beta }_{6}{BORDER}+{\beta }_{7}{WTO}+\varepsilon \end{array}$$
(6)
$$\begin{array}{l}{\mathrm{ln}}{TRADE}={\beta }_{0}+{\beta }_{1}{\mathrm{ln}}\,{CLEARANCE}+{\beta }_{2}{\mathrm{ln}}{DIS}+{\beta }_{3}{\mathrm{ln}}{GDPJ}\\\qquad\qquad\qquad+\,{\beta }_{4}{\mathrm{ln}}{GDPC}+{\beta }_{5}{OPEN}\\\qquad\qquad\qquad+\,{\beta }_{6}{BORDER}+{\beta }_{7}{WTO}+\varepsilon \end{array}$$
(7)
$$\begin{array}{l}{\mathrm{ln}}{TRADE}={\beta }_{0}+{\beta }_{1}{\mathrm{ln}}{TIME}+{\beta }_{2}{\mathrm{ln}}{DIS}+{\beta }_{3}{\mathrm{ln}}{GDPJ}\\\qquad\qquad\qquad+\,{\beta }_{4}{\mathrm{ln}}{GDPC}+{\beta }_{5}{OPEN}\\\qquad\qquad\qquad+\,{\beta }_{6}{BORDER}+{\beta }_{7}{WTO}+\varepsilon \end{array}$$
(8)
$$\begin{array}{l}{\mathrm{ln}}{TRADE}={\beta }_{0}+{\beta }_{1}{\mathrm{ln}}\,{INFRASTRUCTURE}+{\beta }_{2}{\mathrm{ln}}{DIS}\\\qquad\qquad\qquad+\,{\beta }_{3}{\mathrm{ln}}{GDPJ}+{\beta }_{4}{\mathrm{ln}}{GDPC}+{\beta }_{5}{OPEN}\\\qquad\qquad\qquad+\,{\beta }_{6}{BORDER}+{\beta }_{7}{WTO}+\varepsilon \end{array}$$
(9)

Empirical analyses

Analysis of statistical index results

The descriptive statistical results are shown in Table 3. According to the results in the table, there are great differences in the data results of the “Belt and Road” initiative countries. First of all, there is a big difference in China’s import and export to the “Belt and Road” initiative countries: China’s import and export to Bhutan, Maldives, Bosnia and Herzegovina, North Macedonia and other countries remained low from 2011 to 2022, with an average annual import and export value of no more than $300 million. Trade with Singapore, India, Russia and other countries have remained at more than USD 50 billion since 2011. Secondly, the population size of the “Belt and Road” initiative countries is significantly different: the population of Maldives, Bhutan, Montenegro and other countries is less than one million between 2011 and 2022, while India’s population remains above one billion. Third, the scores of various indicators related to logistics in countries along the route are not the same: from the perspective of the comprehensive index of logistics performance, Singapore and other countries have maintained a score of more than 4, and the comprehensive ranking is among the top ten in the world, while Mongolia, Myanmar, Laos, Tajikistan, Turkmenistan and other countries have a low logistics level ranking of 100. From the perspective of each sub-index, the differences between countries are obvious, and the development status of the “Belt and Road” initiative countries is uneven.

Table 3 Descriptive statistical results.
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LPI comprehensive index regression

On the basis of descriptive statistics, this paper further uses Stata15.0 software to conduct regression analysis on the panel data of the “Belt and Road” initiative countries from 2011 to 2022. Since the data cross section (N) > time series (T), it is a short panel and does not require a unit root test. Through collinearity diagnosis, it was found that the VIF values of each index were less than 10, indicating that there was no multicollinearity in the data. The results of the Hausman test are shown in Table 4, and the P value is 0.0017, which is less than 0.1. Therefore, the results are significant. The original hypothesis that the panel data model is a random effect model is rejected, and the fixed effect model is supported. The fixed effect model is used to analyze the data from 2011 to 2022 by controlling the country and time at the same time. The regression results are shown in Table 5.

Table 4 Hausman test results.
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Table 5 Regression result.
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According to the regression results, the impact of international logistics performance of the “Belt and Road” initiative countries on China’s import and export trade is as follows:

$$\begin{array}{l}{\mathrm{ln}}{TRADE}=-0.029+0.062{\mathrm{ln}}{LPI}-0.116{\mathrm{ln}}{DIS}\\\qquad\qquad\qquad+\,0.803{\mathrm{ln}}{GDPJ}+0.1{\mathrm{ln}}{GDPC}+0.223{OPEN}\\\qquad\qquad\qquad-\,0.048{BORDER}+0.011{WTO}+\varepsilon \end{array}$$
(10)

According to the regression results in Table 5, the impact of LPI on China’s import and export trade is significantly positive under the condition of 10%, indicating that the higher the LPI of the “Belt and Road” initiative countries, the more conducive to the trade between China and the country.

In the regression results of endogenous variables, the coefficient of DIS is −0.116, which is significant at the 1% level. Therefore, the distance between China and the “Belt and Road” initiative countries has a significant negative impact on China’s trade volume. The farther the distance is, the more unfavorable it is for China’s import and export to the Belt and Road Initiative countries. In China’s international trade, distance cost is still an important influencing factor. The economic volume coefficient of the countries along the route is 0.803, indicating that the economic volume of the countries along the route has a certain impact on China’s imports and exports to the country. The higher the GDP is, the higher the economic development level of the country is, and the higher the corresponding consumption level is, thus driving China’s import and export to the country. China’s economic volume coefficient is 0.1, which is significantly positive at the 1% level. Therefore, the improvement of China’s economic volume will significantly promote the growth of international trade volume. In addition, the degree of opening to the outside world has a significant role in promoting international trade, with a coefficient of 0.223, indicating that the higher the degree of opening to the outside world of countries along the route will be conducive to China’s import and export to the country.

Through the results of dummy variable data, it can be seen that the BORDER and WTO coefficients are-0.048 and 0.011, respectively, and the BORDER is significant at the level of 10%, indicating that the national border is not conducive to improving China’s import and export of goods. Because the climate environment of the bordering countries is close to China, the differences in resources and production factors may not be obvious enough, so that BORDER is negatively correlated with TRADE. The WTO performance is not significant, indicating that whether to join the WTO organization cannot be used as the strongest factor affecting trade between countries. To a certain extent, the differences in the types of goods traded between China and countries of different sizes will affect the volume of trade between countries. For example, some countries have parallel production with China, which leads to a decrease in trade between China and the country.

The comparison of the results in Table 5 shows that the impact of international logistics performance on China’s import and export to large-scale countries is significantly positive at the 1% level. In addition, the impact of international logistics performance on small and medium-sized countries is negative and insignificant at the 10% level, respectively. To a certain extent, it is due to the small total national demand of small and medium-sized countries. The improvement of international logistics performance has also led to the improvement of the national internal logistics system and promoted the better utilization of national internal resources. Therefore, continuing to invest resources to enhance the international logistics performance level of small and medium-sized countries is not conducive to the growth of import and export trade volume, which is more obvious in small-scale countries, and reasonable allocation of resources is particularly important.

LPI sub-index regression

In order to study the impact of LPI’s specific sub-indicators on China’s import and export to the “Belt and Road” initiative countries, this paper replaces LPI with six sub-indicators TRACE, SERVICE, SHIPMENTS, CLEARANCE, TIME, INFRASTRUCTURE for regression analysis. The results are shown in Table 6.

Table 6 The regression results of LPI sub-indicators on China’s import and export.
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From the regression results, it can be seen that TRACE, SHIPMENTS, CLEARANCE and TIME are not significant at the 10% level, indicating that logistics cargo tracking ability, international freight price competitiveness, customs clearance efficiency and logistics timeliness have little impact on China’s import and export to the “Belt and Road” initiative countries. The impact of SERVICE on import and export trade is positive, which is significant at the level of 10%, and INFRASTRUCTURE is positive at the level of 1%. That is, the logistics service capacity and logistics infrastructure quality of the Belt and Road Initiative countries have a greater impact on China’s import and export trade. Logistics service capacity includes inventory capacity, operation capacity and logistics reliability of the logistics system. The progress of logistics inventory capacity and operation capacity will be conducive to the supply of resources and business development of international trade enterprises (Wang 2023). The improvement of logistics reliability will increase consumers ‘ online purchase intention to a certain extent and promote the positive development of international trade (Yuan and Zhang 2023). The quality of logistics infrastructure is an important guarantee for efficient transportation of goods (Yuan et al. 2023). Therefore, China’s trade import and export have a certain dependence on the level of international logistics performance. The improvement of the relevant sub-indicators of the logistics performance index has a certain role in promoting China’s import and export trade.

Through the regression analysis of comprehensive indicators, it can be seen that the impact of international logistics performance on large-scale countries is the most significant. In order to deeply explore the impact of sub-indicators of international logistics performance on large-scale countries, this paper introduces the sub-indicators of international logistics performance indicators into large-scale countries, and replaces LPI for regression analysis. The results are shown in Table 7.

Table 7 The regression results of LPI sub-indicators on China’s import and export to large-scale countries.
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From the regression results in Table 7, it can be seen that TRACE and TIME have no significant impact on China’s import and export to large-scale countries. SHIPMENTS is significant at the 5% level. SERVICE, CLEARANCE and INFRASTRUCTURE are significant at the 1% level, and the coefficients are 0.254,0.532,0.485 and 0.449, respectively. The international freight price competitiveness, logistics service capacity, customs clearance efficiency and logistics-related infrastructure level of the “Belt and Road” initiative countries have a significant positive effect on China’s trade import and export.

Robustness test

In order to avoid the influence of extreme values on the empirical results of the selected samples, this paper removes individual outliers and conducts robustness test analysis. Among the 61 sample countries along the “Belt and Road”, China’s annual average import and export volume to Bhutan, North Macedonia, Bosnia and Herzegovina and Moldova from 2011 to 2022 is less than USD 100 million, which has a large gap with the average value of China’s import and export volume to the “Belt and Road” initiative countries. Therefore, in order to avoid the impact of such extreme data on the experimental results, this paper eliminates the sample data of four countries, including Bhutan, North Macedonia, Bosnia and Herzegovina and Moldova, and performs multiple regression analysis on the remaining sample data. The regression results are shown in Table 8.

Table 8 Regression results of eliminating outlier samples.
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Combined with the regression results, it can be seen that the LPI coefficient passed the significance test under the condition of 5%, excluding the influence of sample selection bias on the empirical results of this paper. That is, the international logistics performance of the Belt and Road Initiative countries has a significant role in promoting the growth of trade volume between China and the country.

Since 2020, the new coronavirus epidemic has traumatized the economies of various countries to a certain extent and has had a certain impact on the country’s import and export trade. In order to avoid the interference of such factors on the regression results, the sample time interval is shortened to 2011–2020, and the regression is carried out again. The results are shown in Table 9, and the estimated coefficient of LPI is significantly positive at the level of 10%, which proves that under the condition of weakening the interference of economic turbulence factors, the improvement of logistics performance level of the “Belt and Road” initiative countries has a significant role in promoting China’s trade import and export, and the conclusions of this paper are still robust.

Table 9 Regression results of the reduced sample interval.
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The data are tailed in the range of 5–95%. The second column in Table 10 shows that the international logistics performance of the “Belt and Road” initiative countries has a positive impact on China’s import and export trade, which is significant at the level of 5%, the coefficient is small, and the main research conclusions have not changed.

Table 10 Regression results of tail reduction processing.
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Since there may be a certain time difference in the effect of international logistics performance level on import and export trade volume, this paper lags the explained variable TRADE by one period to explore the lag effect of LPI on TRADE, which helps to alleviate the possible two-way causality. The results in Table 11 show that the impact of LPI on TRADE lags one period is consistent with the benchmark results, so the benchmark regression is robust.

Table 11 Explained variables lag one period.
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Conclusions

By adding the international logistics performance index to the trade gravity model, this paper analyzes the impact of the logistics performance of the “Belt and Road” initiative countries on China’s import and export trade. At the same time, the countries along the 'Belt and Road' are divided into three scales: large, medium and small, to explore the differences in the impact of logistics performance on the import and export of China and these three scale countries. According to the empirical analysis, the following conclusions can be drawn:

First, the improvement of the logistics performance level of the “Belt and Road” initiative countries has a certain role in promoting the increase of trade volume between China and the country. The international logistics performance index of the “Belt and Road” initiative countries has the most significant impact on China’s import and export to large-scale countries. The impact of LPI on China’s import and export trade is significantly positive under the condition of 10%. Therefore, the improvement of the logistics performance index of the 'Belt and Road' initiative countries is conducive to the increase of trade volume between China and the country. The impact of international logistics performance on China’s import and export to large-scale countries is significantly positive at the 1% level, small-scale countries are significantly negative at the 10% level, and medium-scale countries are not significant.

Second, the sub-indicators of the international logistics performance index of the countries along the “Belt and Road” have different degrees of influence on the import and export volume. Among them, logistics service capacity has a significant impact at the level of 10%, and the quality of logistics infrastructure is significant at the level of 1%, and the coefficient is positive. Therefore, the improvement of logistics service capacity and logistics infrastructure quality will help promote the growth of import and export volume. However, TRACE, SHIPMENTS, CLEARANCE and TIME have no significant impact on import and export volume. Therefore, logistics cargo tracking capability, international freight price competitiveness, customs clearance efficiency and logistics timeliness have little impact on China’s import and export to the Belt and Road Initiative countries.

Third, among the sub-indicators of international logistics performance of large-scale countries along the 'Belt and Road', international freight price competitiveness, logistics service capacity, customs clearance efficiency and logistics-related infrastructure level have a significant role in promoting import and export trade, and the impact of cargo tracking capacity and logistics timeliness is not significant. SERVICE, CLEARANCE and INFRASTRUCTURE are significant at the 1% level, with coefficients of 0.532,0.485 and 0.449, respectively, so the impact of logistics service capacity is the greatest.

Practical implications

Based on the relevant conclusions of this paper, it is concluded that the improvement of the international logistics performance of the 'Belt and Road' initiative countries is conducive to promoting the development of China’s international trade, and the factors that have a greater impact on the growth of import and export trade in the sub-indicators of international logistics performance are clarified, which provides a certain basis for the implementation of the 'Belt and Road' initiative. In addition, combined with the research conclusions, targeted suggestions are put forward to provide certain reference values for the improvement of national logistics and trade levels and the implementation direction of the “Belt and Road” initiative.

First, improve logistics performance and reduce trade costs. The regression results show that the international logistics performance of the “Belt and Road” initiative countries has a significant and positive impact on China’s import and export, indicating that the level of logistics performance will promote the economic and trade exchanges between China and the “Belt and Road” initiative countries. The implementation of China’s 'Belt and Road' initiative is of great significance to the deepening of international cooperation. However, due to the large differences in the level of logistics performance among the “Belt and Road” initiative countries, this difference will restrict the development of intra-regional trade to a certain extent, and then weaken the benefits of the “Belt and Road” initiative. Therefore, it is particularly important to give full play to the role of the Asian Infrastructure Investment Bank and the Silk Road Fund to ensure the financial support for the process of improving the logistics performance level of the “Belt and Road” initiative countries. In addition, make full use of advanced digital economy and technology to promote more efficient and lower-cost trade between the “Belt and Road” initiative countries.

Second, strengthen infrastructure facilities and reduce trade barriers between countries along the route. Whether from the LPI comprehensive index regression or the regression results of each sub-index, the coefficient of distance is negative, indicating that the geographical distance between China and the “Belt and Road” initiative countries will have a negative impact on China’s import and export, that is, distance is still an important factor affecting trade costs. However, there are still some problems and obstacles in the logistics facilities of various countries. Therefore, it is necessary to increase the capital investment and investment in various facilities related to logistics, improve the sub-indicators of logistics performance, and improve logistics competitiveness and reduce trade costs by improving infrastructure quality and logistics service capabilities.

Third, improve the logistics performance of large-scale countries and promote the overall development of countries along the “Belt and Road”. Comparing the regression results of the three models of large, medium and small, the LPI passed the significance test of China’s import and export to large-scale countries at the 1% level. International logistics performance has the most significant impact on China’s import and export to large-scale countries along the “Belt and Road”, and the impact of logistics service capacity, customs clearance efficiency and logistics-related infrastructure level in each sub-index is the most significant. That is to say, the improvement of logistics performance of large-scale countries along the route will promote China’s import and export trade to a greater extent. Therefore, in order to promote the high-quality development of the “Belt and Road”, the government can increase investment in infrastructure construction in large-scale countries, promote the development of their import and export trade, and enhance the overall development of the “Belt and Road”.

Limitation and future research

In the research, the “Belt and Road” initiative countries are used as research samples. The sample interval is not broad enough, and the data source has certain limitations. Future research can consider many countries in the world with trade. Secondly, according to the number of populations, this paper divides different countries into three categories: large-scale countries, medium-scale countries and small-scale countries, and explores the different effects of international logistics performance on import and export trade in different countries. In the future, it can be further studied according to other aspects such as national income level, national geographical location and national economic development level. Finally, the fixed effect model is adopted in this paper. The research method is relatively simple, and the selection of control variables and sub-indicators is limited. Future research can try different research methods, add different control variables and sub-indicators to improve the technicality and comprehensiveness of the research. Although there are some limitations in this study, this study has certain positive significance for enriching the literature in the field of international logistics performance and international trade development, and enriches the current knowledge.