Impacts of the Sustainable Development of Cross-Border E-Commerce Pilot Zones on Regional Economic Growth

Abstract

This paper evaluates the sustainable development of cross-border e-commerce pilot zones and their impact on regional economic growth. A comprehensive performance evaluation system is constructed to assess the degree of sustainable development in the first five batches of cross-border e-commerce pilot zones in China between 2011 and 2020, which reveals significant regional differences and a clear “Matthew effect”. We also quantify the specific role of cross-border e-commerce pilot zones in promoting regional economic growth; specifically, we demonstrate that the level of sustainable development of cross-border e-commerce pilot zones has a significant positive impact on regional economic growth and show that these effects vary according to regional distribution, city level, and the degree of sustainable development of cross-border e-commerce pilot zones. On this basis, we explore the mechanism through which these factors influence one another and identify three main channels on which to focus for further development: industrial structure upgrades, institutional innovation, and consumption upgrades. Finally, based on empirical results, we propose differentiated policy suggestions for various regions and city levels through the provision of theoretical and practical support for promoting the healthy and sustainable development of cross-border e-commerce pilot zones and the stable growth of regional economies.

1. Introduction

Sustainable development is development that meets the needs of the present without compromising the ability of future generations to meet their own needs [1]. In recent years, cross-border e-commerce has gradually become an important topic in sustainable development research.

Cross-border e-commerce is the process of selling goods and services online to consumers in different countries using leveraging e-commerce websites. Cross-border e-commerce enables businesses to access new markets and customers, as well as to diversify their product offerings and sources of supply [2,3,4]. As a relatively new mode of international trade, cross-border e-commerce has several advantages, such as its low cost, high efficiency, and convenience. Moreover, this strategy provides new opportunities and challenges for enterprises to expand into overseas markets, enhance their international competitiveness, and promote trade balance [5,6,7]. With the acceleration of globalization and informatization, cross-border e-commerce has become a leading force in global trade in terms of interactive communication, resource sharing, and business model innovation, and it has disrupted traditional trade mechanisms [8,9].

The relationship between cross-border e-commerce and regional economic development can be examined from various perspectives. First, cross-border e-commerce can facilitate regional integration and cooperation via reducing trade barriers, enhancing information flow, and creating common standards and regulations. Second, cross-border e-commerce can foster regional innovation and competitiveness via stimulating demand, increasing productivity, and promoting knowledge spillovers. Finally, cross-border e-commerce can contribute to regional social development via creating employment opportunities, improving living standards, and empowering marginalized groups.

To adapt to the development trends and demand for cross-border e-commerce, the Chinese government established the first cross-border e-commerce pilot zone in 2015, with the goal of promoting upgrades in and development of the cross-border e-commerce industry via exploring innovative regulatory systems and operation modes [10]. This pilot zone is an important measure in terms of China opening up to the wider world. Its main functions are to facilitate trade, enable digitalization and paperless transactions, increase the scale and level of foreign trade, and promote economic transformations and upgrades. As of November 2022, China has successively established 165 cross-border e-commerce pilot zones nationwide, covering many cities and regions, including Chongqing, Guangzhou, Kunming, Fuzhou, Zhengzhou, Qingdao, Shenzhen, and Ningbo, among others [11].

These cross-border e-commerce pilot zones aim to help China promote the transformation and upgrade of foreign trade processes and regional economic development under continuously evolving conditions. As a result, the construction and advancement of these zones have become hot issues for academics and policy makers [12,13,14,15]. As an important part of the regional economy, a cross-border e-commerce pilot zone plays an increasingly crucial role in promoting regional economic growth, especially in terms of trade liberalization, facilitation, and internationalization. This function has significant implications. The sustainable development of cross-border e-commerce pilot zones can also improve the international competitiveness and innovation abilities of a regional economy [16]. Therefore, in the context of China’s active support and optimization of cross-border e-commerce policies and developments, it is crucial to explore methods for scientifically and systematically measuring the level of sustainable development of cross-border e-commerce pilot zones to better understand how they promote regional economic growth.

Nonetheless, there are several practical issues and challenges that arise from the rapid development of these pilot zones. These issues include an insufficient regulatory system, frequent cross-border online transaction disputes, uneven development of pilot zones, and intense competition, which not only hamper the development of cross-border e-commerce but also limit the scale of growth of these pilot zones. At the same time, existing studies lack in-depth analysis of the relationship study between the existing development of cross-border e-commerce pilot zones and the established goals, and how the relationship between the impact of cross-border e-commerce pilot zones and regional economic development are yet to be studied. Research on these issues will help to better understand the development level of cross-border e-commerce pilot zones; grasp the future development direction and the evaluation of policy implementation effects; clarify the influence mechanism between the development of cross-border e-commerce pilot zones and regional economic growth; and provide more targeted policy recommendations to promote the long-term development of cross-border e-commerce pilot zones and use the policy to promote the growth of the whole regional economy.

This study aims to explore the impact of the level of development of cross-border e-commerce pilot zones on the regional economy. First, from the perspective of performance evaluation of cross-border e-commerce pilot zones, this study selects evaluation indicators in three dimensions: foundation, service, and growth, and uses data related to the regional economic development of the first five batches of cross-border e-commerce pilot zones from 2011 to 2020 to conduct a comprehensive evaluation of the development level of cross-border e-commerce pilot zones. This allows an understanding of the current development level of cross-border e-commerce pilot zones and the effect of their policy implementation. Secondly, based on the measurement results of the development level of cross-border e-commerce pilot zones, we explore the mechanism of its influence on regional economic development. Combining the theories of innovation diffusion, industrial agglomeration, and economic growth, we empirically test and analyze whether industrial structure upgrading, institutional innovation, and consumption upgrading are effective mechanisms to influence the development level of cross-border e-commerce pilot zones on regional economic growth.

Therefore, this article examines the levels of sustainable development of cross-border e-commerce pilot zones and their impacts on regional economic growth. We construct a comprehensive performance evaluation system, asses the level of sustainable development of cross-border e-commerce pilot zones, and quantify the specific role of these pilot zones for promoting regional economic growth. Furthermore, we propose a mechanism through which the level of sustainable development of cross-border e-commerce pilot zones affects regional economic growth. The results elucidate the degree of heterogeneity in this impact, as well as specific mechanistic aspects.

The contribution of this work is threefold:

First, we measured the level of sustainable development of cross-border e-commerce pilot zones according to performance evaluations. Sixteen evaluation indicators were selected from three dimensions (i.e., basic, service, and growth), including the level of digital economy development and the financial development environment. These indices can comprehensively and accurately reflect the current situation and potential for the sustainable development of cross-border e-commerce pilot zones.

Second, we propose a mechanism describing how the level of sustainable development of cross-border e-commerce pilot zones impacts regional economic growth. We explore the degree of its impact and the relevant channels through panel regression analysis, focusing on three mechanistic schemes: industrial structure upgrading, institutional innovation, and consumption upgrading. The proposed mechanism simultaneously considers the heterogeneity of regional distribution, city level, and the level of sustainable development of cross-border e-commerce pilot zones, thereby revealing the internal logic and external conditions for optimizing regional economic growth.

Third, based on the empirical results, we discuss differentiated policies that can be implemented for various regions and city levels. In this way, we offer theoretical and practical support for promoting the healthy and sustainable development of cross-border e-commerce pilot zones and the stable growth of regional economies, while providing a reference for the construction of pilot zones in other regions.

The remainder of this paper is arranged as follows: the Section 2 presents a literature review; the Section 3 describes the index system for evaluating the level of sustainable development of cross-border e-commerce pilot zones and introduces the main research methods applied in this work; the Section 4 reports the empirical results; the Section 5 discusses the tests and analysis of the empirical results and proposes the corresponding mechanisms; the Section 6 summarizes the conclusions based on the results and puts forward relevant policy suggestions.

2. Literature Review

Cross-border e-commerce pilot zones represent a new mode of regional opening-up [17,18,19], and their impact on regional economic growth has emerged as a key issue of concern for academics and policy makers [20,21,22,23]. To date, domestic and foreign research on cross-border e-commerce pilot zones has mainly focused on the following four aspects:

(1)

Cross-border e-commerce pilot zones. The research in this field mainly introduces the definition, connotation, function, and goal of cross-border e-commerce pilot zones [24,25,26], as well as the background, developmental processes, and status quo of China’s cross-border e-commerce pilot zones [27,28,29]. These studies provide an important foundation for a deeper understanding of the basic situations and development trends related to cross-border e-commerce pilot zones [30,31,32,33].

(2)

Evaluations of sustainable development of cross-border e-commerce pilot zones. Research on this topic mainly explores how to scientifically evaluate the sustainable development level of cross-border e-commerce pilot zones through establishing various evaluation index systems and methods, e.g., analytic hierarchy processes [34,35,36,37], grey correlation methods [38,39], and data envelopment analysis methods [40,41,42]. These studies provide useful references for the comparative analysis of sustainable development levels of cross-border e-commerce pilot zones across different regions and city levels [43,44].

(3)

Regional economic growth. The research in this area mainly analyzes the concept, characteristics, and influencing factors of regional economic growth [45,46,47,48], as well as the current situation and challenges facing regional economic growth in China [49,50,51,52]. These studies provide an important theoretical basis and empirical evidence for exploring the relationship between cross-border e-commerce pilot zones and regional economies [53,54,55,56].

(4)

The relationship between cross-border e-commerce pilot zones and regional economic growth. Research focusing on this aspect mainly examines how cross-border e-commerce and pilot zones affect regional economic growth, e.g., through which channels and pathways [57,58,59], the extent of this impact [60,61,62], and the degree of heterogeneity [63,64,65]. It is believed that cross-border e-commerce and pilot zones have a positive effect on regional economic growth, mainly via facilitating trade [66], promoting digital economy development [67], cultivating new industry formats [68], and supporting upgrades to the industrial supply chain [69]. Some studies have revealed certain heterogeneities in the impacts of cross-border e-commerce and pilot zones on regional economic growth, particularly in terms of regional distribution [70], city level [60], and the degree of cross-border e-commerce development [71,72].

In summary, the current body of the literature on cross-border e-commerce pilot zones has elucidated some key aspects, although certain crucial knowledge gaps remain. For example, the methods for measuring the sustainable development level of cross-border e-commerce pilot zones require improvements. Specifically, the current evaluation index system and approach cannot fully reflect the sustainable development level of cross-border e-commerce pilot zones. In addition, the effects of cross-border e-commerce and pilot zones on regional economic growth, as well as the relevant mechanisms, merit further exploration. Finally, the policies implemented to promote the sustainable development of cross-border e-commerce pilot zones should be optimized. Therefore, the present study aims to enrich the current body of the literature in the field by filling these knowledge gaps.

3. Materials and Methods

3.1. Measuring the Level of Sustainable Development of Cross-Border E-Commerce Pilot Zones

3.1.1. Indicator Selection

The performance evaluation of cross-border e-commerce pilot zones conducted in this study used a comprehensive system. Based on existing research [73,74,75], we selected measurement indicators of the sustainable development level of cross-border e-commerce pilot zones from three dimensions (basic, service, and growth) to ensure that economic, social, environmental, and other key factors were comprehensively considered. The specific dimensions and sub-indicators are presented in

Table 1. Evaluation indicators of the level of sustainable development of cross-border e-commerce pilot zones.

Dimension	Indicator	Calculation Method	Data Source
Basic	Density of cross-border e-commerce companies	The ratio of the number of cross-border e-commerce enterprises to the total number of enterprises in the city	China customs enterprise import and export credit information publicity platform
	Cross-border e-commerce consumer density	The ratio of the number of cross-border e-commerce consumers to the total population of the city	Internal data from the Ministry of Commerce and cities in the cross-border e-commerce pilot zones
	Cross-border e-commerce transaction volume	Annual transaction volume of cross-border e-commerce pilot zones in cities in the test area	Internal data from the Ministry of Commerce and cities in the cross-border e-commerce pilot zones
	Density of foreign-invested enterprises	The ratio of the number of foreign-invested enterprises to the total number of enterprises in the city	Internal data, such as city yearbooks, from cross-border e-commerce pilot zones
Service	Number of cross-border payment companies	The number of registered enterprises carrying out cross-border point payments in the cities within the cross-border e-commerce pilot zones	Internal data, such as city yearbooks, from cross-border e-commerce pilot zones; China customs enterprise import and export credit information publicity platform
	Number of cross-border logistics companies	Number of cross-border logistics enterprises in cities within the cross-border e-commerce pilot zones	Internal data, such as city yearbooks, from cross-border e-commerce pilot zones; China customs enterprise import and export credit information publicity platform
	Number of cross-border e-commerce platforms	The number of cross-border e-commerce platform companies established in the cities within the cross-border e-commerce pilot zones	Internal data, such as city yearbooks, from cross-border e-commerce pilot zones; China customs enterprise import and export credit information publicity platform
	Number of operators of cross-border regulatory Sites	The number of cross-border supervision operators in cities within the cross-border e-commerce pilot zones	Internal data, such as city yearbooks, from cross-border e-commerce pilot zones; China customs enterprise import and export credit information publicity platform
Growth	Digital economic environment	Digital Economy Development Index	The Fifth Institute of Electronics of Ministry of Industry and Information Technology; China Internet Network Information Center; China Digital Economy Development Report
	Human capital	The ratio of the total number of students in colleges and universities at the end of the year to the total population of the region at the end of the year	Wind databases; city local statistical yearbook of cross-border e-commerce pilot zones
	Financial environment	Financial Inclusion Index	Research group of Peking University Digital Finance Research Center
	Business environment	The national ranking of the business environment of cities within the cross-border e-commerce pilot zones	Evaluation report on the business environment of Chinese cities

.

The basic factors include cross-border e-commerce enterprise density, consumer density, and transaction scale as three secondary indicators [76]. Foreign-invested enterprise density was included as a new secondary indicator to expand the scope of indicator selection within the basic efficiency index in the existing literature. In particular, the cross-border e-commerce enterprise density is an indicator of the number of cross-border e-commerce enterprises attracted via the pilot zone, which can reflect the scale and speed of development of the pilot zone. Cross-border e-commerce consumer density reflects the activity and frequency of cross-border online shopping from the perspective of consumers. This is an important indicator to measure market demand and consumption in pilot zone cities. Cross-border e-commerce transaction scale is another important indicator that measures the developmental level of cross-border e-commerce pilot zones through reflecting the transaction activity and economic benefits of pilot zone cities. The number of foreign-invested enterprises reflects the cross-border e-commerce foundation and the ability of pilot zone cities to attract foreign capital. Therefore, it is an important indicator to measure the internationalization of pilot zone cities.

The service factors include important indicators for evaluating the level of development of cross-border e-commerce pilot zones. In the present work, we selected four sub-indicators: cross-border payment enterprises and cross-border logistics enterprises, as well as novel indicators, cross-border e-commerce trading platforms and cross-border supervision site operators. The number of cross-border payment enterprises reflects the level of construction of cross-border payment systems in pilot zone cities, while the number of cross-border logistics enterprises serves as a measure of the degree of improvement in cross-border logistics facilities. The number of cross-border e-commerce platforms is an important indicator that reflects the diversity and market competition within the cross-border e-commerce market and trading channels. Cross-border supervision site operators can ensure fair competition and order in the cross-border e-commerce market. These indicators cover the service facilities required for cross-border e-commerce businesses. In general, the better the fundamental infrastructure of cross-border e-commerce development, the higher the service efficiency index of the pilot zones, and the more ideal the development situation of cross-border e-commerce pilot zones.

The growth factors include four sub-indicators (digital economy environment, human capital, financial environment, and business environment of pilot zone cities), which comprehensively reflect the potential and capabilities in terms of the sustainable development of pilot zones. The digital economy environment indicator reflects the status of information technology infrastructure construction, e-commerce application popularization, digital transformation abilities, and other key aspects of pilot zones. It is an important measure of the digital economic development in the pilot zones. Improving the digital economy environment can enhance the network connectivity and data transmission speed required for cross-border e-commerce, promote innovations and the diversification of cross-border e-commerce, and provide more technical support and motivation for advancements in cross-border e-commerce pilot zones [77]. The human capital indicator reflects the talent reserve, talent cultivation, and labor quality in pilot zones. This is a manifestation of the human resource-derived advantages of pilot zones. Abundant human capital can provide professional, technical, and management support for enterprises to ensure that the developmental needs of cross-border e-commerce pilot zones are met [78]. The financial environment indicator indicates the degree of openness, supervision, and service of the financial markets among pilot zones. This factor is a manifestation of the financial support system of pilot zones. An efficient and high-quality financial environment can increase the financing and payment efficiency of cross-border e-commerce transactions, while providing financial support and services for cross-border e-commerce [79]. The business environment indicator reflect the policy, investment, and market environments in pilot zones. Efficient and effective government services can increase the convenience of cross-border e-commerce development [80]. Meanwhile, increased policy support can provide more policy dividends for cross-border e-commerce, and policy stability can provide more developmental space and long-term guarantees for cross-border e-commerce.

3.1.2. Construction of Evaluation System

In the evaluation system, the coefficient of the variation method is used to weight each indicator for objective measurement, and then a cross-border e-commerce operation performance index is constructed. Specifically, the coefficient of variation method can consider the variation degree of the indicator, the difference in the average value, and more accurately reflect the relative importance of the indicator. By calculating and analyzing the indicator data, the weight of each indicator in the overall index is obtained to ensure that each indicator contributes equally to the overall index. The establishment of this indicator system can provide a scientific and reasonable method and basis for evaluating the performance of cross-border e-commerce operations.

The coefficient of variation method was used in this paper to assign weights to each indicator to objectively measure their importance. Then, a comprehensive performance indexing system was constructed to analyze cross-border e-commerce operation. Specifically, the coefficient of variation method can consider the degree of variation and differences in average values of indicators, which allows it to reflect the relative importance of these indicators more accurately [81,82]. By calculating and analyzing the data related to the indicators, we can obtain the weight of each indicator in the context of the total index to ensure that each indicator contributes equally [83,84]. The construction of this indicator system can inform scientific analytical methods and serve as a basis for evaluating the operational performance of cross-border e-commerce [85,86].

The score of a city in a certain dimension i can be expressed as shown in Equation (1),

$$\begin{array}{c}{X}_i={\omega }_i\frac{x_i-x_{min}}{x_{max}-x_{min}}\end{array}$$

(1)

where $X_i$ represents the score of a city in dimension $i$; ${\omega }_i$ represents the weight of the ith indicator in the comprehensive evaluation, such that ${\omega }_i\in \left(\mathrm{0,1}\right)$; $x_i$ is the actual value of the $i$th indicator; and $x_{min}$ and $x_{max}$ are the minimum and maximum values of the $i$th indicator in all pilot zones, respectively.

The weight of each indicator is then calculated using a coefficient of variation method, which can reveal the differences and relative importance of various indicators to achieve more accurate evaluation results. Specifically, for each indicator, we first calculate its standard deviation ${Stdev}_i$ and average value ${Average}_i$. The coefficient of variation formula for each indicator is shown in Equation (2):

$$\begin{array}{c}{CV}_i=\frac{{Stdev}_i}{{Average}_i}\end{array}$$

(2)

Then, Equation (3) can be used to calculate the weight of each indicator, where ${\sum }_i^{n}C{V}_i$ represents the sum of coefficient of variation in all indicators.

$$\begin{array}{c}{\omega }_i=\frac{C{V}_i}{{\sum }_i^{n}C{V}_i} \end{array}$$

(3)

The basic efficiency index, service efficiency index, and growth efficiency index of cross-border e-commerce pilot zone cities are denoted as ${Foundation}_i$, ${Serving}_i$, and ${Growth}_i$, respectively. The calculations of these indices (Equations (4)–(6)) are based on the Euclidean distance method.

$$\begin{array}{c} {Foundation}_i=1-\sqrt{\frac{{\sum }_{i=1}^n{\left(X_i-{\omega }_i\right)}^2}{{\sum }_{i=1}^n{{\omega }_i}^2}} \end{array}$$

(4)

$$\begin{array}{c}{Serving}_i=1-\sqrt{\frac{{\sum }_{i=1}^n{\left(X_i-{\omega }_i\right)}^2}{{\sum }_{i=1}^n{{\omega }_i}^2}} \end{array}$$

(5)

$$\begin{array}{c}{Growth}_i=1-\sqrt{\frac{{\sum }_{i=1}^n{\left(X_i-{\omega }_i\right)}^2}{{\sum }_{i=1}^n{{\omega }_i}^2}} \end{array}$$

(6)

According to Equations (4)–(6), the final comprehensive performance index $PL$ of each pilot zone city can be calculated using Equation (7):

$$\begin{array}{c} PL=1-\sqrt{\frac{{\left(1-{Foundation}_i\right)}^2+{\left(1-{Serving}_i\right)}^2+{\left(1-{Growth}_i\right)}^2}{3} } \end{array}$$

(7)

3.1.3. Computational Results and Analysis

As of February 2023, China has set up 165 cross-border e-commerce comprehensive pilot zones in 297 prefecture-level cities. The research data came from the Ministry of Commerce, China City Statistical Yearbook, China Customs, Wind database, etc. In order to ensure the availability, continuity, and effectiveness of the data, this paper selected the data related to the economic development of 105 cross-border e-commerce comprehensive pilot areas in the first five batches from 2011 to 2020, and excluded the areas with serious data deficiency (Suifenhe, Hunchun, Manzhouli, Xiongan New Area, Dehong Dai, and Jingpo Autonomous Prefecture).

In addition, in terms of the selection of data, it is found that the city statistical Yearbook provides the data of the whole city and the data of the municipal districts. Since not all cross-border e-commerce comprehensive pilot zones are set up in urban areas, the paper selects the data of the whole city in order to comprehensively evaluate the impact of cross-border e-commerce comprehensive pilot zones on the regional economy. In addition, the establishment of cross-border e-commerce comprehensive pilot zone will not only affect the urban area, but also affect the economic growth of the whole city, so it is more rigorous and accurate to choose the data of the whole city to study the impact of cross-border e-commerce comprehensive pilot zone on regional economic development.

The weight of each indicator in the cross-border e-commerce pilot zone was determined according to the method described, and the specific values are shown in

Table 2. Weight coefficients of indices for evaluating the sustainable development of cross-border e-commerce pilot zones.

Dimension	Indicator	Weight Factor
Basic	Density of cross-border e-commerce companies	0.2251
	Density of cross-border e-commerce consumers	0.1199
	Volume of cross-border e-commerce transactions	0.4160
	Density of foreign-invested enterprises	0.2400
Service	Number of cross-border payment companies	0.2982
	Number of cross-border logistics companies	0.1851
	Number of cross-border e-commerce platforms	0.2804
	Number of cross-border regulatory site operators	0.2362
Growth	Digital economy environment	0.4569
	Human capital	0.2933
	Financial environment	0.1170
	Business environment	0.1329

.

In the basic dimension, the cross-border e-commerce transaction volume has the highest weight (0.4160), indicating that the transaction volume is the key factor for measuring the developmental level of the cross-border e-commerce pilot zone. In this case, the overseas e-commerce market is more prosperous, and the exchange of goods and services is more frequent. The density of cross-border e-commerce enterprises and the density of foreign-invested enterprises also have relatively high weight coefficients (0.2251 and 0.2400, respectively), indicating that these types of enterprises play key roles in the development of the cross-border e-commerce pilot zone. A large number of cross-border e-commerce enterprises may mean that the pilot zone has a more complete industrial chain and a wider range of market choices. However, the weight coefficient of cross-border e-commerce consumer density is low (0.1199), which may suggest that the relative importance of the number of consumers is low in terms of evaluating the development of the cross-border e-commerce pilot zone based only on consumption. Thus, the number of participants may not fully reflect the developmental level of the cross-border e-commerce pilot zone.

In the service dimension, the weight coefficients of the four indicators are relatively balanced. The cross-border e-commerce platform is the core hub connecting consumers, enterprises, and suppliers, and cross-border e-commerce transaction enterprises provide consumers and enterprises with rich and convenient payment options. With lower transaction costs, cross-border e-commerce logistics companies can directly affect the quality, speed, and price of logistics services in the pilot zone, while cross-border supervision field operators can ensure fair competition and order in the market. It is clear that the development of the cross-border e-commerce pilot zone must comprehensively consider multiple service aspects and coordinate the development of various fields to effectively improve the overall competitiveness.

In the growth dimension, the weight of the digital economic environment index has the highest coefficient (0.4569) among all indicators in all three dimensions. Optimizing the digital economic environment can provide infrastructural and technical support, as well as market opportunities for the cross-border e-commerce pilot zone. It also helps to stimulate the vitality of innovation and increase the competitiveness of enterprises, thereby promoting the rapid growth of the cross-border e-commerce pilot zone. The weight coefficient of human capital is 0.2933, which indicates that talents play an important role in the growth of the cross-border e-commerce pilot zone; specifically, high-quality talent can help enterprises better respond to market changes, enhance their innovation capabilities, and achieve industrial upgrades. The weight coefficients of the financial environment (0.1170) and business environment (0.1329) are similar, and they are generally less important than other growth indicators. However, a good financial environment and business environment can still enhance the financing channels for enterprises, reduce financing costs, create favorable development conditions for cross-border e-commerce pilot zones, and reduce operating costs and risks for enterprises, all of which can support the sustainable development of cross-border e-commerce pilot zones.

Based on the indicator weight coefficients in Table 2, we first eliminated cities with significant data missing during the observation period (Suifenhe, Hunchun, Manzhouli, Xiong’an New Area, Dehong Dai, and Jingpo Autonomous Prefecture). We then calculated the comprehensive development level and sustainable development level of cross-border e-commerce pilot zones in the first five batches from 2011 to 2020. The average values corresponding to the levels of cross-border e-commerce development in these pilot zones from 2011 to 2020 were then calculated.

Table 3. The top ten and bottom ten pilot zone cities in terms of average developmental level.

Cities	Average Level of Basic Efficiency	Average Level of Service Efficiency	Average Level of Growth Efficiency	Average Level of Development in Cross-Border E-Commerce Pilot Zones	Rank	Batch	Echelon
Hangzhou	46.24	79.95	67.34	72.04	1	1	1
Shanghai	43.54	78.47	55.74	69.29	2	2	1
Shenzhen	35.05	80.87	37.56	59.23	3	2	1
Beijing	20.60	53.61	78.28	56.17	4	3	1
Guangzhou	26.85	51.88	46.93	48.75	5	2	1
Tianjin	20.80	36.73	26.54	34.31	6	2	2
Chengdu	22.15	26.93	36.60	32.54	7	2	2
Wuhan	29.77	27.17	30.48	29.86	8	3	2
Qingdao	19.62	22.90	24.86	22.03	9	2	2
Suzhou	30.07	7.06	19.30	21.62	10	2	2
…	…	…	…	…	…	…	…
Luzhou	2.14	4.66	0.00	2.14	91	5	3
Anqing	2.13	4.87	0.00	2.13	92	5	3
Heihe	2.10	4.19	0.20	2.10	93	5	3
Huangshi	2.07	4.53	0.24	2.07	94	5	3
Yan’an	2.00	4.23	0.00	2.00	95	5	3
Yueyang	1.92	4.69	0.03	1.92	96	5	3
Maoming	1.90	4.81	0.24	1.90	97	5	3
Dongying	1.71	4.91	0.17	1.71	98	5	3
Panjin	1.30	4.37	0.14	1.30	99	5	3
Haidong	0.77	4.00	0.05	0.77	100	5	3

presents the top ten and bottom ten pilot zone cities in terms of their average developmental level.

The computational results in Table 3 reveal that there is a significant gap in the developmental level of China’s first five batches of cross-border e-commerce pilot zones. The Hangzhou, Shanghai, Shenzhen, Beijing, and Guangzhou cross-border e-commerce pilot zones were the top five in terms of average developmental level during the observation period, and they were far higher than the other evaluated pilot zones. The already significant differences in regional development levels may gradually increase due to the “siphon effect” of cross-border e-commerce development, resulting in a “Matthew effect”, i.e., “the strong get stronger, and the weak get weaker”. In general, the development level of cross-border e-commerce pilot zones in eastern China is significantly higher than that in central and western China, showing a gradual trend of decline. This phenomenon indicates that geographical location, infrastructure, policy environment, and other factors influence the development of cross-border e-commerce pilot zones. However, the developmental levels of most pilot zones are relatively low (except for the Hangzhou, Shanghai, Shenzhen, Beijing, and Guangzhou cross-border e-commerce pilot zones). This observation reveals that China’s cross-border e-commerce system is still in an early stage of development, although it exhibits enormous developmental potential. To fully tap into these potentials, governments, enterprises, and research institutions need to continuously improve and promote the policy systems, technological innovations, and talent cultivation of cross-border e-commerce pilot zones for future developments. These discrepancies in terms of developmental levels also imply that there are some shortcomings when it comes to the development of cross-border e-commerce pilot zones. Specifically, they must be continuously improved and promoted in future development efforts. For example, there may be problems, such as unbalanced resource allocation, poor policy implementation, or incomplete industrial chains. In response to these problems, governments and relevant departments can take measures to promote inter-regional cooperation, improve resource utilization efficiency, break down regional barriers to development, and achieve coordinated development of cross-border e-commerce pilot zones.

In the subdivision dimension, Shenzhen has the highest average service efficiency (80.87), which is much higher than the other examined pilot zones. This result is consistent with the actual situation in that region. As an important economic center and developed e-commerce area in China, Shenzhen’s cross-border e-commerce pilot zone has received significant support and development opportunities, which have enabled a series of comprehensive cross-border e-commerce services, including logistics, warehousing, freight, and business consulting, to help cross-border e-commerce companies improve their operational efficiency and increase their international competitiveness. The service efficiency levels of Hangzhou, Shanghai, Beijing, and Guangzhou are generally higher than those of other pilot zones, and there is a significant gap between these top tier pilot zones and the others. This observation suggests that there are large regional differences in the number of cross-border e-commerce payments, logistics, platform companies, and site supervision operators in China’s cross-border e-commerce pilot zones. In terms of their basic efficiency and growth efficiency levels, the performance of Shanghai, Beijing, and Guangzhou are significantly higher than in Shenzhen, although the relative gap is smaller than that within the service efficiency level. These results show that the developmental levels of China’s cross-border e-commerce pilot zones still leave room for improvement. The developmental factors must be continuously enhanced to promote the sustainable development of the entire cross-border e-commerce industry.

According to the calculations of the sustainable development levels of the cross-border e-commerce pilot zones, there is a somewhat positive correlation between the sustainable development level of the pilot zone and the batches approved. However, this relationship is not completely positive, i.e., the higher the batch, the higher the development level of the pilot zones. Overall, after years of development, the development levels of the first three batches of cross-border e-commerce pilot zones are significantly higher than those of the fourth and fifth batches. Further analysis revealed that the cross-border e-commerce pilot zones in the second batch developed strongly (especially Shanghai, Shenzhen, and Guangzhou), and their development levels even caught up with the first batch (including Hangzhou). However, the development of the third batch of cross-border e-commerce pilot zones is generally weaker than the previous two batches (except Beijing, Wuhan, and several other pilot zone cities), and the development level of cross-border e-commerce pilot zones in the central region is generally more robust. Owing to the large number, wide scope, and short time span of the third, fourth, and fifth batches of pilot zone cities, the dividends related to their policy development have not been fully released; according to available data, however, there is still a large gap between the development levels of the first and second batches of cross-border e-commerce pilot zones. These results indicate that the successful development of the pilot zones depends on policy support and duration of operating time, although it also requires continuous improvements and optimizations in many aspects related to the pilot zone foundation, service, and growth potential (e.g., improving the logistics system, receiving financial support, service quality). The operating time of a cross-border e-commerce pilot zone approved by the state is indeed one of the important factors influencing the development of the pilot zone, although it is not the only determining factor.

3.2. Empirical Analysis

3.2.1. Variable Selection

As of February 2023, China had established 165 cross-border e-commerce pilot zones in 297 prefecture-level cities. The research data for this study were obtained from the Ministry of Commerce, China City Statistical Yearbook, China Customs, Wind Database, and other sources. To ensure the availability, continuity, and validity of the data, we selected information related to the economic development of the first five batches comprising 105 cross-border e-commerce pilot zones from 2011 to 2020, and we excluded regions with significant amounts of missing data (e.g., Suifenhe, Hunchun, Manzhouli, Xiong’an New Area, Dehong Dai, and Jingpo Autonomous Prefecture).

In addition, the data selection process revealed that the city statistical yearbook provides both city-wide data and data for smaller urban areas. Because not all cross-border e-commerce pilot zones are located in urban areas, we focused on the city-wide data to comprehensively evaluate the impact of cross-border e-commerce pilot zones on regional economies. Moreover, the establishment of cross-border e-commerce pilot zones affects the economic growth of the whole city—not only urban areas. Therefore, it is more rigorous and accurate to use city-wide data to study the impact of cross-border e-commerce pilot zones on regional economic development.

The research objects for the present study were the developmental levels of cross-border e-commerce pilot zones and regional economic development levels. To obtain more reliable estimations, we considered additional factors that affect regional economic growth as control variables and introduced non-ratio variables into the econometric model in natural logarithm form to reduce the heteroscedasticity of variables. The details regarding the selected variables are presented in

Table 4. Variables used in empirical analysis.

Type	Name	Meaning	Specification
Dependent variable	ln(GDP)	Regional GDP growth rate	Natural logarithm of regional GDP
	ln(PGDP)	Regional GDP growth rate per capita	Natural logarithm of regional GDP per capita
Core explanatory variable	DL	Development level of cross-border e-commerce pilot zone	Calculated as described above
Mediating variables	ISU	Industrial structural upgrade	The ratio of the total output value of the tertiary industry to the total output value of the secondary industry
	SI	System innovation	Fan Gang China Marketization Index
	CU	Consumption upgrade	Per capita consumption of urban residents
Control variables	SAVE	Total savings	Year-end savings balance of urban and rural residents/GDP
	IRIE	Innovation and Entrepreneurship	Innovation and Entrepreneurship Index
	SZG	Scientific spending	R&D investment/GDP
	INTERNET	Information	Natural logarithm of the number of Internet accesses

.

These variables are introduced in more detail below.

(1) Dependent variable (${GDP}_{it}$): One of the research objects of this work was the level of regional economic development, which is usually measured according to the regional gross domestic product (GDP) or per capita gross domestic product (PGDP). In general, the GDP or PGDP (i.e., high or low) can reflect the economic strength and developmental level of a region. To measure regional economic development, we used the natural logarithm of the real GDP as a dependent variable. The data used for this work came from the China City Statistical Yearbook of each pilot zone city from 2011 to 2020.

(2) Core explanatory variable (${DL}_{it}$): The main focus of this paper, and the core explanatory variable, is the developmental levels of cross-border e-commerce pilot zones. This indicator is determined based on the indicator selection, evaluation system construction, and the computational methods and results described in the previous section.

(3) Mediating variables ($M$): Industrial structure upgrading ($ISU$), institutional innovation ($SI$), and consumption upgrading ($CU$) were considered as mediating variables in this work and are described in detail below:

a. Industrial structure upgrading ($ISU$): Clark’s law states that technological advancements and economic development will accelerate changes to the economic structure, causing the industrial structure to become increasingly complex. After the technological revolution, the trend of “economic servitization” emerged, and the traditional method of using the non-agricultural output value ratio to measure industrial structure upgrading was no longer reasonable. Therefore, we used the ratio of the tertiary industry output value to the secondary industry output value to measure industrial structure. If the ISU factor increases, this means that the industrial structure is optimized and upgraded.

b. Institutional innovation ($SI$): Innovative driving force is one of the key factors for a country’s economic development, and studies have shown that institutional innovation in various regions of China has a significant positive effect on economic growth [87,88]. The marketization index is an important indicator for measuring the degree of marketization, which reflects the competitiveness and developmental level of a region’s market environment; this parameter can also be regarded as a manifestation of institutional innovation.

c. Consumption upgrading ($CU$): The development of cross-border e-commerce is closely related to consumption upgrading. Regional economic growth is not only an economic problem of balancing efficiency and equity, but it is also a social problem that involves multiple factors, including institutional innovation and consumption upgrading, among others. Industrial structure upgrading and consumption upgrading both stimulate and support regional economic growth. Thus, we apply the per capita consumption level of urban residents to measure the consumption upgrading indicator.

(4) Control variables ($C_{it}$): A series of economic indicators were considered as control variables to reduce the impact of other potential variables on the computed regional economic development level. This allows for a more accurate assessment of the relationship between the cross-border e-commerce pilot zone development and regional economic growth. The control variables used in this work are described in detail below.

a. Total savings rate ($SAVE$): The total savings rate is a region’s overall saving rate, which reflects residents’ savings and economic development in the region. A high total savings rate means that residents have sufficient savings funds, which can be used for investments and consumption, thereby supporting regional economic growth. Therefore, we used the ratio of the year-end total savings balance of urban and rural residents to the regional GDP to measure the indicator of total savings rate.

b. Innovation and entrepreneurship ($IRIE$): Regional economic development is closely related to regional innovation and entrepreneurship capabilities. Improving the level of innovation and entrepreneurship can increase the competitiveness of enterprises in the region via introducing new technologies, products, and markets, thereby promoting the economic vitality of the whole region. Based on previous research [89,90], we used the innovation and entrepreneurship index from Enterprises’ Big Data Research Center of Peking University as a measurement indicator.

c. Scientific expenditure ($SZG$): Increasing urban scientific expenditure can promote technological innovations, improve product quality, and enable production efficiency through using advanced technologies and management methods, thereby increasing the level of regional economic growth. Scientific expenditure can also foster talent aggregation and skill improvement to provide continuous human support for regional economic development. The present work uses the ratio of R&D input to GDP as a measurement indicator of scientific expenditure.

d. Informationization ($INTERNET$): This parameter can reflect a region’s situation in terms of information infrastructure, informationization implementation, and digital economy scale. Promoting regional informationization can trigger regional economic integration and coordinated development via accelerating inter-regional economic links and trade circulation. Therefore, we used the natural logarithm of the number of internet accesses as a measurement indicator of the regional informationization level.

Theoretical analysis of the influence of the development level of cross-border e-commerce comprehensive pilot zone on regional economic growth on stage of setting indicators is based on the diffusion of innovation theory, industrial agglomeration theory and economic growth theory. This paper selects three influencing mechanisms based on these three theories and the characters of the cross-border e-commerce pilot zone. They are industrial structure upgrading, institutional innovation, and consumption upgrading as the key analysis objects, and analyzes the promoting effect of cross-border e-commerce comprehensive pilot zones on regional economic development from different dimensions. At the same time, the research hypothesis is put forward: the development level of a cross-border e-commerce comprehensive pilot zone has a positive impact on regional economic growth, and this impact mechanism is mainly realized by promoting industrial structure upgrading, promoting institutional innovation, and promoting consumption upgrading.

For the stage of setting variables, we select 16 evaluation indicators from 3 dimensions of basic, service, and growth to measure the development level of the cross-border e-commerce comprehensive pilot zone. The basic efficiency index selects the density of cross-border e-commerce enterprises, the density of cross-border e-commerce consumers, and the scale of cross-border e-commerce transactions as the three secondary indicators. The density of foreign-invested enterprises is added as a new secondary index to update the index selection of basic efficiency index in the original literature.

The service efficiency index selects the number of cross-border payment enterprises which reflects the level of cross-border payment system construction in pilot cities, and the number of cross-border logistics enterprises can measure the improvement in cross-border logistics facilities. Also, the number of cross-border e-commerce trading platforms is an important indicator that reflects the diversity of cross-border e-commerce trading markets and trading channels and the degree of market competition. The number of operators in the cross-border supervision site can reflect the supervision efficiency of the cross-border e-commerce comprehensive pilot zone, that is, whether the supervision system of the cross-border e-commerce comprehensive pilot zone is sound and the level of supervision implementation and enforcement is appropriate.

According to the current economic and social development status, the growth efficiency index selects four sub-indicators, including digital economic environment, human capital, financial environment, and business environment of the pilot city, to comprehensively reflect the potential and ability of the comprehensive pilot area in sustainable development.

3.2.2. Model Specification

A. Benchmark Model

This paper focuses on the developmental levels of cross-border e-commerce pilot zones and their impact on regional economic growth, while also exploring the governing mechanism. We adopted the traditional trade gravity model as the benchmark model, as expressed in Equation (8),

$$\begin{array}{c}{Y}_{it}={\beta }_0+{\beta }_1{DL}_{it}+\alpha C_{it}+{\mu }_i+{\eta }_t+{\epsilon }_{it}\end{array}$$

(8)

where $Y_{it}$ represents the economic development level of city $i$ in year $t$, which is measured by the $lnGDP$ and $lnPGDP$ of each region; ${DL}_{it}$ represents the sustainable development level of the cross-border e-commerce pilot zone in city $i$ in year $t$, which is determined by the previous performance evaluation; $C_{it}$ represents a control variable; ${\mu }_i$, ${\eta }_t$, and ${\epsilon }_{it}$ are the regional fixed effect, time fixed effect, and error term, respectively; and ${\beta }_1$ is the coefficient of the core explanatory variable, reflecting the impact of the cross-border e-commerce pilot zone sustainable development level on regional economic growth. If the value of ${\beta }_1$ is positive and significant, the sustainable development level of the cross-border e-commerce pilot zone has a positive effect on regional economic growth; if ${\beta }_1$ is negative and significant, the sustainable development level of the cross-border e-commerce pilot zone has a negative effect on regional economic growth. If ${\beta }_1$ is not significant, the sustainable development level of the cross-border e-commerce pilot zone has a negligible impact on regional economic growth.

B. Mechanistic Analysis

To further explore the mechanism through which the sustainable development level of the cross-border e-commerce pilot zones influences regional economic growth, a mediating effect model was introduced. Specifically, the stepwise test regression coefficient method (Equation (9)) was adopted on the basis of existing research [91,92],

$$\left\{\begin{array}{l}{Y}_{it}=c_0+c_1{DL}_{it}+c_2{C}_{it}+{\mu }_i+{\eta }_t+{\epsilon }_{it}\\ M_{it}=a_0+a_1{DL}_{it}+a_2{C}_{it}+{\mu }_i+{\eta }_t+{\epsilon }_{it}\\ Y_{it}=b_0+b_1{DL}_{it}+b_2{M}_{it}+b_3{C}_{it}+{\mu }_i+{\eta }_t+{\epsilon }_{it}\end{array}\right.$$

(9)

where $M_{it}$ is the intermediary variable of the corresponding mechanism (e.g., $ISU$, $SI$, or $CU$). In the mediation effect model, $a$, $b$, and $c$ represent regression coefficients. Specifically, the $c_1$ represents the total effect of ${DL}_{it}$ on $Y_{it}$; $a_1$ represents the influence of the independent variable ${DL}_{it}$ on the mediator variable $M_{it}$; and $b_1$ represents the direct effect of ${DL}_{it}$ on $Y_{it}$ after controlling for the influence of the mediator variable $M_{it}$.

According to the stepwise regression method, after sequentially regressing the mediation effect model (comprising three formulas), it is possible to conclude that there is a mediating effect if (i) the estimation results show that $c_1$, $a_1$, and $b_2$ all pass the significance test, (ii) $a_1\times b_2$ has the same sign as $b_1$, and (iii) $b_1$ is smaller than $c_1$ (or its significance is reduced).

3.2.3. Data Sources

The basic data for the dependent variable in the empirical analysis presented in this paper came from the statistical yearbooks of the first five batches of cross-border e-commerce pilot zones in China from 2011 to 2020. The basic data for the explanatory variable came from the Ministry of Commerce, city statistical yearbooks, and China Customs database, which were used to calculate the developmental levels of cross-border e-commerce pilot zones in China. The basic data for the control variables and mediating variables were compiled from the Ministry of Commerce, city statistical yearbooks, and other sources. For data with missing values, a linear interpolation method was used to fill these gaps.

Table 5. Descriptive statistics of variables.

Variable	Observation	Mean	Standard Deviation	Median	Minimum	Maximum
GDP	1000	5.01 × 107	5.31 × 107	3.15 × 107	2.80 × 106	3.87 × 108
PGDP	1000	72,861.03	38,543.25	65,733.000	8580.000	4.68 × 105
DL	1000	9.67	12.34	5.670	0.000	100.000
INTERNET	1000	191.88	190.79	138.500	5.000	2088.000
SAVE	1000	0.65	0.29	0.625	0.004	2.726
SZG	1000	0.00	0.00	0.003	0.000	0.023
CXCYZS	1000	89.40	11.14	93.520	35.282	100.000
ISU	1000	0.07	0.01	0.068	0.000	0.078
SI	1000	12.13	2.27	12.149	5.824	19.017
CU	1000	13,610.16	6580.01	12,619.214	1990.546	71,028.552

shows the descriptive statistics of the variables.

4. Results

4.1. Hausman Test

The data used in this paper comprise panel data from 100 cross-border e-commerce pilot zone cities from 2011 to 2020. When establishing a regression analysis model, the Hausman test was used to determine whether to use a fixed-effects or random-effects model. The panel analysis conducted in this work includes stepwise regression of the full sample, regression of panel data sub-samples, and regression of endogeneity and a robustness test of panel data, and the Hausman test was used in each case for model selection.

Table 6. Results of the Hausman Test.

Parameter	Coefficient
Chi-square test value	202.83
p-value	0.0000

shows the results of the Hausman Test for the benchmark model, which rejects the null hypothesis; therefore, the empirical analysis in this work adopts a fixed-effects model.

4.2. Benchmark Regression Analysis

To ensure the authenticity and reliability of the regression results, we controlled for individual effects and time effects via introducing various control variables step-by-step for the regression, and the results are summarized in

Table 7. Benchmark regression results.

	(1)	(2)	(3)	(4)	(5)
Variable	$\mathit{l}\mathit{n}\mathit{G}\mathit{D}\mathit{P}$	$\mathit{l}\mathit{n}\mathit{G}\mathit{D}\mathit{P}$	$\mathit{l}\mathit{n}\mathit{G}\mathit{D}\mathit{P}$	$\mathit{l}\mathit{n}\mathit{G}\mathit{D}\mathit{P}$	$\mathit{l}\mathit{n}\mathit{G}\mathit{D}\mathit{P}$
ln_DL	0.5792 ***	0.3230 ***	0.2862 ***	0.2311 ***	0.2482 ***
	(11.97)	(5.00)	(4.71)	(4.76)	(5.30)
ln_INTERNET		0.2343 ***	0.2084 ***	0.1725 ***	0.1436 ***
		(5.19)	(4.75)	(3.75)	(3.45)
SZG			32.5837 ***	33.2236 ***	29.8214 ***
			(5.93)	(5.61)	(6.04)
IRIE				0.0069 ***	0.0063 ***
				(2.87)	(3.03)
SAVE					−0.2445 ***
					(−4.84)
Constant	16.2907 ***	15.6037 ***	15.6697 ***	15.3210 ***	15.6593 ***
	(189.59)	(102.01)	(107.95)	(108.23)	(101.38)
City FE	YES	YES	YES	YES	YES
Year FE	YES	YES	YES	YES	YES
N	999	999	999	999	999
$adj. R^2$	0.6704	0.6848	0.7237	0.7396	0.7728

Notes: The values in parentheses are $t$ values, and *** represent significance at the 1% significance levels.

.

In Table 7, column (1) shows the regression result without introducing any control variables, which reveals that the regression coefficient of the impact of the cross-border e-commerce pilot zone development level on regional economic growth is 0.5792. This passes the test at the 1% significance level, indicating a positive impact, i.e., the sustainable development of cross-border e-commerce pilot zones promotes regional economic growth.

The stepwise regression results after introducing the control variables are shown in columns (2) to (5), revealing that the regression coefficient of the impact of the cross-border e-commerce pilot zone development level on regional economic growth is still positive and passes the test at the 1% significance level. The variable sign and degree of significance have not changed appreciably, which indicates that the control variables are reasonable and effective. Meanwhile, after introducing the control variables, the adjusted R² values of each regression model are all greater than 0.5, and the F-statistics all pass the test at the 1% significance level, indicating that the overall fit of each regression model is relatively good.

Considering the final regression results in column (5), the regression coefficient of the impact of the cross-border e-commerce pilot zone development level on regional economic growth is 0.2482, which passes the test at the 1% significance level. The theoretical mechanistic analysis discussed in the previous section indicates that cross-border e-commerce pilot zones can provide a superior environment and more resources for cross-border e-commerce enterprises in the region, thereby promoting the rapid development and growth of cross-border e-commerce. Additionally, cross-border e-commerce pilot zones can increase the competitiveness of enterprises through providing various services, such as trade, logistics, finance, and technology to promote the expansion of international trade businesses. Finally, cross-border e-commerce pilot zones can also attract foreign investments and improve the regional international influence by supporting the diversification and outward-oriented development of the regional economy.

According to the regression results for each control variable, the regression coefficients associated with informationization, scientific expenditures, and innovation and entrepreneurship are all positive and statistically significant at the 1% significance level, which indicates that these control variables have a positive impact on regional economic growth. The regression coefficient of the total savings level is −0.2445, which is significantly negative at the 1% significance level, contrary to expectations. This is likely because the high total savings level may have a negative impact on current economic consumption, and insufficient demand will lead to excess social production capacity [93], which reduces the economic benefits of enterprises and ultimately slows the regional economic development.

5. Discussion

5.1. Endogeneity and Robustness Tests

The endogeneity problem in empirical research leads to bias in the results, and therefore, it is necessary to test the endogeneity to ensure reliable outcomes. Similarly, robustness test methods are used to verify the stability of the empirical results.

5.1.1. Endogeneity Test

To minimize the endogeneity bias caused by the possible time path dependence of economic activities, an IV (instrumental variable) estimation method was used, with the lagged (one period) explanatory variable as an instrumental variable. This approach eliminates the bias caused by endogeneity via exploiting the independence of instrumental variables.

Table 8. Endogeneity test results.

	(1)	(2)
	IV	IV
ln_lag_DL	0.5545 ***	0.3080 ***
	(30.65)	(11.81)
ln_INTERNET		0.1045 ***
		(7.07)
SZG		25.6995 ***
		(8.49)
IRIE		0.0025 **
		(2.19)
SAVE		−0.2127 ***
		(−8.91)
Constant	16.3854 ***	16.1172 ***
	(508.74)	(179.85)
N	899	899
adj. R2	0.6402	0.7048
LM	18.56	8.56
	[0.0000]	[0.0043]
Wald	135.66	30.26

Notes: The values in parentheses are $t$ values, and **, *** represent significance at the 5% and 1% significance levels, respectively.

shows the regression results for the instrumental variable with the lagged (one period) cross-border e-commerce pilot zone as an instrumental variable. The regression coefficient is positive for both models and passes the test at the 1% significance level.

In addition, based on the LM test and Wald test, the results in Table 8 indicate that there is no endogeneity problem or weak instrumental variable problem, meaning that the alternative instrumental variable is also effective. The sign of the regression coefficient and significance level are consistent with previous analyses, thus confirming the validity and reliability of the regression results discussed above.

5.1.2. Robustness Tests

To ensure the robustness and reliability of the empirical results reported herein, data tailoring and replacement variable indicators were used for robustness testing.

Data tailoring was conducted using the Winsorize tailoring method, which involves tailoring and processing for sample data at the 1% and 99% percentiles, followed by regression analysis. Meanwhile, $PGDP$ was replaced as a new dependent variable for further regression analysis. The robustness test regression results are shown in

Table 9. Robustness test results.

	(1)	(2)
Variable	Data Tailoring	Replace Dependent Variable
Wln_DL	0.2640 ***
	(5.28)
Wln_INTERNET	0.1316 ***
	(3.17)
WSZG	33.4724 ***
	(6.31)
WIRIE	0.0063 ***
	(3.01)
WSAVE	−0.2748 ***
	(−5.76)
ln_DL		0.1977 ***
		(4.90)
ln_INTERNET		0.1256 ***
		(3.35)
SZG		13.4466 ***
		(2.69)
IRIE		0.0086 ***
		(4.71)
SAVE		−0.2120 ***
		(−4.20)
Constant	15.6969 ***	9.4187 ***
	(106.08)	(58.67)
N	999	999
adj. R2	0.6864	0.6627

Notes: The values in parentheses are $t$ values, and *** represent significance at the 1% significance levels.

.

The regression result after data tailoring and processing reveals that the regression coefficient of the explanatory variable is 0.2640, which passes the test at the 1% significance level. Additionally, the significance level and coefficient sign are consistent with the previous results, indicating that the regression result remains stable after processing the outliers (i.e., it is not affected by outliers). Similarly, the results obtained after replacing the dependent variable show that the value of the cross-border e-commerce pilot zone development level is 0.1977, which also passes the test at the 1% significance level. Thus, replacing the dependent variable shows that the cross-border e-commerce pilot zone development level can effectively promote regional economic growth. When controlling for other variables that may affect the results, the regression coefficients obtained from the empirical research described in this paper are generally consistent with the previous benchmark regression results, indicating that the empirical results are sufficiently stable.

5.2. Heterogeneity Tests

Considering that the cross-border e-commerce pilot zone cities may have different impacts on regional economic growth due to regional distribution, city level, and pilot zone development level, we further examined the heterogeneity effects of these parameters on regional economic growth through sub-sample processing of the entire sample.

5.2.1. Regional Distribution Heterogeneity

Table 10. Regional distribution heterogeneity regression results.

	(1)	(2)	(3)
	Eastern China	Central China	Western China
Variable	$\mathit{l}\mathit{n}\_\mathit{G}\mathit{D}\mathit{P}$	$\mathit{l}\mathit{n}\_\mathit{G}\mathit{D}\mathit{P}$	$\mathit{l}\mathit{n}\_\mathit{G}\mathit{D}\mathit{P}$
ln_DL	0.314 ***	0.105 ***	0.280 ***
	(9.92)	(2.69)	(4.50)
ln_INTERNET	0.161 ***	0.0994 ***	0.110 ***
	(7.80)	(3.55)	(3.45)
SZG	23.25 ***	48.39 ***	54.14 ***
	(6.15)	(7.86)	(4.23)
IRIE	0.00504 ***	0.00927 ***	0.00765 ***
	(3.68)	(4.94)	(2.99)
SAVE	−0.224 ***	−0.179 ***	−0.393 ***
	(−6.71)	(−3.74)	(−6.43)
Constant	15.66 ***	15.66 ***	15.48 ***
	(138.57)	(112.88)	(86.20)
N	590	239	169
R2	0.660	0.736	0.728
Number of codes	59	24	17

Notes: The values in parentheses are $t$ values, and *** represent significance at the 1% significance levels.

shows the empirical heterogeneity regression results for three regions: Eastern China, Central China, and Western China.

The regression coefficient related to how the development level of the cross-border e-commerce pilot zone in the east impacts regional economic growth is 0.314 at the 1% significance level, which is higher than that in the central and western regions. This result indicates that in the eastern region, the economy is relatively more developed and the cross-border e-commerce pilot zone includes relatively complete infrastructure that has developed rapidly; together, these aspects have led to a more positive impact on regional economic growth. The regression coefficient related to the influence of the cross-border e-commerce pilot zone development level in the central region on regional economic growth is 0.105 at the 1% significance level. The impact of the development level of the cross-border e-commerce pilot zone in the western region on regional economic growth has a coefficient of 0.280 at the 1% significance level. These results show that compared with the eastern region, the development of cross-border e-commerce pilot zones in the central and western regions can promote regional economic growth, although the effect is small. This is because the development of the cross-border e-commerce pilot zone is influenced by numerous factors, including market size, market consumption capacity, logistics foundation, government policies, and human resources. The foundation for the development of all aspects of the central and western regions is relatively weak. Meanwhile, the eastern region has more developed infrastructure and superior resource endowments; it also benefits from a favorable policy environment. However, the current policy preference is transitioning to the central and western regions, and although the developmental levels of the cross-border e-commerce pilot zones in these regions are relatively low, they are constantly improving.

According to the empirical results and analysis, the coefficient describing how the development level of the cross-border e-commerce pilot zones in the western region influence regional economic growth is slightly higher than that in the central region. This observation indicates that the economic development of the western region is gradually accelerating, benefiting from the “Western Development”. The active promotion of a series of supporting policies, such as industrial restructuring and upgrading, has enabled remarkable progress. Although the western region is lagging behind the other regions in terms of infrastructure and industrial development, the rise of the western region has provided favorable conditions for economic diversification and spatially coordinated development. In the future, it will be beneficial to make full use of cross-border e-commerce pilot zone policies to effectively promote regional economic growth and increase international competitiveness.

5.2.2. City Level Heterogeneity

The sub-sample was analyzed to determine whether the city level of cross-border e-commerce pilot zone cities induced different effects on regional economic growth. For this analysis, 100 cross-border e-commerce pilot zones were divided into 3 groups: municipal, sub-provincial, and prefecture-level cities.

Table 11. City-level heterogeneity regression results.

	(1)	(2)	(3)
	Municipalities	Sub-Provincial Cities	Prefecture-Level Cities
Variable	$\mathit{l}\mathit{n}\_\mathit{G}\mathit{D}\mathit{P}$	$\mathit{l}\mathit{n}\_\mathit{G}\mathit{D}\mathit{P}$	$\mathit{l}\mathit{n}\_\mathit{G}\mathit{D}\mathit{P}$
ln_DL	0.630 ***	0.531 ***	0.191 ***
	(2.83)	(5.50)	(7.92)
ln_INTERNET	0.0731 **	0.0997 **	0.143 ***
	(2.32)	(2.28)	(9.09)
SZG	48.31 *	27.03 ***	26.01 ***
	(1.78)	(5.07)	(7.04)
IRIE	0.116 **	0.0302 ***	0.00773 ***
	(2.18)	(2.78)	(7.34)
SAVE	−0.786 *	−0.419 ***	−0.243 ***
	(−1.99)	(−3.59)	(−9.50)
Constant	5.870 ***	13.33 ***	15.50 ***
	(7.74)	(15.21)	(196.14)
N	40	150	809
R2	0.668	0.819	0.684
Number of codes	4	15	81

Notes: The values in parentheses are $t$ values, and *, **, *** represent significance at the 10%, 5% and 1% significance levels, respectively.

shows the sub-sample regression results for these city levels, where the municipalities were directly under the central government.

The regression coefficients of the cross-border e-commerce pilot zone developmental levels for municipalities directly under the central government, sub-provincial cities, and prefecture-level cities are all positive and pass the test at the 1% significance level, indicating that pilot zones in all three examined city levels have a positive impact on regional economic growth. The impact of municipalities is the highest, followed by sub-provincial cities, while prefecture-level cities have relatively low impact. These distinctions may be related to factors, such as the city development level, economic scale, infrastructure, and industrial layout.

In China, municipalities directly under the central government and sub-provincial cities usually have higher political statuses, which means that they can obtain more resources and policy support. They also have better economic foundations and more complete infrastructure, which allow them to attract cross-border e-commerce enterprises and related industries, thereby promoting the development and upgrades of the cross-border e-commerce industry. Overall, this allows them to have more positive impacts on regional economic growth. Compared with municipality-level cities and sub-provincial cities, prefecture-level cities are generally weaker in terms of their political status, economic foundation, and infrastructure. These aspects make it more difficult to harness the potential of cross-border e-commerce pilot zones in prefecture-level cities, thus affecting their contributions to regional economic growth.

In addition, municipalities directly under central government and sub-provincial cities often have more open market environments and more convenient transportation conditions, which are conducive to cross-border e-commerce docking with international markets.

5.3. Mechanistic Analysis

The theoretical hypothesis outlined in the discussion above proposes that the cross-border e-commerce pilot zone developmental level will affect regional economic growth by impacting industrial structure upgrades and institutional innovation aspects. Therefore, we conducted empirical tests to elucidate the transmission mechanism relating cross-border e-commerce pilot zone development and regional economic growth.

5.3.1. Upgrading the Industrial Structure

The fixed-effects regression model concerning the individual steps and time points of the industrial structure upgrading mechanism is presented in

Table 12. Industrial structure upgrading impact mechanism results.

	(1)	(2)	(3)
Variable	$\mathit{l}\mathit{n}\_\mathit{G}\mathit{D}\mathit{P}$	$\mathit{I}\mathit{S}\mathit{U}$	$\mathit{l}\mathit{n}\_\mathit{G}\mathit{D}\mathit{P}$
ln_DL	0.2482 ***	0.0100 ***	0.2080 ***
	(5.30)	(5.85)	(9.08)
ln_INTERNET	0.1436 ***	0.0009 ***	0.1078 ***
	(3.45)	(8.27)	(7.34)
SZG	29.8214 ***	0.0848 ***	26.5229 ***
	(6.04)	(3.56)	(8.71)
IRIE	0.0063 ***	0.0001 ***	0.0042 ***
	(3.03)	(6.87)	(4.12)
SAVE	−0.2445 ***	−0.0007 ***	−0.2167 ***
	(−4.84)	(−3.72)	(−8.80)
ISU			3.8887 ***
			(9.15)
Constant	15.6593 ***	0.0561 ***	13.4778 ***
	(101.38)	(93.43)	(53.86)
N	999	990	990
adj. R2	0.6728	0.6399	0.6674

Notes: The values in parentheses are $t$ values, and *** represent significance at the 1% significance levels.

.

In this table, column (1) shows the benchmark regression results for how cross-border e-commerce pilot zone development affects regional economic growth, column (2) shows the regression results for how cross-border e-commerce pilot zone development affects industrial structure upgrades, and column (3) shows the specific impact regression results for how cross-border e-commerce pilot zone development and industrial structure upgrades impact regional economic growth under the action of industrial structure upgrading.

Notably, the explanatory variable (i.e., cross-border e-commerce pilot zone development level) in the three models passed the significance test, and the regression coefficient of industrial structure upgrading in column (3) also passed the significance test, indicating that there is a partial mediation effect. The specific regression coefficients revealed that the impact coefficient of cross-border e-commerce pilot zone development on industrial structure upgrading is positive (0.0100) and significant at the 1% significance level. This result indicates that the development of cross-border e-commerce pilot zones will increase the level of industrial structure upgrades, which is consistent with the theoretical analysis and verifies the research hypothesis. Further analysis indicated that the regression coefficient of the industrial structure upgrading level in column (3) is significant at the 1% level, indicating that cross-border e-commerce pilot zone development will promote regional economic growth via supporting industrial structure upgrades.

Specifically, cross-border e-commerce pilot zones can promote upgrades and transformations of traditional industries during the development of cross-border e-commerce industries, thus enabling regional economic growth:

First, cross-border e-commerce pilot zones can generate industrial agglomeration effects by attracting a large number of cross-border e-commerce enterprises, which will drive local economic development and promote local industrial advancements. For example, the development of the e-commerce industry requires significant logistical and warehousing service support, which will simultaneously drive the development of the related industries.

Second, cross-border e-commerce pilot zones can also promote local enterprises’ technological and managerial improvements, thereby increasing the competitiveness of the entire region. For example, cross-border e-commerce enterprises and platforms often have advanced technology and management experience, which allows local enterprises to enhance their own technology and management aspects through cooperation, learning, and competition with these enterprises.

Third, cross-border e-commerce pilot zones can also promote local service industry development. Cross-border e-commerce industry development requires a lot of service support in terms of payments, logistics, finance, and other services, which will promote local service industry development and growth.

In summary, cross-border e-commerce pilot zones can have a positive impact on regional economic growth through industrial upgrading, which supports regional economic transformations and upgrades.

5.3.2. Institutional Innovation

The fixed-effects regression model of the individual steps and time points related to the institutional innovation mediation transmission mechanism is presented in

Table 13. Institutional innovation impact mechanism results.

	(1)	(2)	(3)
Variable	$\mathit{l}\mathit{n}\_\mathit{G}\mathit{D}\mathit{P}$	$\mathit{S}\mathit{I}$	$\mathit{l}\mathit{n}\_\mathit{G}\mathit{D}\mathit{P}$
ln_DL	0.2482 ***	1.8291 ***	0.0697 ***
	(5.30)	(14.25)	(3.16)
ln_INTERNET	0.1436 ***	0.9832 ***	0.0463 ***
	(3.45)	(12.22)	(3.44)
SZG	29.8214 ***	91.8013 ***	19.5965 ***
	(6.04)	(5.34)	(7.25)
IRIE	0.0063 ***	0.0622 ***	0.0001
	(3.03)	(10.91)	(0.08)
SAVE	−0.2445 ***	−0.9367 ***	−0.1521 ***
	(−4.84)	(−6.72)	(−6.88)
SI			0.1012 ***
			(19.46)
Constant	15.6593 ***	−1.2932 ***	15.7763 ***
	(101.38)	(−2.95)	(231.65)
N	999	990	990
adj. R2	0.6728	0.7265	0.7468

Notes: The values in parentheses are $t$ values, and *** represent significance at the 1% significance levels.

. The explanatory variable (cross-border e-commerce pilot zone development level) in all three models passed the significance test, and the mediation variable (institutional innovation level) in column (3) also passed the significance test, indicating a partial mediation effect. The regression impact coefficient of cross-border e-commerce pilot zone development on the institutional innovation level is positive (1.8291) and significant at the 1% significance level. This result indicates that cross-border e-commerce pilot zone development will drive regional institutional innovation, which is consistent with the theoretical analysis and verifies the research hypothesis.

Further analysis revealed that the regression coefficient of the institutional innovation level in column (3) is significant at the 1% level, indicating that the cross-border e-commerce pilot zone development will support regional economic growth by promoting institutional innovation. Cross-border e-commerce pilot zones play a key role in institutional innovation by focusing on optimizing the policy environment and enhancing the international business atmosphere. These efforts help to attract foreign investments and technologies, which inject vitality into the regional economy. With policy support, enterprises are more likely to obtain financial and technical assistance, thus accelerating the pace of industrial upgrading and efficiency improvements.

In addition, cross-border e-commerce pilot zones actively promote innovation and entrepreneurship, support technology transfer and industrial incubation, and cultivate new economic growth points. By constructing an innovation ecosystem, pilot zones encourage industrial technological upgrades and innovation-driven development. These factors jointly provide strong support and guarantees for rapid regional economic development. In this context, cross-border e-commerce pilot zones can help enterprises optimize resource allocation by improving operational efficiency, reducing trade costs, and improving supply chain management. The pilot zones also use digital and information technologies to improve service quality and meet growing consumer demands. This developmental approach improves regional competitiveness and forms a virtuous circle, thereby continuously promoting regional economic growth.

5.3.3. Consumption Upgrading

The fixed-effects regression model of the individual steps and time points related to the consumption diversification mechanism is presented in

Table 14. Consumption upgrading impact mechanism results.

	(1)	(2)	(3)
Variable	$\mathit{l}\mathit{n}\_\mathit{G}\mathit{D}\mathit{P}$	$\mathit{l}\mathit{n}\_\mathit{C}\mathit{U}$	$\mathit{l}\mathit{n}\_\mathit{G}\mathit{D}\mathit{P}$
ln_DL	0.2482 ***	0.2903 ***	0.0675 ***
	(5.30)	(10.48)	(3.99)
ln_INTERNET	0.1436 ***	0.1413 ***	0.0557 ***
	(3.45)	(8.10)	(5.35)
SZG	29.8214 ***	19.2396 ***	17.8465 ***
	(6.04)	(5.16)	(8.19)
IRIE	0.0063 ***	0.0121 ***	0.0012 *
	(3.03)	(9.87)	(1.66)
SAVE	−0.2445 ***	−0.1931 ***	−0.1244 ***
	(−4.84)	(−6.41)	(−7.01)
ln_CU			0.6224 ***
			(32.29)
Constant	15.6593 ***	7.1674 ***	11.1982 ***
	(101.38)	(76.23)	(75.47)
N	999	999	999
adj. R2	0.6728	0.6109	0.8322

Notes: The values in parentheses are $t$ values, and *, *** represent significance at the 10% and 1% significance levels, respectively.

.

Again, the explanatory variable (cross-border e-commerce pilot zone development level) in all three models passed the significance test, and the mediation variable (consumption diversification) in column (3) also passed the significance test, indicating a partial mediation effect. The impact coefficient of the cross-border e-commerce pilot zone development level on consumption diversification is positive (0.2903) and significant at the 1% significance level, indicating that cross-border e-commerce pilot zone development will promote consumption diversification. This result is consistent with the theoretical analysis and verifies the research hypothesis.

Further analysis indicated that the regression coefficient of consumption diversification in column (3) is also significant at the 1% level, meaning that the cross-border e-commerce pilot zone development will promote regional economic growth through consumption upgrading. Cross-border e-commerce pilot zones can effectively promote consumption upgrades by supporting brand transformations and upgrades, optimizing the product supply chain, and promoting new consumption modes (e.g., “boundaryless retail” and “social e-commerce”). Consumption upgrading is an important driving force of economic growth because it can improve productivity, increase employment and income, and inject vitality into the regional economy. To take advantage of consumption upgrading, enterprises need to constantly improve their product quality and service level to meet consumers’ increasingly diversified and personalized needs. This type of consumer-driven change stimulates innovation in research and development, while supporting the production and marketing of enterprises, thus promoting industrial structure adjustments and optimization.

Cross-border e-commerce pilot zones also enable consumers to access high-quality domestic and foreign goods and services more conveniently, which improves consumer experience and satisfaction. In addition, consumption upgrading can promote the integration and synergy of traditional industries and emerging industries, thus forming new industrial chains and formats. Combined online and offline “new retail” modes and “social e-commerce” (carried out through social media) are new business models emerging in the context of consumption upgrading. These formats promote regional economic development and create employment opportunities and industrial development space for society. In the consumption upgrading process, cross-border e-commerce pilot zones can also promote the development of logistical, financial, cultural, and creative industries. This helps to foster industrial synergy and agglomeration, which further promote regional economic growth.

6. Conclusions

In this work, we established a cross-border e-commerce pilot zone sustainable development evaluation system and applied it to measure and analyze the developmental levels of China’s first five batches of cross-border e-commerce pilot zones. We also explored the impact mechanism and effects of cross-border e-commerce pilot zone development on regional economic growth. The results indicated that the sustainable development of cross-border e-commerce pilot zones has a significant positive impact on regional economic growth, mainly through three pathways: promoting industrial structure upgrades, institutional innovation, and consumption upgrades. However, these impacts exhibit heterogeneity in terms of regional distribution, city level, and cross-border e-commerce pilot zone sustainable development level. Our analysis also revealed significant gaps and shortcomings in the development of China’s cross-border e-commerce pilot zones; improvements are required in multiple areas, spanning the foundation, services, and growth.

Based on the research results presented herein, we propose the following policy suggestions:

(1)

Strengthen the cooperation and exchange between cross-border e-commerce pilot zones, break down regional development barriers, encourage resource sharing and complementary advantages, and improve the overall competitiveness and synergy of cross-border e-commerce pilot zones.

(2)

Increase policy support for cross-border e-commerce pilot zones, tailor relevant laws and regulations, establish a supervision system, provide more policy dividends, create development space for cross-border e-commerce enterprises, and stimulate market vitality to stimulate innovation.

(3)

Accelerate the digital transformation of cross-border e-commerce pilot zones, promote innovation and upgrading of information technology, financial services, and logistics, and provide more efficient, convenient, and secure transaction environments to increase the service quality for cross-border e-commerce.

(4)

Foster talent cultivation for cross-border e-commerce pilot zones, attract human capital, provide professional, technical, and management support for cross-border e-commerce, and promote industrial upgrades and innovations.

The limitations of our study are: (1) The data selected in this study mainly come from the regional economic development data of the first five batches of cities in the comprehensive pilot zone of cross-border e-commerce from 2011 to 2020. The comprehensive pilot zone of cross-border e-commerce has been further developed to include the seventh batch (November 2022), while the final comprehensive pilot zone examined in this paper fails to include the data of the two batches of cities newly developed in 2022. (2) We mainly discuss the impact mechanism of cross-border e-commerce comprehensive pilot zones on regional economic growth from three aspects: industrial structure upgrading, institutional innovation, and consumption upgrading. However, in fact, there may be other important influencing factors that have not been taken into account, such as employment and population mobility, investment, brand building, consumer preferences, etc.

As far as academic implications are concerned, cross-border e-commerce will have an increasingly significant impact on regional economic development as a new trade mode. In the future research, more attention should be paid to the development dynamics and policy changes of cross-border e-commerce comprehensive pilot zones under the background of economic globalization, and the interactive relationship between cross-border e-commerce and the regional economy should be extensively discussed, so as to provide more valuable research results for policy makers and practitioners.