1. Introduction
High-quality development (HD) is a development theme of China’s 14th Five-Year Plan. Concerning this, promoting the quality of foreign trade is an important starting point for implementing the Plan. It is proposed to improve the quality of China’s foreign trade by innovating service trade (ST), accelerating the development of new trade forms, and improving the level of trade digitalization to provide important support for HD in economies. HD is a development mode with quality and efficiency as the main goals, which means lower production input cost, better resource allocation efficiency, and better development efficiency. HD emphasizes coordinated development between people, the economy, and society [1]. It is a more efficient and sustainable way of social development supported by innovation [2]. After years of rapid development, China’s economic development has turned to the period of HD [3,4], and new growth momentum for HD is the focus of general attention. High-quality development of service trade (HDST) contains two meanings. The first is the static indicators’ growth such as the scale and performance of ST, and the second is the optimization of dynamic indicators such as trade structure and innovation ability [5]. These are important for enhancing the competitiveness of foreign trade and improving HD. The means of promoting HDST is a problem that requires urgent solutions presently.
With the continuous improvement of the information technology level, digital economy (DE) is deeply integrated into various fields of economic development [6]. DE refers to components of economic output based solely or primarily on digital technologies [7]. The convergence of a series of innovations has led to the transformation and development of DE [8]. In this process, DE injects new development momentum into traditional industries [9] and gradually nurtures new business models and development advantages [10], which promotes HD [11,12]. DE can effectively improve economic development levels [13]. At present, China’s ST is in a bottleneck development period, and a vigorous DE brings new momentum for promoting ST. In the global value chain, the position of China’s service industry has been enhanced by developing DE, and DE has become an important momentum for HDST in China [14]. Through the deepening integration of digital technology (DT) and various fields of the service industry, new driving forces for promoting HDST will be stimulated. Additionally, important technologies and elements will be provided to support HDST, thus driving the improvement of the overall economic level.
This study first discusses the impact of DE in promoting HDST in China from a theoretical aspect and analyzes the mediating effect of human capital level. Consequently, the fixed-effect model, mediating effect model, robustness test, and heterogeneity test have been used to empirically examine the impact of DE on promoting HDST and its mechanism. This was based on panel data from 18 sample regions in China from 2012 to 2021. After in-depth research, suggestions for providing references for relevant departments to formulate policies are provided. At present, there are few empirical studies on the impact of DE in promoting HDST in China. The research results of this study provide a theoretical basis for promoting HDST in China through developing DE and deepening the integration of ST and DT. In addition, this study deeply analyzes the intermediary role of human capital level, which further provides theoretical support for promoting HDST in China. Research results further enrich the existing research and have a very important practical significance in the context of China’s vigorous efforts to promote HD.
The rest of the contents are structured as follows: In Section 2, the literature review is presented. In Section 3, theoretical analysis and hypotheses are provided. In Section 4, variable design and model setting are introduced. In Section 5, empirical analysis is presented. In Section 6, conclusions and suggestions are provided.
2. Literature Review
2.1. High-Quality Development of Service Trade
With the rapid development of the service economy, ST has been increasingly valued by various countries, which can effectively promote transformation and growth of the economy and trade [15]. The development of contemporary ST has condensed more advanced production factors such as knowledge and technology. In comparison, the service sector with lower trade costs tends to have higher production efficiency [16].
With the continuous expansion of the ST scale, its structure also tends to be technology and knowledge-intensive industries [17], and its influence on economic growth continues to increase [18]. The development of ST is increasingly important [19] and becomes an important momentum for improving the economy [20]. The development level of ST is also an important reflection of the country’s economic level and international competitive advantage [21]. Developing ST is an important cornerstone for building a strong trading country and an important channel to improve the economy and enhance comprehensive strength. The HDST provides important support for enhancing international competitiveness [22], and is of great significance for improving the economy and enhancing the voice of the global value chain.
For a long time, America has taken a leading position in the field of ST, especially in technology and knowledge-intensive industries, with strong competitive advantages [23,24]. After years of attention and development, the scale of China’s ST has been expanding and remarkable results have been achieved. As an important part of China’s foreign trade, ST has played an important role in optimizing and upgrading the trade structure [25]. The results of Figure 1 show that China’s ST presents a positive and stable development trend. Except for a slight decline in the proportion of ST in foreign trade due to COVID-19 in 2020 and 2021, China’s emerging ST (excluding tourism and transportation) has a good momentum of development in general. The proportion of its ST in foreign trade also shows a steady growth trend. However, compared with America and other powerful countries, China’s ST has long been in a deficit. This indicates weak international competitiveness [26], especially in technology and knowledge-intensive industries such as intellectual property usage fees, without a competitive advantage [27]. The HDST in China still faces many difficulties. In this regard, Li and Lv [28] pointed out that the service industry was an important basis for promoting ST, and the added value of ST could be improved by optimizing and upgrading the service industry structure.
At present, the digitalization trend of ST is significant, and digital elements play an important role in promoting the development of ST [5], which can inject new momentum into HDST.
2.2. Digital Economy
DE is the product of integrating DT and economic activities [29]. With the support of information technology, DE presents remarkable advantages in terms of development momentum, development efficiency, and development quality [30]. The development of the DE has redefined national competitive advantages [31], and become the key force in changing global economic structure and reshaping the global competitive landscape [32].
From the perspective of promoting domestic economic development, DE is an important momentum [33] and has a significant impact on production and lifestyle. There are some bottlenecks in the process of transitioning from a linear economy to a circular economy [34], and digitalization can play an important role in supporting a circular economy [35]. The digital transformation of enterprises can reduce costs and improve innovation capabilities, thus improving production efficiency [36]. While improving the production efficiency of enterprises, consumer data can be better analyzed, and matching efficiency for supply and demand can also be effectively improved [37], thus promoting the expansion of consumption. In addition, by actively promoting the speed of industrial transformation [38] and improving the rationalization level of industrial structure [39], DE can effectively optimize industrial structure [40,41], improve the ability of industrial innovation, and provide important support for improving quality and efficiency of the economy [42]. For HD of China’s economy, DE plays a important positive role by promoting innovation development [43]. DE can effectively reduce economic costs such as search and transportation [44], and the development of the internet can better promote companies’ R&D and innovation [45]. Regardless of economic level, digital development can exert a positive influence on the growth of a country’s economy [46].
From the perspective of promoting the development of foreign trade, digitalization has swept all trade models, and digital transformation has given new development vitality to traditional trade models and spawned new models [47]. DE can effectively promote the export scale and improve export quality [48]. The convergence of industrial digitalization and digital industrialization has promoted the improvement of export technology [49] and significantly improved the export competitiveness of China’s manufacturing industry [50]. This means DE has become an important momentum for promoting HD of foreign trade. On the one hand, digital transformation has effectively reduced trade costs and created more new opportunities for enterprises and consumers [51]. On the other hand, the vigorous development of digital trade is promoted based on the in-depth development of DT. The development of digital trade has improved the efficiency of traditional trade [52]. Compared with traditional trade, digital trade is faster, cheaper, and can generate higher economies of scale [53]. Digital trade not only helps to promote innovation and reduce trade costs but also forms new trade contents and trade benefits through innovation [54]. It also becomes an important engine to promote growth of foreign trade [55]. Meanwhile, the development of DE has an important impact on human capital [56], promotes transformation and upgrading of human capital [57], and significantly improves the level of human capital structure [58]. The upgrading of human capital structure actively promotes the improvement of regional innovation ability [59], improves the technical level of export products, and promotes the improvement of foreign trade competitiveness. For the development of ST, DE can enhance the export competitiveness of ST [60], and provide an important driving force for promoting HDST.
While DE brings opportunities, there are also some risks worth noting. Digital technologies such as big data are now widely used in various industries, which has led to big loopholes in data privacy and security. Additionally, personal data privacy cannot be effectively protected. Meanwhile, the development of DT allows data to flow more quickly and freely across the world, which also poses a threat to a country’s national security and financial system. The state also faces greater challenges in financial regulation. Besides, some digital giant platforms may form market monopolies, preventing potential companies from entering the market, which is adverse to innovation and fair competition. In addition, the development of DT will also eliminate some low-skilled industrial workers, which has a certain impact on the stability of the job market [37]. With digital transformation, enterprises also face information security challenges and risks such as security vulnerabilities [61]. Shang et al. [62] found that enterprises mainly faced 21 risk factors in the digital transformation process, such as risk caused by information lag or distortion, and the risk of data exposure.
Due to the influence of economic level and investment in DE construction, there are obvious differences existing in developing levels of DE in the world. For developed countries, DE has been considered important for a long time and has become an integral part of economic development [63]. For developing countries, DE is becoming increasingly important [64]. However, many developing countries have shortcomings, such as weak digital infrastructure and a lack of development funds for enterprises. This makes the development advantages and potential of DE not well tapped and utilized in these countries [65]. After years of attention and development, the development of China’s DE has achieved remarkable results, although the overall digitalization level is still far behind developed countries. However, in e-commerce and some other fields, China has a certain leading advantage. The development of DE injects new impetus into the economy, which can only alleviate but not reverse the downward trend of potential growth of the economy in China due to economic maturity. With the development of DE, facing challenges such as invasion of privacy, oligopoly, labor unemployment in traditional industries, and financial risks, the Chinese government needs to strengthen monitoring and maximize the benefits of digital development [66].
2.3. High-Quality Development of Service Trade and Digital Economy
DE has brought a new round of opportunities for ST. Digital transformation is crucial [67]. The most prominent feature of contemporary ST is digitalization, and the in-depth application and reform of digitalization have promoted the innovative development of ST. Through research, Choi [68] found that increasing internet usage and access in a country could promote the growth of ST. Zhang [69] found that the increase in the level of internet use actively promoted the growth of China’s ST. DT has effectively reduced the cost of service provision [70], and the distance cost of ST has been reduced with the development of the internet and improved connectivity between countries [71]. On the basis of greatly improving the cross-border trade ability of services [72], DT has actively promoted the transformation of the ST mode and the form of industrial organization. Using sample data from 49 countries, Nath and Liu [73] studied the impact of ICT on 10 ST projects, such as finance and transportation, and found that the development of ICT had positive impacts on these 10 ST projects to varying degrees.
HDST is an important engine for HD of China’s economy. HDST not only refers to the expansion of trade scale but more importantly, the optimization of trade structure, development of innovation ability, and the improvement of competitiveness. The development and application of DT reduce the cost of ST, expand its scope, and create new services [5]. It thus provides a superior development environment for ST and significantly improves the development efficiency of ST. With the development of DE, the internal momentum for promoting HDST in China has become increasingly prominent, and new business forms and advantages have emerged. With the development of DE, digital infrastructure is continuously improved, which promotes technology innovation, significantly improves regional total factor productivity [74], and provides important material and technical support for HDST. Qian [75] found that service industries with different degrees of digitalization have great differences in efficiency loss; the higher level of digitization, the less loss of efficiency. DE plays a positive role in optimizing the service industry structure and its HD [76]. The structure of ST continues to be optimized and upgraded, laying a solid foundation for HDST when the continuous development of DT is relied on. In addition, the continuous development of digital communication technology while reducing trade costs has also promoted the trading ability of a wider range of services [77]. Meanwhile, the development of DE deepens the integration of DT and ST and gives birth to new business forms such as digital service trade [78]. Compared with traditional ST, digital service trade is more extensive in application space and more advanced in production factors. Digital service trade is conducive to technological innovation [79], and its development can actively promote economic growth [80]. With the continuous deepening of the digital development of the global economy, digital service trade is increasingly important. It is an effective means to reshape national competitive advantages [81] and an important starting point for promoting HDST in China.
2.4. Summary
From the literature review, the research results of DE in promoting economic and trade development are relatively rich. However, a few research considers the impact of DE on the HDST. Additionally, there is very little research on the relationship between DE and HDST in foreign countries. Relevant researches in China are still in the initial stage, and the existing research is mainly discussed and elaborated from the theoretical aspect, and there are a few empirical research. Based on the construction of relatively reasonable evaluation index systems for DE and HDST, this study explores the impact of DE on HDST in China from both theoretical and empirical perspectives. Additionally, suggestions are proposed for HDST in China from the perspective of developing DE. This study is a further supplement to existing research results and provides an important reference for relevant departments to make decisions.
3. Theoretical Analysis and Hypothesis
3.1. High-Quality Development of China’s Service Trade and Digital Economy
With the development of DE, the application and integration of DT are promoted in various industries. Relying on DT, resource allocation of the service industry has been further optimized, production efficiency has been further improved, digital transformation of traditional service enterprises has been actively promoted, and the service model and the quality of service supplied have been improved. Through the usage of DT such as big data, enterprises can better understand the service needs of consumers and meet such needs more efficiently. DT not only effectively reduces the cost of service provision and the distance cost of ST, but also realizes the matching of supply and demand faster and more accurately. By reducing cost and improving the efficiency of ST, optimizing and upgrading the industrial structure of ST, developing DE can effectively improve the quality and comprehensive competitiveness of ST. In addition, innovatively applicating DT is an important momentum for developing new business forms [82]. The deep integration of DE and ST has spawned many new business forms, which have new competitive advantages, promoting the innovative development of ST and providing an important engine for HDST.
Based on the above discussion, Hypothesis 1 is proposed.
DE can actively promote HDST in China.
3.2. The Mediating Effect of Human Capital
Lim and Kim [83] studied the influence of immigration on the export trade of America and found that immigrants from countries with high levels of human capital effectively improved the export trade of America. In the digital transformation process, human capital is a key factor enabling the improvement of the economy and trade, and continuous improvement of human capital can promote HDST. On the one hand, a better level of human capital is conducive to developing the service industry [84], meanwhile, human capital accumulation can promote innovation of technology, and in DE, the higher level of human capital accumulation, the stronger role of DE in promoting a service-oriented industrial structure [85], which lays a good industrial foundation for developing ST. On the other hand, the development of DT enables practitioners in the ST industry to have more opportunities and ways to obtain education and training, and effectively improve practitioners’ knowledge and skills. The improvement of practitioners’ overall knowledge and skills can promote the improvement of production efficiency in the ST industry. In addition, DE not only brings more development opportunities to the ST industry but also makes the ST industry’s demand for high-tech and high-knowledge talents more urgent. This also forces practitioners to constantly improve and optimize their skills to meet the developing needs of the industry. Meanwhile, enterprises also need to take measures to attract more high-skilled talents into the ST industry. Thus, it promotes the growth of highly skilled personnel in the industry and optimizes the human capital structure, which can effectively promote high-end ST and support innovation in the ST industry.
Based on the above discussion, Hypothesis 2 is proposed.
DE can promote HDST in China by improving human capital level.
4. Variable Design and Model Setting
4.1. Variable Design
4.1.1. The Explained Variable
HDST: To reflect HDST in China more comprehensively, this article refers to relevant research literature [86,87]. Considering the availability of data and characteristics of ST, it combines the requirements of HD and the actual development situation of China’s ST. The evaluation index system is constructed from four dimensions of ST: development basis, openness, sustainability, and innovation level. The weight of each index and the HDST index in sample regions are calculated by the entropy weight method. The specific index system composition and index weight are shown in Table 1.
Due to space constraints, Figure 2 only shows the average value of HDST in 18 sample regions from 2012 to 2021. For HDST, results show that Beijing and Shanghai have high levels. The development of ST is unbalanced in different regions of China, and there are obvious differences [88].
4.1.2. Explanatory Variable
DE: Existing studies mainly measure DE through two methods: One is to use a single index, such as the network readiness index, and the other is to construct a comprehensive index system. Milošević et al. [89] used 13 variables such as e-commerce sales to measure the digitalization of the economy. Zhang et al. [90] constructed an evaluation system considering three levels of DE: Infrastructure, industrial development, integration, and application. Wang et al. [91] measured DE from four aspects: Infrastructure, social impact, digital innovation, and digital application, growth of economy, and jobs. Referring to the above research and taking into account data availability and the development situation of China’s DE, the evaluation index system of DE in this study is constructed considering three dimensions: digital infrastructure, digital industry development, and digital innovation level. The weight of each index and DE index in sample regions are calculated by the entropy weight method. The specific index system composition and index weight are shown in Table 2.
Due to space constraints, Figure 3 only shows the average value of DE in 18 sample regions from 2012 to 2021. For DE, the results show that Guangdong and Jiangsu have high levels. In different regions of China, the level of DE is of great difference, and the regional DE level has a high consistency with the economic level [91].
4.1.3. Control Variables
This study selected the development of goods trade (CT), government intervention (GI), the proportion of employees in the service industry (SE), and resident income level (RI) as control variables. Among them, the development of trade in goods (CT) is measured by the proportion of trade in goods to GDP; government intervention (GI) is measured by local government budget expenditure as a share of local GDP; the proportion of employees in the service industry (SE) is measured by the proportion of employees in the tertiary industry in total employment of local people; resident income level (RI) is measured by the per capita disposable income of urban residents. To unify the dimension and alleviate the influence of heteroscedasticity, the resident income level takes the natural logarithm value.
4.1.4. Mediator Variable
Human capital level (HC): Yu and Wu [92] constructed the human capital index system considering three dimensions: knowledge, health, and technology. This study mainly focuses on the improvement of knowledge and skills of human capital caused by DE. Therefore, constructing an index system for measuring the level of human capital from two levels: Knowledge and technology. The knowledge level includes two indicators: The proportion of universities per 10,000 people and the government’s education expenditure; the technological level includes two indicators: The intensity of R&D expenditure (R&D expenditure/GDP), and the number of patents granted.
Table 3 is the description of the variables. All data comes from the China Statistical Yearbook, Yearbook of Provinces, Statistical Yearbook of Provinces, Business Yearbook of Provinces, and Peking University Digital Finance Research Center. Due to the serious lack of ST data in some regions of China, a total of 18 samples of provinces, municipalities, and autonomous regions were retained in this article. For missing data in the retained samples, the mean method is used to fill in. If the total ST value of the region in a year is available, but the import and export data are missing, then the export value is filled using the mean method, and the import value is equated to the total ST value minus the export value.
4.2. Model Setting
To analyze impact of DE on HDST in China, based on Tao and Zhang, who conducted a study on the impact of DE on ST using panel data at the national level [93], the model is constructed as follows:
HDSTp,t = α0 + α1DEp,t + α2Xp,t + μp + δt + εp,t (1)
where p indicates region and t indicates time; HDSTp,t is the explained variable, representing the HDST level of region p in year t. DEp,t is the core explanatory variable, representing the DE level of region p in year t. Xp,t are control variables. μp controls individual fixed effects; δt controls time fixed effect; εp,t represents random disturbance term.To further study the indirect impact of DE on HDST in China, the mediating effect model is used to test the transmission mechanism of Hypothesis 2. The model is constructed as follows:
Mp,t = β0 + β1DEp,t + β2Xp,t + μp + δt + εp,t (2)
HDSTp,t = γ0 + γ1DEp,t + γ2Mp,t + γ3Xp,t + μp + δt + εp,t (3)
Here, Mp,t represents the mediator variable, that is, human capital level. If the regression coefficient α1 of DE in model (1) is significantly positive, then model (2) and model (3) are tested successively. Otherwise, there is no intermediary effect. If the β1 in model (2) is significantly positive, which indicates that DE has a significant impact on the intermediary variable; then model (3) is tested. If both γ1 and γ2 in model (3) are significantly positive, which indicates that human capital plays a part in the mediating effect. If γ1 is not significant, γ2 is significantly positive, indicating that human capital plays a complete mediating role. γ1 represents the direct effect, and β1 × γ2 represents the intermediate effect.
5. Empirical Analysis
5.1. Descriptive Statistics of Variables
Results in Table 4 show that, for HDST, the average is 0.166, the minimum is 0.030, and the maximum is 0.686; for DE, the average is 0.167, the minimum is 0.009, and the maximum is 0.882. Results further show great differences in the level of HDST and DE in different regions of China.
5.2. Regression Results of the Benchmark Model
In this part, according to the Hausman test results, the fixed-effect model is used for parameter estimation to empirically test the impact of DE on HDST. Meanwhile, the robustness of the model is tested by the stepwise regression method. Column (1) in Table 5 only adds the core explanatory variable DE for regression, results indicate that DE has a significantly positive impact on HDST in China. Control variables CT, GI, SE, and RI are gradually added to columns (2)–(5). As control variables are added one by one, the R2 of the model increases, indicating that the explanatory power of the model is enhanced and effective.
As to the core explanatory variable, the development level of DE has a significant positive impact on HDST. After the addition of control variables, the impact of DE on HDST has increased, and its positive impact is very significant. This indicates that DE has positively promoted HDST in China. Based on this, Hypothesis 1 is verified. For different regions in China, it is necessary to seize opportunities for the development of DE, combine regional development advantages, and deepen the integration of the regional service industry and DT, thus promoting HDST. Compared with previous studies, Tao and Zhang [93] conducted empirical research using sample data from 92 countries and pointed out that DE actively promoted the development of national or regional ST. They argue that regarding ST export, high-income countries or regions have a more obvious role in promoting ST, while in terms of ST import, the promotion effect of low-income countries or regions is more obvious. Li [94] used the comparative method and other research methods to analyze the impact of DE on China’s ST and pointed out that DE effectively optimized and upgraded the structure of the service industry. However, the study argues that there were some difficulties in the core technology of China’s digital infrastructure, and only by breaking through these difficulties could China’s digital service trade gain an international voice in the global value chain. Overall, although there are differences in specific research perspectives, the relevant research results all reflect that DE has a positive role in the development of ST.
Moreover, all the control variables were identified to have a significant positive impact on HDST. First, the development of trade in goods has promoted HDST in China. Karmali and Sudarsan [95] found trade in goods an important factor affecting ST. They also suggested that the growth of trade in goods could drive the growth of ST, and the growth of developed countries’ effect is higher than developing countries. Second, the Chinese government has introduced numerous policies in recent years to improve the development of ST, providing a guarantee for HDST. For example, the free trade zone policy has played a significant role in upgrading the service industry structure [96], laying a good foundation for HDST. Third, the rise in the employment level of the service industry reflects the good development momentum of the service industry and provides a better talent base for the service industry. This further optimizes and upgrades the service industry structure, which is conducive to the HDST. Fourth, improving resident income levels is conducive to China’s ST. Given China’s actual situation, on the one hand, the rise in residents’ income levels reflects good economic development. Rondinelli and Kasarda [97] pointed out that economic growth can promote the improvement of trade levels. On the other hand, it also upgrades the service consumption demand and improves the developing quality of ST.
5.3. The Robustness Test
5.3.1. The Endogeneity Test
The impact of DE on HDST may also have endogenous problems. First, both may be affected by unobservable factors. Second, there may be a two-way causal relationship between them. For this reason, this study draws on the idea of Ma et al. [98] and uses the number of fixed phone users at the end of the past years as an instrumental variable to conduct a two-stage least squares regression (2SLS). On the one hand, the development of DE comes from the use of fixed phones and the popularity of users. On the other hand, the number of fixed phone users at the end of the historical year has little impact on the current HDST. In this part, the logarithm of the number of fixed phone users at the end of the year in each sample region of China during 1981–1990 is selected as the instrumental variable, denoted as LNFT. Results in Table 6 show that DE still plays a significant role in HDST after considering the endogeneity problem.
5.3.2. Replacing the Explained Variable
The export status of ST is an important reflection of a country’s trade and economic strength, and countries with good development of ST often have strong service export capacity [99]. Here, the export value of ST is used to reflect the sustainability of ST in the original index system of HDST. This replaces the TC index of ST and ST development index in the original HDST index system to form a new index system. It is therefore re-calculated to get a new evaluation index of HDST. The panel fixed-effect model is used for re-evaluation. Results in Table 7 show that DE still has a significant positive impact on HDST after replacing the explained variable, which indicates that the original conclusion is stable.
5.4. The Heterogeneity Test
The heterogeneity test is used here to verify whether the above regression results exist as heterogeneous. Based on the actual development situation in China, this article focuses on analyzing the heterogeneity of the impact of DE on HDST from two aspects: Different regions, and different periods.
5.4.1. The Regional Heterogeneity Test
Different regions in China differ greatly in terms of economic development level and resource endowment. Concerning existing classification methods, this article divides the sample areas into three regions: Eastern, central, and western, and analyzes the impact of DE on HDST from different regions. Among them, Beijing, Jiangsu, Tianjin, Guangdong, Zhejiang, Shanghai, Fujian, and Hainan belong to the eastern region; Henan, Heilongjiang, Hunan, and Anhui belong to the central region; Chongqing, Sichuan, Guizhou, Yunnan, Shaanxi, and Xinjiang belong to the western region. Due to the small number of samples in the central region, in the analysis of heterogeneity, the central region and the western region are combined into one region: Central and western region.
Columns (1)–(2) in Table 8 show the regression results of the eastern, central, and western regions. The regression coefficients of DE in the regions all have positive significance. This indicates that the promotion effect of DE on HDST has not changed substantially due to regional differences. However, the influence of different regions is different, and the influence of the central and western regions is higher than eastern region. Specifically, due to the advantages of the developed economy, a relatively high level of industrial structure, a relatively perfect infrastructure, and other aspects, the development of DE in the eastern region has actively improved the service industry and ST, and now is in a period of stable development. For the central and western regions, the Chinese government has focused on continuously promoting strategic support for regional development in recent years, effectively improving regional digital infrastructure, DT, and digital industry. Compared with the previous relatively backward development basis, the development of the DE has released more vitality and influence. For later development, it is necessary to further strengthen the integration of DE and regional advantageous industries and further stimulate the development vitality of DE.
5.4.2. The Time Heterogeneity Test
The development of the DE has obvious period characteristics. In December 2015, at the opening ceremony of the Second World Internet Conference, the initiative to promote the construction of ‘digital China’ was formally put forward for the first time. Additionally, a new journey of ‘digital China’ construction began. Therefore, this article takes 2016 as the time node to study the impact of DE on HDST in China during 2012–2015 and 2016–2021. Columns (4)–(5) of Table 8 show the regression results for two time periods, respectively. Regression coefficients of the two time periods have positive significance, indicating that the promotion effect of DE on HDST has not changed substantially according to the period, but the influence of different periods is different, and the influence coefficient of 2016–2021 is higher than that of 2012–2015. Specifically, China has long attached importance to the development and application of the internet and modern information technology, which has provided a good foundation and environment for DE. In recent years, China has further increased policy support, which has effectively improved DE and effectively promoted the integrated development of DE and industry. It has also derived many new business forms and new models and actively promoted HDST.
5.5. Analysis of the Mediating Effect
From the perspective of human capital, this article has analyzed the intermediary transmission mechanism of DE affecting HDST. Here, the mediating effect model is used to test the transmission mechanism. According to the results in Table 9, DE promotes HDST in China by improving human capital. Again, human capital has a partial mediating effect on the impact of DE on HDST. The intermediary effect of human capital is 0.195 (0.816 × 0.239). Hypothesis 2 is therefore verified. For ST in various regions of China, DE can enhance the regional human capital level, further develop regional innovation capability, and promote HDST.
6. Conclusions and Suggestions
6.1. Conclusions
Through the construction of an evaluation index system, this article takes human capital as a mediator variable. The fixed-effect model and the mediating effect model are used to empirically test the impact of DE on HDST in China in multiple dimensions and its internal mechanism. The research results show that, first, DE can actively promote HDST in China, and the conclusion is still valid after the robustness test. Second, DE can promote HDST in China by improving human capital level. Third, the impact of DE on HDST in China is heterogeneous. Compared with the eastern region, DE has a greater promoting effect on HDST in the central and western regions. After 2015, DE has a greater promoting effect on HDST in China.
6.2. Suggestions
Based on the above discussion, these suggestions are put forward.
First, local governments should further increase policy support for developing DE. They should improve the construction of digital infrastructure, and give priority to the development of basic technologies closely related to DE, such as big data and blockchain. The integration of DT and industry should be strengthened, and more importance should be attached to the cultivation and development of new forms and models of DE. It is necessary to continuously optimize the environment for the development and innovation of DE, strengthen the innovation of DT, and attach importance to the transformation and application of DT achievements. By comprehensively improving the DT level and DE, the HDST will be further improved, and new development momentum will be injected into the HD of the economy and trade.
Second, different regions in China differ greatly in terms of economic development level and resource advantages. Different regions should combine their regional advantages to develop DE and ST, strengthen the integration of competitive industries and DT, and fully stimulate the vitality of DE. For example, DE is conducive to developing tourism service trade, especially in regions with high tourism resource endowments [100]. China’s Yunnan Province has comparative advantages in tourism resources. Through deepening the application of DT in the tourism industry, strengthening deep integration of traditional tourism service trade and DT, and innovating the supply mode of tourism service, transaction costs could be reduced. The efficiency of tourism service trade could be improved to build a more advanced and dynamic value chain of tourism service trade. For areas with weak development of DT, it is necessary to speed up the construction of digital infrastructure, and accelerate the process of digitization, thus improving the level of the economy and trade. For regions with more developed DT, it is necessary to further focus on DT innovation, and strengthen the cultivation and development of new forms and models of DE. In summary, all regions should combine their characteristics, find the right development orientation, fully tap the advantages of DE, improve the level of DE, and promote HD of economy and trade.
Third, it is necessary to increase the training and development of talent teams and comprehensively improve human capital. For college students, it is necessary to strengthen innovation cultivation and entrepreneurship ability, conform to the current construction process of ‘digital China’, and properly integrate the basic courses of DT into the talent training system of college students. For on-the-job personnel, appropriate digital skills training can be conducted. For R&D personnel, it is necessary to formulate a series of measures to encourage their innovativeness and provide a superior innovation environment for them. For the HDST, it is necessary to train a group of interdisciplinary talents who master the professional knowledge and skills of DT and ST. At the same time, the external talent introduction strategy should be improved. By continuously optimizing and upgrading human capital, the stock of human capital in the field of ST should be fully revitalized to provide a solid human capital guarantee for DE to promote HDST.
6.3. Limitations
Some limitations exist in this study. First, it does not consider whether there is a spatial spillover effect resulting from the impact of DE on HDST. Second, this study only considers the intermediate variable of human capital level, and other possible intermediary variables are not studied. As a result, future research can take inferences from this study and investigate these two aspects.
Conceptualization, C.D.; methodology, C.D.; software, Y.X.; validation, C.D., D.T. and Y.X.; formal analysis, C.D.; investigation, C.D.; resources, C.D.; data curation, C.D.; writing—original draft preparation, C.D. and D.T.; writing—review and editing, C.D., D.T. and Y.X.; visualization, D.T., C.D. and Y.X.; supervision, D.T.; project administration, D.T.; funding acquisition, C.D. All authors have read and agreed to the published version of the manuscript.
Not applicable.
Not applicable.
Data can be available from the authors on request.
The authors declare no conflict of interest.
Footnotes
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.
The HDST Index system.
| Primary Indicator | Secondary Indicator | Weight |
|---|---|---|
| Development basis | The proportion of tertiary industry in the GDP | 0.039 |
| Employment in information transmission, software and information technology services | 0.158 | |
| Openness | FDI in the service industry | 0.122 |
| Sustainability | TC index of ST | 0.032 |
| Scale of ST development (ST volume/GDP) | 0.227 | |
| Innovation level | Number of patents granted | 0.177 |
| Technology market maturity (technology market turnover/GDP) | 0.245 |
The DE Index system.
| Primary Indicator | Secondary Indicator | Weight |
|---|---|---|
| Digital infrastructure | Number of internet broadband access ports | 0.065 |
| Penetration of mobile phone (expressed in number of mobile phones per 100 people) | 0.037 | |
| Number of domains | 0.131 | |
| Digital industry development | Digital Financial Inclusion Index (expressed in Peking University Digital Financial Inclusion Index) | 0.031 |
| Software and information technology services size (expressed in software revenue) | 0.171 | |
| E-commerce scale | 0.139 | |
| Digital innovation level | R&D funds for industrial enterprises above designated size | 0.124 |
| R&D personnel of industrial enterprises above designated size | 0.137 | |
| Number of invention patent applications of industrial enterprises above designated size | 0.165 |
Description of Variables.
| Type | Variable | Symbol | Definition |
|---|---|---|---|
| Explained variable | High-quality development of service trade | HDST | Index system of HDST |
| Explanatory variable | Digital economy | DE | Index system of DE |
| Control variables | Development of goods trade | CT | Trade volume of goods/GDP |
| Government intervention | GI | Government budget expenditure/GDP | |
| Proportion of employees in the service industry | SE | Employees in the tertiary industry/Total employment | |
| Resident income level | RI | Per capita disposable income of urban residents | |
| Mediator variable | Human capital level | HC | Human capital index system |
Descriptive Statistics of Variables.
| Variable | N | Mean | Min | Max | Std. Dev. | |
|---|---|---|---|---|---|---|
| Explained variable | HDST | 180 | 0.166 | 0.030 | 0.686 | 0.154 |
| Explanatory variable | DE | 180 | 0.167 | 0.009 | 0.882 | 0.160 |
| Control variables | CT | 180 | 0.174 | 0.006 | 0.646 | 0.151 |
| GI | 180 | 0.231 | 0.107 | 0.429 | 0.079 | |
| SE | 180 | 45.930 | 21.800 | 83.100 | 12.423 | |
| RI | 180 | 10.453 | 9.785 | 11.320 | 0.331 | |
| Mediator variable | HC | 180 | 0.195 | 0.025 | 0.808 | 0.132 |
Notes: Results displayed in the table were obtained using STATA 14.
The fixed-effect regression results.
| Variable | (1) | (2) | (3) | (4) | (5) |
|---|---|---|---|---|---|
| DE | 0.466 *** |
0.523 *** |
0.527 *** |
0.534 *** |
0.530 *** |
| CT | 0.150 ** |
0.154 *** |
0.154 *** |
0. 148 *** |
|
| GI | 0.267 *** |
0.294 *** |
0. 315 *** |
||
| SE | 0.001 ** |
0. 002 ** |
|||
| RI | 0.090 * |
||||
| Constant | 0.089 *** |
0.053 *** |
−0.008 |
−0.068 ** |
−0.984 * |
| Province | Yes | Yes | Yes | Yes | Yes |
| Year | Yes | Yes | Yes | Yes | Yes |
| N | 180 | 180 | 180 | 180 | 180 |
| R2 | 0.776 | 0.787 | 0.810 | 0.817 | 0.821 |
Notes: Results displayed in the table were obtained using STATA 14. *, **, and ***, respectively, represent p < 0.1, p < 0.05, and p < 0.01; t-statistics are in parentheses.
2SLS Regression.
| Variable | First-Stage Regression | Second-Stage Regression |
|---|---|---|
| Explained Variable: DE | Explained Variable: HDST | |
| LNFT | 0.153 *** |
|
| DE | 0.681 *** |
|
| Control variables | Yes | Yes |
| Province | Yes | Yes |
| Year | Yes | Yes |
| N | 180 | 180 |
| R2 | 0.958 | 0.987 |
Notes: Results displayed in the table were obtained using STATA 14. *** represents p < 0.01; t-statistics or z-statistics are in parentheses.
Replace the Explained Variable.
| Variable | Explained Variable: HST |
|---|---|
| DE | 0.577 *** |
| Constant | −1.713 ** |
| Control variables | Yes |
| Province | Yes |
| Year | Yes |
| N | 180 |
| R2 | 0.808 |
Notes: Results displayed in the table were obtained using STATA 14. **, and ***, respectively, represent p < 0.05, and p < 0.01; t-statistics are in parentheses.
The Heterogeneity Test.
| Variable | (1) | (2) | (3) | (4) | (5) |
|---|---|---|---|---|---|
| Regional Heterogeneity | Time Heterogeneity | ||||
| Eastern | Central and Western | 2012–2015 | 2016–2021 | ||
| DE | 0.495 *** |
0.570 *** |
0.426 *** |
0.542 *** |
|
| CT | 0.061 |
0.170 ** |
0.044 |
0.022 |
|
| GI | 0.924 *** |
0.163 ** |
0.368 * |
0.401 *** |
|
| SE | 0.003 |
0.001 ** |
0.001 |
0.001 |
|
| RI | 0.157 * |
0.039 |
−0.003 |
0.223 |
|
| Constant | −1.793 * |
−0.450 |
0.012 |
−2.421 |
|
| Province | Yes | Yes |
Yes | Yes | |
| Year | Yes | Yes | Yes | ||
| N | 80 | 100 | 72 | 108 | |
| R2 | 0.890 | 0.768 | 0.624 | 0.734 | |
Notes: Results displayed in the table were obtained using STATA 14. *, **, and ***, respectively, represent p < 0.1, p < 0.05, and p < 0.01; t-statistics are in parentheses.
The Mediating Effect Test of Human Capital.
| Variable | HC | HDST |
|---|---|---|
| DE | 0.816 *** |
0.336 *** |
| HC | 0.239 ** |
|
| Control Variables | Yes | Yes |
| Province | Yes | Yes |
| Year | Yes | Yes |
| N | 180 | 180 |
| R2 | 0.889 | 0.838 |
Notes: Results displayed in the table were obtained using STATA 14. **, and ***, respectively, represent p < 0.05, and p < 0.01; t-statistics are in parentheses.
References
1. Huang, X.; Binqing, C.A.I.; Yalin, L.I. Evaluation index system and measurement of high-quality development in China. Rev. Cercet. Interv. Soc.; 2020; 68, pp. 163-178. [DOI: https://dx.doi.org/10.33788/rcis.68.11]
2. Bei, J. Study on the “high-quality development” economics. China Polit. Econ.; 2018; 1, pp. 163-180. [DOI: https://dx.doi.org/10.1108/CPE-10-2018-016]
3. Jahanger, A. Influence of FDI characteristics on high-quality development of China’s economy. Environ. Sci. Pollut. R.; 2021; 28, pp. 18977-18988. [DOI: https://dx.doi.org/10.1007/s11356-020-09187-0]
4. Zhibiao, L.; Yonghui, L. Structural transformation, TFP and high-quality development. China Econ.; 2022; 17, pp. 70-82. [DOI: https://dx.doi.org/10.19602/j.chinaeconomist.2022.01.06]
5. Zhou, L.; Xia, Q.; Sun, H.; Zhang, L.; Jin, X. The role of digital transformation in high-quality development of the services trade. Sustainability; 2023; 15, 4014. [DOI: https://dx.doi.org/10.3390/su15054014]
6. Yao, W.; Sun, Z. The Impact of the Digital Economy on High-Quality Development of Agriculture: A China Case Study. Sustainability; 2023; 15, 5745. [DOI: https://dx.doi.org/10.3390/su15075745]
7. Okpalaoka, C. Research on the digital economy: Developing trends and future directions. Technol. Forecast. Soc.; 2023; 193, 122635. [DOI: https://dx.doi.org/10.1016/j.techfore.2023.122635]
8. Ayres, R.U.; Williams, E. The digital economy: Where do we stand?. Technol. Forecast. Soc.; 2004; 71, pp. 315-339. [DOI: https://dx.doi.org/10.1016/j.techfore.2003.11.001]
9. Ding, Y.; Zhang, H.; Tang, S. How does the digital economy affect the domestic value-added rate of Chinese exports?. J. Glob. Inf. Manag.; 2021; 29, pp. 71-85. [DOI: https://dx.doi.org/10.4018/JGIM.20210901.oa5]
10. Berawi, M.A.; Suwartha, N.; Asvial, M.; Harwahyu, R.; Suryanegara, M.; Setiawan, E.A.; Surjandari, I.; Zagloel, T.Y.M.; Maknun, I.J. Digital innovation: Creating competitive advantages. Int. J. Technol.; 2020; 11, pp. 1076-1080. [DOI: https://dx.doi.org/10.14716/ijtech.v11i6.4581]
11. Tao, Z.; Zhi, Z.; Shangkun, L. Digital economy, entrepreneurship, and high-quality economic development: Empirical evidence from urban China. Front. Econ. China; 2022; 17, pp. 393-426. [DOI: https://dx.doi.org/10.3868/s060-015-022-0015-6]
12. Lee, C.C.; Tang, M.; Lee, C.C. Reaping digital dividends: Digital inclusive finance and high-quality development of enterprises in China. Telecommun. Policy; 2023; 47, 102484. [DOI: https://dx.doi.org/10.1016/j.telpol.2022.102484]
13. Mardonakulovich, B.M.; Bulturbayevich, M.B. Digital economy: Sustainable and high-quality economic growth. Academicia Globe Indersci. Res.; 2020; 1, pp. 9-16.
14. Kan, D.; Lyu, L.; Huang, W.; Yao, W. Digital economy and the upgrading of the global value chain of China’s service industry. J. Theor. Appl. Electron. Commer.; 2022; 17, pp. 1279-1296. [DOI: https://dx.doi.org/10.3390/jtaer17040065]
15. Xu, X.; Arshad, M.A.; Mahmood, A. Analysis on international competitiveness of service trade in the Guangdong–Hong Kong–Macao greater bay area based on using the entropy and gray correlation methods. Entropy; 2021; 23, 1253. [DOI: https://dx.doi.org/10.3390/e23101253]
16. Miroudot, S.; Sauvage, J.; Shepherd, B. Trade costs and productivity in services sectors. Econ. Lett.; 2012; 114, pp. 36-38. [DOI: https://dx.doi.org/10.1016/j.econlet.2011.09.005]
17. Breinlich, H.; Criscuolo, C. International trade in services: A portrait of importers and exporters. J. Int. Econ.; 2011; 84, pp. 188-206. [DOI: https://dx.doi.org/10.1016/j.jinteco.2011.03.006]
18. Javed, A. South Asia’s services trade: Barriers and prospects for integration. Int. J. Manag.; 2019; 6, pp. 751-760.
19. Nath, H.K.; Liu, L.; Tochkov, K. Comparative advantages in US bilateral services trade with China and India. J. Asian Econ.; 2015; 38, pp. 79-92. [DOI: https://dx.doi.org/10.1016/j.asieco.2015.04.002]
20. Feng, R.; Shen, C.; Huang, L.; Tang, X. Does trade in services improve carbon efficiency?—Analysis based on international panel data. Technol. Forecast. Soc.; 2022; 174, 121298. [DOI: https://dx.doi.org/10.1016/j.techfore.2021.121298]
21. Shi, L.; Zhang, Q. Evaluation on the development of Sino-US service trade under Sino-US trade friction. Int. J. Front. Soc.; 2021; 3, pp. 67-71. [DOI: https://dx.doi.org/10.25236/IJFS.2021.031012]
22. Yuan, Q. The high-quality development of China’s service trade: Trade status Quo, challenges and development countermeasures. Front. Econ. Manag.; 2022; 3, pp. 315-322. [DOI: https://dx.doi.org/10.6981/FEM.202202_3(2).0040]
23. Hisanaga, M. Comparative Advantage Structure of US International Services; KIER Discussion Paper Series; Kyoto University, Institute of Economic Research: Kyoto, Japan, 2007.
24. Liu, Y.; Chen, W. The Comparative study on Sino-US service trade competition. IETI Trans. Soc. Sci. Humanit.; 2020; 7, pp. 164-170. [DOI: https://dx.doi.org/10.6896/IETITSSH.202005_7.0021]
25. Zhu, T. Study on the impact of cross-border e-commerce development on China’s service trade exports. Highlights Bus. Econ. Manag.; 2023; 10, pp. 313-319. [DOI: https://dx.doi.org/10.54097/hbem.v10i.8114]
26. Chen, S.; Li, L. Research on the development prospect of “China-Asean” service trade—Analysis based on the manufacturing level of service industry. Adv. Econ. Manag. Res.; 2022; 2, pp. 169-175. [DOI: https://dx.doi.org/10.56028/aemr.2.1.169]
27. Jiang, L.; Lin, C. Analysis on the international competitiveness of China’s trade in services. Emerg. Mark. Financ. Trade; 2020; 56, pp. 3033-3043. [DOI: https://dx.doi.org/10.1080/1540496X.2019.1611558]
28. Li, N.; Lv, D. Development strategy of international service trade based on big data. Proceedings of the 2020 International Conference on Artificial Intelligence, Computer Networks and Communications; Lijiang, China, 27–30 December 2020; [DOI: https://dx.doi.org/10.1088/1742-6596/1852/2/022016]
29. Mukhtorovna, N.D. Importance of foreign investments in the development of the digital economy. Res. J. Anal. Inventig.; 2021; 2, pp. 219-224.
30. Brynjolfsson, E.; Collis, A.; Diewert, W.E.; Eggers, F.; Fox, K.J. GDP-B: Accounting for the Value of New and Free Goods in the Digital Economy; NBER Working Paper Series; National Bureau of Economic Research: Boston, MA, USA, 2019; [DOI: https://dx.doi.org/10.3386/w25695]
31. Pan, X. A new competitive situation in the digital economy and China’s actions. China Int. Stud.; 2020; 82, pp. 123-140.
32. Shan, S.; Liu, C. Research on the Impact of Financial Deepening on Digital Economy Development: An Empirical Analysis from China. Sustainability; 2023; 15, 11358. [DOI: https://dx.doi.org/10.3390/su151411358]
33. Limna, P.; Kraiwanit, T.; Siripipatthanakul, S. The growing trend of digital economy: A review article. Int. J. Comput. Sci. Res.; 2022; 6, pp. 1-11. [DOI: https://dx.doi.org/10.25147/ijcsr.2017.001.1.106]
34. Aldieri, L.; Brahmi, M.; Bruno, B.; Vinci, C.P. Circular Economy Business Models: The Complementarities with Sharing Economy and Eco-Innovations Investments. Sustainability; 2021; 13, 12438. [DOI: https://dx.doi.org/10.3390/su132212438]
35. Hedberg, A.; Šipka, S. Toward a circular economy: The role of digitalization. One Earth; 2021; 4, pp. 783-785. [DOI: https://dx.doi.org/10.1016/j.oneear.2021.05.020]
36. Zhang, T.; Shi, Z.Z.; Shi, Y.R.; Chen, N.J. Enterprise digital transformation and production efficiency: Mechanism analysis and empirical research. Econ. Res.-Ekon. Istraz.; 2022; 35, pp. 2781-2792. [DOI: https://dx.doi.org/10.1080/1331677X.2021.1980731]
37. Spence, M. Government and economics in the digital economy. J. Gov. Econ.; 2021; 3, 100020. [DOI: https://dx.doi.org/10.1016/j.jge.2021.100020]
38. Guan, H.; Guo, B.; Zhang, J. Study on the impact of the digital economy on the upgrading of industrial structures—Empirical analysis based on cities in China. Sustainability; 2022; 14, 11378. [DOI: https://dx.doi.org/10.3390/su141811378]
39. Zheng, X.; Zhang, X.; Fan, D. Digital transformation, industrial structure change, and economic growth motivation: An empirical analysis based on manufacturing industry in Yangtze River Delta. PLoS ONE; 2023; 18, e0284803. [DOI: https://dx.doi.org/10.1371/journal.pone.0284803]
40. Lee, S.; Kim, M.; Park, Y. ICT co-evolution and Korean ICT strategy: An analysis based on patent data. Telecommun. Policy; 2009; 33, pp. 253-271. [DOI: https://dx.doi.org/10.1016/j.telpol.2009.02.004]
41. Heo, P.; Lee, D. Evolution of the linkage structure of ICT industry and its role in the economic system: The case of Korea. Inform. Technol. Dev.; 2019; 25, pp. 424-454. [DOI: https://dx.doi.org/10.1080/02681102.2018.1470486]
42. Su, J.; Su, K.; Wang, S. Does the digital economy promote industrial structural upgrading?—A test of mediating effects based on heterogeneous technological innovation. Sustainability; 2021; 13, 10105. [DOI: https://dx.doi.org/10.3390/su131810105]
43. Ding, C.; Liu, C.; Zheng, C.; Li, F. Digital economy, technological innovation and high-quality economic development: Based on spatial effect and mediation effect. Sustainability; 2022; 14, 216. [DOI: https://dx.doi.org/10.3390/su14010216]
44. Goldfarb, A.; Tucker, C. Digital economics. J. Econ. Lit.; 2019; 57, pp. 3-43. [DOI: https://dx.doi.org/10.1257/jel.20171452]
45. Glavas, C.; Mathews, S. How international entrepreneurship characteristics influence Internet capabilities for the international business processes of the firm. Int. Bus. Rev.; 2014; 23, pp. 228-245. [DOI: https://dx.doi.org/10.1016/j.ibusrev.2013.04.001]
46. Myovella, G.; Karacuka, M.; Haucap, J. Digitalization and economic growth: A comparative analysis of Sub-Saharan Africa and OECD economies. Telecommun. Policy; 2020; 44, 101856. [DOI: https://dx.doi.org/10.1016/j.telpol.2019.101856]
47. Ciuriak, D.; Ptashkina, M. The Digital Transformation and the Transformation of International Trade; International Centre for Trade and Sustainable Development (ICTSD): Geneva, Switzerland, 2018; Inter-American Development Bank (IDB): Washington, DC, USA, 2018.
48. Abeliansky, A.; Hilbert, M. Digital technology and international trade: Is it the quantity of subscriptions or the quality of data speed that matters?. Telecommun. Policy; 2017; 41, pp. 35-48. [DOI: https://dx.doi.org/10.1016/j.telpol.2016.11.001]
49. Xu, Y.; Xu, L. The convergence between digital industrialization and industrial digitalization and export technology complexity: Evidence from China. Sustainability; 2023; 15, 9081. [DOI: https://dx.doi.org/10.3390/su15119081]
50. Wang, F.; Guo, B.; Wang, Z.; Wu, Y. The impact of digital economy on the export competitiveness of China’s manufacturing industry. Math. Biosci. Eng.; 2023; 20, pp. 7253-7272. [DOI: https://dx.doi.org/10.3934/mbe.2023314]
51. Casalini, F.; González, J.L.; Moïsé, E. Approaches to Market Openness in the Digital Age; OECD Trade Policy Papers OECD Publishing: Paris, France, 2019; [DOI: https://dx.doi.org/10.1787/818a7498-en]
52. Beaumont-Smith, G.; Kim, A.B. The Coronavirus Pandemic Highlights the Critical Importance of Digital Trade; The Heritage Foundation: Washington, DC, USA, 2020.
53. Mulenga, R.; Mayondi, M. Impact of digital services trade on economic growth of developing, emerging and developed countries: P-VAR approach. Am. J. Econ.; 2022; 6, pp. 58-85. [DOI: https://dx.doi.org/10.47672/aje.1053]
54. Chen, Z.; Lin, J.; Li, J.; Chen, Z. Digital trade: Definition, measurement and development. Sci. Soc. Res.; 2022; 4, pp. 112-118. [DOI: https://dx.doi.org/10.36922/ssr.v4i1.1320]
55. Zhang, L.; Pan, A.; Feng, S.; Qin, Y. Digital economy, technological progress, and city export trade. PLoS ONE; 2022; 17, e0269314. [DOI: https://dx.doi.org/10.1371/journal.pone.0269314]
56. Samoilovych, A.; Popelo, O.; Kychko, I.; Samoilovych, O.; Olyfirenko, I. Management of human capital development in the era of the digital economy. J. Intell. Manag. Decis.; 2022; 1, pp. 56-66. [DOI: https://dx.doi.org/10.56578/jimd010107]
57. Korshunova, S.A. The role and specificity of human capital in the formation of a digital economy. Proceedings of the International Scientific and Practical Forum “Industry. Science. Competence. Integration”; Moscow, Russia, 28 November 2019.
58. Li, M.; Zhou, Y. Effect of digital economy development on human capital structure. Front. Econ. China; 2022; 17, pp. 104-133. [DOI: https://dx.doi.org/10.3868/s060-015-022-0005-9]
59. Lee, S.Y.; Florida, R.; Gates, G. Innovation, human capital, and creativity. Int. Rev. Public Adm.; 2010; 14, pp. 13-24. [DOI: https://dx.doi.org/10.1080/12294659.2010.10805158]
60. Li, H.; Han, J.; Xu, Y. The effect of the digital economy on services exports competitiveness and ternary margins. Telecommun. Policy; 2023; 47, 102596. [DOI: https://dx.doi.org/10.1016/j.telpol.2023.102596]
61. Gebremeskel, B.K.; Jonathan, G.M.; Demesie, S. Information security challenges during digital transformation. Proced. Comput. Sci.; 2023; 219, pp. 44-51. [DOI: https://dx.doi.org/10.1016/j.procs.2023.01.262]
62. Shang, C.; Jiang, J.; Zhu, L.; Saeidi, P. A decision support model for evaluating risks in the digital economy transformation of the manufacturing industry. J. Innov. Knowl.; 2023; 8, 100393. [DOI: https://dx.doi.org/10.1016/j.jik.2023.100393]
63. Mulaydinov, F. Digital economy is a guarantee of government and society development. Elem. Educ. Online; 2021; 20, pp. 1474-1479. [DOI: https://dx.doi.org/10.17051/ilkonline.2021.03.164]
64. Dahlman, C.; Mealy, S.; Wermelinger, M. Harnessing the Digital Economy for Developing Countries; OECD Development Centre Working Papers OECD Publishing: Paris, France, 2016; [DOI: https://dx.doi.org/10.1787/4adffb24-en]
65. Bukht, R.; Heeks, R. Digital Economy Policy in Developing Countries; DIODE Working Papers Centre for Development Informatics: Manchester, UK, 2018; [DOI: https://dx.doi.org/10.2139/ssrn.3540027]
66. Zhang, L.; Chen, S. China’s Digital Economy: Opportunities and Risks; IMF Working Papers International Monetary Fund: Washington, DC, USA, 2019; [DOI: https://dx.doi.org/10.5089/9781484389706.001]
67. Al-Badrany, A.S.S.; Al, R.J.S.A.D. The impact of the digital economy on international trade, the case of Egypt for the period (1990–2020). Integr. J. Res. Arts Humanit.; 2023; 3, pp. 163-173. [DOI: https://dx.doi.org/10.55544/ijrah.3.2.28]
68. Choi, C. The effect of the Internet on service trade. Econ. Lett.; 2010; 109, pp. 102-104. [DOI: https://dx.doi.org/10.1016/j.econlet.2010.08.005]
69. Zhang, Y. Influence effect of Internet on the optimization of China’s international trade structure based on gravity model. Math. Probl. Eng.; 2022; 2022, 4771947. [DOI: https://dx.doi.org/10.1155/2022/4771947]
70. Kikuchi, T.; Iwasa, K. A simple model of service trade with time zone differences. Int. Rev. Econ. Financ.; 2010; 19, pp. 75-80. [DOI: https://dx.doi.org/10.1016/j.iref.2009.02.004]
71. Nixon, C. Digital Trade is the Way forward for New Zealand: A Preliminary Assessment of the Costs and Benefits of Digital Trade; NZIER: Wellington, New Zealand, 2021.
72. Ahmedov, I. The impact of digital economy on international trade. Eur. J. Bus. Manag. Res.; 2020; 5, 389. [DOI: https://dx.doi.org/10.24018/ejbmr.2020.5.4.389]
73. Nath, H.K.; Liu, L. Information and communications technology (ICT) and services trade. Inf. Econ. Policy; 2017; 41, pp. 81-87. [DOI: https://dx.doi.org/10.1016/j.infoecopol.2017.06.003]
74. Pan, W.; Xie, T.; Wang, Z.; Ma, L. Digital economy: An innovation driver for total factor productivity. J. Bus. Res.; 2022; 139, pp. 303-311. [DOI: https://dx.doi.org/10.1016/j.jbusres.2021.09.061]
75. Qian, W.; Liu, H.; Pan, F. Digital economy, industry heterogeneity, and service industry resource allocation. Sustainability; 2022; 14, 8020. [DOI: https://dx.doi.org/10.3390/su14138020]
76. Shao, Y. The Impact of Digital Economy on the High-Quality Development of Service Industry in Beijing. Proceedings of the 2022 International Conference on Bigdata Blockchain and Economy Management (ICBBEM 2022); Wuhan, China, 25–27 April 2022; [DOI: https://dx.doi.org/10.2991/978-94-6463-030-5_15]
77. Jiang, M.; Jia, P. Does the level of digitalized service drive the global export of digital service trade? Evidence from global perspective. Telemat. Inform.; 2022; 72, 101853. [DOI: https://dx.doi.org/10.1016/j.tele.2022.101853]
78. Li, B.; Zhang, S. Research on the development path of China’s digital trade under the background of the digital economy. J. Internet Digit. Econ.; 2022; 2, pp. 1-14. [DOI: https://dx.doi.org/10.1108/JIDE-10-2021-0010]
79. Wen, H.; Chen, W.; Zhou, F. Does digital service trade boost technological innovation?: International evidence. Soc.-Econ. Plan. Sci.; 2023; 88, 101647. [DOI: https://dx.doi.org/10.1016/j.seps.2023.101647]
80. Zhu, W.; Li, X.F.; Sun, B. Digital Trade and Economic Growth from the Perspective of Digital Services. Proceedings of the 2021 9th International Conference on Social Science, Education and Humanities Research (SSEHR 2021); Paris, France, 17–19 December 2021; [DOI: https://dx.doi.org/10.25236/ssehr.2021.062]
81. Dong, Y.; Xiao, B.; Wang, X. Research on the impact of barriers to cross-border data flows on digital services trade Competitiveness mediation effect analysis based on FDI in the services industry. Asian J. Soc. Sci. Manag. Technol.; 2022; 4, pp. 187-196.
82. Turcan, V.; Gribincea, A.; Birca, I. Digital economy-A premise for economic development in the 20th century. Econ. Sociol. Theor. Sci. J.; 2014; 2, pp. 109-115.
83. Lim, G.; Kim, C. The role of human capital in networks effects: Evidence from US exports. Global Econ. Rev.; 2011; 40, pp. 299-313. [DOI: https://dx.doi.org/10.1080/1226508X.2011.601637]
84. Ma, H.; Sun, Y.; Yang, L.; Li, X.; Zhang, Y.; Zhang, F. Advanced Human Capital Structure, Industrial Intelligence and Service Industry Structure Upgrade—Experience from China’s Developments. Emerg. Mark. Financ. Trade; 2022; 59, pp. 1372-1389. [DOI: https://dx.doi.org/10.1080/1540496X.2022.2133960]
85. Rong, R.; Wang, X.; Wang, T.; Hua, L. The impact of the digital economy on the servitization of industrial structures: The moderating effect of human capital. Data Sci. Manag.; 2023; 6, pp. 174-182. [DOI: https://dx.doi.org/10.1016/j.dsm.2023.06.003]
86. Tang, J.; Xia, J. Construction and implementation path of the evaluation index system of high-quality development of China’s service trade. J. Beijing Univ. Technol.; 2020; 20, pp. 47-57. (In Chinese) [DOI: https://dx.doi.org/10.12120/bjutskxb20200547]
87. Wu, Y.; Zhang, S. Research on the evolution of high-quality development of China’s provincial foreign trade. Sci. Program. Neth.; 2022; 2022, 3102157. [DOI: https://dx.doi.org/10.1155/2022/3102157]
88. Chen, L. Exploration of current situations, problems and measures of service trade development in China. Proceedings of the 2016 4th International Education, Economics, Social Science, Arts, Sports and Management Engineering Conference (IEESASM 2016); Yinchuan, China, 13–14 August 2016; [DOI: https://dx.doi.org/10.2991/ieesasm-16.2016.110]
89. Milošević, N.; Dobrota, M.; Rakočević, S.B. Digital economy in Europe: Evaluation of countries’ performances. Zb. Rad. Ekon. Fak. Rij.; 2018; 36, pp. 861-880. [DOI: https://dx.doi.org/10.18045/zbefri.2018.2.861]
90. Zhang, W.; Zhao, S.; Wan, X.; Yao, Y. Study on the effect of digital economy on high-quality economic development in China. PLoS ONE; 2021; 16, e0257365. [DOI: https://dx.doi.org/10.1371/journal.pone.0257365] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/34547019]
91. Wang, J.; Dong, K.; Dong, X.; Taghizadeh-Hesary, F. Assessing the digital economy and its carbon-mitigation effects: The case of China. Energy Econ.; 2022; 113, 106198. [DOI: https://dx.doi.org/10.1016/j.eneco.2022.106198]
92. Yu, B.; Wu, Y. How can upgrading human capital solve overcapacity?. J. Soft Sci.; 2023; 5, pp. 122-129. (In Chinese)
93. Tao, A.; Zhang, Z. The impact of digital economy on service trade development: An empirical study based on national panel data. China Econ. Manag.; 2019; 36, 11948.(In Chinese)
94. Li, N. The promotion of digital economy to development of China’s service trade. Proceedings of the XV International Conference “Russian Regions in the Focus of Changes” (ICRRFC 2020); Ekaterinburg, Russia, 12–14 November 2020; [DOI: https://dx.doi.org/10.2991/aebmr.k.210213.006]
95. Karmali, D.; Sudarsan, P.K. Impact of trade in goods on trade in services: A country level panel data analysis. Indian J. Econ. Bus.; 2008; 7, pp. 145-154.
96. Guan, C.; Huang, J.; Jiang, R.; Xu, W. The impact of pilot free trade zone on service industry structure upgrading. Econ. Anal. Policy; 2023; 78, pp. 472-491. [DOI: https://dx.doi.org/10.1016/j.eap.2023.03.024]
97. Rondinelli, D.A.; Kasarda, J.D. Foreign trade potential, small enterprise development and job creation in developing countries. Small Bus. Econ.; 1992; 4, pp. 253-265. [DOI: https://dx.doi.org/10.1007/BF00388621]
98. Ma, J.; Shen, K.; Wang, Z. Research on improving the efficiency of service industry with the development of digital economy. J. Nanjing Univ. Financ. Econ.; 2023; 240, pp. 65-75. (In Chinese)
99. Zhang, Y. The impact of FDI inflows on China’s service trade exports from the perspective of industry heterogeneity. J. Bus. Econ.; 2022; 854, pp. 152-157. (In Chinese)
100. Zhang, J.; Shang, Y. The influence and mechanism of digital economy on the development of the tourism service trade—Analysis of the mediating effect of carbon emissions under the background of COP26. Sustainability; 2022; 14, 13414. [DOI: https://dx.doi.org/10.3390/su142013414]
© 2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.
Details
; Xu, Yifan 3 1 Endicott College of International Studies, Woosong University, Daejeon 34606, Republic of Korea;
2 School of Law and Business, Sanjiang University, Nanjing 210012, China; School of Management Science and Engineering, Nanjing University of Information Science & Technology, Nanjing 210044, China
3 School of Computer Science, Nanjing University of Information Science & Technology, Nanjing 210044, China