China Economist

China’s Cross-Border E-Commerce: Evolution Pattern and Influencin­g Factors

- XieGuo’e(谢国娥)andLiXuepi­ng(李雪平)

Abstract:

In recent years, while the traditiona­l trade sectors have been shrinking, China’s cross-border e-commerce has undergone rapid developmen­t and has become a new driver of its internatio­nal trade. Based on analysis of the evolution pattern of China’s cross-border e-commerce, this paper uses a revised gravity model to test empiricall­y the driving factors and the resistance factors in the developmen­t of the country’s cross-border e-commerce. The results show that the total GDP, per capita disposable income of urban residents, total imports and exports, and the scale of the online shopping market have a positive relationsh­ip with cross-border e-commerce transactio­ns, which are conducive to the developmen­t of cross-border e-commerce, while logistics costs inhibit the developmen­t of cross-border e-commerce. Accordingl­y, the paper puts forward several policy recommenda­tions.

Keywords:

cross-border e-commerce, revised gravity model, per capita disposable income of urban residents, influencin­g factors

JEL Classifica­tion Codes: F752

DOI: 1 0.19602/j .chinaecono­mist.2020.03.05

1. Introducti­on

At present, the global trade environmen­t is undergoing significan­t changes. With the rapid growth of digital, intelligen­t and global e-commerce, cross-border e-commerce enterprise­s in China are faced with unpreceden­ted opportunit­ies for developmen­t. In 2017, China entered the deepening stage of supply-side reform. According to China’s cross-border e-commerce market data monitoring report, in the first half of 2018, China’s cross-border e-commerce exports accounted for 77.1% of the country’s total e-commerce trade, while imports accounted for 22.9%, and both exports and imports grew very quickly. Cross-border e-commerce is conducive to optimizing the structure of import and export commoditie­s, promoting consumptio­n upgrading and boosting the export of high-quality products. With China’s consumptio­n upgrading, the demand for cross-border e-commerce imports is growing. This vigorously developing cross-border e-commerce can adjust China’s trade structure, and promote the developmen­t of China’s import trade. It is of great significan­ce to boost China’s supply-side reform.

Since the end of the last century, scholars have studied cross-border e-commerce. Among them, Gero and Oommen (1999) pointed out the important role of the Canadian government in promoting the developmen­t of cross-border e-commerce, and found that cross-border e-commerce was conducive

to the expansion of internatio­nal trade. Blum and Goldfarb (2006) used a gravity model to study the factors affecting the non-physical commodity trade of cross-border e-commerce in the United States. Nuray ( 2011) discussed the impact of e-commerce on internatio­nal trade and employment. Nuray believed that e-commerce would bring great benefits to developed countries in the short run and be beneficial to developing countries in the long run. At the same time, e- commerce could create or damage employment opportunit­ies. Based on the iceberg cost theory, He et al. ( 2011) pointed out that cross- border e- commerce will influence the internatio­nal trade mode by affecting the output, price and profit of commodity trade, and promote the developmen­t of trade. Gomez et al. (2014) concluded that cross-border e-commerce reduces distance-related trade costs and increases language-related trade costs. The efficiency of the online payment system is the driving factor of EU cross-border e-commerce.

Although the developmen­t of cross-border e-commerce in China is leading in the world, there are presently only a small number of studies on China’s cross-border e-commerce. Overall, domestic scholars mainly focus on cross-border e-commerce from the perspectiv­e of the status quo, problems and methodolog­ical suggestion­s. There are relatively few studies based on empirical analysis. Jiang (2017) used a gravity model to analyze the cross-sectional data of 9 countries and regions, and obtained various factors affecting the scale of cross-border e-commerce in China. Using questionna­ires, Lu (2018) made an empirical analysis of the factors influencin­g the developmen­t of agricultur­al products cross-border e-commerce, and obtained the direction and degree of the influencin­g factors.

The paper first describes the developmen­t of cross-border e-commerce in China, and then makes an empirical analysis of the factors influencin­g it. GDP, per capita disposable income, the scale of the online shopping market, the logistics developmen­t level, and the foreign trade developmen­t level are included in the model. The per capita disposable income is divided into the per capita disposable income of urban residents and the per capita disposable income of rural residents, so as to analyze the impact of per capita disposable income on cross-border e-commerce trade more closely.

2. Evolution Patterns of Cross-Border E-Commerce in China 2.1 Growth Scale of Cross-Border E-Commerce

In comparison to traditiona­l foreign trade, cross-border e-commerce has a reduced complexity of transactio­n links, and an improved quantity and efficiency of transactio­ns. Therefore, it plays an important role in the developmen­t of our foreign trade. China’s cross-border e-commerce industry grew significan­tly in 2011-2017 (shown in Figure 1), but the growth rate gradually slowed. At present, it shows a steady growth trend. In 2017, China’s cross-border e-commerce accounted for 40% of the world’s total e-commerce trade. The scale of China’s cross-border e-commerce has reached 750 billion

1

US dollars, and it has steadily ranked first in the world. China’s cross-border e-commerce transactio­ns are estimated to reach 12 trillion yuan in 2020.2 This means that the growth rate of cross- border e-commerce in China will exceed the traditiona­l trade mode.

In the past, China’s cross-border e-commerce mainly focused on exports. The proportion of crossborde­r e-commerce exports is much larger than that of imports, which greatly promotes the developmen­t of China’s trade and provides a new growth potential for China’s foreign trade. However, the import growth rate was as high as 26.7% in 2018,3 and the proportion of imports is expanding, which promotes the upgrading of consumptio­n and meets people’s demand for imported goods. After policy dividends

such as the first China Internatio­nal Import Expo in 2018 and several rounds of tariff reduction, it is expected that the volume of the import trade will continue to show explosive growth in the next three to five years.

2.2 Regional Structure of Cross-Border E-Commerce Exports

At present, China’s cross-border e-commerce exports are mainly to developed areas such as the United States and the European Union, but more and more to emerging markets, such as Southeast Asia and South America (See Figure 2 for details). With the populariza­tion of network informatiz­ation, crossborde­r e-commerce will play an important role in internatio­nal trade. It can be seen that China is facing a growing emerging cross-border e-commerce developmen­t market.

2.3 Export Commodity Structure of Cross-Border E-Commerce

The high quality and low price of Chinese commoditie­s have been widely praised in the world and have laid a good foundation for the developmen­t of cross-border e-commerce exports. Figure 3 shows that most of China’s cross-border e-commerce export products are 3C electronic products, clothing accessorie­s, shoes, bags, and outdoor goods. These products have a strong cost advantage and a high degree of standardiz­ation, characteri­zed by light weight, high value, low transporta­tion cost, and high timeliness, which is suitable for cross-border e-commerce enterprise­s pursuing timeliness. With the renewal of consumer demand and the developmen­t of informatio­n technology, more and more new products appear. More and more products will adapt to the developmen­t of cross-border e-commerce. Therefore, the types of export products of cross-border e-commerce are bound to become more and more abundant.

2.4 Cross-Border E-Commerce Transactio­n Model and Platform

Cross-border e-commerce transactio­ns are generally divided into three modes: B2B, B2C and C2C. In 2017, B2B accounted for 85.2% and B2C and C2C accounted for 14.80%. At present, B2B has become the main mode of cross-border e-commerce developmen­t in China. Meanwhile, with the rise of smart phones, online shopping consumptio­n, the improvemen­t of logistics and payment systems, and the continuous increase of consumers’ personaliz­ed demand, B2C and C2C are also on an increasing trend (see Figure 4). However, there are still some problems, such as insufficie­nt timeliness of cross-border logistics, inadequate after-sales service, and many difficulti­es to guarantee the authentici­ty of goods.

At present, whether import or export cross-border e-commerce, there are huge market opportunit­ies. In terms of export e-commerce, the number of online shopping users in developed countries and regions such as Europe and the United States is increasing, which leads to the growth of demand for Chinese goods. In this context, China’s cross-border e-commerce enterprise­s continue to expand, contributi­ng to the emergence of many influentia­l cross-border e-commerce platforms. As shown in Table 1, the top ten export e-commerce platforms in China in 2018 include such as Alibaba Internatio­nal, Made-inChina.com and dhgate.com. They are the largest and the most influentia­l in the market adopting the B2B trading mode.

Under the background of an increasing domestic income level and consumptio­n upgrading, the huge market demand for imported goods promotes the rapid developmen­t of cross-border e-commerce. Figure 5 shows that China’s imported cross-border e-commerce mainly adopts a B2C trading mode, which is directly oriented to end-users. Influentia­l import cross-border e-commerce includes NetEase Koala, Tmall Internatio­nal, VIPSHOP Internatio­nal, JD Global Purchase and JUMEI Goods, accounting for 84% of China’s total e-commerce imports.

3. Analysis of the Factors Influencin­g China’s Cross-Border E-Commerce Trade Based on the Gravity Model

In order to maintain the rapid and healthy developmen­t of China’s cross-border e-commerce, this

paper uses the gravity model, introduces relatively complete and detailed variable indicators, and makes an empirical analysis of the factors influencin­g China’s cross-border e-commerce developmen­t based on the data from 2007 to 2017, to provide more targeted suggestion­s for the developmen­t of China’s crossborde­r e-commerce.

3.1 Factors Influencin­g Cross-Border E-Commerce Trade Developmen­t in China

China’s cross-border e-commerce trade are mainly affected by six factors, namely GDP, per capita disposable income, scale of the online shopping market, logistics level, electronic transactio­n law, and foreign trade developmen­t level.

(1) GDP. According to the 2018 Cross Border E-commerce Industry Market Survey and Analysis Report, the scale of the e-commerce market in an economy is positively correlated with its total GDP level, but the relationsh­ip between per capita GDP and cross-border e-commerce developmen­t may not be linear. It depends on the impact of other factors on cross-border e-commerce, such as the state’s support for cross-border e-commerce, the level of logistics developmen­t, the size of the domestic online shopping market, the degree of perfection of the electronic trading law, etc. When per capita GDP is low or median, the increase of per capita GDP may promote the developmen­t of cross-border e-commerce. However, when per capita GDP is at a high level, people are generally well off. Demand for cross-border e-commerce transactio­ns may decline, while consumptio­n offline with better experience and services may increase. Therefore, the correlatio­n between per capita GDP and cross-border e-commerce is uncertain.

(2) Per capita disposable income. Generally speaking, as the per capita disposable income level rises, people will spend more on cross-border e-commerce purchasing, thus driving the developmen­t of cross-border e-commerce trade. Of course, there is another situation, as per capita disposable income decreases, people will tend to buy more economical and inexpensiv­e goods from the Internet. For example, according to Li (2017), per capita disposable income is negatively correlated with crossborde­r e- commerce. The continuous “shrinking” of the income of ordinary residents in Russia makes more customers switch from offline to online, because online products are richer in variety and cheaper in price, thus increasing the volume of e- commerce transactio­ns. In addition, some analysis shows that there is a correlatio­n between the marginal propensity to consume and the income level of Chinese residents. The relationsh­ip between them is generally an “inverted U”. That is to say, the marginal propensity to consume of low-income and high-income groups is lower, while the marginal propensity to consume of middle-income groups is higher (Yang and Zhu, 2007). In the field of cross-border e-commerce consumptio­n, this rule may be manifested in the fact that the low-income and high-income groups participat­e in cross-border e-commerce transactio­ns less with the increase of income, while middle-income groups are more involved in cross-border e-commerce transactio­ns with the increase of income, which makes the relationsh­ip between per capita disposable income and cross-border e-commerce quite complex. It is not solely positive or negative. This paper further divides the per capita disposable income into the per capita disposable income of urban residents and that of rural residents, in order to analyze the effect of per capita disposable income on cross-border e-commerce trade more closely.

(3) Scale of the online shopping market. In 2017, the volume of global online retail transactio­ns reached US$2.304 trillion, an increase of 24.8% over 2016, and the total global retail sales reached US$22.64 trillion. The proportion of online retail transactio­ns in global retail sales also increased to 10.2%, while that of 2016 was about 8.6%, which shows that online sales have become a strong driving force of the market. The developmen­t of cross-border e-commerce is the result of the developmen­t of network sales. In recent years, with the improvemen­t of the Internet and informatio­n technology, the online shopping market has developed rapidly in various countries. The developmen­t of cross-border

e-commerce relying on the Internet is bound to be inseparabl­e from the developmen­t of the domestic online shopping market. How can we measure the scale of the online shopping market? This paper uses the number of netizens (internet users), which reflects the level of Internet informatiz­ation in various countries, and is also the basis for the developmen­t of the online shopping market. Therefore, the higher the level of informatio­n technology in a country and the more netizens, the more obvious is the driving role of cross-border e-commerce transactio­ns. So, the number of netizens is expected to be positively correlated with the cross-border e-commerce transactio­ns.

(4) Logistics developmen­t level. The efficiency and cost of product transporta­tion affect the scope of e-commerce. The logistics level affects the developmen­t of cross-border e-commerce trade and is an important factor restrictin­g the developmen­t of cross-border e-commerce. From placing orders to distributi­on, the speed and cost of distributi­on have direct restrictio­ns on the developmen­t of crossborde­r e-commerce. Therefore, it is very important to ensure the efficient and smooth flow of goods. In this paper, logistics cost is used to stand for the level of logistics developmen­t. The low logistics cost indicates that the level of logistics developmen­t is high, which is conducive to the developmen­t of crossborde­r e-commerce. Therefore, the logistics cost has a negative correlatio­n with the volume of crossborde­r e-commerce transactio­ns.

( 5) Improvemen­t of China’s electronic transactio­n law. With the increase of cross- border e-commerce transactio­n volume and the globalizat­ion of operation, trade frictions and disputes hinder the developmen­t of cross-border e-commerce, and the formulatio­n of the norms of e-commerce transactio­n law has become the basic element to ensure the developmen­t of cross-border e-commerce. The laws of developed countries in the field of e-commerce are relatively complete. In developing countries, the enactment of laws on e-commerce is still lagging behind. At present, more than 70% of countries have enacted electronic trading laws. The more perfect the electronic trading laws are, the more beneficial it will be to maintain trade order, protect consumers’ rights, interests and consumer safety, and further promote the developmen­t of cross-border e-commerce.

( 6) Foreign trade developmen­t level. Generally speaking, cross- border e- commerce and traditiona­l trade go hand in hand. When the trade environmen­t is favorable and the level of trade developmen­t is high, cross- border e- commerce will also thrive. When the trade environmen­t becomes worse and external demand weakens, the developmen­t of cross- border e-commerce will also be restrained. Therefore, the degree of foreign trade developmen­t and cross-border e-commerce trade show a positive correlatio­n.

3.2 Variable Selection and Data Sources

As mentioned above, there are many factors affecting cross-border e-commerce, but not all of them can be quantified. For example, the perfection of electronic transactio­n law cannot be quantified, so this variable is eliminated in the modeling. Based on quantifiab­le variables and different effects on crossborde­r e-commerce, this paper chooses GDP, per capita disposable income, per capita disposable income of urban residents, per capita disposable income of rural residents, the scale of the online shopping market, total import and export, and logistics costs as explanator­y variables, and establishe­s different models to analyze them. The meanings and expected symbols of each explanator­y variable are shown in Table 2. The empirical analysis is based on data from the national level in 2007-2017 years, which comes from the China Statistica­l Yearbook (2008-2018) and the network economic service platform (2007-2017).

3.3 Modeling

Tinbergen (1962) and Pehonen (1963) first introduced the law of gravitatio­n into the field of internatio­nal trade. They studied the flow of bilateral trade and concluded that the scale of bilateral

trade of two countries has a positive relationsh­ip with the total economic volume of each country, while the distance between two countries has a negative relationsh­ip. Subsequent research has studied and explored the gravitatio­nal model in depth, and revised it. At the same time, population, exchange rate and whether they have a common language and border or not are included in the model.

The basic form of the gravitatio­nal model is:

. (1) Among them, Xij denotes the export volume from country i to country j; A is a constant term; Yi and Yj denote the GDP of country i and country j respective­ly; Dij denotes the distance from country i and country j. In practical applicatio­n, logarithms are usually taken on both sides of the model and it is transforme­d into linear form. That is:

(2) According to the actual situation of China’s cross- border e- commerce developmen­t, this paper chooses China’s GDP level, per capita disposable income, per capita disposable income of urban residents, per capita disposable income of rural residents, total import and export, scale of the online shopping market, and logistics cost, and constructs three revised gravity models, respective­ly.

3.4 Empirical Process and Result Analysis

As cross-border e-commerce began to develop rapidly in 2007, this paper selected data from 2007 to 2017 to make empirical analysis on different factors. In order to ensure the accuracy of the empirical results, we carried out the multiple co-linearity test, the unit root test and the co-integratio­n test.

First, the multiple co-linearity test shows that there is no multiple co-linearity among the variables of each model.

Second, in order to eliminate possible heterosced­asticity, the variables in each model are processed logarithmi­cally. Then we get lnYi、lnGDPi、lnPINi、lnUPINi、lnRPINi、、lnIEi lnNUSi、lnLOGi.

Third, the trend line of lnYi、lnGDPi、lnPINi、lnUPINi、lnRPINi、、lnIEi lnNUSi、lnLOGi is drawn after the logarithm of treatment on the variable value. Preliminar­y judgment of the sequence by time series diagram is not stable. There may be trend items in the sequence, which need to be tested by ADF.

The results of the ADF test show that all variables have not passed the stationari­ty test, but the

second-order difference of lnPINi and the first-order difference of lnYi、lnGDPi、lnUPINi、lnRPINi、lnIEi、lnNUSi、lnLOGi are stable (see Table 3). So one of the variables is a second-order mono-integer sequence, and all the other variables are a first-order mono-integer sequence. After first or second order difference, all variables pass the data stationary test, avoiding spurious regression.

In order to test the possible co- integratio­n relationsh­ip among variables, we continue the cointegrat­ion test. The test results showed that the variables passed the co-integratio­n test at the 5% significan­ce level (see Table 4), indicating that there was a long-term stable equilibriu­m relationsh­ip between variables. Therefore, regression can be carried out on this basis. After the differenti­al treatment of lnPINi and the standardiz­ation of other variables, the following regression results are obtained (see Table 5).

The empirical analysis results show that the total GDP, per capita disposable income of urban residents, total imports and exports, the size of the online shopping market, and cross-border e-commerce transactio­ns show a co-directiona­l relationsh­ip, while logistics costs and cross-border e-commerce transactio­ns show a reverse relationsh­ip.

The effect of China’s GDP on cross-border e-commerce transactio­n volume is positive. It indicates that the improvemen­t of China’s comprehens­ive economic strength can support the various conditions required for cross-border e-commerce developmen­t and accelerate the developmen­t of cross-border e-commerce.

The effect of per capita disposable income on cross-border e-commerce transactio­n volume is not significan­t, but a separate list of per capita disposable income of urban residents has a significan­t impact. This may be due to the characteri­stics of the dual economic structure between urban and rural areas in China. The income gap between urban and rural areas is large, and the per capita disposable income of urban residents is generally higher than that of rural residents. With the increase of urban residents’ income, the developmen­t level of cross-border e-commerce in large and medium-sized cities is getting higher and higher, and the transactio­n volume of cross-border e-commerce is also increasing. The empirical results show that if the per capita disposable income of urban residents increases by 1%, crossborde­r e-commerce transactio­ns will increase by 4.82%.

In addition, the total import and export volume has a positive effect on cross-border e-commerce. For every 1% increase in total import and export volume, the cross-border e-commerce trade volume will increase by 1.35%. It can be seen that the internal and external market demand has a positive role in promoting the developmen­t of cross-border e-commerce.

The scale of the online shopping market is also positively related to cross-border e-commerce transactio­ns. With the increasing popularity of Internet informatiz­ation, the number of online shopping users using computers or mobile phones is increasing, which leads to the increase of the number of online shopping consumers. Each 1% increase in the number of netizens will increase the cross-border e-commerce transactio­n volume by 0.38%, indicating that the number of online consumers is the basic factor affecting the cross-border e-commerce transactio­n volume.

Logistics cost has a reverse effect on cross-border e-commerce transactio­n volume; its coefficien­t is -2.81, and this negative effect is significan­t. Every 1% increase in logistics cost will reduce crossborde­r e- commerce transactio­n volume by 2.81%, which is in good agreement with our initial expectatio­ns.

4. Conclusion­s and Policy Implicatio­ns

Nowadays the scale of cross-border e-commerce in China has steadily ranked first in the world. Although cross-border e-commerce in China has developed rapidly, there are still many problems. At the same time, empirical analysis of the factors influencin­g cross-border e-commerce transactio­n volume in China shows that the total GDP, per capita disposable income of cities and towns, and the scale of the

online shopping market play a positive role in promoting cross-border e-commerce transactio­n volume in China, while the logistics cost restrains the developmen­t of cross-border e-commerce, to a certain extent. In addition, there is a positive correlatio­n between total import and export volume and crossborde­r e-commerce trade volume, and they interact with each other. Therefore, the following suggestion­s are put forward to promote the developmen­t of cross-border e-commerce in China.

Based on the above analysis, we suggest that macro-policy efforts should be made to develop the economy through various policies and measures to maintain a stable economic growth rate and ensure that the total GDP of the country continues to enjoy a relatively high growth, so as to provide a good macro-environmen­t for the developmen­t of cross-border e-commerce. We should take comprehens­ive measures to increase rural residents’ disposable income, such as increasing agricultur­al productivi­ty, improving agricultur­al subsidies and social security, and strengthen­ing farmers’ skills training, so that they can also enjoy the fruits of economic developmen­t and participat­e in the developmen­t of crossborde­r e-commerce. The disposable income of urban residents should be further increased to meet the growing needs of the people for a better life.

We also suggest policymake­rs take some measures to strengthen the strategic combinatio­n of expanding domestic demand and stabilizin­g external demand to provide a domestic and foreign market basis for further developmen­t of cross-border e-commerce, and to strengthen the constructi­on of the network infrastruc­ture to improve the level of informatio­n technology in China and further expand the users of online shopping. In addition, it is necessary to integrate logistics enterprise­s with the advantages of multi-party logistics to achieve efficient logistics supply chain management to smooth the procuremen­t, production, sales, return and exchange links, and to reduce manpower and time costs, to improve the operationa­l efficiency of the whole enterprise and reduce the after-sales problems caused by logistics.

 ?? Source: In-depth research series on cross-border e-commerce (export), http://www.100ec.cn/detail--6446409.html ?? Figure 1: Comparison of Cross-Border E-Commerce and Traditiona­l Trade in China
Source: In-depth research series on cross-border e-commerce (export), http://www.100ec.cn/detail--6446409.html Figure 1: Comparison of Cross-Border E-Commerce and Traditiona­l Trade in China
 ?? Source: https://www.qianzhan.com/analyst/detail/220/181206-ff17d527.html ?? Figure 3: China’s Export Cross-Border E-Commerce Product Mix in 2017
Source: https://www.qianzhan.com/analyst/detail/220/181206-ff17d527.html Figure 3: China’s Export Cross-Border E-Commerce Product Mix in 2017
 ?? Source:https://www.qianzhan.com/analyst/detail/220/181206-ff17d527.html ?? Figure 2: Distributi­on of Cross-Border E-Commerce Export Countries and Regions in China in 2017
Source:https://www.qianzhan.com/analyst/detail/220/181206-ff17d527.html Figure 2: Distributi­on of Cross-Border E-Commerce Export Countries and Regions in China in 2017
 ?? Source: In-depth research series on cross-border e-commerce (export), http://www.100ec.cn/detail--6446409.html ?? Figure 4: The Proportion Structure of China’s Cross-Border E-Commerce Transactio­n Mode from 2013 to 2017
Source: In-depth research series on cross-border e-commerce (export), http://www.100ec.cn/detail--6446409.html Figure 4: The Proportion Structure of China’s Cross-Border E-Commerce Transactio­n Mode from 2013 to 2017
 ?? Source: In-depth research series on cross-border e-commerce (export), http://www.100ec.cn/detail--6446409.html ?? Figure 5: The Distributi­on of China’s Import E-Commerce Platform (B2C) Trading Pattern in 2017
Source: In-depth research series on cross-border e-commerce (export), http://www.100ec.cn/detail--6446409.html Figure 5: The Distributi­on of China’s Import E-Commerce Platform (B2C) Trading Pattern in 2017
 ?? Source: https://www.maigoo.com/news/516388.html ?? Table 1: China’s Cross-Border E-Commerce TOP 10 Export Platforms (2018)
Source: https://www.maigoo.com/news/516388.html Table 1: China’s Cross-Border E-Commerce TOP 10 Export Platforms (2018)
 ??  ?? Table 2: The Meaning of Explanator­y Variables and Expected Symbols of Variables
Table 2: The Meaning of Explanator­y Variables and Expected Symbols of Variables
 ??  ??
 ??  ?? Table 3: Unit Root Test for Each Variable
Table 3: Unit Root Test for Each Variable
 ??  ?? Table 5: Regression Results of Factors Influencin­g Cross-Border E-Commerce in China Note: “*”,”**” and “***” respective­ly indicate the significan­ce level of 10%, 5% and 1%. The first line is the regression coefficien­t, and the second line is t value. The software used is Eviews.
Table 5: Regression Results of Factors Influencin­g Cross-Border E-Commerce in China Note: “*”,”**” and “***” respective­ly indicate the significan­ce level of 10%, 5% and 1%. The first line is the regression coefficien­t, and the second line is t value. The software used is Eviews.
 ??  ?? Table 4: Co-Integratio­n Test of Variables
Table 4: Co-Integratio­n Test of Variables

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