Analysis of the Correlation between Cross-Border E-Commerce and Economic Growth Based on Hierarchical Multilevel Gray Evaluation Model

Nie Chen,Miaochao Chen

doi:10.1155/2022/8455404

Abstract

Cross-border e-commerce is a new form of global trade development under the background of “Internet+,” and it is also a new engine driving economic development. Cross-border e-commerce is growing rapidly and has broad development prospects. As a pioneering pilot zone for comprehensive cross-border e-commerce, it has played a leading role in the development of the country’s cross-border e-commerce industry. This paper takes China’s 35 cross-border e-commerce comprehensive pilot areas as the research object, selects the annual data of 31 provinces across the country, and conducts an empirical research based on the gray-related Internet development level and economic growth. It analyzes the influencing factors of cross-border e-commerce development, constructs a cross-border e-commerce development influencing factor model, and applies gray theory to conduct an empirical analysis of the correlation between cross-border e-commerce development influencing factors and cross-border e-commerce. The research results show that foreign direct investment has the greatest correlation with the number of websites and webpages; the number of patent applications has the greatest correlation with the number of domains and websites; the total fixed assets have the greatest correlation with the number of Internet users and the number of mobile phones at the end of the year; the total amount of foreign investment enterprises in and out. It has the greatest correlation with the number of URLs and Webpages; GDP has the greatest correlation with the number of Internet users and the number of mobile phones at the end of the year. The Internet infrastructure and popularity have a close relationship with economic growth, and the relationship between foreign investment and patent applications and the level of Internet development is more significant.

Highlights

In the recent years, the inherent relationship between the Internet and economic growth has become one of the academic research hotspots
According to the empirical results, the following conclusions can be drawn: foreign direct investment has the greatest correlation with the number of websites and Webpages, and the smallest correlation with the penetration rate of mobile phones and the Internet
(1) e number of patent applications has the largest correlation with the number of domain names and URLs, and the smallest correlation with the penetration rate of mobile phones and the Internet. e total fixed assets have the greatest correlation with the number of Internet users and the number of mobile phones at the end of the year, and the smallest correlation with the number of Webpages and the penetration rate of mobile phones

Summary

Introduction

The inherent relationship between the Internet and economic growth has become one of the academic research hotspots. E cross-border e-commerce ecosystem is composed of multiple modules such as buyers and sellers, public service agencies, professional service agencies, and the government [10–15] Gaoxincai analyzed the contribution rate of information elements and found that there is a significant positive correlation between the level of regional informatization and the level of economic development. Meilin used the gray correlation method and linear regression model to analyze the regional economic growth level of a region to a large extent determined by the level of informatization construction. Is paper uses the gray correlation model to quantitatively study the degree of correlation between the Internet development level and economic growth indicators, and calculate and analyze the degree of correlation between the indicators. Cross-border e-commerce is achieved by buyers and sellers located in different zones, through the Internet information platform to achieve the information exchange and transaction of various goods or services, and through the provision of offline logistics services

Gray Relational Model

Example Analysis

Conclusion