Green Progress of Cross-border E-Commerce Industry Utilizing Random Forest Algorithm and Panel Tobit Model

• Published in: Applied artificial intelligence Vol. 37; no. 1
• Main Author: Feng, Ye
• Format: Journal Article
• Language: English
• Published: Philadelphia Taylor & Francis 31.12.2023; Taylor & Francis Ltd; Taylor & Francis Group
• Subjects: Algorithms; Economic models; Efficiency; Electronic commerce; International trade; Resource utilization; Supply chains
• ISSN: 0883-9514; 1087-6545
• DOI: 10.1080/08839514.2023.2219561

As both economies and trade broadly globalize, cross-border e-commerce (CBEC) as a branch of international trade has shown great potential for development. The construction of a CBEC realizes the integration and utilization of resources between the CBEC trading platform as the core element and other components of the system, cross-border logistics, payment enterprises, suppliers, and demanders, and improves the overall economic benefits. A model of economic progress at the expense of the environment emerges in the radical development of companies that do not consider the environment and simply earn high incomes at the cost of consuming resources. In this context, it is of great theoretical and empirical importance to examine how to improve the production efficiency of the CBEC supply chain, improve ecological quality and realize the production mode of "low input, high output, and low pollution." In this study, we evaluate the green development of the CBEC industry and study the factors that affect its efficiency level. According to the results of influencing factors, this paper mainly uses the random forest algorithm and panel Tobit approach to investigate the affecting attributes of environmental efficiency and suggest policies to improve the green progression efficiency of the CBEC industry.