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- Title
Research on the Evaluation of Cross-Border E-Commerce Overseas Strategic Climate Based on Decision Tree and Adaptive Boosting Classification Models.
- Authors
Lei, Yi; Qiu, Xiaodong
- Abstract
At present, China's cross-border e-commerce has ushered in a golden period of development. When developing cross-border e-commerce, enterprises should first assess the market climate of the target country and reasonably select the target country. Based on the PESTEL theory, an evaluation index system is established for China's cross-border e-commerce overseas strategic climate. Taking "One Belt, One Road" as the opportunity and background, the overseas strategic climate of cross-border e-commerce in 62 countries along the "One Belt, One Road" is selected as the research object, and the Decision Tree and Adaptive Boosting classification methods in machine learning are applied to train and predict the established index system. Finally an overall picture of the overseas strategic climate of the 62 countries is obtained. The results are compared and analysed in depth to identify the most suitable countries for cross-border e-merchants and to provide reference for cross-border e-merchants investors.
- Subjects
CHINA; CROSS-border e-commerce; DECISION trees; RESEARCH evaluation; CLASSIFICATION; MACHINE learning
- Publication
Frontiers in Psychology, 2021, Vol 12, p1
- ISSN
1664-1078
- Publication type
Article
- DOI
10.3389/fpsyg.2021.803989