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The development dilemma and countermeasures of Chinese cross-border e-commerce enterprises under the background of big data.

Authors :
Chen, Guofang
Source :
Journal of Computational Methods in Sciences & Engineering. 2023, Vol. 23 Issue 2, p1087-1099. 13p.
Publication Year :
2023

Abstract

Cross-border e-commerce has gradually emerged with the popularity of the Internet in the world. It represents a new business model of e-commerce. The public is still the same as the daily shopping model on e-commerce platforms. However, cross-border e-commerce can be divided into two parts at home and abroad. With the continuous emergence of new social models such as the Metaverse, the data generated by online social networking is becoming larger and larger, and data science has developed accordingly, and the effective use of data has become the key to the rapid development of various industries. Big data technology is the key to data science. A data processing and analysis technology generated in the development process, its use in the development of cross-border e-commerce enterprises will help enterprises to create products that are more in line with the actual requirements of the masses, increase the profits of enterprise operations, and allow enterprises to complete the era of data science smooth transition. This paper first describes the big data technology and related theories of cross-border e-commerce, and then takes Alibaba as an example to describe the SWOT analysis of my country's cross-border e-commerce enterprises, and then analyzes the development dilemma of China's cross-border e-commerce enterprises, and finally designs The development strategy of my country's cross-border e-commerce enterprises based on big data is presented. Through a questionnaire survey of cross-border e-commerce enterprises that use big data technology in my country, it is found that cross-border e-commerce enterprises that combine big data technology have a greater understanding of overseas customers' consumption psychology, integration of warehousing and logistics resources, and talent training. promote. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
14727978
Volume :
23
Issue :
2
Database :
Academic Search Index
Journal :
Journal of Computational Methods in Sciences & Engineering
Publication Type :
Academic Journal
Accession number :
162876926
Full Text :
https://doi.org/10.3233/JCM-226632