Affiliations: [a] Business School, Wuchang University of Technology, Wuhan, Hubei, China
| [b] School of Economics, Wuhan Donghu University, Wuhan, Hubei, China
| [c] Accounting Department, Faculty of Commerce, Kafr Elsheikh University, Egypt
Correspondence:
[*]
Corresponding author. Xiaoyong Xiao, School of Economics, Wuhan Donghu University, Wuhan, 430212, Hubei, China. E-mail: xiechao_dhxy@163.com.
Abstract: Social media has accumulated a large number of users by its community, which has greatly changed and affected people’s lifestyles. Social media not only provides convenience for users to make friends, entertainment, information acquisition and other activities, but also provides an ideal way for the development of e-commerce with the advantages of fast transmission speed and accurate audience. The content and behavior of social e-commerce platforms are mostly generated and dominated by users, who are the key subjects that determine the development of platforms and the profitability of enterprises. The main purpose of this study is to enrich the theoretical system of data mining for social e-commerce users and provide a theoretical basis and reference for platform and business management and operation of social e-commerce. First, based on the information ecology and information dissemination perspective, this paper constructs the model of information flow in social e-commerce. Second, based on the social network analysis method, analyzes the social network of social e-commerce users; Finally, based on the integrated model of technology acceptance and use (UTAUT), the theory of perceived risk and the theory of trust, the conceptual model of influencing factors of initial information adoption by users of social e-commerce is constructed, and the key influencing factors are identified by using Delphi method and DEMATEL method. The experimental results show that the degree of centrality of the new technology application is the largest, 5.250, which is the key factor influencing the initial information adoption of social e-commerce users. User satisfaction has the largest influence on the continuous information adoption intention of social e-commerce users, with the influence factor reaching 1.223, followed by IT self-efficacy (0.948), user relationship network structure (0.771), social e-commerce platform quality (0.637), perceived usefulness (0.419) and emotional attachment intensity (0.409).
Keywords: Internet of things and big data, social e-commerce, data mining, user data
