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A SECPG model for purchase behavior analysis in social e‐commerce environment
Author(s) -
Lv Junjie,
Wang Tong,
Wang Hao,
Yu Jianye,
Wang Yuanzhuo
Publication year - 2020
Publication title -
international journal of communication systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.344
H-Index - 49
eISSN - 1099-1131
pISSN - 1074-5351
DOI - 10.1002/dac.4149
Subject(s) - purchasing , reputation , computer science , e commerce , commodity , social commerce , relation (database) , key (lock) , marketing , social media , business , world wide web , computer security , data mining , social science , finance , sociology
Summary In social e‐commerce environment, consumers share commodity information with others frequently. It is urgent for social e‐commerce enterprises or merchants to learn rules about commodity information dissemination so as to improve the purchase rate of goods and predict the sales trend at the same time. In this paper, we extend the social e‐commerce customers' purchasing behavior game model (SECPG model) to simulate multiple complex social e‐commerce networks, so as to further quantify internal relation between users' information dissemination and online shopping behavior to a certain extent and predict the purchase rate in diverse social e‐commerce networks. The concept of relationship update frequency is introduced to the updating mechanism in social e‐commerce, and simulations are carried out for networks with various update frequency of social relations. Numerical simulations show that individuals' reputation and cost‐to‐benefit ratio both have specific ranges of influence on the purchase rate in social e‐commerce environment. And relationship update frequency is also a key factor for users to spread purchase information.

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