Exploring the core factors of online purchase decisions by building an E-Commerce network evolution model |
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| Affiliation: | 1. School of Business and Tourism Management, Yunnan University, Kunming, 650091, China;2. School of Information Science and Technology, Yunnan Normal University, Kunming, 650500, China;3. School of Business, Yango University, Fuzhou, 350015, China;1. School of Economics and Management, Tongji University, Shanghai, 200 092, China;2. College of Business Administration, Shanghai Business School, Shanghai, 201 400, China;1. University of Economics and Law of VNU-HCM, Quarter 3, Linh Xuan Ward, Thu Duc District, Ho Chi Minh City, Viet Nam;2. Faculty of Business Administration, Ton Duc Thang University, No. 19 Nguyen Huu Tho Street, Tan Phong Ward, District 7, Ho Chi Minh City, Viet Nam;1. School of Business and Economics, Universiti Putra Malaysia, Selangor, Malaysia;2. Centre of Value Creation and Human Well-being, Faculty of Economics and Management, Universiti Kebangsaan Malaysia, Bangi, Selangor, Malaysia;1. Symbiosis Institute of Business Management, Bengaluru, India;2. Symbiosis International (Deemed University), Pune, India;3. Xavier Institute of Management, XIM University, Bhubaneswar, India;4. EM Normandie Business School, METIS Lab, France;5. Management Development Institute, Murshidabad, India;6. School of Economics and Management, China University of Geosciences, Wuhan, China;7. Macquarie Business School, Macquarie University, Sydney, Australia |
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| Abstract: | With the continuous development of the Internet and information technology, online shopping has become a popular purchase mode. The in-depth analysis of consumer decision-making in online shopping is an important issue. Our purpose is to study how the factors of the shopping web pages corporately affect online purchase decisions and determine which are the core factors that affect consumer purchase decisions. We screen the influencing factors on the shopping webpage and deploy e-commerce network evolution based on various weight combinations of these factors to generate sales distributions of online products. By comparing these simulated sales distributions to the real data, the optimal weight of each factor is obtained. The results show that sales volume and the number of high-quality negative comments are the most important factors influencing consumers' decision-making, the number of comments and the number of comments with pictures are relatively minor factors, store type and video presentation of the products have the least impact. The optimal simulated sales distribution is very close to the real case and verifies that the introduced network evolution technology is applicable. The proposed model can be used as a uniform evaluation platform for correlational study, which is an important link in the purchase research chain. |
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| Keywords: | e-commerce Online shopping Purchase decision Complex network Network evolution |
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