Research and Application of Compulsive Buying Behaviors of Consumers in E-Commerce Livestreaming on Big Data

Abstract

Due to the rise of e-commerce live streaming, more and more Chinese people liked live streaming shopping in recent years. In the era of digital economy, e-commerce platform has developed into a data platform ecosystem built around data resources and data mining technology system. The most typical application of big data is also concentrated in the field of e-commerce livestreaming. E-commerce live streaming platform is a multidisciplinary research field. It is not easy to have a comprehensive understanding of the knowledge structure in this field. In this study, the purpose of this study is to derive and empirically validate a stimulus–organism–response (SOR) model that explains the factors influencing the compulsive buying behavior of customers in livestreaming service platforms offered by well-established e-commerce leaders in China, such as Alibaba Taobao Live. Based on the analysis of the research conclusion, this study proposes that the operators of store livestreaming should improve customers' trust and purchase intention from the aspects of utilitarian value, hedonic value, social value, and perceived value, as well as the use of edge information advantages. Therefore, from the perspective of customer psychology and based on the stimulus–organic–response (S–O–R) theory, this paper empirically analyzes the impact of livestreaming marketing mode on customers' compulsive buying decisions by using structural equation modeling.