文献类型：期刊文献

英文题名：Price Dispersion, Bargaining Power, and Consumers' Online Shopping Experience in e-Commerce: Evidence from Online Transactions

作者：Li, Zongwei[1];Ren, Lingling[1];Li, Zhenyu[1];Chen, Jianing[1];Tian, Xu[1];Zhang, Yanhui[2]

机构：[1]Shanghai Inst Technol, Sch Econ & Management, Shanghai 200235, Peoples R China;[2]East China Univ Sci & Technol, Sch Business, Shanghai 200237, Peoples R China

年份：2023

卷号：2023

外文期刊名：MATHEMATICAL PROBLEMS IN ENGINEERING

收录：;EI(收录号：20230413425625);WOS:【SCI-EXPANDED(收录号:WOS:000915778600001)】；

基金：AcknowledgmentsThis work was supported by the National Natural Science Foundation of China (71974130) and the National Social Science Fund of China (18BGL093).

语种：英文

外文关键词：Cluster analysis - Dispersions - Learning systems - Regression analysis

摘要：With the development of artificial intelligence and machine learning technology, online shopping is increasingly becoming the mainstream shopping method. It is challenging to investigate the correlation between price dispersion and bargaining. In accordance with the assimilation-contrast theory, this study theorizes about the influence of price dispersion on consumers' bargaining power and it aims to analyze the moderating role of online shopping experience of consumers. Therefore, this paper develops a discrete price model to measure the dispersion of product prices in the marketplace. Cluster analysis was subsequently conducted to preliminary explore the association between price dispersion and bargaining. With the construction of a multiple regression model, the phenomena found by the cluster analysis are further analyzed. The results indicate that the bargaining power of consumers increases with the increase of the price dispersion level. At high levels of the price dispersion, high-experienced consumers exhibit greater bargaining power than low-experienced consumers. At low levels of price dispersion, low-experienced consumers have higher bargaining power than high-experienced consumers. Finally, we demonstrate the validity and robustness of the study results by grouping regressions and replacing four measures of price dispersion.