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Price Dispersion, Bargaining Power, and Consumers’ Online Shopping Experience in e-Commerce: Evidence from Online Transactions

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  • Zongwei Li
  • Lingling Ren
  • Zhenyu Li
  • Jianing Chen
  • Xu Tian
  • Yanhui Zhang
  • Bin Liu

Abstract

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.

Suggested Citation

  • Zongwei Li & Lingling Ren & Zhenyu Li & Jianing Chen & Xu Tian & Yanhui Zhang & Bin Liu, 2023. "Price Dispersion, Bargaining Power, and Consumers’ Online Shopping Experience in e-Commerce: Evidence from Online Transactions," Mathematical Problems in Engineering, Hindawi, vol. 2023, pages 1-12, January.
  • Handle: RePEc:hin:jnlmpe:6638665
    DOI: 10.1155/2023/6638665
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    Cited by:

    1. Mishall Al-Zubaidie & Ghanima Sabr Shyaa, 2023. "Applying Detection Leakage on Hybrid Cryptography to Secure Transaction Information in E-Commerce Apps," Future Internet, MDPI, vol. 15(8), pages 1-20, August.

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