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Exploring the Effectiveness of Seller Reputation Mechanism Using Online Sales Data

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  • Ying Wang

    (School of Economics and Management, Beijing Jiaotong University, Haidian, Beijing, China)

  • Lei Huang

    (School of Economics and Management, Beijing Jiaotong University, Haidian, Beijing, China)

  • Yi Guo

    (School of Economics and Management, Beijing Jiaotong University, Haidian, Beijing, China)

Abstract

This paper attempts to explore the effectiveness of the seller reputation mechanism by an empirical study using online sales data collected from TaoBao.com. A comparison analysis of seller reputation metrics of TaoBao, Amazon, and jd are carried out before the selection of the seller reputation metrics. The seller reputation metrics of small appliances are used as the input for the study considering the quality homogeneity among different sellers of the market, and the sales performance is measured by the sales amount of the recent month. The univariate analysis are performed to find out the effect of different seller reputation metrics on the sales performance, and the attribute selection technique is then applied to reveal the most significant factors contributing to the sales performance. The result indicates the significance of the user subjective assessment on the sales performance.

Suggested Citation

  • Ying Wang & Lei Huang & Yi Guo, 2014. "Exploring the Effectiveness of Seller Reputation Mechanism Using Online Sales Data," Journal of Electronic Commerce in Organizations (JECO), IGI Global, vol. 12(2), pages 46-58, April.
    • Handle: RePEc:igg:jeco00:v:12:y:2014:i:2:p:46-58
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