Satisfaction and dissatisfaction in online auctions: an empirical analysis

Xiaowen Huang (Department of Management, Miami University, Oxford, Ohio, USA)
Byron J. Finch (Department of Management, Miami University, Oxford, Ohio, USA)

International Journal of Quality & Reliability Management

ISSN: 0265-671X

Publication date: 7 September 2010



The purpose of this paper is to empirically test the validity of a two‐factor theory for seller service quality in the online auction context.


A sample of 2,000 buyer feedbacks about seller performance (1,000 positive and 1,000 negative) was collected from eBay. Content analysis of positive and negative feedback was conducted and the frequencies of mention of specific service quality attributes were compared.


Analysis of total mentions and exclusive mentions of service quality attributes showed significantly different content for positive and negative feedback, supporting the validity of two‐factor theory in this context and adding to the understanding of customer expectations in this environment.

Practical implications

The paper's findings can guide sellers' allocation of efforts in service design, so they can establish and maintain the reputation necessary to attract bidders and successfully compete in high‐risk online environments like eBay.


The paper extends the understanding of quality determinants in a service environment substantially different to traditional environments because of the risks to which buyers are exposed, information asymmetry, and the lack of previous experience with buyers. In addition, the finding of support for two‐factor theory is in a direct contrast with the conventional, one‐factor model subscribed by most quality researchers in the operations management field, and highlights the importance of investigating customer satisfaction and dissatisfaction separately in the online auction environment.



Huang, X. and Finch, B. (2010), "Satisfaction and dissatisfaction in online auctions: an empirical analysis", International Journal of Quality & Reliability Management, Vol. 27 No. 8, pp. 878-892.

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