User heterogeneity and its impact on electronic auction market design: An empirical exploration

Ravi Bapna, Paulo Goes, Alok Gupta, Yiwei Jin

Research output: Contribution to journalReview articlepeer-review

221 Scopus citations

Abstract

While traditional information systems research emphasizes understanding of end users from perspectives such as cognitive fit and technology acceptance, it fails to consider the economic dimensions of their interactions with a system. When viewed as economic agents who participate in electronic markets, it is easy to see that users' preferences, behaviors, personalities, and ultimately their economic welfare are intricately linked to the design of information systems. We use a data-driven, inductive approach to develop a taxonomy of bidding behavior in online auctions. Our analysis indicates significant heterogeneity exists in the user base of these representative electronic markets. Using online auction data from 1999 and 2000, we find a stable taxonomy of bidder behavior containing five types of bidding strategies. Bidders pursue different bidding strategies that, in aggregate, realize different winning likelihoods and consumer surplus. We find that technological evolution has an impact on bidders' strategies. We demonstrate how the taxonomy of bidder behavior can be used to enhance the design of some types of information systems. These enhancements include developing user-centric bidding agents, inferring bidders' under-lying valuations to facilitate real-time auction calibration, and creating low-risk computational platforms for decision making.

Original languageEnglish (US)
Pages (from-to)21-43
Number of pages23
JournalMIS Quarterly: Management Information Systems
Volume28
Issue number1
DOIs
StatePublished - Mar 2004

Keywords

  • Bidding strategies
  • Calibration
  • Electronic markets
  • Online auctions
  • Simulation
  • Smart agents
  • User behavior taxonomy
  • Valuation discovery

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