A theoretical and empirical investigation of multi-item on-line auctions

  • Authors:

  • Ravi Bapna;Paulo Goes;Alok Gupta

  • Affiliations:

  • Department of Operations and Information Management, School of Business Administration, University of Connecticut, Storrs, CT 06269, USA E-mail: &lcub/bapna&semi/paulo&semi/alok&rcub/@sba.uconn. ...;Department of Operations and Information Management, School of Business Administration, University of Connecticut, Storrs, CT 06269, USA E-mail: &lcub/bapna&semi/paulo&semi/alok&rcub/@sba.uconn. ...;Department of Operations and Information Management, School of Business Administration, University of Connecticut, Storrs, CT 06269, USA E-mail: &lcub/bapna&semi/paulo&semi/alok&rcub/@sba.uconn. ...

  • Venue:
  • Information Technology and Management
  • Year:
  • 2000

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Abstract

In this paper we explore and analyze the structure of Internet auctions from an analytical and an empirical perspective. Such web-based auctions are rapidly emerging as a mercantile process of choice in the electronic marketplace. We observe current Internet auctions for one-time products, such as rapidly aging hardware, and analyze them within the framework of the existing auction theory. While traditional auction theory focuses on single-item auctions, we observe that a majority of on-line auctions are multi-item auctions. A significant contribution of this work is the theoretical derivation of the structure of the winning bids in multi-item progressive on-line auctions. Additionally, for comparative purposes, we explore the structural characteristics of alternative multi-item auction mechanisms proposed in the auction theory. We derive hypotheses based on our analytical results and compare two different types of auction mechanisms. We test the traditional auction theory assumption regarding the homogeneity of bidders and present the first ever empirically derived classification and performance-comparison of on-line bidders. We test our hypotheses using real-world empirical data obtained by tracking a premier web-based auction site. Statistical analysis of the data indicates that firms may gain by choosing alternative auction mechanisms. We also provide directions for further exploration of this emerging but important dimension of electronic commerce.