"Everything should be made as simple as possible, but not simpler." - Albert Einstein

Seminar Announcement

Analysis of Bidding Behaviors on Ebay

Bruce Bugbee, M.S. Candidate, Department of Statistics, Colorado State University

Monday, April 5, 2010

10:00 a.m., room 008, Statistics Bldg

ABSTRACT

In the past decade, online auctioning has become one of the most successful business innovations.  eBay is the global leader in this marketspace.  This paper focuses on understanding bidder behaviour in order to provide insight into the design of information systems to support online auctions.  In contrast to previous work that uses discrete bidding information, we implement a functional viewpoint of the bidding path.  The similarity between paths is measured in the functional space using L2 distance, which allows us to utilize K-means and PAM clustering methods.  We apply this method to a large sample of collectible (1968 Camaro) and commodity (Digital Camera) eBay auction data to explore current bidding behaviours.  We identify two different clusters of bidding behavior across both items which is associated with a specific winning percentage.  Sniping exists as a component of both behaviours, but a hybrid approach has emerged.  A framework to guide future research on online auctions is presented. 

Advisory Committee:

Dr. Haonan Wang, Advisor
Dr. Stephen Hayne, Co-Advisor
Dr. Mary Meyer, Committee Member
Dr. Leo Vijayasarathy, Computer Information Systems, Outside Member