Online auctions are fast gaining popularity in today's electronic commerce.
Relative to offline auctions, there is a greater degree of multiple bidding and
late bidding in online auctions, an empirical finding by some recent research.
These two behaviors (multiple bidding and late bidding) are of ``strategic''
importance to online auctions and hence important to investigate. In this
article we empirically measure the distribution of bid timings and the extent
of multiple bidding in a large set of online auctions, using bidder experience
as a mediating variable. We use data from the popular auction site
\url{www.eBay.com} to investigate more than 10,000 auctions from 15 consumer
product categories. We estimate the distribution of late bidding and multiple
bidding, which allows us to place these product categories along a continuum of
these metrics (the extent of late bidding and the extent of multiple bidding).
Interestingly, the results of the analysis distinguish most of the product
categories from one another with respect to these metrics, implying that
product categories, after controlling for bidder experience, differ in the
extent of multiple bidding and late bidding observed in them. We also find a
nonmonotonic impact of bidder experience on the timing of bid placements.
Experienced bidders are ``more'' active either toward the close of auction or
toward the start of auction. The impact of experience on the extent of multiple
bidding, though, is monotonic across the auction interval; more experienced
bidders tend to indulge ``less'' in multiple bidding.Comment: Published at http://dx.doi.org/10.1214/088342306000000123 in the
Statistical Science (http://www.imstat.org/sts/) by the Institute of
Mathematical Statistics (http://www.imstat.org