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The rise of the Internet and e-commerce has seen the emergence of a number of new business models, and adaptations of others (Rappa, 2004). One important example of a successful adaptation is the online auction.
Most traditional auctions attracted attention from limited numbers, e.g., the very wealthy, or specific-interest groups such as used car salesmen, real estate developers, or fresh produce and livestock dealers. In contrast, online auctions have changed the profile of interested parties significantly (Gilkeson & Reynolds, 2003).
Online auctions based on the Internet have resulted in lowered barriers to entry, improved flow of information, enhanced power of buyers, increased efficiencies, and intensified competition (Ibeh, Luo & Dinnie, 2005). Accessibility has also dramatically increased: the ubiquity of the Internet means that many more people have access to online auctions and to the information relating to any specific auction, than would be the case for traditional fixed-time-and-place auctions.
In many ways, online auctions follow the approaches of traditional auctions. Thus online auctions can be open or sealed bid, single or multiple item lots, a seller can set a reserve price or not, and either the first in descending order (Dutch auction) or the last bid in ascending order (English auction) can be the winning one. Bidding can open at zero with a hidden price reserve, or the seller can predetermine the opening bid price (Massad & Tucker, 2000).
Hofacker (1999) noted five categories of risk associated with auctions: time between purchase and delivery, vendor trustworthiness, security, brand integrity, and privacy. All of these apply to online auctions as well as traditional auctions. However, despite the risks, online auctions have been found to exceed in-person auctions both with regard to opening bid prices and average final prices (Massad & Tucker, 2000).
In any auction, final prices paid for the goods being auctioned are the ultimate indication of success. Stern and Stafford (2006) identified three groups of factors which determine final prices in online auctions: buyer factors, seller factors, and site factors. Other auction research literature also supports these three groups. Each group of factors is examined below.