Economic and experimental analysis and design of auction-based online mercantile processes
Date of Completion
January 1999
Keywords
Business Administration, General|Economics, Commerce-Business|Mass Communications
Degree
Ph.D.
Abstract
Traditionally, the posted-price based electronic catalog process has served as the mechanism of choice for conducting electronic commerce activity on the web. Increasingly, business auctions are gaining popularity as an efficient and flexible on-line mercantile channel. We characterize the various dimensions of online auctions and focus our attention on the business-to-consumer (B2C) dimension. Typically, such auctions sell multiple-units of identical products. However, much of traditional auction theory has focussed on analyzing single-item auctions. We demonstrate the lack of applicability of single-item results in multi-item settings. We derive a general expression that characterizes the multiple equilibria that can arise in such auctions and segregate these into desirable and undesirable categories. Additionally, we show that number of such equilibria grows combinatorially with the number of items being sold. ^ Using empirical data from real-world online auctions we sift through the multitude of decision variables that auctioneers could control and identify the bid-increment as the key revenue impacting one. ^ We also present the first ever categorization of consumer bidding strategies in online auctions, and study the interaction between the bid-increment and such strategies. With a motive of providing concrete strategic directions to online auctioneers we derive an upper bound beyond which the bid-increment should not be set. Empirical evidence shows in retrospect that setting a bid increment higher than the upper bound has a negative impact on auctioneer's revenue. Finally, we discuss a controlled laboratory experiment that utilizes salient monetary incentives and allows us to further test our analytical and empirical findings. ^
Recommended Citation
Bapna, Ravi, "Economic and experimental analysis and design of auction-based online mercantile processes" (1999). Doctoral Dissertations. AAI9942563.
https://digitalcommons.lib.uconn.edu/dissertations/AAI9942563