Pallab Sanyal

Effect of Information Feedback on Bidder Behavior in Continuous Combinatorial Auctions

Combinatorial auctions---in which bidders can bid on combinations of goods---can increase the economic efficiency of a trade when goods have complementarities. Recent theoretical developments have lessened the computational complexity of these auctions, but the issue of cognitive complexity remains an unexplored barrier for the online marketplace. This study uses a data-driven approach to explore how bidders react to the complexity in such auctions using three experimental feedback treatments. Using cluster analyses of the bids and the clicks generated by bidders, we find three stable bidder strategies across the three treatments. Further, these strategies are robust for separate experiments using a different setup. We also benchmark the continuous auctions against an iterative form of combinatorial auction---the combinatorial clock auction. The enumeration of the bidding strategies across different types of feedback, along with the analysis of their economic implications, is offered to help practitioners design better combinatorial auction environments. This paper was accepted by Lorin Hitt, information systems.

Effect of Information Feedback on the Outcomes and Dynamics of Multisourcing Multiattribute Procurement Auctions

Electronic auctions are increasingly being used to facilitate the procurement of goods and services in organizations. Multiattribute auctions, which allow bids on multiple dimensions of the product and not just price, are information technology-enabled sourcing mechanisms that can increase the efficiency of procurement for configurable goods and services compared to price-only auctions. Given the strategic nature of procurement auctions, the amount of information concerning the buyers preferences that is disclosed to the suppliers has implications on the profits of the buyer and the suppliers and, consequently, on the long-term relationship between them. This study explores novel feedback schemes for multisourcing multiattribute auctions that require limited exchange of strategic information between the buyer and the suppliers. To study the impact of feedback on the outcomes and dynamics of the auctions, we conduct laboratory experiments wherein we analyze bidder behavior and economic outcomes under three different treatment conditions with different types of information feedback. Our results indicate that, in contrast to winner-take-all multiattribute auctions, multisourcing multiattribute auctions, with potentially multiple winners, allow bidders (i.e., suppliers) to extract more profit when greater transparency in terms of provisional allocations and prices is provided. We develop several insights for mechanism designers toward developing sustainable procurement auctions that efficiently allocate multiple units of an asset with multiple negotiable attributes among multiple suppliers.

Impact of information feedback in continuous combinatorial auctions: an experimental study of economic performance

Advancements in information technology offer opportunities for designing and deploying innovative market mechanisms that can improve the allocation and procurement processes of businesses. For example, combinatorial auctions--in which bidders can bid on combinations of goods--have been shown to increase the economic efficiency of a trade when goods have complementarities. However, the lack of real-time decision support tools for bidders has prevented this mechanism from reaching its full potential. With the objective of facilitating bidder participation in combinatorial auctions, this study, using recent research in real-time bidder support metrics, discusses several novel feedback schemes that can aid bidders in formulating combinatorial bids in real-time. The feedback schemes allow us to conduct continuous combinatorial auctions, where bidders can submit bids at any time. Using laboratory experiments with two different setups, we compare the economic performance of the continuous mechanism under three progressively advanced levels of feedback. Our findings indicate that information feedback plays a major role in influencing the economic outcomes of combinatorial auctions. We compare several important bid characteristics to explain the observed differences in aggregate measures. This study advances the ongoing research on combinatorial auctions by developing continuous auctions that differentiate themselves from earlier combinatorial auction mechanisms by facilitating free-flowing participation of bidders and providing exact prices of bundles on demand in real time. For practitioners, the study provides insights on how the nature of feedback can influence the economic outcomes of a complex trading mechanism.

Competitive bidding for health insurance contracts: lessons from the online HMO auctions

Healthcare is an important social and economic component of modern society, and the effective use of information technology in this industry is critical to its success. As health insurance premiums continue to rise, competitive bidding may be useful in generating stronger price competition and lower premium costs for employers and possibly, government agencies. In this paper, we assess an endeavor by several Fortune 500 companies to reduce healthcare procurement costs for their employees by having HMOs compete in open electronic auctions. Although the auctions were successful in generating significant cost savings for the companies in the first year, i.e., 1999, they failed to replicate the success and were eventually discontinued after two more years. Over the past decade since the failed auction experiment, effective utilization of information technologies have led to significant advances in the design of complex electronic markets. Using this knowledge, and data from the auctions, we point out several shortcomings of the auction design that, we believe, led to the discontinuation of the market after three years. Based on our analysis, we propose several actionable recommendations that policy makers can use to design a sustainable electronic market for procuring health insurance.

Characteristics and Economic Consequences of Jump Bids in Combinatorial Auctions

Jump bidding, which refers to bidding above the minimum necessary, is a robust behavior that has been observed in a variety of ascending auctions in the field as well as the laboratory. However, the phenomenon has yet to be studied in combinatorial auctions, which are a type of multiobject auction that allows bidders to bid on a set of objects. Such auctions have been found to be beneficial when objects exhibit synergy, e.g., are complementary. In this paper, we explore jump bidding behavior in combinatorial auctions as a function of design choices of the mechanism. In particular, we examine the effects of price revelation schemes on the nature and extent of jump bidding. Furthermore, we study the effects of jump bidding on the economic performance of the auctions. To conduct our study, first, we develop hypotheses using auction theories and behavioral theories of how people use reference prices as anchors, and second, we conduct a laboratory experiment to test our hypotheses and examine bidder behavior. We find that the nature of the prices that the auctioneer chooses to offer as feedback to the bidders can considerably influence their jump bidding behavior, leading to significant differences in auction outcomes. We demonstrate that in combinatorial auctions, in addition to the theories of jump bidding proposed in the literature, bounded rationality of the bidders plays a part in the nature and extent of jump bidding. Our study reveals that in the cognitively challenging package-bidding environment, bidders often pursue computationally frugal but suboptimal heuristics. Our results have important policy implications for mechanism designers.