Management Science

Anandalingam, G.; Raghavan, S.

doi: 10.1287/mnsc.1040.0395pmid: N/A

Anandalingam, G.; Day, Robert W.; Raghavan, S.

doi: 10.1287/mnsc.1040.0345pmid: N/A

This paper presents an introductory survey for this special issue of Management Science on electronic markets. We acquaint the reader with some fundamental concepts in the study of electronic market mechanisms, while simultaneously presenting a survey and summary of the essential literature in this area. Along the way, we position each of the papers presented in this special issue within the existing literature, demonstrating the deep impact of these 14 articles on an already broad body of knowledge.

Deltas, George; Engelbrecht-Wiggans, Richard

doi: 10.1287/mnsc.1040.0330pmid: N/A

This paper presents an equilibrium explanation for the persistence of naive bidding. Specifically, we consider a common value auction in which a “naive” bidder (who ignores the winner's curse) competes against a fully rational bidder. We show that the naive bidder earns higher equilibrium profits than the rational bidder when the signal distribution is symmetric and unimodal. We then consider a sequence of such auctions with randomly selected participants from a population of naive and rational bidders, with the proportion of bidder types in the population evolving in response to their relative payoffs in the auctions. We show that the evolutionary equilibrium contains a strictly positive proportion of naive bidders. Finally, we consider more general examples in which a naive bidder matched against a rational bidder does (i) worse than his rational opponent, but (ii) better than a rational bidder matched against another rational bidder. Again, the evolutionary equilibrium contains a strictly positive proportion of naive bidders. The results suggest that overconfident recent entrants in Internet and other low transaction-cost auctions of items that appeal to a mass audience may earn higher payoffs than their experienced competitors and, thus, will not eventually be driven from the market.

Terwiesch, Christian; Savin, Sergei; Hann, Il-Horn

doi: 10.1287/mnsc.1040.0337pmid: N/A

We present a formal model of haggling between a name-your-own-price retailer and a set of individual buyers. Rather than posting a price, the retailer waits for potential buyers to submit offers for a given product and then chooses to either accept or reject them. Consumers whose offers have been rejected can invest in additional haggling effort and increment their offers. This pricing model allows the name-your-own-price retailer to engage in price discrimination: As haggling is costly for the potential buyer, customers with a high willingness to haggle will achieve lower transaction prices. However, because haggling is costly, it reduces overall welfare and diminishes the benefits of price discrimination. Our study is motivated by several name-your-own-price retailers that have recently emerged on the Internet. Based on detailed transaction data of a large German name-your-own-price retailer, we present a model of consumer haggling. We then show how this model can be used to improve the decision making of the retailer, who needs to choose a threshold price above which all offers are accepted. Another decision variable for the retailer lies in the user interface design, which allows the retailer to either facilitate or to hinder the haggling of the consumer.

Ding, Min; Eliashberg, Jehoshua; Huber, Joel; Saini, Ritesh

doi: 10.1287/mnsc.1040.0331pmid: N/A

E-commerce has proved to be fertile ground for new business models, which may be patented (for up to 20 years) and have potentially far-reaching impact on the e-commerce landscape. One such electronic market is the reverse-auction model popularized by Priceline.com. There is still uncertainty surrounding the survival of such new electronic markets currently available on the Internet. Understanding user behavior is necessary for better assessment of these sites' survival. This paper adds to economic analysis a formal representation of the emotions evoked by the auction process, specifically, the excitement of winning if a bid is accepted, and the frustration of losing if it is not. We generate and empirically test a number of insights related to (1) the impact of expected excitement at winning, and frustration at losing, on bids across consumers and biddings scenarios; and (2) the dynamic nature of the bidding behavior—that is, how winning and losing in previous bids influence their future bidding behavior.

Carare, Octavian; Rothkopf, Michael

doi: 10.1287/mnsc.1040.0328pmid: N/A

Theorists have long believed that Dutch auctions are strategically equivalent to standard sealed bidding. However, in recent controlled experiments with actual Dutch and sealed-bid Internet auctions of collectibles, the Dutch auctions produced significantly more revenue. We believe that this happened, in part, because the Internet Dutch auctions are a slow process in which bidders incur incremental transaction costs if they delay bidding. This paper presents models of slow Dutch auctions that include these costs and explain this belief. We first present a decision-theoretic model of a slow Dutch auction. While simple, the decision-theoretic model is fairly general and provides the basic intuition underlying our revenue results. We then develop a game-theoretic model of a slow Dutch auction. We derive two symmetric, payoff-equivalent equilibria of the game in the absence of a cost of return and then consider the more general case of costly return. When the cost of return is in an appropriate range, the seller's expected revenue is an increasing function of that cost.

Sandholm, Tuomas; Suri, Subhash; Gilpin, Andrew; Levine, David

doi: 10.1287/mnsc.1040.0336pmid: N/A

Combinatorial auctions where bidders can bid on bundles of items can lead to more economically efficient allocations, but determining the winners is 𝒩𝒫-complete and inapproximable. We present CABOB, a sophisticated optimal search algorithm for the problem. It uses decomposition techniques, upper and lower bounding (also across components), elaborate and dynamically chosen bid-ordering heuristics, and a host of structural observations. CABOB attempts to capture structure in any instance without making assumptions about the instance distribution. Experiments against the fastest prior algorithm, CPLEX 8.0, show that CABOB is often faster, seldom drastically slower, and in many cases drastically faster—especially in cases with structure. CABOB's search runs in linear space and has significantly better anytime performance than CPLEX.We also uncover interesting aspects of the problem itself. First, problems with short bids, which were hard for the first generation of specialized algorithms, are easy. Second, almost all of the CATS distributions are easy, and the run time is virtually unaffected by the number of goods. Third, we test several random restart strategies, showing that they do not help on this problem—the run-time distribution does not have a heavy tail.

Günlük, Oktay; Ladányi, Lászlo; de Vries, Sven

doi: 10.1287/mnsc.1040.0332pmid: N/A

When combinatorial bidding is permitted in auctions, such as the proposed FCC Auction #31, the resulting full valuations and winner-determination problem can be computationally challenging. We present a branch-and-price algorithm based on a set-packing formulation originally proposed by Dietrich and Forrest (2002, “A column generation approach for combinatorial auctions,” in Mathematics of the Internet: E-Auction and Markets. The IMA Volumes in Mathematics and Its Applications, Vol. 127, Springer-Verlag, New York, 15–26). This formulation has a variable for every possible combination of winning bids for each bidder. Our algorithm exploits the structure of the XOR-of-OR bidding language used by the FCC. We also present a new methodology to produce realistic test problems based on the round-by-round results of FCC Auction #4. We generate 2,639 test problems, which involve 99 items and are substantially larger than most of the previously used benchmark problems. Because there are no real-life test problems for combinatorial spectrum auctions with the XOR-of-OR language, we used these test problems to observe the computational behavior of our algorithm. Our algorithm can solve all but one test problem within 10 minutes, appears to be very robust, and for difficult instances compares favorably to the natural formulation solved using a commercial optimization package with default settings.Although spectrum auctions are used as the guiding example to describe the merits of branch and price for combinatorial auctions, our approach applies to auctions of multiple goods in other scenarios similarly.

Kwon, R. H.; Anandalingam, G.; Ungar, L. H.

doi: 10.1287/mnsc.1040.0335pmid: N/A

In combinatorial auctions, multiple distinct items are sold simultaneously and a bidder may place a single bid on a set (package) of distinct items. The determination of packages for bidding is a nontrivial task, and existing efficient formats require that bidders know the set of packages and/or their valuations. In this paper, we extend an efficient ascending combinatorial auction mechanism to use approximate single-item pricing. The single-item prices in each round are derived from a linear program that is constructed to reflect the current allocation of packages. Introduction of approximate single-item prices allows for endogenous bid determination where bidders can discover packages that were not included in the original bid set. Due to nonconvexities, single-item prices may not exist that are exact marginal values. We show that the use of approximate single-item prices with endogenous bidding always produces allocations that are at least as efficient as those from bidding with a fixed set of packages based on package pricing. A network resource allocation example is given that illustrates the benefits of our endogenous bidding mechanism.

Kwasnica, Anthony M.; Ledyard, John O.; Porter, Dave; DeMartini, Christine

doi: 10.1287/mnsc.1040.0334pmid: N/A

In this paper we present a new improved design for multiobject auctions and report on the results of experimental tests of that design. We merge the better features of two extant but very different auction processes, the Simultaneous Multiple Round (SMR) design used by the FCC to auction the electromagnetic spectrum and the Adaptive User Selection Mechanism (AUSM) of Banks et al. (1989, “Allocating uncertain and unresponsive resources: An experimental approach,” RAND Journal of Economics, Vol. 20, No. 1, pp. 1–25). Then, by adding one crucial new feature, we are able to create a new design, the Resource Allocation Design (RAD) auction process, which performs better than both. Our experiments demonstrate that the RAD auction achieves higher efficiencies, lower bidder losses, higher net revenues, and faster times to completion without increasing the complexity of a bidder's problem.