Comparing the Spanish and the discriminatory auction formats: A discrete model with private information

The Spanish Treasury is the only Treasury in the world that uses a hybrid system of discriminatory and uniform price auctions to sell government debt: winning bidders pay their bid price for each unit if this is lower than the weighted average price of winning bids (WAP), and pay the WAP otherwise. Following Gordy [Gordy, M., 1996. Multiple bids in a multiple-unit common-value auction. Board of Governors of the Federal Reserve System], we model the Spanish auction as a common value auction of multiple units with private information, allowing for multiple bids. Numerical analysis shows that bidders spread their bids more in the Spanish than in the discriminatory auction and bid higher for the first unit, and that the expected seller’s revenue is higher in the Spanish than in the discriminatory auction within a reasonable set of parameter values.     

Exact methods for combinatorial auctions

This is a summary of the author’s PhD thesis supervised by Frits Spieksma and defended on 20 December 2006 at the Katholieke Universiteit Leuven. The thesis is written in English and is available from the author’s website (http://www.econ.kuleuven.be/dries.goossens/public). This work deals with combinatorial auctions, i.e., auctions where bidders can bid on sets of items. We study two special cases, namely the total quantity discount auction and the matrix bid auction.      

Allocative efficiency in simulated multiple-unit combinatorial auctions with quantity support

We study the behavior of the Quantity Support Mechanism, a support tool, which suggests new bids for bidders in semi-sealed-bid combinatorial auctions. The support tool gives bidders a shortlist of provisionally winning bids (price–quantity combinations) they can choose from. We conducted a series of simulations to test the efficiency of the final allocations in the auctions. Our results indicate that quantity support auctions are more efficient than auctions without it, although the theoretical optimum is not always reached. Also, in our experiments, quantity support auctions led to a lower total cost to the buyer than non-combinatorial auctions, where the items were auctioned individually. The simulation results also show that the QSM cannot entirely overcome the threshold problem and what we call the “puzzle problem”.     

Non-linear anonymous pricing combinatorial auctions

In combinatorial auctions the pricing problem is of main concern since it is the means by which the auctioneer signals the result of the auction to the participants. In order for the auction to be regarded as fair among the various participants the price signals should be such that a participant that has won a subset of items knows why his bid was a winning bid and that agents that have not acquired any item easily can detect why they lost. The problem in the combinatorial auction setting is that the winner determination problem is a hard integer programming problem and hence a linear pricing scheme supporting the optimal allocation might not exist.     

Design of discrete Dutch auctions with an uncertain number of bidders

The focus of this paper is on Dutch auctions where the bidding prices are restricted to a finite set of values and the number of bidders follows a Poisson distribution. The goal is to determine what the discrete bid levels should be to maximize the auctioneer’s expected revenue, which is the same as the average selling price of the object under consideration. We take a new approach to the problem by formulating the descending-price competitive bidding process as a nonlinear program. The optimal solution indicates that the interval between two successive bids should be wider as the Dutch auction progresses. Moreover, the auctioneer’s maximum expected revenue increases with the number of bid levels to be set as well as the expected number of bidders. Numerical examples are provided to illustrate the key results from this study and their managerial implications are discussed.     

All-pay auctions with pre- and post-bidding options

Motivated by the emergence of online penny or pay-to-bid auctions, in this study, we analyze the operational consequences of all-pay auctions competing with fixed list price stores. In all-pay auctions, bidders place bids, and highest bidder wins. Depending on the auction format, the winner pays either the amount of their bid or that of the second-highest bid. All losing bidders forfeit their bids, regardless of the auction format. Bidders may visit the store, both before and after bidding, and buy the item at the fixed list price. In a modified version, we consider a setting where bidders can use their sunk bid as a credit towards buying the item from the auctioneer at a fixed price (different from the list price). We characterize a symmetric equilibrium in the bidding/buying strategy and derive optimal list prices for both the seller and auctioneer to maximize expected revenue. We consider two situations: (1) one firm operating both channels (i.e. fixed list price store and all-pay auction), and (2) two competing firms, each operating one of the two channels.     

Pricing in multiple-item procurement auctions with a common to all items fixed cost

In a sealed bid multiple-item procurement auction, bidders may incur a fixed cost, which is common to all items. The paper develops pricing methods which ensure that a preset percentage profit level is always realized and the fixed cost is completely recovered, even if the eventual order is for some of the items at reduced quantities. One approach sets constraints and determines acceptable orders. Another alternative is to provide appropriate discounts. Finally, a third method considers fixed prices and imposes constraints that address the exposure problem of recovering the fixed cost. These methods may also be used for pricing combinatorial auctions.     

Choice of item pricing feedback schemes for multiple unit reverse combinatorial auctions

Recently, interest in combinatorial auctions has extended to include trade in multiple units of heterogeneous items. Combinatorial bidding is complex and iterative auctions are used to allow bidders to sequentially express their preferences with the aid of auction market information provided in the form of price feedbacks. There are different competing designs for the provision of item price feedbacks; however, most of these have not been thoroughly studied for multiple unit combinatorial auctions. This paper focuses on addressing this gap by evaluating several feedback schemes or algorithms in the context of multiple unit auctions. We numerically evaluate these algorithms under different scenarios that vary in bidder package selection strategies and in the degree of competition. We observe that auction outcomes are best when bidders use a naïve bidding strategy and competition is strong. Performance deteriorates significantly when bidders strategically select packages to maximize their profit. Finally, the performances of some algorithms are more sensitive to strategic bidding than others.     

基于树型结构的采购组合拍卖获胜概率计算方法研究

在基于树型结构的采购组合拍卖模型的研究基础上,建立了这一类采购组合拍卖的投标获胜概率的数学模型,给出了投标获胜概率的求解方法.通过算例,详细分析了具体计算方法的规律性和可行性.投标获胜概率的计算方法本身具有重要意义,同时能够为投标者提供决策依据和行为参考;也为进一步研究采购组合拍卖的投标期望收益、均衡策略和机制设计奠定了必要的理论基础.     

Designing sniping agents

Sniping agents are increasingly being deployed to assist bidders in acquiring items in online auctions. This paper reviews the extant auction literature and proposes an overarching sniping agent design framework that could potentially increase the commercial viability of snipping agents. For better alignment between the functions of sniping agents and the needs of human bidders, we review existing literature based on three fundamentals: (1) knowledge about human bidder behavior, (2) awareness of the product(s) desired by a bidder, and (3) an understanding of the research on bidding agents and auction design. The output of this review is the explicit consideration of iterative combinatorial auction agent design, fuzzy set representation of the bidder’s preferences and dynamic derivation of bidding strategies according to the progress of ongoing auctions.     

考虑全局投标者后悔心理行为的组合拍卖的投标均衡策略

许多实验研究表明投标者在拍卖过程中往往表现出预期后悔心理行为,并且投标者的预期后悔心理行为将会对投标策略产生影响,但以往大多是针对单物品拍卖研究考虑投标者后悔心理行为的投标均衡策略,而针对多物品拍卖情形的研究较少关注。本文着重研究了考虑投标者后悔心理行为的组合拍卖的投标均衡策略问题,在全局投标者存在预期后悔心理行为的假设下,依据Engelbrecht-Wiggans和Katok提出的后悔函数刻画了投标者的后悔心理行为,在此基础上,构建了组合拍卖模型,通过分析给出了全局投标者投标均衡策略需要满足的充分和必要条件。进一步地,依据构建的模型,通过数值实验分析了局部投标者人数、组合效应系数和全局投标者后悔参数对全局投标者投标策略的影响。最后,通过一个关于无线电频谱组合拍卖的算例说明了本文给出的模型及投标均衡策略确定方法的潜在应用和优越性。     

A new end-of-auction model for curbing sniping

The online auction market has been growing at a spectacular rate. Most auctionsare open-bid auctions where all the participants know the current highest bid.This knowledge has led to a phenomenon known as sniping, whereby somebidders may wait until the last possible moment before bidding, therebydepriving other bidders of the opportunity to respond and also preventingsellers from obtaining the highest price for an item. This is especially true inthe case of the commonly used second-price, fixed-deadline auction. We considera procedure involving a randomly determined stopping time and show that thisapproach eliminates the potential benefits to a sniper. The scheme enables allbidders to compete more fairly and promotes an early bidding strategy, which islikely to increase the price received by the seller while providing adequatebidding opportunities for would-be buyers.     

Investigating buyer and seller strategies in online auctions

The annual turnover of online auctions is already in tens of billions of dollars and this amount is predicted to grow substantially over the next few years. Hence, it is important to know how buyers and sellers can influence their chances of success. Therefore, data were collected from eBay auctions for three different categories of collectible items, namely those with a published guide price, those with a rough guide price and those having no easily obtainable guide price. The options available to buyers and sellers of items were then analysed. It was found that it was hard for the seller to influence an item's achieved price significantly, apart from items with no guide price where the starting price could have an effect. Most bidders bid close to the current value and so there were insufficient data to determine the consequences of timing on the placing of high bids. For low bids, delaying a bid was found to improve significantly the chances of winning for one of the data sets.     

The buy price in auctions with discrete type distributions

This paper considers second-price, sealed-bid auctions with a buy price where bidders’ types are discretely distributed. We characterize all equilibria in which bidders whose types are less than the buy price bid their own valuations. Budish and Takeyama (2001) analyze the two-bidder, two-type framework. They show that if bidders are risk-averse, then the seller can obtain a higher expected revenue from the auction with a certain buy price than from the auction without a buy price. We extend their revenue improvement result to the n-bidder, two-type framework. In case of three or more types, however, bidders’ risk aversion is not a sufficient condition for a revenue improvement. We point out that even if bidders are risk-averse, the seller cannot always obtain a higher expected revenue from the auctions with a buy price.     

An efficient local search algorithm for the winner determination problem

Combinatorial auction, which allows bidders to bid on combinations of items, is an important type of market mechanism. The winner determination problem (WDP) has extensive applications in combinatorial auctions, and attracts more and more attention due to its strong relevance to business. However, this problem is intractable in theory as it has been proven to be NP-hard, and is also a challenging combinatorial optimization problem in practice. This paper is devoted to designing an efficient heuristic algorithm for solving the WDP. This proposed heuristic algorithm dubbed abcWDP is based on an effective yet simple local search framework, and equipped with three novel strategies, i.e., configuration checking, free-bid exploiting, and pseudo-tie mechanism. Extensive computational experiments on a broad range of benchmarks demonstrate that abcWDP performs much better than state-of-the-art algorithms and CPLEX in terms of both revenue and running time. More encouragingly, our abcWDP algorithm as a sequential algorithm even achieves better computational results than the multi-thread implemented algorithm \(\hbox {CA}_\mathrm{RA}\), which confirms its efficiency.     

An auction with positive externality and possible application to overtime rules in football,soccer, and chess

We analyze auctions with positive externality, wherein the utility of each player who submitted a losing bid is strictly increasing in the price paid by the winning bidder. Such an auction was recently proposed for determining the starting team and the starting yard line in an overtime period in American football. We analyze the NFL case and also consider other football leagues, as well as tie-breaking by penalty shots in soccer, and overcoming a draw situation in chess.     

Dynamic lot-sizing in sequential online retail auctions

Retailers often conduct non-overlapping sequential online auctions as a revenue generation and inventory clearing tool. We build a stochastic dynamic programming model for the seller’s lot-size decision problem in these auctions. The model incorporates a random number of participating bidders in each auction, allows for any bid distribution, and is not restricted to any specific price-determination mechanism. Using stochastic monotonicity/stochastic concavity and supermodularity arguments, we present a complete structural characterization of optimal lot-sizing policies under a second order condition on the single-auction expected revenue function. We show that a monotone staircase with unit jumps policy is optimal and provide a simple inequality to determine the locations of these staircase jumps. Our analytical examples demonstrate that the second order condition is met in common online auction mechanisms. We also present numerical experiments and sensitivity analyses using real online auction data.     

A new pricing scheme based on DEA for iterative multi-unit combinatorial auctions

Iterative Multi-unit Combinatorial Auctions are auctions in which: bidders can express bids in successive rounds until a stopping rule is held; there are multiple units of each item; and bids are bundles of items. Data Envelopment Analysis (DEA) is a nonparametric method for measuring the relative efficiency of a set of homogeneous units. In this work, we present an algorithm for solving an iterative multi-unit combinatorial auction in which the auctioneer computes at each round a linear anonymous price for each item by using a DEA model and pushes bidders to express bids according to them. A computational study is carried out in order to check the performance of the proposed design.      

An experimental test of alternative models of bidding in ascending auctions

The theory and behavior of the clock version of the ascending auction has been well understood for at least 20 years. The more widely used oral outcry version of the ascending auction that allows bidders to submit their own bids has been the subject of some recent controversy mostly in regard to whether or not jump bidding, i.e. bidders submitting bids higher than required by the auctioneer, should be allowed. Isaac, Salmon & Zillante (2005) shows that the standard equilibrium for the clock auction does not apply to the non-clock format and constructs an equilibrium bid function intended to match with field data on ascending auctions. In this study, we will use economic experiments to provide a direct empirical test of that model while simultaneously providing empirical evidence to resolve the policy disputes centered around the place of jump bidding in ascending auctions.Received: March 2005The authors would like to thank Florida State University for providing the funding for the experiments in this paper and Bradley Andrews for programming assistance.     

基于网上拍卖的共同价值托投标分析

基于信息不对称条件下的共同价值模型,刻画了网上拍卖过程中可能存在的托投标行为,并运用博弈理论结合竞价关系求解了竞标者的赢标概率和最优竞价策略．研究发现,在共同价值模型下,参与竞标的人数与嬴者诅咒的发生存在联系;在最高出价者赢标的概率模型基础上,分别建立了是否存在托投标行为时的竞标者收益模型,并求解了竞标者的均衡竞价策略．