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。     

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.     

多维信息招标下招标代理机构与投标方串谋的博弈模型及分析

在项目业主不具备自行招标能力的工程招标中,招标代理机构利用代理权设租并与投标方串谋的现象屡禁不止.在多维信息招标相关理论基础上构建了招标代理方与行贿投标方串谋的博弈模型,求解了腐败存在下的最优招标机制、均衡腐败金以及均衡腐败概率,分析了腐败概率的影响因素.研究表明调查力度、惩罚力度的加强以及行贿投标方的实际综合质量水平的提高有利于降低腐败发生的概率,而投标方数量的增加可能会促进腐败的发生.     

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.     

On the robustness of non-linear personalized price combinatorial auctions

Though the VCG auction assumes a central place in the mechanism design literature, there are a number of reasons for favoring Iterative Combinatorial Auctions (ICAs). Several promising ICA formats were developed based on primal–dual and subgradient algorithms. Prices are interpreted as a feasible dual solution and the provisional allocation is interpreted as a feasible primal solution. iBundle(3), dVSV and Ascending Proxy Auction result in VCG payoffs when the coalitional value function satisfies buyer submodularity and bidders bid straightforward, which is an ex-post Nash equilibrium in this case. iBEA and CreditDebit auctions do not even require the buyer submodularity and achieve the same properties for general valuations. Often, however, one cannot assume straightforward bidding and it is not clear from the theory how these non-linear personalized price auctions (NLPPAs) perform in this case. Robustness of auctions with respect to different bidding behavior is a critical issue for any application. We conducted a large number of computational experiments to analyze the performance of NLPPAs with respect to different bidding strategies and valuation models. We compare NLPPAs with the VCG auction and with ICAs with linear prices, such as ALPS and the Combinatorial Clock Auction. While NLPPAs performed very well in case of straightforward bidding, we observe problems with revenue, efficiency, and speed of convergence when bidders deviate.     

How to bid in unified second-price auctions when requests are duplicated

In display advertising auctions, a unique display opportunity may trigger many bid requests being sent to the same buyer. Bid request duplication is an issue: programmatic bidding agents might bid against themselves. In a simplified setting of unified second-price auctions, the optimal solution for the bidder is to randomize the bid, which is quite unusual. Our results motivate the recent switch to a unified first-price auction by showing that a unified second-price auction could have been detrimental to all participants.     

A model of a two-stage all-pay auction

The present paper studies a simple two-stage model of an all-pay auction under complete information. All-pay auctions are often used to model competition with irreversible investments such as political lobbying, and in the existing models, the equilibrium outcomes are quite different from the winner-pay auctions (under complete information): The unique equilibrium is in non-degenerate mixed strategies in the sealed-bid all-pay auction, and the highest value bidder wins at (virtually) no cost in the dollar auction. In sharp contrast with those existing models, the equilibrium outcome in the present setting is almost identical to the winner-pay auctions. That is, (a) the highest value bidder wins with probability one, and (b) the revenue of the seller is equal to the second highest value among the bidders. Also, from a mechanism-design point of view, the present game form is more robust than other all-pay mechanisms in that the seller does not need any information about the bidders’ valuations. Although the analysis focuses on the two-bidder two-stage case, the results extend to arbitrary numbers of bidders and stages.     

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．     

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.     

Visualizing Online Auctions

Online auctions have been the subject of many empirical research efforts in the fields of economics and information systems. These research efforts are often based on analyzing data from Web sites such as eBay.com which provide public information about sequences of bids in closed auctions, typically in the form of tables on HTML pages. The existing literature on online auctions focuses on tools like summary statistics and more formal statistical methods such as regression models. However, there is a clear void in this growing body of literature in developing appropriate visualization tools. This is quite surprising, given that the sheer amount of data that can be found on sites such as eBay.com is overwhelming and can often not be displayed informatively using standard statistical graphics. In this article we introduce graphical methods for visualizing online auction data in ways that are informative and relevant to the types of research questions that are of interest. We start by using profile plots that reveal aspects of an auction such as bid values, bidding intensity, and bidder strategies. We then introduce the concept of statistical zooming (STAT-zoom) which can scale up to be used for visualizing large amounts of auctions. STAT-zoom adds the capability of looking at data summaries at various time scales interactively. Finally, we develop auction calendars and auction scene visualizations for viewing a set of many concurrent auctions. The different visualization methods are demonstrated using data on multiple auctions collected from eBay.com.     

Auctions with bidder-determined allowable combinations

Combinatorial auctions are desirable as they enable bidders to express the synergistic values of a group of assets and thus may lead to better allocations. Compared to other types of auctions, they keep bidders from being exposed to risks (of receiving only parts of combinations that would be valuable to them) or from being overly cautious (in order to minimize such risks). However, computation time needed to determine the set of optimal winning combinations in a general combinatorial auction may grow exponentially as the auction size increases, and this is sometimes given as a reason for not using combinatorial auctions. To determine the winning allocation in a reasonable time, a bid taker might try to limit the kinds of allowable combinations, but bidders may disagree on what combinations should be allowed, and this may make limiting the allowable combinations politically infeasible.This paper proposes and tests successfully a new approach to managing the computational complexity of determining the set of winning combinations. The main idea is to let bidders themselves determine and prioritize the allowable combinations. Using bidder-determined combinations has two nice properties. First, by delegating the decision on what is biddable to the bidders who know what combinations are important to them, the bid taker is able to be (and appear) fair. Second, since bidders know their economics and have the incentive to get important combinations included, bidder prioritization of combinations will tend to assure that the most economically-important combinations are included in determining the winning set of bids if the bid taker is not able to consider all of the combinations submitted by bidders. The proposed auction process is useful in situations, such as government auctions, in which the bid taker is reluctant to limit the allowable combinations.     

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.     

Optimal bidding in auctions of mixed populations of bidders

A mixed population of bidders consists of two asymmetric groups. Members of the first group are game-theoretic players, who maximize their expected profit and incorrectly believe that their opponents act similarly. The second group of bidders adopts an irrational strategy: they either choose their bids randomly following a given probability distribution, in a “naïve” form of bidding, or follow a decision-theoretic approach, maximizing their expected profit under the assumption that all other bids are random. In a sealed bid private-value procurement auction we examine the optimal strategy of a new player, who has perfect knowledge of the structure of the mixed bidder population and enters the auction. The optimal bid of the new bidder is derived when the cost and mark-up follow a uniform distribution in [0, 1]. The effect of the relative size of the group of game-theoretic bidders and the population size on the optimal bid price is established.     

Auctions with synergy and resale

We study a sequential auction of two objects with two bidders, where the winner of the package obtains a synergy from the second object. If reselling after the two auctions occurs, it proceeds as either monopoly or monopsony take-it-or-leave-it offer. We find that a post-auction resale has a significant impact on bidding strategies in the auctions: Under the monopoly offer, there does not exist an equilibrium (symmetric or asymmetric) where bidders reveal their types with positive probability. Under the monopsony offer, however, we can identify symmetric increasing equilibrium strategies in auctions for both items. While allowing resale always improves efficiency, we demonstrate that the effect of resale on expected revenue and the probability of exposure are both ambiguous.     

面向电子逆向拍卖的多属性报价建议模型

针对多属性拍卖中报价的复杂性和现有报价指导模型的局限性,提出了一个以拍卖方的总价值提升为基本约束,以投标人的利润最大化为目标的多属性报价建议模型,并引入二元变量解决了定性属性的推荐问题。当投标人具有不同的投标能力和偏好时,模型可根据投标人的投标要求进行报价推荐;当存在单位价值相同的推荐报价时,模型设置了相应的约束以鼓励早投标行为。最后,还从理论上证明了该模型的稳定性,并通过算例说明了模型的可行性。     

Predicting the probability of winning sealed bid auctions: a comparison of models

This paper is concerned with predicting the probability of tendering the lowest bid in sealed bid auctions. Four of the leading models from the bidding literature are shown to be subsumed within a generalised model. These models are then tested relative to the equal probability model by an empirical analysis of a large sample of real construction contract bidding data via all-in, one-out and one-on sample frames. A binomial test is used to measure the ability to predict the identity of the lowest bidders and the average logscore is used to measure the ability to predict the probability of each bidder being the lowest. Optimal cut-off criterion values are determined for defining the minimum size of dataset needed for disaggregating bidders. The work also highlights the importance of (1) the treatment of new entrants and general shortage of data on individual bidders, and (2) the treatment of predicted ties.     

Core-selecting package auctions

Auctions that select core allocations with respect to reported values generate competitive levels of sales revenues at equilibrium and limit bidder incentives to use shills. Among core-selecting auctions, the ones that minimize seller revenues also maximize incentives for truthful reporting, produce the Vickrey outcome when that lies in the core and, in contrast to the Vickrey auction, and create no incentive for a seller to exclude qualified bidders. Core-selecting auctions are related to and share properties with stable matching mechanisms.     

Using bid data for the management of sequential,multi-unit,online auctions with uniformly distributed bidder valuations

Internet auctions for consumers’ goods are an increasingly popular selling venue. We have observed that many sellers, instead of offering their entire inventory in a single auction, split it into sequential auctions of smaller lots, thereby reducing the negative market impact of larger lots. Information technology also makes it possible to collect and analyze detailed bid data from online auctions. In this paper, we develop and test a new model of sequential online auctions to explore the potential benefits of using real bid data from earlier auctions to improve the management of future auctions. Assuming a typical truth-revealing auction model, we quantify the effect of the lot size on the closing price and derive a closed-form solution for the problem of allocating inventory across multiple auctions when bidder valuation distributions are known. We also develop a decision methodology for allocating inventory across multiple auctions that dynamically incorporates the results of previous auctions as feedback into the management of subsequent auctions, and updating the lot size and number of auctions. We demonstrate how information signals from previous auctions can be used to update the auctioneer’s beliefs about the customers’ valuation distribution, and then to significantly increase the seller’s profit potential. We use several examples to reveal the benefits of using detailed transaction data for the management of sequential, multi-unit, online auctions and we demonstrate how these benefits are influenced by the inventory holding costs, the number of bidders, and the dispersion of consumers’ valuations.     

两种记分函数下多属性拍卖投标均衡策略

以拍卖人期望收益最大化为机制设计目标,讨论两种不同偏好的记分函数条件下,最高得分密封投标拍卖和连续完全信息多属性英式拍卖中,卖者的最优投标策略和买者的最优拍卖设计问题,主要结论是:1)无论选择哪种拍卖方式和记分函数,拍卖人均有动机隐瞒自己的真实偏好,除非竞价人是同质的或参与人数足够多.2)竞价人最优属性策略qi*与拍卖...     

Flow auctions

Flow goods (like electricity) are sold through auctions in a dynamic framework. An important design question is the frequency of such auctions. We use a simple dynamic auction model in continuous time to answer this question. We focus on the relationship between the persistency of bidders’ valuations and the optimal choice of frequency. If the seller focuses on the equilibrium in which bidders follow a repeated static Nash strategy, then the frequency of auctions should typically increase when persistency declines. However, accounting for the fact that bidders can follow different equilibria that are collusive in nature, the comparative statics are reversed, forcing the seller to reduce the frequency when bidders’ valuations are less persistent. The argument builds on the fact that high frequency auctions are more conducive to collusion among bidders.