基于内生投标人的拍卖

讨论了参与者是内生性的第一价格和第二价格密封拍卖的均衡报价策略 ,两种不同的拍卖形式产生相同的预期收入 ;由于中止值的存在 ,卖方预期收入可能随着潜在参与者的增加而减少 .对拍卖商来说 ,如果投标人是风险回避的 ,那么第一价格密封拍卖比第二价格密封拍卖产生更高的预期收益 .     

多物品拍卖的捆绑销售策略

拍卖商在拍卖多个不同物品的过程中,面临着是捆绑拍卖还是分开拍卖的问题.本文讨论在第二价格密封拍卖(维克里拍卖)方式下,拍卖商拍卖多个不同物品时,其所采取的最优策略(捆绑拍卖或是分开拍卖)与投标人的数量以及投标人对物品的估价的关系.     

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。     

保险动态惩罚机制对网约车平台监督作用的演化博弈研究

采用演化博弈方法,研究保险公司与网约车平台之间的博弈演化过程,分析了在保险公司监督下,网约车平台策略选择的影响因素,并比较了静态惩罚机制和动态惩罚机制下网约车平台与保险公司博弈的均衡策略。研究发现,保险公司的惩罚性保费可以促使网约车平台的策略选择发生改变。在静态惩罚机制下,网约车平台和保险公司的策略选择呈周期波动模式,不能收敛;在动态惩罚机制下,网约车平台和保险公司的博弈呈现螺旋收敛的演化轨迹,且收敛的均衡点不随策略选择的初始概率不同而改变。研究结论明确了保险在网约车行业管理中的社会监督职能,并为保险公司保费的制定提供理论参考。     

两阶段主从博弈均衡解的存在性

首先给出带参数的纳什均衡问题Γ(x),在此基础上给出了具有带参数的纳什均衡约束的两阶段主从博弈问题G.可以证明带参数的纳什均衡点是存在的,即无论领导者选择何种策略,跟随者的最佳回应集都是非空的.最后推出了关于两阶段主从博弈均衡点的存在性定理.     

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.     

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...     

公共资产预算配置的拍卖机制设计

本文探讨在财政部门作为政府出资人的框架下,通过设计一套可行的竞标机制来提高预算项目的配置效率。结合运用机制设计理论和拍卖理论与方法建立竞标机制设计模型,在保证竞标预算单位参与投标和真实显示自己效率的条件下最大化拍卖者——政府出资人的期望效用,并通过求解此模型得到最优的竞标机制。鉴于最优机制在形式上的复杂性,给出了第二高得分拍卖这种最优拍卖方式。最后对公共资产配置预算的规则如何确定才能减少效率损失进行了归纳。     

第一密封价格逆向拍卖机制博弈研究

在供应商对拟投标项目成本估计独立、不同分布的条件下,通过建立不公开保留价的第一价格逆向拍卖机制博弈模型,推导了供应商的最优报价策略,博弈均衡存在时采购者最优保留价满足的条件,发现供应商的报价高于他的成本估计,进一步得到了与该采购机制资源配置效率有关的结论:参与投标的人数越多供应商报价溢出成本部分越少;成本越低的供应商期望支付越大.这对于现实采购拍卖的政策建议为:设法让更多供应商参与竞标,能有效选择优势供应商、降低采购成本、增加社会福利.     

博弈论视角的多属性逆向拍卖评标行为研究

技术属性和商务属性间强负相关性会诱导两组评标专家间的对立情绪和不合作行为,评标管理部门对评标专家的组织管理是评标公平性的重要因素. 以博弈论为工具分别建立了多属性逆向拍卖分组评标机制下技术专家和商务专家之间、管理部门与评标专家之间行为的理论模型和研究框架,分析了纯策略纳什均衡解存在的条件.然后,分析了影响技术与商务专家、 管理部门与评标专家之间策略选择的因素,揭示了评标参数对均衡的影响. 为便于研究博弈主体行为,基于Matlab GUI平台开发了分组多属性逆向拍卖评标和管理行为仿真系统. 数值仿真了评标环境的改变和决策参数的不同对均衡结果的影响.     

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.     

Dynamic bidding strategies in search-based advertising

Search-based advertising allows the advertisers to run special campaigns targeted to different groups of potential consumers at low costs. Google, Yahoo and Microsoft advertising programs allow the advertisers to bid for an ad position on the result page of a user’s query when the user searches for a keyword that the advertiser relates to its products or services. The expected revenue generated by the ad depends on the ad position, and the ad positions of the advertisers are concurrently determined after an instantaneous auction based on the bids of the advertisers. The advertisers are charged only when their ads are clicked by the users. To avoid excessive ad expenditures due to sudden surges in the keyword-search activities, each advertiser reserves a fixed finite daily budget, and the ads are not shown in the remainder of the day when the budget is depleted. Arrival times of keyword-search instances, ad positions, ad selections, and sales generated by the ads are random. Therefore, an advertiser faces a dynamic stochastic total net revenue optimization problem subject to a strict budget constraint. Here we formulate and solve this problem using dynamic programming. We show that there is always an optimal dynamic bidding policy. We describe an iterative numerical approximation algorithm that uniformly converges to the optimal solution at an exponential rate of the number of iterations. We illustrate the algorithm on numerical examples. Because dynamic programing calculations of the optimal bidding policies are computationally demanding, we also propose both static and dynamic alternative bidding policies. We numerically compare the performances of optimal and alternative bidding policies by systematically changing each input parameter. The relative percentage total net revenue losses of the alternative bidding policies increases with the budget loading, but were never more than 3.5 % of maximum expected total net revenue. The best alternative to the optimal bidding policy turned out to be a static greedy bidding policy. Finally, statistical estimation of the model parameters is visited.     

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.     

基于高斯分布的在线采购机制设计及竞争分析

依附于互联网电子商务的在线采购拍卖交易, 对传统的贝叶斯离线拍卖理论提出新的挑战, 因为面对不同时间点的投标, 采购电商必须即可决策出是否中标以及购买价格。鉴于此, 对于诸如石油、煤、粮食等无限可分商品的电子采购, 本文基于投标具有高斯分布特征设计了一种激励相容的在线采购策略, 演绎出在线采购的数学模型, 利用Runge-Kutta数值算法, 通过Matlab编程求解出采购电商在线定价策略的需求曲线及其对应的竞争比, 最后, 利用数值模拟, 将在线采购机制策略与纯竞争分析得到的在线采购策略比较, 结果显示利用了高斯分布信息的在线采购策略的竞争性能由于利用了投标的统计信息而得到了提高。     

On the impact of low-balling: Experimental results in asymmetric auctions

The paper reports on a series of asymmetric auction experiments with private-independent values and two buyers. Maskin and Riley (2000) showed, under some conditions, that if one buyer has a greater probability than the other of not being able to bid, first-price auctions could yield lower revenues to the seller than second-price auctions. The data rejected this prediction because of an important overbidding when subjects received low values in first-price auctions. In this asymmetric setting, the observed overbidding cannot be explained by the usual risk aversion hypothesis and the detection of a learning pattern indicates that subjects used more an adaptive behaviour than a static one. An ad hoc bidding strategy for the buyers who are the most likely to bid explains the observed low bids better than the risk neutral equilibrium strategy. Finally, as subjects appear to have bid in equilibrium as if there were two other competitors instead of only one, their bidding behaviour can be thought to have displayed an over anxiousness about winning. Received: January 1999/Final version June 2001     

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.     

Robust strategic bidding in auction-based markets

In this paper, we propose an alternative methodology for devising revenue-maximizing strategic bids under uncertainty in the competitors’ bidding strategy. We focus on markets endowed with a sealed-bid uniform-price auction with multiple divisible products. On recognizing that the bids of competitors may deviate from equilibrium and are of difficult statistical characterization, we proposed a two-stage robust optimization model with equilibrium constraints aiming to devise risk-averse strategic bids. The proposed model is a trilevel optimization problem that can be recast as a particular instance of a bilevel program with equilibrium constraints. Reformulation procedures are proposed to find a single-level equivalent formulation suitable for column-and-constraint generation (CCG) algorithm. Results show that even for the case in which an imprecision of 1% is observed on the rivals’ bids in the equilibrium point, the robust solution provides a significant risk reduction (of 79.9%) in out-of-sample tests. They also indicate that the best strategy against high levels of uncertainty on competitors’ bid approaches to a price-taker offer, i.e., bid maximum capacity at marginal cost.     

Anonymous sealed bid auction protocol based on a variant of the dining cryptographers’ protocol

Sealed bid auctions are a popular means of high-stakes bidding, as they eliminate the temporal element from the auction process, allowing participants to take less emotional, more thoughtful decisions. In this paper, we propose a digital communication protocol for conducting sealed bid auctions with high stakes, where the anonymity of bids as well as other aspects of fairness must be protected. The Dining Cryptographers?? Protocol (denoted by DC) was presented by David Chaum in 1988. The protocol allows the participants to broadcast a message anonymously. In a recent paper (Another Twist in the Dining Cryptographers?? Protocol, submitted to the Journal of Cryptology) the authors propose a variant of the original DC eliminating its main disadvantages. In this paper we present a cryptographic protocol realizing anonymous sealed bid auctions, such as first price or Vickrey auction, based on this variant. The proposed scheme allows to identify at least one dishonest participant violating the protocol without using of Trusted Third Parties. Additionally, we require that bids are binding. It is achieved by enabling all participants acting in concert (the so-called ??angry mob??) to find out the identity of the winner, in case the winner fails to make the purchase.