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.     

制造商为小本经营情况下零售商购货机制的合同设计

考虑零售商采用逆向拍卖方式到个小本经营的制造商处购货,研究供应链中如何设计合同使得零售商单位时间的支出费用最低,采用最优控制的方法和委托代理理论中的显示原理,得出零售商的最优购货机制,同时给出两个简单的购货机制——打分拍卖机制和固定生产时间下的价格拍卖。结果表明由制造商承担的制造费用越多,零售商的进货价格越高;在简单机制下,制造商承担制造费用的大小并不影响最优生产率的制定。     

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。     

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。     

Mitigating supply risk: an approach with quantity flexibility procurement

This paper considers a buyer that procures from its major supplier whose production is subject to random yield risk. To mitigate supply risk, the buyer can procure from another reliable supplier who provides quantity flexibility (QF) contract. Under both deterministic and stochastic demand, we study the buyer’s optimal procurement decisions. We analyze the structural properties of optimal solutions and identify the conditions under which the quantity flexibility procurement policy should be used. We also examine the effect of supply risk, flexibility, wholesale price and demand risk on the procurement decisions. We find that the higher supply risk and demand risk reduce the buyer’s profit but have different impact on the buyer’s order policy. For the QF supplier, it may not obtain more orders by providing larger flexibility to the buyer, on the contrary, doing this may benefit the risky supplier. For the QF supplier or risky supplier, given its competitor’s wholesale price, it can increase its order share by lower wholesale price.     

研发外包中考虑服务商道德风险与资金限制的支付契约

针对研发外包中服务商道德风险防范与激励问题,在考虑服务商自有资金限制下,设计了研发外包支付契约,分析了契约的特性。研究表明,服务商自有资金的多少会影响支付契约的激励效果。当服务商自有资金很少时,支付契约对道德风险的防范与激励效果较差。当服务商自有资金达到一定量时,随着自有资金的增多,支付契约的激励效果越来越强,特别的当服务商自有资金超过很大一个量时,支付契约能激励服务商实现系统最优的工作努力程度。     

Short communication: DEA based auctions simulations

In this paper we use simulations to numerically evaluate the Hybrid DEA – Second Score Auction. In a procurement setting, the winner of the Hybrid auction by design receives payment at the most equal to the Second Score auction. It is therefore superior to the traditional Second Score scheme from the point of view of a principal interested in acquiring an item at the minimum price without losing in quality. For a set of parameters we quantify the size of the improvements and show that the improvement depends intimately on the regularity imposed on the underlying cost function. In the least structured case of a variable returns to scale technology, the hybrid auction only improved the outcome for a small percentage of cases. For other technologies with constant returns to scale, the gains are considerably higher and payments are lowered in a large percentage of cases. We also show that the number of the participating agents, the concavity of the principal value functions, and the number of quality dimensions impact the expected payment.     

Revenue deficiency under second-price auctions in a supply-chain setting

Consider a firm, called the buyer, that satisfies its demand over two periods by assigning both demands to a supplier via a second-price procurement auction; call this the Standard auction. In the hope of lowering its purchase cost, the firm is considering an alternative procedure in which it will also allow bids on each period individually, where there can be either one or two winners covering the two demands; call this the Multiple Winner auction. Choosing the Multiple Winner auction over the Standard auction can in fact result in a higher cost to the buyer. We provide a bound on how much greater the buyer’s cost can be in the Multiple Winner auction and show that this bound is tight. We then sharpen this bound for two scenarios that can arise when the buyer announces his demands close to the beginning of the demand horizon. Under a monotonicity condition, we achieve a further sharpening of the bound in one of the scenarios. Finally, this monotonicity condition allows us to generalize this bound to the T-period case in which bids are allowed on any subset of period demands.     

基于前景理论的混合不确定情景下在线多属性反向拍卖的赢者确定方法

在线反向拍卖在当今的经济社会发展中扮演越来越重要的角色,其主要应用于采购招标领域。而在实际的采购拍卖中有关商品属性和供应商信息等方面常会存在一定程度的不确定性,且这些不确定性的刻画又存在着多种模糊表述形式,这些都将增加采购方的风险预期和竞标供应商赢者确定的难度。为此,本文基于前景理论及模糊集理论,研究了同时存在精确数、区间数、三角模糊数、梯形模糊数和语义模糊术语五种属性描述方式的在线多属性反向拍卖的赢者确定问题,提出了一种更具一般性的混合不确定情景下的在线多属性反向拍卖赢者(中标者)确定方法。最后,通过数值算例和比较分析验证了本文所提方法的合理性与有效性,并通过稳健性分析进一步说明方法的稳定性和适用性。     

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.     

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 multi-attribute e-auction mechanism for procurement: Theoretical foundations

We describe a multi-attribute e-auction mechanism, with a focus on its theoretical foundations. Our mechanism is designed for auctioning multiple units of a good, primarily in B2B transactions. It can be used in various types of forward and reverse auctions/RFQs (Request for Quote), although the emphasis in this paper is on procurement. To incorporate the auction owner’s preferences across issues/attributes in an auction/negotiation setting, we adopt a novel application of the ‘pricing out’ technique. Another key feature of our mechanism is the optimization-based ‘suggested price’ decision support component, which momentarily gives the best price acceptable to the buyer.     

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...     

Fraction auctions: The tradeoff between efficiency and running time

This paper studies the sales of a single indivisible object where bidders have continuous valuations. In Grigorieva et al. [14] it was shown that, in this setting, query auctions necessarily allocate inefficiently in equilibrium. In this paper we propose a new sequential auction, called the c-fraction auction. We show the existence of an ex-post equilibrium, called bluff equilibrium, in which bidders behave truthfully except for particular constellations of observed bids at which it is optimal to pretend a slightly higher valuation. We show c-fraction auctions guarantee approximate efficiency at any desired level of accuracy, independent of the number of bidders, when bidders choose to play the bluff equilibrium. We discuss the running time and the efficiency in the bluff equilibrium. We show that by changing the parameter c of the auction we can trade off efficiency against running time.     

Application of multi-dimensional procurement auction in single-period inventory models

Procurement is one of the major activities in the Manufacturing Resource Planning (MRP II), which is closely coupled with inventory management. Any improvement in this area will have a direct impact on the performance of the entire supply chain. Auction mechanism can be a successful procurement method when there are several potential suppliers available. In this paper, we consider a single-period inventory model when the selection of the supplier is done through a reverse auction with bids consisting of several attributes, namely price, shortage quantity, and lead time. The multi-dimensionality of the bid increases the complexity of the underlying problem creating a need for an approach to determine an approximate optimal target level. This is needed for the initiation of the auction and the procurement process. Monte-Carlo simulation method was used to investigate the performance of the approximation. Simulation results show that the analytical method provides an acceptable approximation for the optimal target inventory level.     

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.     

An interactive approach for Bi-attribute multi-item auctions

The advances in the technological infrastructure and in the Internet led electronic auctions to become popular. With online sites, people buy/sell inexpensive products/services through auctions. In this paper, we develop an interactive approach that provides aid to both the buyer and the bidders in a bi-attribute, multi-item auction environment. Our approach is applicable for both reverse and forward auctions. We test our approach for underlying linear preference functions of the buyer. We also adapt it as a heuristic for the case the buyer has a nonlinear preference function. The test results show that our approach works well.     

Sourcing decisions with capacity reservation contracts

By committing to long-term supply contracts, buyers seek to lower their purchasing costs, and have products delivered without interruption. When a long-term contract is available, suppliers are less pressured to find new customers, and can afford to charge a price lower than the prevailing spot market price. We examine sourcing decisions of a firm in the presence of a capacity reservation contract that this firm makes with its long-term supplier in addition to the spot market alternative. This contract entails delivery of any desired portion of a reserved fixed capacity in exchange for a guaranteed payment by the buyer. We investigate rational actions of the two parties under two different types of periodic review inventory control policies used by the buyer: the two-number policy, and the base stock policy. When typical demand probability distributions are considered, inclusion of the spot market source in the buyer’s procurement plan significantly reduces the capacity commitments from the long-term supplier.     

Pareto-optimal insurance contracts with premium budget and minimum charge constraints

In view of the fact that minimum charge and premium budget constraints are natural economic considerations in any risk-transfer between the insurance buyer and seller, this paper revisits the optimal insurance contract design problem in terms of Pareto optimality with imposing these practical constraints. Pareto optimal insurance contracts, with indemnity schedule and premium payment, are solved in the cases when the risk preferences of the buyer and seller are given by Value-at-Risk or Tail Value-at-Risk. The effect of our constraints and the relative bargaining powers of the buyer and seller on the Pareto optimal insurance contracts are highlighted. Numerical experiments are employed to further examine these effects for some given risk preferences.