The Power of Fair Pricing Mechanisms

We explore the revenue capabilities of truthful, monotone (“fair”) allocation and pricing functions for resource-constrained auction mechanisms within a general framework that encompasses unlimited supply auctions, knapsack auctions, and auctions with general non-decreasing convex production cost functions. We study and compare the revenue obtainable in each fair pricing scheme to the profit obtained by the ideal omniscient multi-price auction. We show that for capacitated knapsack auctions, no constant pricing scheme can achieve any approximation to the optimal profit, but proportional pricing is as powerful as general monotone pricing. In addition, for auction settings with arbitrary bounded non-decreasing convex production cost functions, we present a proportional pricing mechanism which achieves a poly-logarithmic approximation. Unlike existing approaches, all of our mechanisms have fair (monotone) prices, and all of our competitive analysis is with respect to the optimal profit extraction.     

A dynamic model of bidding patterns in sponsored search auctions

We develop an infinite horizon alternative-move model of the unique second-price sponsored search auction. We use this model to explain two distinguishable bidding patterns observed in our bidding data: bidding war cycle and stable bid. With examples, we show that only a small portion of the value generated may be extracted by search engines, if advertisers are engaged in bidding war cycles. Finally, we show the impact of auction design on advertiser bids and search engine revenue.     

A new bidding framework for combinatorial e-auctions

Bidding languages define the means through which participants in an electronic auction define bids and express requirements on their execution. The current state of combinatorial auction market design indicates that no existing bidding language is general enough to support auctions of both divisible and indivisible commodities. In this paper, we propose a novel bidding framework based on a two-level representation of a combined bid. At the inner level, bidding operators impose conditions on the executed proportions of packages of atomic single-item bids. Partial bids defined this way are then recursively combined through logical operators to produce a final combined bid that is submitted to the auctioneer. We present a formal specification of the framework, and analyze how it impacts the mathematical programming formulation of the allocation problem. An application in the context of combinatorial auctions of financial assets illustrates the utilization of the proposed bidding framework.     

基于拍卖理论和高斯过程回归学习的频谱分配算法

针对认知无线网络中认知用户的频谱分配问题,提出了一种基于拍卖理论和高斯过程回归学习的频谱分配算法。该算法基于VCG拍卖模型,考虑认知用户对通信质量的要求,构造出更有效的收益函数。在频谱拍卖过程中,认知用户通过学习拍卖历史数据预测其他认知用户的竞价,并最优化其竞价策略。频谱拍卖人根据各认知用户提交的竞价来分配频谱资源。理论分析和仿真结果证明了该算法是有效的,并且能够提高频谱利用率和认知用户的收益。     

Two-level workload characterization of online auctions

Online auctions are rapidly becoming one of the significant forms of electronic commerce for buying and selling goods and services. A good understanding of the workload of auction sites should provide insights about their activities and help in improving the quality of the service provided to their users. This paper presents a site level and a user level workload characterization of a real online auction site using data collected by automated agents. The main contributions of this paper are as follows: (i) a detailed workload characterization of a real auction site; (ii) an analysis of the presence of heavy tailed distributions in this workload; (iii) an analysis of the bidding activity during closing minutes of auctions; and (iv) an analysis of the arrival rate process of bidders and bids within clusters based on different attributes. These results can be used to devise dynamic pricing and promotion models to improve revenue throughput of online auction sites.     

基于歧视性的第二价格拍卖算法的激励机制

在基于对等网(P2P)的大数据实时应用中,针对如何遏制视频点播(VOD)系统中的节点搭便车行为,提出了基于歧视性的第二价格拍卖算法的激励机制。节点之间以分布式动态拍卖的方式获取各自所需视频数据块,拍卖中,拍卖节点首先根据歧视性原则判断竞标节点的预算是否足以参与竞标,并根据允许参与竞标的节点数目设置上传带宽;然后根据竞标节点的出价确定赢得竞标的节点;最后竞标节点在接收到数据块后根据第二价格方案支付拍卖节点仅次于拍卖最高价格的第二高价格的要价作为节点的收益。分析节点的收益、节点带宽的利用率以及贡献节点/自私节点的比例,表明该方案能有效地激励节点积极地参与视频数据块的共享,同时高效地利用节点的上传带宽。     

认知网络中基于竞价模型的切换频谱分配

通过对最新竞价算法的分析,针对频谱分配过程中频谱使用率低下的缺点,提出一种认知无线电中基于竞价机制的具有较高频谱使用率的频谱分配算法。引入干扰价格,通过设置干扰价格指数,降低系统干扰,保证主用户的服务质量。数值仿真结果表明,该算法通过多次分配有效地提高了频谱的利用率,增加了系统的吞吐量。     

Instant overbooking framework for cognitive radio networks

In recent years, new emerging wireless technologies necessitate more spectrum resources compared to before. Related to this fact, cognitive radio and its capabilities provide promising functionalities in efficient management of the spectrum. In this paper, to maximize both spectrum utilization and revenue of network operators, we propose an Instant Overbooking Framework for Cognitive Radio networks (IOFCR) where different overbooking policies can be employed. Besides, the framework includes policies in order to decide which requesting secondary users (SUs) can be denied and which Active SUs can be ejected when a primary user (PU) activity is sensed. The effects of different pricing strategies used in a booking interval are also analyzed. To evaluate IOFCR, we use performance measures such as total net revenue, spectrum utilization, overbooking limit, number of free blocks, average service period, percentage of denied SUs forwarding their booking request and percentage of ejected Active SUs. In addition to being a first overbooking framework for Cognitive Radio Networks that takes several system parameters like PU on-rate, Active SU on-rate and Requesting SU show-rate into the account, to the best of our knowledge, this paper makes key contributions concerning the pricing policies, denial of requesting SUs, ejection and priority levels of active SUs. Finally, we numerically analyze the IOFCR performance by conducting numerous simulations and show the efficiency and validity in accordance with comprehensive measures mentioned above.     

Design of online auctions: Proxy versus non-proxy settings

Recent years have witnessed the rapid development of online auctions. Currently, some online auctions, such as eBay, introduce a proxy bidding policy, under which bidders submit their maximum bids and delegate to a proxy agent to automatically outbid other competitors for the top bidder, whereas other online auctions do not. This paper compares these two widely used auction mechanisms (proxy setting and non-proxy setting) and characterizes the equilibrium bidding behavior and the seller's expected revenue. We find the proxy auction outperforms the non-proxy auction in terms of the seller's expected revenue. This dominance result is not prone to the specific bid announcement policy, the bidder's knowledge regarding the number of bidders, the impact of traffic congestion along the bidding process, the number of items sold through the auction, and the existence of a reserve price.We further find that the proxy setting usually fails to sustain the truthful bidding as a dominant strategy equilibrium even if no minimum bid increments are adopted, and the possibility of a low-valuation-bidder dilemma where the low-valuation bidders could be better off if all bidders collude to bid at the last minute. We also discuss the dramatically different equilibrium bidding behaviors under the two auction mechanisms.     

Performance Evaluation of Multi-Object Auctions

The paper evaluates the performance of two multi-object auction models: sequential and simultaneous, using different performance measures. The objects put up for auction have different synergies for different bidders. We define different types of bidders who can exist in these multi-object auction models. The classification of bidders is based on the bidding strategies they use. We then study the effects of different parameters in auction and bidding strategies, on the performance of these auction models by simulating them using a JAVA based framework.This material is based upon work supported by a National Science Foundation grant (DMI 9800449) to the Dharmaraj Veeramani last author. The authors also thank the referees of the paper and the area editors for their valuable comments on the work.     

Bidding strategies for realistic multi-unit sealed-bid auctions

When autonomous agents decide on their bidding strategies in real world auctions, they have a number of concerns that go beyond the models that are normally analyzed in traditional auction theory. Oftentimes, the agents have budget constraints and the auctions have a reserve price, both of which restrict the bids the agents can place. In addition, their attitude need not be risk-neutral and they may have uncertainty about the value of the goods they are buying. Some of these issues have been examined individually for single-unit sealed-bid auctions. However, in this paper, we extend this analysis to the multi-unit case, and also analyze the multi-unit sealed-bid auctions in which a combination of these issues are present, for unit-demand bidders. This analysis constitutes the main contribution of this paper. We then demonstrate the usefulness in practice of this analysis; we show in simulations that taking into account all these issues allows the bidders to maximize their utility. Furthermore, using this analysis allows a seller to improve her revenue, i.e. by selecting the optimal reserve price and auction format.     

Cheating in online auction – Towards explaining the popularity of English auction

Action frauds constitute largest part of all Internet frauds. Cheating is a kind of fraud that does not have direct evidences of its occurrence. We conduct theoretical studies as well as simulation experiments to find out the effect of cheating in three important types of auctions: English auction, first-price sealed-bid, and second-price sealed-bid auction. Our cheating environment consists of shill bidding, bid shading and false bidding in English, first-price and second-price auction, respectively. In the experiments ordinary bidders, bidders with the equilibrium bidding strategy, and cheaters compete with each other. Both theoretical and experimental results confirm that the equilibrium bidding strategies indeed increases the bidders’ expected utility. Therefore, it can be concluded that adoption of rational bidding strategies can combat cheating. It is found that most of the auction sites intuitively prefer English auction to other auction mechanisms. There is not much theoretical or experimental evidence to support such an intuition. We use honest bidder’s expected gain and honest seller’s revenue loss as a basis to compare these three important auctions types. The analysis of the results reveals English auction to be the most preferred mechanism from both honest buyer’s and honest seller’s point of view. This result can be used as an experimental evidence to explain the popularity of English auction over the Internet.     

Two pricing mechanisms for a service provider when customers’ delay costs are value-related

In this paper, we study two pricing mechanisms for a provider that serves delay-sensitive customers, one is the uniform pricing and the other is the priority auction. The expected delay cost of a customer is assumed to depend on his value for the service (i.e. the unit delay cost is a strictly increasing function of his value) and the expected sojourn time caused by the number of customers in the system (and his payment-based position in the queue if auction is adopted). Hence, each customer reacts to the service provider’s pricing mechanism by deciding whether or not to enter the service system and how much he pays. This resulting problem is a Stackelberg game. When auction is adopted, by using of adverse selection, we derive a feasible scheme in which customers with higher value would like to pay more. We further compare the performance of these two pricing mechanisms. Our numerical examples show that auction performs better not only in terms of revenue making but also in terms of social welfare improvement. Interestingly, auction can also render more customer surplus in most instances, which differs from the common techniques in revenue management field.     

P2P资源的拍卖激励机制

激励机制是P2P（对等网）中的一个重要的研究课题。P2P这种新的成功模式需要建立一个应用已有成熟的技术的激励机制来实现。本文提出了一种在P2P环境申基于拍卖的激励机制。在P2P所有资源都标以虚拟价格,P2P中节点通过拍卖来决定它获得需要的怎样所应该付出的代价,并用虚拟货币进行支付,而节点通过贡献资源得到虚拟货币。在这种激励机制下,节点可以最大化利用自己的资源,如果P2P每个节点都能够实现资源的最大化利用,我们就可以实现在P2P中自私的节点也愿意贡献自己的资源这一目的。     

Name-Your-Own-Price seller’s information revelation strategy with the presence of list-price channel

This study examines the Name-Your-Own-Price (NYOP) retailer’s information revelation strategy when competing with list-price channel. We propose an integrated economic framework focusing on the comparison of expected consumer surplus from bidding at NYOP auction and guaranteed consumer surplus from buying at a list price. We then conduct an empirical study to examine the effects of seller-supplied price information on NYOP bidding outcome (especially on expected winning probability and the number of bidders). The results of our study strongly indicate the effects of seller-supplied information on expected winning probability (as well as the expected consumer surplus) in a NYOP auction. We also illustrate the strategic implications of seller-supplied price information via a revenue simulation for the NYOP seller. Our results suggest that NYOP seller may increase his expected revenue by (1) provide only the upper bound of its threshold price when list price is high (low expected consumer surplus from buying at list price); (2) provide only the lower bound of its threshold price when list price is low (high expected consumer surplus from buying at list price); (3) provide both the upper and lower bound of its threshold price when consumer surplus of buying at list price is unknown.     

Interplay between Buy-It-Now price and last minute bidding on online bidding strategies

Sellers and buyers on online auction sites like eBay have the option of setting and executing auction parameters such as auction length, Buy-It-Now price, starting price, reserve price, etc. Understanding why bidders choose to execute the Buy-It-Now price as opposed to submitting a bid at the last minute of an auction helps managers better choose auction parameters and generate more revenue. In this paper, we first study online bidder behavior pertaining to the execution of the Buy-It-Now option as opposed to the last minute bidding strategy on eBay. Consequently, we study the seller’s decision to set a Buy-It-Now option and the amount of it. Our main finding is that a dominant strategy for the seller is to offer a Buy-It-Now option at the beginning of the auction. An early bidder arriving at the auction site is indifferent in choosing threshold Buy-It-Now prices or moving onto the auction and under particular circumstances strategically waiting for the last minutes of the auction to submit a bid. We also provide conditions on the existence of a set of equilibria which predicts the outcome of the game of executing the Buy-It-Now option versus last-minute bidding on eBay.     

应急物资采购及代储服务交易的逆向组合拍卖机制设计

建立市场化的政企联合储备模式已经成为应急物资储备体系建设的重要方式.基于此,着眼于应急物资采购及代储服务的交易问题,设计一个逆向组合拍卖机制.在此拍卖机制中,政府是拍卖的买方兼委托人,企业是拍卖的卖方兼竞拍者,应急物资采购及代储服务是拍卖商品.首先,通过一个报童模型建立政府决策行为与拍卖活动之间的关系,并提出企业的投标策略;其次,建立最小化供需偏差和最大化供给数量的竞胜标决定模型;最后,提出一个符合实际背景的数值算例对拍卖机制进行模拟和验证.研究表明,所提出的逆向组合拍卖机制不仅具有经济效率,还能够促进政府一次性达成与多家企业在多个周期的合作.由此可见,运用拍卖机制解决应急物资政企联合储备的交易问题具备理论的优越性和现实的适用性.     

Adaptive Auction Framework for Spectrum Market in Cognitive Radio Networks

For the recent decade, cognitive radio networks have received much attention as an alternative to the traditional static spectrum allocation policy since the licensed spectrum channels are not being used efficiently. The most critical issue of the cognitive radio networks is how to distribute the idle spectrum channels to the secondary users opportunistically. The auction-based market is desirable for the trade of idle spectrum channels since the secondary users can purchase a channel in timely manner and the licensed primary users can earn the additional profit while not using the channels. Among the auction algorithms proposed for the spectrum market, we focus on the TASG framework, which consists of two nested auction algorithms, because it enables the group-buying of spectrum channels for the secondary users with limited budgets, and possesses many positive properties such as budget-balance, individual rationality and truthfulness. However, the TASG framework is not very attractive to the market participants since the seller earns the small revenue and the buyer has the low utility. In this paper, we propose a new auction framework for the spectrum markets, called aDaptive and Economically robust Auction-based Leasing (DEAL), that keeps all the benefits of TASG while improving the utility (or revenue) of the participants. To this end, we develop an enhanced inner-auction algorithm, called the Global Auction algorithm in our DEAL framework, and adapt the involved parameters dynamically based on the previous bids from the potential buyers. Simulation results demonstrate that our framework significantly outperforms the previous TASG.     

eMediator: A Next Generation Electronic Commerce Server

This paper presents eMediator , an electronic commerce server prototype that demonstrates ways in which algorithmic support and game–theoretic incentive engineering can jointly improve the efficiency of e–commerce. eAuctionHouse , the configurable auction server, includes a variety of generalized combinatorial auctions and exchanges, pricing schemes, bidding languages, mobile agents, and user support for choosing an auction type. We introduce two new logical bidding languages for combinatorial markets: the XOR bidding language and the OR–of–XORs bidding language. Unlike the traditional OR bidding language, these are fully expressive. They therefore enable the use of the Clarke–Groves pricing mechanism for motivating the bidders to bid truthfully. eAuctionHouse also supports supply/demand curve bidding. eCommitter , the leveled commitment contract optimizer, determines the optimal contract price and decommitting penalties for a variety of leveled commitment contracting mechanisms, taking into account that rational agents will decommit strategically in Nash equilibrium. It also determines the optimal decommitting strategies for any given leveled commitment contract. eExchangeHouse , the safe exchange planner, enables unenforced anonymous exchanges by dividing the exchange into chunks and sequencing those chunks to be delivered safely in alternation between the buyer and the seller.     

Forward looking Nash equilibrium for keyword auction

We introduce the concept of forward looking Nash equilibrium for the position auction (also called the generalized second price auction), a widely studied protocol for Internet advertisement bidding processes. We show that it has a unique solution for the position auction. Most importantly, the cost each bidder pays and the revenue of the auctioneer under the equilibrium are all equal to those under VCG mechanism. As the position auction is not an incentive compatible protocol, the fact that the forward looking Nash equilibrium results in the same payoff for everyone as in the VCG protocol justifies the practical protocol.