Competition Between Auctions

Even though auctions are capturing an increasing share of commerce, they are typically treated in the theoretical economics literature as isolated. That is, an auction is typically treated as a single seller facing multiple buyers or as a single buyer facing multiple sellers. In this paper, we review the state of the art of competition between auctions. We consider three different types of competition: competition between auctions, competition between formats, and competition between auctioneers vying for auction traffic. We highlight the newest experimental, statistical and analytical methods in the analysis of competition between auctions.auctions, bidding, competition, auction formats, auction houses

A Free Exchange e-Marketplace for Digital Services

The digital era is witnessing a remarkable evolution of digital services. While the prospects are countless, the e-marketplaces of digital services are encountering inherent game-theoretic and computational challenges that restrict the rational choices of bidders. Our work examines the limited bidding scope and the inefficiencies of present exchange e-marketplaces. To meet challenges, a free exchange e-marketplace is proposed that follows the free market economy. The free exchange model includes a new bidding language and a double auction mechanism. The rule-based bidding language enables the flexible expression of preferences and strategic conduct. The bidding message holds the attribute-valuations and bidding rules of the selected services. The free exchange deliberates on attributes and logical bidding rules for automatic deduction and formation of elicited services and bids that result in a more rapid self-managed multiple exchange trades. The double auction uses forward and reverse generalized second price auctions for the symmetric matching of multiple digital services of identical attributes and different quality levels. The proposed double auction uses tractable heuristics that secure exchange profitability, improve truthful bidding and deliver stable social efficiency. While the strongest properties of symmetric exchanges are unfeasible game-theoretically, the free exchange converges rapidly to the social efficiency, Nash truthful stability, and weak budget balance by multiple quality-levels cross-matching, constant learning and informs at repetitive thick trades. The empirical findings validate the soundness and viability of the free exchange

Combinatorial Scoring Auctions

This paper is concerned with a combinatorial, multi-attribute procurement mechanism called combinatorial scoring auction. In the setting that we analyze, private information of the suppliers is multi-dimensional. The buyer wants to procure several items at once. Subsets of these items are characterized by a price as well as by a number of non-monetary attributes called quality (e.g. completion time). The suppliers submit offers specifying prices and quality levels for these subsets. These offers are evaluated according to a quasilinear scoring rule. Based on the resulting scores suppliers win contracts for the delivery of certain items. Such a contract only specifies the set of items a supplier has to deliver and a score that he has to meet. The decision about the specific price-quality combination yielding this contracted score is at the discretion of the supplier who aims at optimizing his own profit. We analyze the equilibria in such auctions and show the link between combinatorial scoring auctions and combinatorial price-only auctions. We demonstrate how this link can be used to employ preexisting knowledge about the equilibrium behavior in regular price-only auctions in the strategic analysis of combinatorial scoring auctions. Our results are the multi-item extension to the results of Asker and Cantillon (2007).mathematical economics;

E-Business Oriented Optimal Online Auction Design

Online auctions, in the absence of spatial, temporal and geographic constraints, provide an alternative supply chain channel for the distribution of goods and services. This channel differs from the common posted-price mechanism that is typically used in the retail sector. In consumer-oriented markets, buyers can now experience the thrill of ‘winning’ a product, potentially at a bargain, as opposed to the typically more tedious notion of ‘buying’ it. Sellers, on the other hand, have an additional channel to distribute their goods, and the opportunity to liquidate rapidly aging goods at greater than salvage values. The primary facilitator of this phenomenon is the widespread adoption of electronic commerce over an open-source, ubiquitous Internet Protocol (IP) based network. In this paper, we derive an optimal bidding strategy in sequential auctions that incorporates option value assessment. Furthermore, we establish that our optimal bidding strategy is tractable since it is independent of the bidding strategies of other bidders in the current auction and is only dependent on the option value assessmen

Rational bidding using reinforcement learning: an application in automated resource allocation

The application of autonomous agents by the provisioning and usage of computational resources is an attractive research field. Various methods and technologies in the area of artificial intelligence, statistics and economics are playing together to achieve i) autonomic resource provisioning and usage of computational resources, to invent ii) competitive bidding strategies for widely used market mechanisms and to iii) incentivize consumers and providers to use such market-based systems. The contributions of the paper are threefold. First, we present a framework for supporting consumers and providers in technical and economic preference elicitation and the generation of bids. Secondly, we introduce a consumer-side reinforcement learning bidding strategy which enables rational behavior by the generation and selection of bids. Thirdly, we evaluate and compare this bidding strategy against a truth-telling bidding strategy for two kinds of market mechanisms – one centralized and one decentralized

Combinatorial Auction-based Mechanisms for Composite Web Service Selection

Composite service selection presents the opportunity for the rapid development of complex applications using existing web services. It refers to the problem of selecting a set of web services from a large pool of available candidates to logically compose them to achieve value-added composite services. The aim of service selection is to choose the best set of services based on the functional and non-functional (quality related) requirements of a composite service requester. The current service selection approaches mostly assume that web services are offered as single independent entities; there is no possibility for bundling. Moreover, the current research has mainly focused on solving the problem for a single composite service. There is a limited research to date on how the presence of multiple requests for composite services affects the performance of service selection approaches. Addressing these two aspects can significantly enhance the application of composite service selection approaches in the real-world. We develop new approaches for the composite web service selection problem by addressing both the bundling and multiple requests issues. In particular, we propose two mechanisms based on combinatorial auction models, where the provisioning of multiple services are auctioned simultaneously and service providers can bid to offer combinations of web services. We mapped these mechanisms to Integer Linear Programing models and conducted extensive simulations to evaluate them. The results of our experimentation show that bundling can lead to cost reductions compared to when services are offered independently. Moreover, the simultaneous consideration of a set of requests enhances the success rate of the mechanism in allocating services to requests. By considering all composite service requests at the same time, the mechanism achieves more homogenous prices which can be a determining factor for the service requester in choosing the best composite service selection mechanism to deploy

Lift-Based Bidding in Ad Selection

Real-time bidding (RTB) has become one of the largest online advertising markets in the world. Today the bid price per ad impression is typically decided by the expected value of how it can lead to a desired action event (e.g., registering an account or placing a purchase order) to the advertiser. However, this industry standard approach to decide the bid price does not consider the actual effect of the ad shown to the user, which should be measured based on the performance lift among users who have been or have not been exposed to a certain treatment of ads. In this paper, we propose a new bidding strategy and prove that if the bid price is decided based on the performance lift rather than absolute performance value, advertisers can actually gain more action events. We describe the modeling methodology to predict the performance lift and demonstrate the actual performance gain through blind A/B test with real ad campaigns in an industry-leading Demand-Side Platform (DSP). We also discuss the relationship between attribution models and bidding strategies. We prove that, to move the DSPs to bid based on performance lift, they should be rewarded according to the relative performance lift they contribute.Comment: AAAI 201

A Rule-driven Approach for Defining the Behavior of Negotiating Software Agents

One problem with existing agent-mediated negotiation systems is that they rely on ad hoc, static, non-adaptive, and hardcoded schemes to represent the behaviour of agents. This limitation is probably due to the complexity of the negotiation task itself. Indeed, while negotiating, software (human) agents face tough decisions. These decisions are based not only on the information made available by the negotiation server, but on the behaviour of the other participants in the negotiation process as well. The information and the behaviour in question are constantly changing and highly uncertain. In the first part of the paper, we propose a rule-driven approach to represent, manage and explore negotiation strategies and coordination information. For that, we divide the behaviour of negotiating agents into protocols, strategies and coordination. Among the many advantages of the proposed solution, we can cite the high level of abstraction, the closeness to human understanding, the versatility, and the possibility to modify the agents' behaviour during the negotiation process. To validate our solution, we ran many agent tournaments, and used the rule-driven approach to implement bidding strategies that are common in the English and Dutch auctions. We also implemented simple coordination schemes across several auctions. The ongoing validation work is detailed and discussed in the second part of the paper. Un des inconvénients qu'on retrouve fréquemment dans les systèmes de négociation par agents est qu'ils reposent sur des schémas ad-hoc, non adaptatifs et figés dans le code pour représenter le comportement des agents. Cette limitation est probablement due à la complexité de l'activité de négociation elle-même. En effet, au cours de la négociation, les agents logiciels (humains) ont des décisions difficiles à prendre. Ces décisions ne sont pas seulement basées sur l'information disponible sur le serveur de négociation, mais aussi sur le comportement des autres participants durant le processus de négociation. L'information et le comportement en question changent constamment et sont très incertains. Dans la première partie de l'article, nous proposons une approche à base de règles pour représenter, gérer et explorer les stratégies de négociation ainsi que l'information de coordination. Parmi les nombreux avantages de la solution proposée, on peut citer le haut niveau d'abstraction, la proximité avec la compréhension humaine, la souplesse d'utilisation et la possibilité de modifier le comportement des agents durant le processus de négociation. Pour valider notre solution, nous avons effectué plusieurs tournois entre agents et utilisé l'approche à base de règles pour implémenter des stratégies simples applicables à l'enchère anglaise et à l'enchère hollandaise. Nous avons aussi implémenté des schémas simples de coordination impliquant plusieurs enchères. Le travail de validation, en cours, est détaillé et discuté dans la seconde partie de l'article.e-negotiation, online auction, software agent, negotiation strategy, coordination, rule-based system, rule engine, Négociation électronique, enchères en ligne, agents logiciels, stratégie de négociation, coordination, système à base de règles, moteur de règles

Preference Revelation in Multi-Attribute Reverse English Auctions: A Laboratory Study

The effects of preference revelation on allocational and Pareto efficiency are studied in a multi-attribute reverse English auction. Multi-attribute reverse auctions have been proposed as market institutions for electronic request for quotation buying processes. Preference revelation is a crucial question in multi-attribute reverse auctions in terms of the efficiency of auction outcomes. Results from a computer-based laboratory experiment are reported and auction outcomes are analyzed regarding the buyer’s and suppliers’ surplus, efficiency, and Pareto efficiency. The results show that suppliers make more profits when preferences are revealed, but not at the expense of the buyer, and that full revelation of the buyer’s preferences significantly increases allocational and Pareto efficiency