Showing papers on "Bidding published in 2003"

The Winner's Curse, Reserve Prices and Endogenous Entry: Empirical Insights From eBay Auctions.

Abstract: Internet auctions have recently gained widespread popularity and are one of the most successful forms of electronic commerce. We examine a unique data set of eBay coin auctions to explore the determinants of bidder and seller behavior. We begin by documenting a number of empirical regularities in our data set of eBay auctions. Next, we specify and estimate a structural econometric model of bidding on eBay. Using our parameter estimates from this model, we measure the extent of the winner’s curse and simulate seller revenue under different reserve prices.

Deciding between competition and collusion

Abstract: We develop an approach to identify and test for bid rigging in procurement auctions. First, we introduce a general auction model with asymmetric bidders. Second, we study the problem of identie cation in our model. We state a set of conditions that are both necessary and sufe cient for a distribution of bids to be generated by a model with competitive bidding. Third, we discuss how to elicit a prior distribution over a e rm' s structural cost parameters from industry experts. Given this prior distri- bution, we use Bayes' s theorem to compare competitive and collusive models of industry equilibrium. Finally, we apply our methodology to a data set of bidding by construction e rms in the Midwest. The techniques we propose are not computationally demanding, use e exible functional forms, and can be programmed using most standard statistical packages.

Late and Multiple Bidding in Second Price Internet Auctions: Theory and Evidence Concerning Different Rules for Ending an Auction

Abstract: In second price internet auctions with a fixed end time, such as those on eBay, many bidders "snipe", i.e., they submit their bids in the closing minutes or seconds of an auction. Late bids of this sort are much less frequent in auctions that are automatically extended if a bid is submitted very late, as in auctions conducted on Amazon. We propose a model of second price internet auctions, in which very late bids have a positive probability of not being successfully submitted, and show that sniping in a fixed deadline auction can occur even at equilibrium in auctions with private values, as well as in auctions with uncertain, dependent values. Sniping in fixed-deadline auctions also arises out of equilibrium, as a best reply to incremental bidding. However, the strategic advantages of sniping are eliminated or severely attenuated in auctions that apply the automatic extension rule. The strategic differences in the auction rules are reflected in the field data. There is more sniping on eBay than on Amazon, and this difference grows with experience. We also study the incidence of multiple bidding, and its relation to late bidding. It appears that one substantial cause of late bidding is as a strategic response to incremental bidding.

Merger Momentum and Investor Sentiment: The Stock Market Reaction to Merger Announcements

Abstract: This paper examines the effects of mergers on bidding firms' stock prices. We find evidence of merger momentum: bidder stock prices are more likely to increase when a merger is announced if recent mergers by other firms have been received well (a "hot" merger market) or if the overall stock market is doing better. However, there is long run reversal. Long-run bidder stock returns are lower for mergers announced when the either merger or stock markets were hot at the time of the merger than for those announced at other times.

Optimization‐based procurement for transportation services

Abstract: This paper presents the concept of optimization-based procurement for transportation services. The approach allows both the shipper and carriers to benefit through the use of a collaborative approach to securing and managing a strategic relationship. Because the shipper's assignment problem involves a combinatorial number of choices and cannot be easily executed manually, the procurement process benefits strongly from the use of optimization. The authors introduce the optimization-based procurement process, briefly analyze the theoretical issues, and discuss lessons learned from its application in practice over the last several years.

Robot exploration with combinatorial auctions

Abstract: We study how to coordinate a team of mobile robots to visit a number of given targets in a partially unknown terrain. Robotics researchers have studied single-item auctions to perform this exploration task but these do not make synergies between the targets into account. We therefore design combinatorial auctions, propose different combinatorial bidding strategies and compare their performance with each other, as well as to single item auctions and an optimal centralized mechanism. Our computational results in teambots, a multi-robot simulator, indicate that combinatorial auctions generally lead to significantly superior team performance than single-item auctions, and generate very good results compared to an optimal centralized mechanism.

Multiobjective optimization for pricing system security in electricity markets

Abstract: This paper proposes a novel technique for representing system security in the operations of decentralized electricity markets, with special emphasis on voltage stability. An interior point method is used to solve the optimal power flow problem with a multiobjective function for maximizing both social benefit and the distance to maximum loading conditions. A six-bus system with both supply and demand-side bidding is used to illustrate the proposed technique for both elastic and inelastic demand, and a 129-bus test system that models the Italian HV transmission network is used for testing the practical applicability of the proposed method. The results obtained show that the proposed technique is able to improve system security while yielding better market conditions through increased transaction levels and improved locational marginal prices throughout the system.

Analysis and Design of Business-to-Consumer Online Auctions

Abstract: Business-to-consumer online auctions form an important element in the portfolio of mercantile processes that facilitate electronic commerce activity. Much of traditional auction theory has focused on analyzing single-item auctions in isolation from the market context in which they take place. We demonstrate the weakness of such approaches in online settings where a majority of auctions are multiunit in nature. Rather than pursuing a classical approach and assuming knowledge of the distribution of consumers' valuations, we emphasize the largely ignored discrete and sequential nature of such auctions. We derive a general expression that characterizes the multiple equilibria that can arise in such auctions and segregate these into desirable and undesirable categories. Our analytical and empirical results, obtained by tracking real-world online auctions, indicate that bid increment is an important factor amongst the control factors that online auctioneers can manipulate and control. We show that consumer bidding strategies in such auctions are not uniform and that the level of bid increment chosen influences them. With a motive of providing concrete strategic directions to online auctioneers, we derive an absolute upper bound for the bid increment. Based on the theoretical upper bound we propose a heuristic decision rule for setting the bid increment. Empirical evidence lends support to the hypothesis that setting a bid increment higher than that suggested by the heuristic decision rule has a negative impact on the auctioneer's revenue.

The Spite Motive and Equilibrium Behavior in Auctions

Abstract: We study auctions where bidders have independent private values but attach a disutility to the surplus of rivals, and derive symmetric equilibria for rst-price, second-price, English, and Dutch auctions. We nd that equilibrium bidding is more aggressive than standard predictions. Indeed, in second-price auctions it is optimal to bid above one’s valuation; that is, bidding \frenzies" can arise in equilibrium. Further, revenue equivalence between second-price and rst-price auctions breaks down, with second-price outperforming rst-price. We also nd that strategic equivalence between second-price and English auctions no longer holds, although they remain revenue equivalent. We conclude that spiteful bidding rationalizes anomalies observed in laboratory experiments across the four auction forms better than the leading alternatives.

Controlling market power and price spikes in electricity networks: Demand-side bidding

Abstract: In this article we report an experiment that examines how demand-side bidding can discipline generators in a market for electric power. First we develop a treatment without demand-side bidding; two large firms are allocated baseload and intermediate cost generators such that either firm might unilaterally withhold the capacity of its intermediate cost generators from the market to benefit from the supracompetitive prices that would result from only selling its baseload units. In a converse treatment, ownership of some of the intermediate cost generators is transferred from each of these firms to two other firms such that no one firm could unilaterally restrict output to spawn supracompetitive prices. Having established a well controlled data set with price spikes paralleling those observed in the naturally occurring economy, we also extend the design to include demand-side bidding. We find that demand-side bidding completely neutralizes the exercise of market power and eliminates price spikes even in the presence of structural market power.

A fuzzy-logic based bidding strategy for autonomous agents in continuous double auctions

Abstract: Increasingly, many systems are being conceptualized, designed, and implemented as marketplaces in which autonomous software entities (agents) trade services. These services can be commodities in e-commerce applications or data and knowledge services in information economies. In many of these cases, there are both multiple agents that are looking to procure services and multiple agents that are looking to sell services at any one time. Such marketplaces are termed continuous double auctions (CDAs). Against this background, this paper develops new algorithms that buyer and seller agents can use to participate in CDAs. These algorithms employ heuristic fuzzy rules and fuzzy reasoning mechanisms in order to determine the best bid to make given the state of the marketplace. Moreover, we show how an agent can dynamically adjust its bidding behavior to respond effectively to changes in the supply and demand in the marketplace. We then show, by empirical evaluations, how our agents outperform four of the most prominent algorithms previously developed for CDAs (several of which have been shown to outperform human bidders in experimental studies).

Empirical Implications of Equilibrium Bidding in First-Price, Symmetric, Common Value Auctions

Abstract: This paper studies federal auctions for wildcat leases on the Outer Continental Shelf from 1954 to 1970. These are leases where bidders privately acquire (at some cost) noisy, but equally informative, signals about the amount of oil and gas that may be present. We develop tests of rational and equilibrium bidding in a common values model that are implemented using data on bids and ex post values. We also use data on tract location and exposr values to test the comparative static prediction that bidders may bid less aggressively in common value auctions when they expect more competition. We find that bidders are aware of the "winner's curse" and their bidding is largely consistent with equilibrium.

Costly Bidding in Online Markets for IT Services

Abstract: Internet-enabled markets are becoming viable venues for procurement of professional services. We investigate bidding behavior within the most active area of these early knowledge markets--the market for software development. These markets are important both because they provide an early view of the effectiveness of online service markets and because they have a potentially large impact on how software development services are procured and provided. Using auction theory, we develop a theoretical model that relates market characteristics to bidding and transaction behavior, taking into account costly bidding. We then test our model using data from an active online market for software development services, which yields contracts for 30%--40% of posted projects. In its current format, however, the studied market may induce excessive bidding by vendors. Consistent with our theoretical predictions and those of Carr (2003), higher-value projects attract significantly more bids, with lower average quality. Greater numbers of bids raise the cost to all participants, due to costly bidding and bid evaluation. Perhaps as a consequence, higher-value projects are also much less likely to be awarded.

Willingness‐to‐pay for community‐based insurance in Burkina Faso

Abstract: PURPOSE: To study the willingness-to-pay (WTP) for a proposed community-based health insurance (CBI) scheme in order to provide information about the relationship between the premium that is required to cover the costs of the scheme and expected insurance enrollment levels. In addition, factors that influence WTP were to be identified. METHODS: Data were collected from a household survey using a two-stage cluster sampling approach, with each household having the same probability of being selected. Interviews were conducted with 2414 individuals and 705 household heads. The take-it-or-leave-it (TIOLI) and the bidding game were used to elicit WTP. RESULTS: The average individual was willing to pay 2384 (elicited by the TIOLI) or 3191 (elicited by the bidding game) CFA (3.17 US dollars or 4.25 US dollars) to join CBI for him/herself. The head of household agreed to pay from 6448 (elicited by the TIOLI) or 9769 (elicited by the bidding game) CFA (8.6 US dollars or 13.03 US dollars) to join the health insurance scheme for his/her household. These results were influenced by household and individual ability-to-pay, household and individual characteristics, such as age, sex and education. The two methods yielded similar patterns of estimated WTP, in that higher WTP was obtained for higher income level, higher previous medical expenditure, higher education, younger people and males. A starting point bias was found in the case of the bidding game. CONCLUSIONS: Both TIOLI and bidding game methods can elicit a value of WTP for CBI. The value elicited by the bidding game is higher than by the TIOLI, but the two approaches yielded similar patterns of estimated WTP. WTP information can be used for setting insurance premium. When setting the premiums, it is important to consider differences between the real market and the theoretical one, and between the WTP and the cost of benefits package. The beneficiaries of CBI should be enrolled at the level of households or villages in order to protect vulnerable groups such as women, elders and the poor.

Competitive Bidding in Auctions with Private and Common Values

Abstract: The objects for sale in most auctions possess both private and common value elements. This salient feature has not yet been incorporated into a strategic analysis of equilibrium bidding behaviour. This paper reports such an analysis for a stylised model in which bidders receive a private value signal and an independent common value signal. We show that more uncertainty about the common value has a negative effect on efficiency. Information provided by the seller decreases uncertainty, which raises efficiency and seller's revenues. Efficiency and revenues are also higher when more bidders enter the auction.

Robust Predictions for Bilateral Contracting with Externalities

Abstract: The paper studies bilateral contracting between one principal and N agents when each agent’s utility depends on the principal’s unobservable contracts with other agents. We show that allowing deviations to menu contracts from which the principal chooses bounds equilibrium outcomes in a wide class of bilateral contracting games without imposing ad hoc restrictions on the agents’ beliefs. This bound yields, for example, competitive convergence as N →� in environments in which an appropriately-defined notion of competitive equilibrium exists. We also examine the additional restrictions arising in two common bilateral contracting games: the “offer game” in which the principal makes simultaneous offers to the agents, and the “bidding game” in which the agents make simultaneous offers to the principal.

Exploring bidding strategies for market-based scheduling

Abstract: A market-based scheduling mechanism allocates resources indexed by time to alternative uses based on the bids of participating agents. Agents are typically interested in multiple time slots of the schedulable resource, with value determined by the earliest deadline by which they can complete their corresponding tasks. Despite the strong complementarities among slots induced by such preferences, it is often infeasible to deploy a mechanism that coordinates allocation across all time slots. We explore the case of separate, simultaneous markets for individual time slots, and the strategic problem it poses for bidding agents. Investigation of the straightforward bidding policy and its variants indicates that the efficacy of particular strategies depends critically on preferences and strategies of other agents, and that the strategy space is far too complex to yield to general game-theoretic analysis. For particular environments, however, it is often possible to derive constrained equilibria through evolutionary search methods.

Competitive Bidding in Auctions with Private and Common Values

Abstract: The objects for sale in most auctions possess both private and common value elements. This salient feature has not yet been incorporated into a strategic analysis of equilibrium bidding behaviour. This paper reports such an analysis for a stylised model in which bidders receive a private value signal and an independent common value signal. We show that more uncertainty about the common value has a negative effect on efficiency. Information provided by the seller decreases uncertainty, which raises efficiency and seller s revenues. Efficiency and revenues are also higher when more bidders enter the auction.

Combinatorial Auctions for Transportation Service Procurement: The Carrier Perspective

Abstract: The procurement of transportation services is an important task for shippers because of the need to control costs at the same time as providing high service levels. When shippers with goods and/or materials to transport seek transportation services from outside companies they typically put out a request for quotes from a set of carriers. They then assign contracts based on negotiated service charges. This process is similar to a simple sealed-bid auction in which each bidder submits a sealed bid for a single item. In the past, when shippers need to procure transportation services for a set of distinctive delivery routes (called lanes) they would obtain quotes for each lane individually and repeat the simple auction process for each lane. Alternatively, they might negotiate for bundles of lanes with a single carrier at a time. However, in the last few years software has been developed to allow shippers to make all lanes available for bidding simultaneously and to allow carriers to simultaneously bid upon combinations of individual lanes. This method of awarding contracts, conventionally called a combinatorial auction, has been reported to result in significant cost savings for shippers. Our research examines the benefits of combinatorial auctions primarily from the carrier's perspective. Preliminary findings, based on a simple simulation model suggest that benefits for carriers can also be significant.

Asymmetry in first‐price auctions with affiliated private values

Abstract: Collusion and heterogeneity across firms may introduce asymmetry in bidding games. A major difficulty in asymmetric auctions is that the Bayesian Nash equilibrium strategies are solutions of an intractable system of differential equations. We propose a simple method for estimating asymmetric first-price auctions with affiliated private values. Considering two types of bidders, we show that these differential equations can be rewritten using the observed bid distribution. We establish the identification of the model, characterize its theoretical restrictions, and propose a two-step non-parametric estimation procedure for estimating the private value distributions. An empirical analysis of joint bidding in OCS auctions is provided. Copyright © 2003 John Wiley & Sons, Ltd.

Using Laboratory Experiments for Policy Making: An Example from the Georgia Irrigation Reduction Auction

Abstract: In recent years, there has been a growing interest in policy applications of different auction systems. This paper reports on a series of experiments that were used to design and implement an auction in a unique policy-making environment. In April, 2000, the Georgia legislature passed a unique law that mandated the state hold an auction in drought years in order to pay some farmers to suspend irrigation. This paper reports the results of laboratory experiments that were used by state policy-makers to determine the auction institution that would be used to fulfill the requirements of this new law. Experimental results are compared with farmers' bidding behavior in the state-run irrigation auction used to reduce water usage in Georgia.

Developing a bidding agent for multiple heterogeneous auctions

Abstract: Due to the proliferation of online auctions, there is an increasing need to monitor and bid in multiple auctions in order to procure the best deal for the desired good. To this end, this paper reports on the development of a heuristic decision making framework that an autonomous agent can exploit to tackle the problem of bidding across multiple auctions with varying start and end times and with varying protocols (including English, Dutch and Vickrey). The framework is flexible, configurable, and enables the agent to adopt varying tactics and strategies that attempt to ensure that the desired item is delivered in a manner consistent with the user's preferences. Given this large space of possibilities, we employ a genetic algorithm to search (offline) for effective strategies in common classes of environment. The strategies that emerge from this evolution are then codified into the agent's reasoning behaviour so that it can select the most appropriate strategy to employ in its prevailing circumstances. The proposed framework has been implemented in a simulated marketplace environment and its effectiveness has been empirically demonstrated.

Incentive-compatible, budget-balanced, yet highly efficient auctions for supply chain formation

Abstract: Engineering automated negotiation across the supply chain is a central research challenge for the important problem of supply chain formation. The difficult problem of designing negotiation strategies is greatly simplified if the negotiation mechanism is incentive compatible, in which case the agents' dominant strategy is to simply report their private information truthfully. Unfortunately, with two-sided negotiation it is impossible to simultaneously achieve perfect efficiency, budget balance, and individual rationality with incentive compatibility. This bears directly on the mechanism design problem for supply chain formation---the problem of designing auctions to coordinate the buying and selling of goods in multiple markets across a supply chain. We introduce incentive compatible, budget balanced, and individually rational auctions for supply chain formation inspired by previous work of Babaioff and Nisan, but extended to a broader class of supply chain topologies. The auctions explicitly discard profitable trades, thus giving up perfect efficiency to maintain budget balance and individual rationality. We use a novel payment rule analogous to Vickrey-Clarke-Groves payments, but adapted to our allocation rule. The first auction we present is incentive compatible when each agent desires only a single bundle of goods, the auction correctly knows all agents' bundles of interest, but the monetary valuations are private to the agents. We introduce extensions to maintain incentive compatibility when the auction does not know the agents' bundles of interest. We establish a good worst case bound on efficiency when the bundles of interest are known, which also applies in some cases when the bundles are not known. Our auctions produce higher efficiency for a broader class of supply chains than any other incentive compatible, individually rational , and budget-balanced auction we are aware of.

Replicating Online Yankee Auctions to Analyze Auctioneers' and Bidders' Strategies

Abstract: We present a simulation approach that provides a relatively risk-free and cost-effective environment to examine the decision space for both bid takers and bid makers in web-based dynamic price setting processes. The applicability of the simulation platform is demonstrated for Yankee auctions in particular. We focus on the optimization of bid takers' revenue, as well as on examining the welfare implications of a range of consumer-bidding strategies--some observed, some hypothetical. While these progressive open discriminatory multiunit auctions with discrete bid increments are made feasible by Internet technologies, little is known about their structural characteristics, or their allocative efficiency. The multiunit and discrete nature of these mechanisms renders the traditional analytic framework of gametheory intractable (Nautz and Wolfstetter 1997). The simulation is based on theoretical revenue generating properties of these auctions. We use empirical data from real online auctions to instantiate the simulation's parameters. For example, the bidding strategies of the bidders are specified based on three broad bidding strategies observed in real online auctions. The validity of the simulation model is established and subsequently the simulation model is configured to change the values of key control factors, such as the bid increment. Our analysis indicates that the auctioneers are, most of the time, far away from the optimal choice of bid increment, resulting in substantial losses in a market with already tight margins. The simulation tool provides a test bed forjointly exploring the combinatorial space of design choices made by the auctioneer's and the bidding strategies adopted by the bidders. For instance, a multinomial logit model reveals that endogenous factors, such as the bid increment and the absolute magnitude of the auction have a statistically significant impact on consumer-bidding strategies. This endogeniety is subsequently modeled into the simulation to investigate whether the effects are significant enough to alter the optimal bid increments or auctioneer revenues. Additionally, we investigate hybrid-bidding strategies, derived as a combination of three broad strategies, such as jump bidding and strategic-at-margin (SAM) bidding. We find that hybrid strategies have the potential of significantly altering bidders' likelihood of winning, as well as their surplus.

Bidding in an Electricity Pay-as-Bid Auction

Abstract: One of the main elements of the recent reform of electricity trading in the United Kingdom is the change from a uniform price auction in the wholesale market to discriminatory pricing. We analyze this change under two polar market structures (perfectly competitive and monopolistic supply), with demand uncertainty. We find that under perfect competition there is a trade-off between efficiency and consumer surplus between the two auction rules. We also establish that a move from uniform to discriminatory pricing under monopoly conditions has a negative impact on profits and output (weakly), a positive impact on consumer surplus, and ambiguous implications for welfare and average prices.

Decentralized supply chain formation: a market protocol and competitive equilibrium analysis

Abstract: Supply chain formation is the process of determining the structure and terms of exchange relationships to enable a multilevel, multiagent production activity. We present a simple model of supply chains, highlighting two characteristic features: hierarchical subtask decomposition, and resource contention. To decentralize the formation process, we introduce a market price system over the resources produced along the chain. In a competitive equilibrium for this system, agents choose locally optimal allocations with respect to prices, and outcomes are optimal overall. To determine prices, we define a market protocol based on distributed, progressive auctions, and myopic, non-strategic agent bidding policies. In the presence of resource contention, this protocol produces better solutions than the greedy protocols common in the artificial intelligence and multiagent systems literature. The protocol often converges to high-value supply chains, and when competitive equilibria exist, typically to approximate competitive equilibria. However, complementarities in agent production technologies can cause the protocol to wastefully allocate inputs to agents that do not produce their outputs. A subsequent decommitment phase recovers a significant fraction of the lost surplus.

Price-taker bidding strategy under price uncertainty

Abstract: This paper provides a framework to obtain the optimal bidding strategy of a price-taker producer. An appropriate forecasting tool is used to estimate the probability density functions of next-day hourly market-clearing prices. This probabilistic information is used to formulate a self-scheduling profit maximization problem that is solved taking advantage of its particular structure. The solution of this problem allows deriving a simple yet informed bidding rule. Results from a realistic case study are discussed in detail.