Number Of Bidders Research Articles

The fixed price offer mechanism in Trade Me online auctions

The fixed-price-offer (FPO) mechanism in Trade Me auctions allows sellers to make a take-it-or-leave-it offer at the conclusion of an unsuccessful auction. Weinvestigate the effects of the FPO option on strategies and outcomes in independent-value auctions. The FPO option induces some bidders with a value above the seller's reserve to wait for an FPO instead of bidding. Overall, the FPO option increases the probability of sale but reduces expected seller revenue compared with a standard auction. The impact of the FPO option is reduced when the number of bidders increases.

Revenue-maximizing Dutch auctions with discrete bid levels

This paper is concerned with setting a predetermined number of bid levels in a Dutch auction to maximize the auctioneer’s expected revenue. As a departure from the traditional methods used by applied economists and game-theorists, a novel approach is taken in this study to tackle the problem by formulating the auctioning process as a constrained nonlinear program and applying standard optimization techniques to solve it. Aside from proposing respective closed-form formulae for computing the optimal bid levels and the auctioneer’s maximum expected revenue, we also show that the bid decrements should be increasing if there are two or more bidders in the Dutch auction. Additionally, the auctioneer’s maximum expected revenue increases with the number of bidders as well as the number of bid levels. Finally, managerial implications of the key findings as well as limitations of this research work are discussed.

Behavioural simulations in spot electricity markets

We study the consistency of behavioural simulation methods used to model the operations of wholesale electricity markets. We include different supply and demand representations and propose the Experience-Weighted Attractions method ( Camerer and Ho, 1999) to encompass several behavioural paradigms. We compare the results across assumptions and to standard economic theory predictions. The match is good under flat and upward-slopping supply bidding, and also for plausible demand elasticity assumptions. Learning is influenced by the number of bids per plant and the initial conditions. The simulations perform best under reinforcement learning, less well under best-response and especially poorly under fictitious play. The overall conclusion is that simulation assumptions are far from innocuous. We link their performance to underlying features, and identify those that are better suited to model liberalised electricity markets.

BUNDLING IN AUCTIONS WITH NON-LINEAR VALUATIONS*

We examine when a revenue-maximising auctioneer prefers to auction a homogenous product in one bundle (a single-object auction) than to sell the item in two or more shares. When the items are super-additive the auctioneer always prefers a single-object auction. When the product valuations are sub-additive, the auctioneer is more likely to choose a share auction when there are a large number of potential bidders. When there are a small number of bidders the auctioneer will tend to prefer a single-object auction.

Pricing Linkages Between Added Value Levels Of The Beef Industry: A Systems Approach

Agricultural commodities, and in particular the livestock industry, experiences cycles in prices, demand, and supply conditions. Large variations can result from a variety of factors which influence the regularity, magnitude, and the severity of the cycles. In the last few years the U.S. Livestock industry has suffered through hard financial times. Grass roots organizations such as WORC have accused the packers for using their economic power gained from concentration and the use of captive supplies for low prices at the slaughter and cow-calf levels. To compound the issue IBP, the largest beef packer, with 33 percent of the beef kill is for sale and has been bid on by other packers, potentially concentrating the industry more and reducing the number of bidders for slaughter cattle. The article found that the inefficiencies and price distortion in the value system were not at the packer level, but rather the retail level and between the feedlot level and the cow-calf levels. Because of changing marketing arrangements, price discovery issues in the concentrated markets needs to be resolved before suspicion will disappear.

Dominance-solvable common-value large auctions

We consider second-price common-value auctions with an increasing number of bidders. We define a strategy of bidder i to be ( ex-post, weakly) asymptotically dominated if there is another strategy for i that does, in the limit, as well against any sequence of strategies of iʼs opponents, and with positive probability does strictly better against at least one sequence. Our main result provides a sufficient condition on the information structure for the process of iteratively deleting asymptotically dominated strategies to terminate after just two iterations, with only one strategy left for each player. This strategy is fully characterized. We also show that, under standard assumptions, a similar condition to that of Wilson (1977) implies our sufficient condition and therefore implies asymptotic dominance solvability.

Bounds on revenue distributions in counterfactual auctions with reserve prices

Measuring auction revenues under counterfactual reserve prices or formats requires knowledge of distributions of bidders' values and private signals. This poses a challenge when bids are observed from first‐price, common‐value auctions. I bound counterfactual revenue distributions without imposing parametric restrictions on the model structure. Using data from U.S. municipal bond auctions, I find first‐price and second‐price auctions under optimal reserve prices lead to little improvement in revenues over existing first‐price formats. The number of bidders has a more significant impact on revenues in optimal auctions. I also find invoking an incorrect assumption of private values in counterfactual analyses results in small errors in predicting revenues from optimal second‐price auctions.

Remedies for information asymmetry in online transaction

PurposeThis study seeks to investigate the signals on which consumers may rely to reduce the problems of information asymmetry on an online auction site. The research aims to develop and test based on information signaling theory. It classifies signals from auction web pages into three types: seller reputation, product condition, and argument quality. To understand how the signals affect consumers' online buying decisions, the study intends to test the impacts of these signals on the auction outcome variables: number of bids, auction success, and willingness to pay.Design/methodology/approachThe paper employs an empirical test with real observation data comprised of 5,013 samples coded from the eBay auction site in the USA. Ordinary least squares (OLS) regression is used to predict the effect of web page signals on the number of bids, logistic regression to determine which web page signals contribute to auction success, and Tobit maximum likelihood estimation to estimate the impact of web page signals on willingness to pay.FindingsResults show that, in addition to the seller's reputation, signals like product condition and the quality of the sellers' arguments on the web page are significantly related to the three auction outcomes. Buyers tend to rely on these signals to resolve information asymmetry in online auction transactions.Originality/valuePast studies have found that the seller's feedback score is central to a positive online auction outcome. This paper is the first to classify web page signals comprehensively and to investigate their impacts on online auction outcomes using real transaction data. The findings provide substantial evidence and implications for both academic research and practitioners in online auctions. A dynamic strategy for success in online auctions is offered in the conclusion section.

The high/low divide: Self-selection by values in auction choice

Most prior theoretical and experimental work involving auction choice has assumed bidders find out their value after making a choice of which auction to enter. We examine whether or not bidders knowing their value prior to making a choice of which among multiple alternative auction formats to enter impacts their choice decision and/or the outcome of the auctions. The results show a strong impact on auction choice. Subjects with low values choose the first price sealed bid auction more often while subjects with high values choose the ascending auction more often. The number of bidders in each auction, revenue, efficiency and average bidder surplus all end up equalized.

B2B multi-attribute e-procurement: an artificial immune system based goal programming approach

This paper presents an artificial immune system (AIS) based goal programming approach for a multi-attribute e-procurement system. Current trends reveal that procurers are now concerned with various attributes of supplier selection, rather than negotiating only on cost. The scenario considered in this paper pertains to the procurement of an homogenous item in a large quantity. In these circumstances, procurers are forced to incorporate multi-attribute bids, dynamics pricing, related business requirements and multiple criteria in bid evaluation. The prime objective is to decide on the supplier and the quantity to be procured from the selected supplier. The problem considered here is NP hard, even without taking into account business constraints, and it becomes computationally prohibitive with an increase in the number of bids and the number of attribute values. In order to solve this problem with minimal computational time and effort, an evolutionary algorithm AIS with a goal programming technique is adopted. The working of the AIS based goal programming approach is evaluated by implementing it for a few simulated problem instances of changing complexity. The effectiveness of the proposed approach is established by a comparative study with other established evolutionary approaches such as a genetic algorithm and a simulated annealing algorithm.

Exploring Market Dispersion and Factors that Predict Auction Success of a Commodity: The Case of Three E-Auction Markets

The current study presents emerging evidence of the heterogeneities of dispersion in price and number of bidders and the combination of factors that predict auction success across electronic auction (e-auction) markets in various countries. We argue that heterogeneities in e-auction markets exist and understanding them can benefit market participants. A spider program was developed to collect live auction data of commodity transactions from e-auction markets in three different countries: Australia, the United Kingdom, and the United States. Our results confirm heterogeneities across these markets. We also found that each e-auction market has a different set of success factors. The article concludes with recommendations to participating members of auctions.

Barriers to Entry in Rail Passenger Services: Empirical Evidence for Tendering Procedures in Germany

As in several other European Union Member States, Germany has used tendering to an increasing degree since the mid-1990s for subsidized passenger rail services. In order to determine whether market entry barriers exist in this market, a dataset of 30 German tendering procedures with start of operations between 1997 and 2007 is analyzed. The data consists of comprehensive primary data provided directly by public transport authorities and operators. On average 11 rail companies requested the tendering documents, but only four per tendering procedure submitted bids. The empirical analysis shows that there are two main tendering conditions that clearly influence the number of bidders. The first is the percentage of risk assumed by the public transport authority for price increases on input factors like personnel or fuel. This shows a positive correlation with the number of bidders. The second is the level of revenue risk to be assumed by the operator, which shows a negative correlation. Both correlations are highly significant. Authorities in Germany as well as in other countries using the tendering instrument should be aware of the influence of uncertainty and therefore avoid imposing untenable risks on operators. A high level of uncertainty will reduce authorities’ efficiency gains by reducing competition and making it necessary for operators to calculate an increased risk premium.

Influence of Number of Bidders and StandardMinimum Price for Investigation to Bid Rate

Influence of Number of Bidders and StandardMinimum Price for Investigation to Bid Rate

Endogenous Competition Alters the Structure of Optimal Auctions

Potential bidders respond to a seller’s choice of auction mechanism for a common-value or affiliated-values asset by endogenous decisions whether to incur an information-acquisition cost (and observe a private estimate), or forgo competing. Privately informed participants decide whether to incur a bid-preparation cost and pay an entry fee, or cease competing. Auction rules and information flows are quite general; participation decisions may be simultaneous or sequential. The resulting revenue identity for any auction mechanism implies that optimal auctions are allocatively efficient; a nontrivial reserve price is revenue-inferior. Optimal auctions are otherwise contentless: any auction that sells without reserve becomes optimal by adjusting any one of the continuous, spanning parameters, e.g., the entry fee. Seller’s surplus-extracting tools are now substitutes, not complements. Many econometric studies of auction markets are seen to be flawed in their identification of the number of bidders.

Simultaneous online auctions: decisions on reserve prices

The simultaneous nature of online auctions changes the horizon a bidder faces. A seller then has to make strategic and/or operational changes in order to adapt. In this study, a three-stage game model is constructed to analyse seller reserve price setting decision in online auctions. The decision of whether a seller should set a reserve price is shown to be a function of the covariance (between expected seller profits and expected rivals) and the expected number of bidders, where the covariance term is jointly determined by possible actions of other sellers.

A cryptographically t‐private auction system

AbstractWe present a cryptographically t‐private protocol for electronic auctions whose low resource demands make it viable for practical use. Our construction is based on Yao's garbled circuits and pseudorandom number generators (PRNGs). Our protocol involves a field of (t + 1)2 parties for the generation of the garbled circuit and permits an arbitrary large number of bidders. The computational requirements are low: Only t + 1 parties of the field have to use the PRNG, the remaining parties execute only primitive computations (XOR, permutations and sharing). The bidders have to stay active for one round of communication, independent of each other. Each bidder has to compute only t + 1 XOR‐operations. We present an implementation and evaluate its performance. The observed running time of our protocol is linear in the size of the auction circuit and the number of bidders and, as expected, grows quadratically in the parameter t. Copyright © 2010 John Wiley & Sons, Ltd.

Competitor analysis in construction bidding

Bidding strategies vary from contractor to contractor, each of which will have different degrees of sensitivity towards the factors affecting their bidding decisions. A competitor analysis using a linear mixed model is proposed for use by contractors as part of a more informed approach in identifying key competitors, and as a basis for formulating bidding strategies. The competitiveness between bids is examined according to: (i) project size, (ii) work sector; (iii) work nature; and (iv) number of bidders. The model was tested empirically by application to a bidding dataset obtained from a large Hong Kong contractor. Allowing for different degrees of sensitivity towards the four bidding variables across competing contractors (i.e. with the model parameters that varied across competing contractors), the results indicate that competitiveness in bidding of this contractor is generally greater than the majority of its competitors.

Corrigendum to “Reserve price signaling” [J. Econ. Theory 135 (1) (2007) 253–268

Abstract We find an error in [H. Cai, J. Riley, L. Ye, Reserve price signaling, J. Econ. Theory 135 (1) (2007) 253–268]. The existence of the separating signaling equilibrium is not challenged, but the related comparative statics, while valid in the case without informational externalities between bidders, do not generalize to the case with informational externalities as claimed by the authors. General results on the influence of the number of bidders are obtained in a linear specification of the informational externalities.

Adverse selection, seller reputation and buyer insurance in online auctions for 1960s-era collectible baseball cards

We investigate the differences between Beckett book values and eBay auction prices using an original data set of 876 auctions for 30 baseball cards from the 1960s era. We find that cards of lower quality generally sell (on eBay) above book price, whereas cards of higher quality generally sell below book price. We find that both the presence of buyer insurance and the number of bids increase eBay prices relative to book values and that the seller's reputation and the number of bids increase the probability that the eBay price will be greater than the corresponding book value.

Properties of the DGS-Auction Algorithm

This paper investigates algorithmic properties and overall performance of the exact auction algorithm in Demange, Gale and Sotomayor (J. Polit. Economy 94: 863---872, 1986) or DGS for short. This task is achieved by interpreting DGS as a graph and by conducting a large number of computer simulations. The crucial step in DGS is when the auctioneer selects a so-called minimal overdemanded set of items because the specific selection may affect a number of performance measures such as the number of iterations and the ratio of elicited preferences. The computational results show that (i) DGS graphs are typically large even for relatively small numbers of bidders and items, (ii) DGS converges slowly and (iii) DGS performs well in terms of preference elicitation. The paper also demonstrates that the modification to DGS based on the Ford---Fulkerson algorithm outperforms all investigated rules for selecting a minimal overdemanded set of items in DGS both in terms of termination speed and preference elicitation.