Basic Bidding Formats: Characteristics and Differences

In standard auction theory, the ‘revenue equivalence theorem’ asserts that the outcomes of the elementary allocation methods coincide. However, bidding processes differ fundamentally with regard to the decision situation of the participants: Is it at all imperative to take into consideration the number of competitors (‘stochastic’ strategy) or not (‘deterministic’ course of action)? Furthermore, established auction theory neglects the operating modes of procurement alternatives under uncertainty. Apart from the lacking knowledge how many rivals have to be beaten, tenderers regularly are ignorant of the buyer’s reserve price. Then it is even more tentative to calculate an offer based on probability theory. Consequently, the suppliers’ propensity to collude increases.

Projection of Private Values in Auctions

We explore how taste projection—the tendency to overestimate how similar others’ tastes are to one’s own—affects bidding in auctions. In first-price auctions with private values, taste projection leads bidders to exaggerate the intensity of competition and, consequently, to overbid—irrespective of whether values are independent, affiliated, or (a)symmetric. Moreover, the optimal reserve price is lower than the rational benchmark, and decreasing in the extent of projection and the number of bidders. With an uncertain common-value component, projecting bidders draw distorted inferences about others’ information. This misinference is stronger in second-price and English auctions, reducing their allocative efficiency compared to first-price auctions. (JEL D11, D44, D82, D83)

Adversarial Risk Analysis for Auctions Using Mirror Equilibrium and Bayes Nash Equilibrium

In this paper, we use the adversarial risk analysis (ARA) methodology to model first-price sealed-bid auctions under quite realistic assumptions. We extend prior work to find ARA solutions for mirror equilibrium and Bayes Nash equilibrium solution concepts, not only for risk-neutral but also for risk-averse and risk-seeking bidders. We also consider bidders having different wealth and assume that the auctioned item has a reserve price.

Incentive-Compatible Learning of Reserve Prices for Repeated Auctions

How can an auctioneer optimize revenue by learning the reserve prices from the bids in the previous auctions? How should the long-term incentives and strategic behavior of the bidders be taken into account? Motivated in part by applications in online advertising, in “Incentive-Compatible Learning of Reserve Prices for Repeated Auctions,” Kanoria and Nazerzadeh investigate these questions. They show that if a seller attempts to dynamically update a common reserve price using the bidding history, buyers will shade their bids, which can hurt the revenue. However, when there is more than one buyer, using personalized reserve prices, the auctioneer can achieve a near-optimal revenue. In their proposed mechanism, the personal reserve price for each buyer is determined using the historical bids of other buyers.

Optimal pricing and ordering policies with different patience levels of consumers

PurposeUsing information systems via data mining and cluster analysis technologies, consumers' strategic behaviour can be measured, and their patience levels can be accurately described. This paper investigates the retailer's pricing and ordering policies when facing strategic consumers with different levels of patience and discusses the impacts of consumers' patience levels and proportions on retailers' maximum expected profits.Design/methodology/approachBy cluster analysing transaction data on the number of websites visited, browsing time and purchase decision time, consumers' patience levels can be obtained. The authors formulate a newsvendor model considering customers' different patience levels. Three scenarios are investigated: two segments of consumers with two different levels of patience (Scenario I), multiple segments of consumers with different levels of patience (Scenario II) and a continuum of consumers whose levels of patience follow a continuous distribution (Scenario III). Then, general formulas are deduced for retailers' optimal prices, ordering quantities and profits.FindingsUnder Scenario I, if the proportion of less patient consumers is greater (less) than a threshold, the retailer's optimal price is equal to the less (more) patient consumers' reserve price. Under Scenario II, once the proportion of fully strategic consumers exceeds a certain threshold, the retailers' optimal price is equal to the fully strategic consumers' reserve price regardless of consumers' patience levels and proportions. Under Scenario III, the retailer's pricing and ordering policies depend on the distribution of their patience level.Originality/valueFew studies have considered consumers' different levels of patience when making retailer pricing and ordering decisions. In this paper, strategic consumer behaviour is measured, and consumers' patience levels and proportions are obtained by cluster analysing consumer transaction data recorded by an information system. Three scenarios in which strategic consumers may be heterogeneous and have different patience levels are investigated. The results can guide retailer decision-making.

Market Selection and the Information Content of Prices

We study information aggregation when n bidders choose, based on their private information, between two concurrent common‐value auctions. There are k s identical objects on sale through a uniform‐price auction in market s and there are an additional k r objects on auction in market r, which is identical to market s except for a positive reserve price. The reserve price in market r implies that information is not aggregated in this market. Moreover, if the object‐to‐bidder ratio in market s exceeds a certain cutoff, then information is not aggregated in market s either. Conversely, if the object‐to‐bidder ratio is less than this cutoff, then information is aggregated in market s as the market grows arbitrarily large. Our results demonstrate how frictions in one market can disrupt information aggregation in a linked, frictionless market because of the pattern of market selection by imperfectly informed bidders.

Execution against Residential Immovable Property in terms of High Court Rule 46A

This article provides an overview of and commentary on High Court Rule 46A, which deals with the procedural rules for executing a judgment debt against residential immovable property. Rule 46A focusses on two main aspects: determining if it is justified to sell the debtor’s home in execution and, if a sale is ordered, setting a reserve price at which the property is to be auctioned. Therefore, this article analyses the provisions of rule 46A that pertain to these two components, which also serve as two layers of protection for a debtor facing the loss of his or her home.