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We report an experiment conducted to gain insight into factors that may affect revenues in English auctions and lotteries, two commonly used charity fund-raising formats. In particular, we examine how changes in the marginal per capita return (MPCR) from the public component of bidding, and how changes in the distribution of values affect the revenue properties of each format. Although we observe some predicted comparative static effects, the dominant result is that lottery revenues uniformly exceed English auction revenues. The similarity of lottery and English auction bids across sales formats appears to drive the excess lottery revenues.

The purpose of this paper is to discuss the concept of group signature, first introduced by Chaum and van Heyst, which allows individual members in a group to create signatures on behalf of the group.

This paper proposes a new English auction scheme based on the concept of group signature using the bulletin board system.

It is found that the proposed scheme can satisfy the requirements of an ideal of English auction scheme.

Compared with other public auction schemes, it is claimed that the scheme presented in this paper can satisfy all requirements of an ideal auction scheme and is superior to other schemes. The scheme's primary merit is in its simplicity and practicality for implementation under insecure communication links.

The reverse electronic auction is a new competitive bidding procedure adopted by the recently enacted European Community (EC) directives on public procurement. It is submitted that the electronic reverse auction has the potential to reduce the tension between the European Commission and national policies of procurement, as it can decrease contracting costs, increase transparency and achieve better economic outcomes as a result of increased competition. This paper relies on auction theory in order to support such statements. A comparison between the traditional sealed-bid method and the reverse auction is further provided.

This paper aims to investigate the presence of varying price points on the impact of product valuations in both English and reverse auctions on potential bidders, that is, those not yet engaged in the auction. Internet auctions, both English style and reverse, constitute one of the success stories of digital commerce.

As its method of research, this paper uses an experimental approach to explore the effects of multiple reference prices.

While previous research has done well to show that a lower initial price decreases barriers to entry and can lead to a higher final price in English-style auctions, this research shows that such a strategy may harm potential bidders’ product perceptions due to multiple reference prices. The authors explore situations of multiple reference prices in the context of reverse auctions, where both higher and lower reference prices are shown to be able to increase product valuations.

Additional research of a variety of products and using a representative sample would enhance the findings of this paper.

The findings show that reference prices have differing impacts, which are dependent upon the goal of either maximizing or minimizing the distance between the initial price and the price consumers are willing to pay in an online auction.

The investigation links differing goals created by the type of auction to the potential impact of the reference price. In addition, we explore the effects of multiple reference prices on consumer valuations.

The purpose of this paper is to investigate the analogy of the human immune system with the economic auction theory.

The paper develops an analogy of bio‐immune system with competitive bidding in auction, then develops a model of the situation and discusses its managerial implications.

The human immune system can be benchmarked to model decision making under competitive environment, such as biddings in auctions and obtains gainful insights.

Various engineering, management, social science, and defense and security‐related applications of the model are suggested.

The paper presents a novel and innovative model with tremendous potential for varied applications.

This paper gives a model of collusion formation and a method of measuring the degree of it among the traders/bidders in the agricultural commodity markets in India. The important assumption is that the bidding is repetitive with a set of common bidders. The theory has been derived based on the behavior of the wholesale market of agricultural commodities in India. The paper is based on full information in the collusion formation. The paper first derives the theoretical structure of the bidders' behavior and thereafter derives a measure of collusion formation with the help of real-life data.

The paper used the standard theory of optimization and the theory of auction and probability statistics.

This is a complete information model of cartel formation. The bidding is repetitive and continues forever in discrete time. Hence bidders behavior is observable. Using the proposed method, if the APMC measures for each market and publishes on a periodic basis, say weekly basis, then it will be easier to break the collusion in the market where relative collision is present. For example, if a farmer has three options to sell in three different markets, then the published data would help them to select the market where the degree of collusion is relatively lower. Moreover, the undesirable loss can be avoided based on the right choice of market. As a result, transaction costs will be optima.

The paper first derives the theoretical structure of the bidders' behavior and thereafter derives a measure of collusion formation with the help of real-life data.

As the demand for online auctions increases, the process of monitoring multiple auction houses, deciding which auction to participate in and making the right bids, become challenging tasks for consumers. Hence, knowing the closing price of a given auction would be an advantage, since this information will ensure a win in a given auction. However, predicting a closing price for an auction is not easy, since it is dependent on many factors. The purpose of this paper is to report on a predictor agent that utilises grey system theory to predict the closing price for a given auction.

The focus of the research is on grey system agent. This paper reports on the development of a predictor agent that attempts to predict the online auction closing price in order to maximise the bidder's profit. The performance of this predictor agent is compared with two well‐known techniques, the Simple Exponential Function and the Time Series, in a simulated auction environment and in the eBay auction.

The grey theory agent gives a better result when less input data are made, while the Time Series Agent can be used with the availability of a lot of information. Although the Simple Exponential Function Agent is able to predict well with less input data, it is not an appropriate method to be applied in the prediction model since its formula is not realistic and applicable in predicting the online auction closing price. The experimental results also showed that using moving historical data produces a higher accuracy rate than using fixed historical data for all three agents.

Grey system theory prediction model, GM(1, 1) has not been applied in online auction prediction. In this paper the authors have applied grey theory into an agent to predict the closing price of an online auction, in order to increase the profit of bidders in the bidding stage. The experimental results show that the accuracy of the grey prediction model is more then 90 per cent, with less then eight historical data inputs.

The main aim of this paper is to review some of the newest and most promising advances in auction theory with an eye to applications to procurement practice. Here we focus in particular on four topics related to multidimensional auctions: 1) how to define a proper scoring rule when the awarding bodies lack the necessary information regarding its own preferences and suppliers’ technology; 2) how to cope with the information disclosure policy regarding the discretional evaluation of some aspects of each contractual proposal; 3) how to use contractors’ reputations based on their past performance in the awarding process; 4) how to control the risk of collusion and corruption in the awarding phase.

The purpose of this paper is to present the prevailing auction and bidding mechanisms in supply chain management. The paper aims to critically examine the implications of these auction mechanisms using the example of the transportation sector.

A framework is presented to highlight the role of internet and information systems in the transportation sector. The paper discusses the complexities associated with embracing these internet‐enabled auction mechanisms and presents some research propositions.

In its present state of affairs an electronic marketplace would become nothing but a virtual place where the competing firms would be indulged in price wars to maintain their presence. A prolonged spur of activities in this direction would lead to a stalemate where the winners are losers.

In the long run it is important that the decisions associated with electronic auctions must be based on more than bargain‐basement price tags. The business intangibles focused on developing a strong buyer‐supplier relationship, will determine the quality of the purchase contract.

The propositions presented here could provide initial impetus for future empirical research that gleans insights regarding the link between the use of electronic auction mechanisms and the strength of buyer‐supplier relationships.

Provides a comprehensive review and some potential research propositions that could enhance our understanding of supply chain management.

A significant number of published empirical studies of real estate auctions abound in real estate literature. These studies focus on the auction price formation process through the comparison of sales from different auctions to revenue from private negotiations. While these studies have made useful contributions to the literature, they are largely confined to data emanating from auctions in the UK format. Other auction formats have been virtually ignored; thus creating a gap in the literature. This study, therefore seeks to extend research in the auction price formation process through an empirical analysis of transaction prices from the perspective of another auction format: first sealed bid auction.

The data for this study consist of a sample size of 120 residential properties sold at auction of the Federal Government Landed Properties (FGLP) in Ikoyi, Lagos, Nigeria. Transaction data for each of the sampled properties were compiled from Vol. 11, No. 3834 of Thisday newspaper. These include open market values (reserve prices), bid prices, numbers of bids, property specific and bidders' attributes. These were then analysed using descriptive, paired t‐test statistic and regression model.

The empirical evidence suggests that auction properties sell at an 11.33 per cent premium relative to predicted market values. Also provided, through the regression model, are variables having a significant impact on the auction prices.

The paper provides empirical evidence of the auction price formation process in first sealed bid auction where published empirical studies are still relatively few. Overall, the results of the analysis presented suggest that auctions offer an optimal method of selling property.