Buy-It-Now prices in eBay Auctions - The Field in the Lab

Electronic commerce has grown extraordinarily over the years, with online auctions being extremely successful forms of trade. Those auctions come in a variety of different formats, such as the Buy-It-Now auction format on eBay, that allows sellers to post prices at which buyers can purchase a good prior to the auction. Even though, buyer behavior is well studied in Buy-It-Now auctions, as to this point little is known about how sellers set Buy-It-Now prices. We investigate into this question by analyzing seller behavior in Buy-It-Now auctions. More precisely, we combine the use of a real online auction market (the eBay platform and eBay traders) with the techniques of lab experiments. We find a striking link between the information about agents provided by the eBay market institution and their behavior. Information about buyers is correlated with their deviation from true value bidding. Sellers respond strategically to this information when deciding on their Buy-It-Now prices. Thus, our results highlight potential economic consequences of information publicly available in (online) market institutions

An investigation of the trading agent competition : a thesis presented in partial fulfilment of the requirements for the degree of Master of Science in Computer Science at Massey University, Albany, New Zealand

The Internet has swept over the whole world. It is influencing almost every aspect of society. The blooming of electronic commerce on the back of the Internet further increases globalisation and free trade. However, the Internet will never reach its full potential as a new electronic media or marketplace unless agents are developed. The trading Agent Competition (TAC), which simulates online auctions, was designed to create a standard problem in the complex domain of electronic marketplaces and to inspire researchers from all over the world to develop distinctive software agents to a common exercise. In this thesis, a detailed study of intelligent software agents and a comprehensive investigation of the Trading Agent Competition will be presented. The design of the Risker Wise agent and a fuzzy logic system predicting the bid increase of the hotel auction in the TAC game will be discussed in detail

Auctions to gas transmission access: The British experience

Auctions to gas transmission access: The British experienc

Seller strategies on eBay: Does size matter?

We examine seller strategies in 1177 Internet auctions on eBay, to understand the diversity of strategies used, and their impacts. Dimensions of strategic choice include the use of a ‘Buy it Now’ option, the level of the starting price, and the use of a secret reserve price. A major focus of our analysis is on differences across sellers with different volumes of sales. The largest volume sellers (termed “retailers”) in our sample employ uniform selling strategies, but lower volume sellers exhibit a wide variety of strategic choices. While some components of sellers’ strategies appear important in raising seller revenue, including starting the auction with a ‘Buy it Now’ offer, the overall impact of seller strategy choices on the outcome appears to be quite small. We interpret this as evidence for the competitiveness of the online auction market for frequently traded items with conventional retail alternatives. An exception is provided by the use of a secret reserve price, which raises the winning bid conditional on a sale, but reduces the probability of a sale. Depending on sellers’ risk aversion and impatience, this may also be an efficient outcome

Online Auctions

The economic literature on online auctions is rapidly growing because of the enormous amount of freely available field data. Moreover, numerous innovations in auction-design features on platforms such as eBay have created excellent research opportunities. In this article, we survey the theoretical, empirical, and experimental research on bidder strategies (including the timing of bids and winner's-curse effects) and seller strategies (including reserve-price policies and the use of buy-now options) in online auctions, as well as some of the literature dealing with online-auction design (including stopping rules and multi-object pricing rules).

How eBay Sellers set “Buy-it-now” prices - Bringing The Field Into the Lab

In this paper we introduce a new type of experiment that combines the advantages of lab and field experiments. The experiment is conducted in the lab but using an unchanged market environment from the real world. Moreover, a subset of the standard subject pool is used, containing those subjects who have experience in conducting transactions in that market environment. This guarantees the test of the theoretical predictions in a highly controlled environment and at the same time enables not to miss the specific features of economic behavior exhibited in the field. We apply the proposed type of experiment to study seller behavior in online auctions with a Buy-It-Now feature, where early potential bidders have the opportunity to accept a posted price offer from the seller before the start of the auction. Bringing the field into the lab, we invited eBay buyers and sellers into the lab to participate in a series of auctions on the eBay platform. We investigate how traders' experience in a real market environment influences their behavior in the lab and whether abstract lab experiments bias subjects' behavior

An Investigation Report on Auction Mechanism Design

Auctions are markets with strict regulations governing the information available to traders in the market and the possible actions they can take. Since well designed auctions achieve desirable economic outcomes, they have been widely used in solving real-world optimization problems, and in structuring stock or futures exchanges. Auctions also provide a very valuable testing-ground for economic theory, and they play an important role in computer-based control systems. Auction mechanism design aims to manipulate the rules of an auction in order to achieve specific goals. Economists traditionally use mathematical methods, mainly game theory, to analyze auctions and design new auction forms. However, due to the high complexity of auctions, the mathematical models are typically simplified to obtain results, and this makes it difficult to apply results derived from such models to market environments in the real world. As a result, researchers are turning to empirical approaches. This report aims to survey the theoretical and empirical approaches to designing auction mechanisms and trading strategies with more weights on empirical ones, and build the foundation for further research in the field

ATTac-2000: An Adaptive Autonomous Bidding Agent

The First Trading Agent Competition (TAC) was held from June 22nd to July 8th, 2000. TAC was designed to create a benchmark problem in the complex domain of e-marketplaces and to motivate researchers to apply unique approaches to a common task. This article describes ATTac-2000, the first-place finisher in TAC. ATTac-2000 uses a principled bidding strategy that includes several elements of adaptivity. In addition to the success at the competition, isolated empirical results are presented indicating the robustness and effectiveness of ATTac-2000's adaptive strategy