1. Edition - August 2010
91.90 Euro
2010. 320 Pages, Hardcover
ISBN-10: 0-470-47565-X
ISBN-13: 978-0-470-47565-2 - John Wiley & Sons






Sample Chapter

Short description
In Modeling Online Auctions, the authors introduce the reader to state-of-the-art statistical methodology for extracting new knowledge from online auction data. Rather than approach the topic from the traditional game-theoretic route, the authors treat the online auction mechanism as a new type of data generator, as well as use statistical and data mining methods to collect, explore, model, and forecast data that arises from online auction databases. Every effort is made to embellish cross-disciplinary fertilization between statistics, data mining, marketing, information systems, and economics and related fields.

From the contents
Preface.

Acknowledgments.

1 Introduction.

1.1 Online Auctions and Electronic Commerce.

1.2 Online Auctions and Statistical Challenges.

1.3 A Statistical Approach to Online Auction Research.

1.4 The Structure of this Book.

1.5 Data and Code Availability.

2 Obtaining Online Auction Data.

2.1 Collecting Data from the Web.

2.2 Web Data Collection and Statistical Sampling.

3 Exploring Online Auction Data.

3.1 Bid Histories: Bids versus "Current Price" Values.

3.2 Integrating Bid History Data With Cross-Sectional Auction Information.

3.3 Visualizing Concurrent Auctions.

3.4 Exploring Price Evolution and Price Dynamics.

3.5 Combining Price Curves with Auction Information via Interactive Visualization.

3.6 Exploring Hierarchical Information.

3.7 Exploring Price Dynamics via Curve Clustering.

3.8 Exploring Distributional Assumptions.

3.9 Exploring Online Auctions: Future Research Directions.

4 Modeling Online Auction Data.

4.1 Modeling Basics (Representing the Price Process).

4.2 Modeling The Relation Between Price Dynamics and Auction Information.

4.3 Modeling Auction Competition.

4.4 Modeling Bid and Bidder Arrivals.

4.5 Modeling Auction Networks.

5 Forecasting Online Auctions.

5.1 Forecasting Individual Auctions.

5.2 Forecasting Competing Auctions.

5.3 Automated Bidding Decisions.

Bibliography.

Index.