Modeling Online Auctions

by Jank, Wolfgang; Shmueli, Galit

• ISBN13: 9780470475652
• ISBN10: 047047565X
• Edition: 1st
• Format: Hardcover
• Copyright: 2010-07-13
• Publisher: Wiley

Summary

The new data challenges associated with online auctions motivate the need for clever statistical ideas and new statistical innovation in order to gain knowledge about bidders, sellers, prices, and a host of other questions of interest.In this book, the authors draw upon their experience of working with online auction data and 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.

Author Biography

Wolfgang Jank, PhD, is Associate Professor of Management Science and Statistics in the Robert H. Smith School of Business at the University of Maryland, where he is also Director of the Center for Complexity in Business. He has published over seventy articles on statistics and data mining in electronic commerce, marketing, information systems, and operations management. Dr. Jank is the coauthor of Statistical Methods in e-Commerce Research (Wiley). Galit Shmueli, PhD, is Associate Professor of Statistics and Director of the eMarkets Research Lab in the Robert H. Smith School of Business at the University of Maryland. Her research focuses on statistical strategy and data mining methods for scientific research and real-world applications. Dr. Shmueli has published over sixty journal articles on statistical and data mining methods related to online auctions and biosurveillance. She is the coauthor of Statistical Methods in e-Commerce Research and Data Mining for Business Intelligence: Concepts, Techniques, and Applications in Microsoft Office Excel with XLMiner, Second Edition, both published by Wiley.

Table of Contents

Preface	p. ix
Acknowledgments	p. xi
Introduction	p. 1
Online Auctions and Electronic Commerce	p. 3
Online Auctions and Statistical Challenges	p. 4
A Statistical Approach to Online Auction Research	p. 6
The Structure of this Book	p. 6
Data and Code Availability	p. 8
Obtaining Online Auction Data	p. 9
Collecting Data from the Web	p. 9
Web Data Collection and Statistical Sampling	p. 18
Exploring Online Auction Data	p. 31
Bid Histories: Bids versus "Current Price" Values	p. 32
Integrating Bid History Data With Cross-Sectional Auction Information	p. 36
Visualizing Concurrent Auctions	p. 41
Exploring Price Evolution and Price Dynamics	p. 44
Combining Price Curves with Auction Information via Interactive Visualization	p. 57
Exploring Hierarchical Information	p. 60
Exploring Price Dynamics via Curve Clustering	p. 63
Exploring Distributional Assumptions	p. 72
Exploring Online Auctions: Future Research Directions	p. 94
Modeling Online Auction Data	p. 96
Modeling Basics (Representing the Price Process)	p. 97
Modeling The Relation Between Price Dynamics and Auction Information	p. 132
Modeling Auction Competition	p. 157
Modeling Bid and Bidder Arrivals	p. 189
Modeling Auction Networks	p. 238
Forecasting Online Auctions	p. 253
Forecasting Individual Auctions	p. 254
Forecasting Competing Auctions	p. 279
Automated Bidding Decisions	p. 291
Bibliography	p. 301
Index	p. 313
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