Jank / Shmueli Modeling Online Auctions

1. Auflage 2010
ISBN: 978-0-470-64259-7
Verlag: John Wiley & Sons
Format: PDF
Kopierschutz: Adobe DRM (»Systemvoraussetzungen)

E-Book, Englisch, 336 Seiten, E-Book

Reihe: Statistics in Practice

Explore cutting-edge statistical methodologies for collecting,analyzing, and modeling online auction data
Online auctions are an increasingly important marketplace, asthe new mechanisms and formats underlying these auctions haveenabled the capturing and recording of large amounts of biddingdata that are used to make important business decisions. As aresult, new statistical ideas and innovation are needed tounderstand bidders, sellers, and prices. Combining methodologiesfrom the fields of statistics, data mining, information systems,and economics, Modeling Online Auctions introduces a new approachto identifying obstacles and asking new questions using onlineauction data.
The authors draw upon their extensive experience to introducethe latest methods for extracting new knowledge from online auctiondata. Rather than approach the topic from the traditionalgame-theoretic perspective, the book treats the online auctionmechanism as a data generator, outlining methods to collect,explore, model, and forecast data. Topics covered include:
* Data collection methods for online auctions and related issuesthat arise in drawing data samples from a Web site
* Models for bidder and bid arrivals, treating the differentapproaches for exploring bidder-seller networks
* Data exploration, such as integration of time series andcross-sectional information; curve clustering; semi-continuous datastructures; and data hierarchies
* The use of functional regression as well as functionaldifferential equation models, spatial models, and stochastic modelsfor capturing relationships in auction data
* Specialized methods and models for forecasting auction pricesand their applications in automated bidding decision rulesystems
Throughout the book, R and MATLAB software are used forillustrating the discussed techniques. In addition, a related Website features many of the book's datasets and R and MATLAB codethat allow readers to replicate the analyses and learn new methodsto apply to their own research.
Modeling Online Auctions is a valuable book for graduate-levelcourses on data mining and applied regression analysis. It is alsoa one-of-a-kind reference for researchers in the fields ofstatistics, information systems, business, and marketing who workwith electronic data and are looking for new approaches forunderstanding online auctions and processes.
Visit this book's companion website by clicking here

Autoren/Hrsg.

Jank, Wolfgang

Shmueli, Galit

Inhaltsverzeichnis

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 AuctionInformation.
3.3 Visualizing Concurrent Auctions.
3.4 Exploring Price Evolution and Price Dynamics.
3.5 Combining Price Curves with Auction Information viaInteractive 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 AuctionInformation.
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.

Über Autor(innen)

WOLFGANG JANK, PhD, is Associate Professor of ManagementScience and Statistics in the Robert H. Smith School of Business atthe University of Maryland, where he is also Director of the Centerfor Complexity in Business. He has published over seventy articleson statistics and data mining in electronic commerce, marketing,information systems, and operations management. Dr. Jank is thecoauthor of Statistical Methods in e-Commerce Research(Wiley).
GALIT SHMUELI, PhD, is Associate Professor of Statisticsand Director of the eMarkets Research Lab in the Robert H. SmithSchool of Business at the University of Maryland. Her researchfocuses on statistical strategy and data mining methods forscientific research and real-world applications. Dr. Shmueli haspublished over sixty journal articles on statistical and datamining methods related to online auctions and biosurveillance. Sheis the coauthor of Statistical Methods in e-CommerceResearch and Data Mining for Business Intelligence:Concepts, Techniques, and Applications in Microsoft OfficeExcel® with XLMiner®, Second Edition, both publishedby Wiley.