Statistical Methods in e-Commerce Research / Statistics in Practice (PDF)

Preface. Acknowledgements. Contributor List. Section I: Overview of E-Commerce Research Challenges. 1. Statistical Challenges in Internet Advertising (Deepak Agarwal). 2. How Has E-Commerce Research Advanced Understanding of the Offline World (Chris Forman and Avi Goldfarb)? 3. The Economic Impact of User-Generated and Firm-Generated Online Content: Directions for Advancing the Frontiers in Electronic Commerce Research (Anindya Ghose). 4. Is Privacy Protection for Data in an E-Commerce World an Oxymoron (Stephen E. Fienberg)? 5. Network Analysis of Wikipedia (Robert H. Warren, Edoardo M. Airoldi, and David L. Banks). Section II: E-Commerce Applications. 6. An Analysis of Price Dynamics, Bidder Networks, and Market Structure in Online Art Auctions (Mayukh Dass and Srinivas K. Reddy). 7. Modeling Web Usability Diagnostics on the Basis of Usage Statistics (Avi Harel, Ron S. Kenett, and Fabrizio Ruggeri). 8. Developing Rich Insights on Public Internet Firm Entry and Exit Based on Survival Analysis and Data Visualization (Robert J. Kauffman and Bin Wang). 9. Modeling Time-Varying Coefficients in Pooled Cross-Sectional E-Commerce Data: An Introduction (Eric Overby and Benn Konsynski). 10. Optimization of Search Engine Marketing Bidding Strategies Using Statistical Techniques (Alon Matas and Yoni Schamroth). Section III: New Methods For E-Commerce Data. 11. Clustering Data with Measurement Errors (Mahesh Kumar and Nitin R. Patel). 12. Functional Data Analysis for Sparse Auction Data (Bitao Liu and Hans-Georg Müller). 13. A Family of Growth Models for Representing the Price Process in Online Auctions (Valerie Hyde, Galit Shmueli, and Wolfgang Jank). 14. Models of Bidder Activity Consistent with Self-Similar Bid Arrivals (Ralph P. Russo, Galit Shmueli, and Nariankadu D. Shyamalkumar). 15. Dynamic Spatial Models for Online Markets (Wolfgang Jank and P.K. Kannan). 16. Differential Equation Trees to Model Price Dynamics in Online Auctions (Wolfgang Jank, Galit Shmueli, and

Wolfgang Jank, PhD, is Associate Professor in the Department
of Decision, Operations & Information Technologies at the
Robert H. Smith School of Business, the University of Maryland. He
has authored or coauthored over fifty refereed articles in his
areas of research interest, which include stochastic optimization
and Monte Carlo methods; nonparametric statistics and functional
data analysis; and the application of statistical problem-solving
to electronic commerce, marketing, aviation, and operations
management.

Galit Shmueli, PhD, is Associate Professor and Director
of the eMarkets Research Laboratory in the Department of Decision,
Operations & Information Technologies at the Robert H. Smith
School of Business, the University of Maryland. She has authored or
coauthored over fifty refereed articles in her main area of
research: the development and adoption of statistical methods to
nonstandard data with applications to the fields of electronic
commerce and biosurveillance. Dr. Shmueli is the coauthor of
Data Mining for Business Intelligence: Concepts, Techniques, and
Applications in Microsoft Office Excel® with
XLMiner®, also published by Wiley.

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