1. Edition - October 2008
93.90 Euro
2008. 430 Pages, Hardcover
ISBN-10: 0-470-12012-6
ISBN-13: 978-0-470-12012-5 - John Wiley & Sons






Sample Chapter

Short description
This book bridges the gap between researchers in statistics and e-commerce, exposing both communities to the opportunities in this evolving area. Statistical Methods in eCommerce Research enables statisticians to better understand the challenges of empirical e-commerce research and to develop new methods for their analyses. It also allows e-commerce researchers to see the statistical challenges, the usefulness of new statistical methods, and how statistical thinking is applied.

From the contents
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. Kennett, 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 Shanshan Wang).

17. Quantile Modeling for Wallet Estimation (Claudia Perlich and Saharon Rosset).

18. Applications of Randomized Response Methodology in E-Commerce (Peter G.M. van der Heijden and Ulf Böckenholt).

Index.