This groundbreaking book introduces the application of statistical
methodologies to e-Commerce data
With the expanding presence of technology in today’s economic
market, the use of the Internet for buying, selling, and investing
is growing more popular and public in nature. Statistical Methods
in e-Commerce Research is the first book of its kind to focus on
the statistical models and methods that are essential in order to
analyze information from electronic-commerce (e-Commerce)
transactions, identify the challenges that arise with new
e-Commerce data structures, and discover new knowledge about
consumer activity.
This collection gathers over thirty researchers and practitioners
from the fields of statistics, computer science, information
systems, and marketing to discuss the growing use of statistical
methods in e-Commerce research. From privacy protection to economic
impact, the book first identifies the many obstacles that are
encountered while collecting, cleaning, exploring, and analyzing
e-Commerce data. Solutions to these problems are then suggested
using established and newly developed statistical and data mining
methods. Finally, a look into the future of this evolving area of
study is provided through an in-depth discussion of the emerging
methods for conducting e-Commerce research.
Statistical Methods in e-Commerce Research successfully bridges the
gap between statistics and e-Commerce, introducing a statistical
approach to solving challenges that arise in the context of online
transactions, while also introducing a wide range of e-Commerce
applications and problems where novel statistical methodology is
warranted. It is an ideal text for courses on e-Commerce at the
upper-undergraduate and graduate levels and also serves as a
valuable reference for researchers and analysts across a wide array
of subject areas, including economics, marketing, and information
systems who would like to gain a deeper understanding of the use of
statistics in their work.
Cuprins
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 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.
Despre autor
Wolfgang Jank, Ph D, 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, Ph D, is Associate Professor and Director
of the e Markets 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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