Prediction of Survival and Attrition of Click-and-Mortar Corporations

Prediction of Survival and Attrition of Click-and-Mortar Corporations

Indranil Bose (University of Florida, USA) and Anurag Agarwal (University of Florida, USA)
Copyright: © 2002 |Pages: 12
DOI: 10.4018/978-1-930708-31-0.ch007
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The World Wide Web has taken the retail industry by storm. In a short span of 5 to 6 years, millions of users around the globe have been introduced to the Web. Whether shopping for merchandise or simply searching for information, the Web has become the avenue of choice for consumers. According to a recent research report by the Angus Reid Group (, as of the end of the year 2000, nearly 120 million of the estimated 300 million worldwide Internet users have already made an online purchase. The Boston Consulting Group ( estimates the e-tailing market to be about $36 billion by 2001. More than half of all online transactions are still made in the US, with the typical American online shopper making seven purchases over three months with a total spending of $828. Advertising, word of mouth, enhanced security, convenience, and the fun of random surfing are among the various factors frequently cited for the popularity of online shopping. This alternate “shopping mall” has led to a tremendous growth in the number of online companies that have started selling merchandise on the Web, ranging from pet supplies to garden tools to cosmetics. Among these companies, there are some that have a physical presence in retailing, like Barnes and Nobles, Wal-Mart, etc. We call them the brick-and-mortar corporations. There are others which engage solely in online transactions with no physical presence. We call them the click-and-mortar corporations, examples of which are,,, etc.

Complete Chapter List

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Table of Contents
Kate A. Smith, Jatinder N.D. Gupta
Chapter 1
Kate A. Smith
Over the last decade or so, we have witnessed neural networks come of age. The idea of learning to solve complex pattern recognition problems using... Sample PDF
Neural Networks for Business: An Introduction
Chapter 2
G. Peter Zhang, Min Qi
Forecasting future retail sales is one of the most important activities that form the basis for all strategic and planning decisions in effective... Sample PDF
Predicting Consumer Retail Sales Using Neural Networks
Chapter 3
Ai Cheo Yeo, Kate A. Smith, Robert J. Willis, Malcolm Brooks
This paper describes a neural network modelling approach to premium price sensitivity of insurance policy holders. Clustering is used to classify... Sample PDF
Using Neural Networks to Model Premium Price Sensitivity of Automobile Insurance Customer
Chapter 4
Edward Ip, Joseph Johnson, Katsutoshi Yada, Yukinobu Hamuro, Naoki Katoh, Stephane Cheung
The data mining activities studied in this chapter concern the early identification of potential high-value customers. Member stores can use this... Sample PDF
A Neural Network Application to Identify High-Value Customers for a Large Retail Store in Japan
Chapter 5
Margarida G.M.S. Cardoso, Fernando Moura-Pires
The aim of our work is to perform a market segmentation of the clients of Pousadas de Portugal, a network for over 40 high-end small hotels, ENATUR.... Sample PDF
Segmentation of the Portuguese Clients of Pousadas de Portugal
Chapter 6
Rob Potharst, Uzay Kaymak, Wim Pijls
The outline of the chapter is as follows. The section on direct marketing explains briefly what it is and discusses the target selection problem in... Sample PDF
Neural Networks for Target Selection in Direct Marketing
Chapter 7
Indranil Bose, Anurag Agarwal
The World Wide Web has taken the retail industry by storm. In a short span of 5 to 6 years, millions of users around the globe have been introduced... Sample PDF
Prediction of Survival and Attrition of Click-and-Mortar Corporations
Chapter 8
Caron H. St. John, Nagraj (Raju) Balakrishnan, James O. Fiet
Corporate managers, business consultants, stock analysts, and academic researchers have long maintained that the strategic decisions of managers... Sample PDF
Corporate Strategy and Wealth Creation: An Application of Neural Network Analysis
Chapter 9
Roger P.G.H. Tan, Jan van den Berg, Willem-Max van den Bergh
In this case study, we apply the Self-Organizing Map (SOM) technique to a financial business problem. The case study is mainly written from an... Sample PDF
Credit Rating Classification Using Self-Organizing Maps
Chapter 10
David West, Cornelius Muchineuta
Some of the concerns that plague developers of neural network decision support systems include: (a) How do I understand the underlying structure of... Sample PDF
Credit Scoring Using Supervised and Unsupervised Neural Networks
Chapter 11
Fred L. Kitchens, John D. Johnson, Jatinder N.D. Gupta
The core of the insurance business is the underwriting function. As a business process, underwriting has remained essentially unchanged since the... Sample PDF
Predicting Automobile Insurance Losses Using Artificial Neural Networks
Chapter 12
Jing Tao Yao, Chew Lim Tan
This chapter describes the application of neural networks in foreign exchange rate forecasting between American dollar and five other major... Sample PDF
Neural Networks for Technical Forecasting of Foreign Exchange Rates
Chapter 13
Mary E. Malliaris, Linda Salchenberger
The use of neural networks represents a new approach to how this type of problem can be investigated. The economics and finance literature is full... Sample PDF
Using Neural Networks to Discover Patterns in International Equity Markets: A Case Study
Chapter 14
Paul Lajbcygier
The pricing of options on futures is compared using conventional models and artificial neural networks. This work demonstrates superior pricing... Sample PDF
Comparing Conventional and Artificial Neural Network Models for the Pricing of Options
Chapter 15
Kate A. Smith, Larisa Lokmic
This chapter examines the use of neural networks as both a technique for pre-processing data and forecasting cash flow in the daily operations of a... Sample PDF
Combining Supervised and Unsupervised Neural Networks for Improved Cash Flow Forecasting
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