Neural Networks in Business: Techniques and Applications

Neural Networks in Business: Techniques and Applications

Jatinder N. D. Gupta, Kate A. Smith

Copyright: © 2002 |Pages: 272

ISBN13: 9781930708310|ISBN10: 1930708319|EISBN13: 9781591400202|ISBN13 Softcover: 9781931777797

DOI: 10.4018/978-1-93070-831-0

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MLA

Gupta, Jatinder N. D., and Kate A. Smith, editors. Neural Networks in Business: Techniques and Applications. IGI Global, 2002. https://doi.org/10.4018/978-1-93070-831-0

APA

Gupta, J. N. & Smith, K. A. (Eds.). (2002). Neural Networks in Business: Techniques and Applications. IGI Global. https://doi.org/10.4018/978-1-93070-831-0

Chicago

Gupta, Jatinder N. D., and Kate A. Smith, eds. Neural Networks in Business: Techniques and Applications. Hershey, PA: IGI Global, 2002. https://doi.org/10.4018/978-1-93070-831-0

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Neural Networks in Business: Techniques and Applications aims to be an introductory reference book for professionals, students and academics interested in applying neural networks to a variety of business applications. The book introduces the three most common neural network models and how they work, followed by a wide range of business applications and a series of case studies presented from contributing authors around the world. Each chapter serves as a tutorial describing how to use the previously described neural network models to solve a given business problem.

Table of Contents

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Front Materials

Title Page

Copyright Page

Preface

Chapters

Introduction

Chapter 1

Neural Networks for Business: An Introduction (pages 1-24)

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 an intelligent data-driven approach is no longer simply an interesting challenge for...

Applications to Retail Sales and Marketing

Chapter 2

Predicting Consumer Retail Sales Using Neural Networks (pages 26-40)

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 operations of retail businesses as well as retail supply chains. This chapter...

Chapter 3

Using Neural Networks to Model Premium Price Sensitivity of Automobile Insurance Customer (pages 41-54)

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 policy holders into homogeneous risk groups. Within each cluster a neural network is...

Chapter 4

A Neural Network Application to Identify High-Value Customers for a Large Retail Store in Japan (pages 55-69)

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 information to establish a close relationship with this select group of customers, thus...

Chapter 5

Segmentation of the Portuguese Clients of Pousadas de Portugal (pages 70-88)

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. The data for this work was provided by a sample of more than 2500 clients that...

Chapter 6

Neural Networks for Target Selection in Direct Marketing (pages 89-111)

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 direct marketing. Target selection for a charity organization is also explained. The...

Applications to Risk Assessment

Chapter 7

Prediction of Survival and Attrition of Click-and-Mortar Corporations (pages 112-123)

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 to the Web. Whether shopping for merchandise or simply searching for information, the...

Chapter 8

Corporate Strategy and Wealth Creation: An Application of Neural Network Analysis (pages 124-139)

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 have a direct influence on firm performance. Although societal and economic trends...

Chapter 9

Credit Rating Classification Using Self-Organizing Maps (pages 140-153)

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 investor’s point of view giving much attention to the insights provided by the unique...

Chapter 10

Credit Scoring Using Supervised and Unsupervised Neural Networks (pages 154-166)

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 the problem domain; (b) How can I discover unknown imperfections in the data which...

Chapter 11

Predicting Automobile Insurance Losses Using Artificial Neural Networks (pages 167-187)

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 early 1600’s in London, England. Ship owners, seeking to protect themselves from...

Applications to Financial Markets

Chapter 12

Neural Networks for Technical Forecasting of Foreign Exchange Rates (pages 189-204)

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 currencies: Japanese yen, Deutsch mark, British pound, Swiss franc and Australian dollar....

Chapter 13

Using Neural Networks to Discover Patterns in International Equity Markets: A Case Study (pages 205-219)

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 of studies that require the researcher to prespecify the exact nature of the...

Chapter 14

Comparing Conventional and Artificial Neural Network Models for the Pricing of Options (pages 220-235)

Paul Lajbcygier

The pricing of options on futures is compared using conventional models and artificial neural networks. This work demonstrates superior pricing accuracy using the artificial neural networks in an important subset of the input...

Chapter 15

Combining Supervised and Unsupervised Neural Networks for Improved Cash Flow Forecasting (pages 236-244)

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 financial services company. The problem is to forecast the date when issued cheques...

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