Neural Networks in Organizational Research

Unicru, Inc., Beaverton, OR. Provides intellectual rationale for use of neural procedures. Topics include when neural networks should be used, modern theories of neural processes, neural networks as a theory development tool, using neural networks in employee selection, overview of methodology, and more. For researchers and practitioners.

Foreword

ix

G. David Garson

Acknowledgments

xi

Introduction

3

(6)

I. Orientation

9

(78)

Neural Networks in Organizational Research

11

(8)

Why Use Neural Networks for Organizational Research?

13

(1)

When Should Neural Networks Be Used?

14

(5)

Science, Organizational Research, and Neural Networks

19

(10)

Scientific Method and Empiricism

19

(1)

The Role of Mathematics

20

(1)

Behavioral Science

21

(3)

Behavioral Research in Organizations

24

(2)

Information Technology, Social Science, and Artificial Intelligence

26

(3)

Neural Network Theory, History, and Concepts

29

(16)

Early Theories

29

(1)

Modern Theories of Neural Processes

30

(7)

Innovation Drives Renewed Interest

37

(1)

Backpropagation Neural Networks

38

(2)

A Taxonomy of Modern Artificial Neural Networks

40

(2)

Supervised Feed-Forward Neural Networks Described in This Book

42

(3)

Neural Networks as a Theory Development Tool

45

(16)

Linearity, Neural Networks, and Organizational Research

46

(1)

A Case for Nonlinearity in Organizational Research

47

(1)

Neural Networks as a Theory Development Tool

48

(4)

Using Artificial Neural Networks as an Exploratory Technique to Model the Job Satisfaction--Job Performance Relationship

52

(4)

Neural Networks and Complexity Theory

56

(1)

Artificial Neural Networks as a Force for Change in Organizational Research

57

(1)

Neural Networks and Applied Research

58

(3)

Using Neural Networks in Organizational Research

61

(26)

Getting Started: Factors to Consider in Evaluating Neural Network Software

62

(5)

Getting Started: Choosing the Right Neural Network

67

(1)

Unsupervised Neural Networks: Using Self-Organizing Maps

68

(3)

Supervised Networks: Training Neural Networks for Prediction and Classification

71

(11)

Neural Networks and Multivariate Statistics in Organizational Research

82

(1)

Interpreting Neural Network Behavior Using Graphics

82

(5)

II. Applications

87

(48)

Statistics, Neural Networks, and Behavioral Research

89

(12)

Neural Networks and Statistics

90

(4)

Neural Networks and Behavioral Prediction in Organizations

94

(7)

Using Neural Networks in Employee Selection

101

(22)

Scientific Employee Selection

102

(1)

Statistical Models of Criterion Validity

103

(1)

Neural Networks and Criterion Validation

104

(1)

Neural Validation Modeling

105

(1)

Why Use Neural Networks for Employee Selection?

105

(5)

Employee Selection Neural Networks

110

(13)

Using Self-Organizing Maps to Study Organizational Commitment

123

(12)

Uncovering Patterns of Commitment With a Self-Organizing Map

124

(2)

Clustering Techniques for Deriving Commitment Profiles

126

(1)

The Study: Rationale and Variables

127

(1)

Overview of Methodology

128

(1)

Data Analysis: k-Means Clustering and Self-Organizing Maps

129

(1)

Findings: k-Means Versus Self-Organizing Map

129

(1)

Implications

130

(5)

III. Implications

135

(24)

Limitations and Myths

137

(8)

Limitations of Neural Networks

137

(4)

Myths

141

(4)

Trends and Future Directions

145

(14)

Neural Networks and Behavioral Research in Organizations

146

(7)

Opportunities for New Research

153

(2)

Neural Network Applications

155

(4)

Appendix: Backpropagation Algorithm

159

(2)

Glossary

161

(4)

References

165

(12)

Index

177

(10)

About the Authors

187

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Neural Networks in Organizational Research

Summary

Table of Contents

Supplemental Materials