Tools for Thinking: Modelling in Management Science

by Michael Pidd

Overview

The third edition of Tools for Thinking builds on the successes of the previous two editions. It creates a bridge between the soft and hard (Operations Research) OR schools of thought and provides an empirically based framework in which to place them. Focusing on modelling as an activity, rather than on models and techniques, Mike Pidd shows how models can be employed to explore possible future scenarios and to make sense of managerial vision.

This third edition has been fully revised and updated without changing its focus.  It features a new chapter on Decision Analysis and includes up-to-date examples using popular softwares, such as Precision Tree, @Risk and Micro Saint Sharp, to illustrate how these help in developing and using management science models as tools for thinking

Product Details

ISBN-13:	9780470721421
Publisher:	Wiley
Publication date:	12/21/2009
Edition description:	3rd ed.
Pages:	304
Product dimensions:	6.50(w) x 9.50(h) x 0.70(d)

About the Author

Mike Pidd is Professor of Management Science at Lancaster University. He has served as President of the Operational Research Society and as Chair of COPIOR (the Committee of Professors in OR). His research interests focus on the development of usable models in management science and computer simulation, most recently in healthcare, and he has published widely in academic journals and books.

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Table of Contents

Preface ix

Acknowledgements xi

Part I Modelling In Management Science 1

1 Models as convenient worlds 3

2 Management Science - making sense of strategic vision 21

3 Problems, problems … 43

4 Some principles of modelling 63

Part II Interpretive Modelling - Soft Management Science 83

5 Soft systems methodology 89

6 Cognitive mapping, SODA and journey-making 109

7 System dynamics 135

8 Decision analysis 157

Part III Mathematical and Logical Modelling 185

9 Optimization modelling - linear programming 187

10 Computer simulation - visual interactive modelling and Monte Carlo simulation 211

11 Heuristic search 241

Part IV Model Assessment and Validation 263

12 Model assessment and validation 265

Index 285