In addition, some parts, especially Challenge 2, do not have one correct solution. This means that I will expect variety in the answers; if two answers are identical this would sug

Sterman

I 1

ISBN : 007238915X TITLE: BUSINESS DYNAMICS : SYSTEMS THINKING I 1

t

RIAL : 291000 CLASS: BUSINESS EXHIB :

Business Dynamics Systems Thinking and

Modeling for a Complex World

John D. Sterman Massachusetts Institute of Technology

Sloan School of Management

Boston Burr Ridge, IL Dubuque, IA Madison, WI New York San Francisco St. Louis Bangkok Bogota Caracas Lisbon London Madrid

Mexico City Milan New Delhi Seoul Singapore Sydney Taipei Toronto

McGraw-Hill Higher Education A Division of f i e McGraw-Hill Companies

BUSINESS DYNAMICS SYSTEMS THINKING AND MOOELING FOR A COMPLEX WORLD

Copyright 0 2000 by The McGraw-Hill Companies, Inc. AU rights reserved. Printcd in the United ' States of America. Except as permitted under the United States Copyright Act of 1976, no part of this publication may be reproduced or dismbuted in any form or by m y means, or stored in a database or retrieval system, without the prior written permission of the publisher.

This book is printed on acid-free paper. .h 4 5 6 7 8 9 0 KGPiKGP 0 9 8 7 6 5 4 3 2

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Library of Congress Cataloging-in-Publication Data

Sterman, John. Business dynamics : systems thinking and modeling for a complex world I John D. Sterman.

Includes hibliographical references and index. ISBN 0-07-231135-5 (alk. paper) 1. Indusmal management. 2. System theory. 3. Management information systems. I.

p. cm.

Title.

HD30.2.S7835 2000 658.4'038'011Ldc21

99-056030

http://www.mhhe.com

For Cindy

ABOUT THE AUTHOR John D. Sterman is J. Spencer Standish Professor of Management at the Sloan School of Management of the Massachusetts Institute of Technology and Director of MIT’s System Dynamics Group. His research centers on the development of practical methods for systems thinking and dynamic modeling of complex sys- tems, with applications to organizational learning and change, operations manage- ment, corporate strategy, and nonlinear dynamics in a wide range of systems, from supply chains to scientific revolutions. He has pioneered the development of man- agement flight simulators of corporate and economic systems. These flight simu- lators are used in research to understand and improve managerial decision making in complex dynamic systems; more importantly, they are now widely used by cor- porations and universities around the world for teaching, problem solving, and pol- icy design. Professor Sterman discovered system dynamics modeling in high school, studied it as an undergraduate at Dartmouth College, and received his PhD from MIT. He has been awarded the Jay W. Forrester Prize, given for the best pub- lished work in the field of system dynamics over the prior five years, and has four times won awards for teaching excellence from the students of the Sloan School.

vi

Preface

Accelerating economic, technological, social, and environmental change challenge managers and policy makers to learn at increasing rates, while at the same time the complexity of the systems in which we live is growing. Many of the problems we now face arise as unanticipated side effects of our own past actions. All too often the policies we implement to solve important problems fail, make the problem worse, or create new problems.

Effective decision making and learning in a world of growing dynamic com- plexity requires us to become systems thinkers-to expand the boundaries of our mental models and develop tools to understand how the structure of complex sys- tems creates their behavior.

This book introduces you to system dynamics modeling for the analysis of pol- icy and strategy, with a focus on business and public policy applications. System dynamics is a perspective and set of conceptual tools that enable us to understand the structure and dynamics of complex systems. System dynamics is also a rigor- ous modeling method that enables us to build formal computer simulations of com- plex systems and use them to design more effective policies and organizations. Together, these tools allow us to create management flight simulators-micro- worlds where space and time can be compressed and slowed so we can experience the long-term side effects of decisions, speed learning, develop our understanding of complex systems, and design structures and strategies for greater success.

The field of system dynamics is thriving. Over the past decade, many top com- panies, consulting firms, and governmental organizations have used system dy- namics to address critical issues. More innovative universities and business schools are teaching system dynamics and finding enthusiastic and growing en- rollments. Hundreds of primary and secondary schools, from kindergarten to high school, are integrating systems thinking, system dynamics, and computer simula- tion into their curricula. Tools and methods for system dynamics modeling, the li- brary of successful applications, and insights into the effective use of the tools with executives and organizations are all expanding rapidly.

vii

viii Preface

FEATURES AND CONTENT University and graduate-level texts, particularly those focused on business and public policy applications, have not kept pace with the growth of the field. This book is designed to provide thorough coverage of the field of system dynamics to- day, by examining

Systems thinking and the system dynamics worldview; Tools for systems thinking, including methods to elicit and map the structure of complex systems and relate those structures to their dynamics; Tools for modeling and simulation of complex systems; Procedures for testing and improving models; Guidelines for working with client teams and successful implementation.

You will learn about the dynamics of complex systems, including the structures that create growth, goal-seeking behavior, oscillation and instability, S-shaped growth, overshoot and collapse, path dependence, and other nonlinear dynamics. Examples and applications include

Corporate growth and stagnation, The diffusion of new technologies, The dynamics of infectious disease such as HIV/AIDS, Business cycles, Speculative bubbles, The use and reliability of forecasts, The design of supply chains in business and other organizations, Service quality management, Transportation policy and traffic congestion, Project management and product development,

and many others. The goal of systems thinking and system dynamics modeling is to improve our

understanding of the ways in which an organization’s performance is related to its internal structure and operating policies, including those of customers, competi- tors, and suppliers and then to use that understanding to design high leverage poli- cies for success. To do so this book utilizes

Process Points that provide practical advice for the successful application of the tools in real organizations. Case studies of System Dynamics in Action that present successful applications ranging from global warming and the war on drugs to reengineering the supply chain of a major computer firm, marketing strategy in the automobile industry, and process improvement in the petrochemicals industry.

System dynamics is not a spectator sport. Developing systems thinking and mod- eling skills requires the active participation of you, the reader, via

Preface ix

Challenges. The challenges, placed throughout the text, give you practice with the tools and techniques presented in the book and will stimulate your original thinking about important real world issues. The challenges range from simple thought experiments to full-scale modeling projects. Simulation software and models. The accompanying CD-ROM and web site (http://www.mhhe.com/sterman) include all the models developed in the text along with state-of-the-art simulation software to run them. There are several excellent software packages designed to support system dynamics modeling. These include ithink, Powersim, and Vensim. The CD and website include the models for the text in all three software formats. The disk also includes fully functional versions of the ithink, Powersim, and Vensim software so you can run the models using any of these packages without having to purchase any additional software. Additionally, the Instructor’s Manual and instructor’s section of the web site include suggested solutions for the challenges, additional assignments, Powerpoint files with the diagrams and figures from the text suitable for transparencies, suggested course sequences and syllabi, and other materials.

INTENDED AUDIENCE The book can be used as a text in courses on systems thinking, simulation model- ing, complexity, strategic thinking, operations, and industrial engineering, among others. It can be used in full or half-semester courses, executive education, and self-study. The book also serves as a reference for managers, engineers, consul- tants, and others interested in developing their systems thinking skills or using sys- tem dynamics in their organizations.

A NOTE ON MATHEMATICS System dynamics is grounded in control theory and the modern theory of nonlin- ear dynamics. There is an elegant and rigorous mathematical foundation for the theory and models we develop. System dynamics is also designed to be a practical tool that policy makers can use to help them solve the pressing problems they con- front in their organizations. Most managers have not studied nonlinear differential equations or even calculus, or have forgotten it if they did. To be useful, system dy- namics modeling must be accessible to the widest range of students and practicing managers without becoming a vague set of qualitative tools and unreliable gener- alizations. That tension is compounded by the diversity of backgrounds within the community of managers, students, and scholars interested in system dynamics, backgrounds ranging from people with no mathematics education beyond high school to those with doctorates in physics.

X Preface

IF YOU DON’T HAVE A STRONG MATHEMATICS BACKGROUND, FEAR NOT

This book presents system dynamics with a minimum of mathematical formalism. The goal is to develop your intuition and conceptual understanding, without sacri- ficing the rigor of the scientific method. You do not need calculus or differential equations to understand the material. Indeed, the concepts are presented using only text, graphs, and basic algebra. Mathematical details and references to more ad- vanced material are set aside in separate sections and footnotes. Higher mathemat- ics, though useful, is not as important as the critical thinking skills developed here.

IF YOU HAVE A STRONG MATHEMATICS BACKGROUND, FEAR NOT Realistic and useful models are almost always of such complexity and nonlinearity that there are no known analytic solutions, and many of the mathematical tools you have studied have limited applicability. This book will help you use your strong technical background to develop your intuition and conceptual understanding of complexity and dynamics. Modeling human behavior differs from modeling phy s- ical systems in engineering and the sciences. We cannot put managers up on the lab bench and run experiments to determine their transfer function or frequency re- sponse. We believe all electrons follow the same laws of physics, but we cannot assume all people behave in the same way. Besides a solid grounding in the mathe- matics of dynamic systems, modeling human systems requires us to develop our knowledge of psychology, decision malung, and organizational behavior. Finally, mathematical analysis, while necessary, is far from sufficient for successful sys- tems thinlung and modeling. For your work to have impact in the real world you must learn how to develop and implement models of human behavior in organiza- tions, with all their ambiguity, time pressure, personalities, and politics. Through- out the book I have sought to illustrate how the technical tools and mathematical concepts you may have studied in the sciences or engineering can be applied to the messy world of the policy maker.

~

FEEDBACK I welcome your comments, criticisms, and suggestions. Suggestions for additional examples, cases, theory, models, flight simulators, and so on, to make the book more relevant and useful to you are especially invited. I will update the website to incorporate user feedback and new materials. Email comments to <[email protected] mit .edu > .

ACKNOWLEDGMENTS This work benefited immensely from the advice, criticism, and encouragement of many colleagues, students, and friends. I owe an immeasurable debt to my first system dynamics teachers, Dana Meadows, Dennis Meadows, and Jay Forrester, for their integrity, high standards, and passionate commitment. I’m particularly indebted to the exceptional students of the MIT Sloan School of Management. They constantly challenge me to make the discipline of system dynamics relevant,

Preface xi

useful, and exciting; I hope they’ve learned as much from me as I’ve learned from them. In addition, I thank my colleagues at the Sloan School and in the system dynamics community around the world, who helped by providing data and exam- ples, reviewing the draft, testing early versions in their courses, and in countless other ways. This group includes (but is not limited to) the following folks and institutions:

Tarek Abdel-Hamid (Naval Postgraduate School); David Andersen, George Richardson (SUNY Albany); Ed Anderson (Univ. of Texas); Carlos Ariza, Sharon Els, Ken Cooper, Jim Lyneis, Hank Taylor (Pugh-Roberts Associates); George Backus (Policy Assessment Corporation); Bent Bakken (Norwegian Defense Re- search Establishment); Yaman Barlas (Bogazici University, Istanbul); Michael Bean (Powersim Corp.); Eric Beinhocker, Damon Beyer, Andrew Doman, Usman Ghani, Maurice Glucksman, Paul Langley, Norman Marshall (McKinsey and Company); Laura Black, John Carroll, Vanessa Colella, Ernst Diehl, Steve Ep- pinger, Charlie Fine, Mila Getmansky, Paulo Goncalves, Janet Gould Wilkinson, Jim Hines, Nan Lux, Brad Morrison, Tim Nugent, Nelson Repenning, Ed Roberts, Scott Rockart, George Roth, Ed Schein, Peter Senge (MIT); Allen and Jane Boorstein; Steve Cavaleri (Central Connecticut State Univ.); Geoff Coyle (Royal Military College of Science, UK, retired); Brian Dangerfield (Univ. of Salford); Pi1 Davidsen (Univ. of Bergen); Jim Doyle, Mike Radzicki, Khalid Saeed (Worcester Polytechnic Institute); Bob Eberlein, Tom Fiddaman, Dan Goldner, David Peterson, Laura Peterson (Ventana Systems); David Foley and Judy Berk; Andy Ford (Washington State Univ.); David Ford (Texas A&M University); Nathan Forrester (A. T. Kearney); Rich Goldbach (Metro Machine Corp.); Chris- tian Haxholdt, Heather Hazard (Copenhagen Business School); Jack Homer (Homer Consulting); Jody House (Oregon Graduate Institute); Bill Isaacs (Dia- logos); Sam Israelit (Arthur Andersen); Nitin Joglekar (Boston Univ. School of Management); Drew Jones (Sustainability Institute); Christian Kampmann, Erik Mosekilde (Technical Univ. of Denmark); Daniel Kim, Virginia Wiley (Pegasus Communications); Craig Kirkwood (Arizona State Univ.); Elizabeth Krahmer Keating (Northwestern Univ.); Don Kleinmuntz (Univ. of Illinois, Urbana-Champaign); David Kreutzer (GKA, Inc.); Robert Landel (Darden School of Business, Univ. of Virginia); David Lane (London School of Economics); Erik Larsen (City University, London); Winston J. Ledet, Winston P. Ledet (The Man- ufacturing Game, Inc.); Ralph Levine (Michigan State Univ.); Angela Lipinski (Society for Organizational Learning); Martin GroBmann, Frank Maier, Peter Milling (Univ. of Mannheim, Germany); Ali Mashayekhi (Sharif Univ. of Tech- nology, Teheran); Nathaniel Mass (GenCorp); Paul Monus (BP/Amoco), John Morecroft, Ann van Ackere, Kim Warren (London Business School); Erling Moxnes (Norwegian School of Economics and Business Administration); Rogelio Oliva (Harvard Business School); Mark Paich (Colorado College); Steve Peterson, Barry Richmond (High Performance Systems); Greg Petsch (Compaq Computer); Nick Pudar (General Motors); Jack Pugh, Julia Pugh, Roberta Spencer (System Dynamics Society), JQrgen Randers (World Wildlife Fund International); Nancy Roberts (Leslie College); Jenny Rudolph (Boston College); Jorge Rufat-Latre (Strategos); Anjali Sastry, Marshall van Alstyne (University of Michigan); Bob Stearns; Susan Sterman; Jim Thompson (Global Prospectus, LLC); John Voyer

xii Preface

(Univ. of Southern Maine); Lyle Wallis (Decisio, Inc.); Jim Waters (Waters Busi- ness Systems); Jason Wittenberg (Harvard Univ.); Eric Wolstenholme (Leeds Busi- ness School, UK); Pave1 Zamudio Ramirez (Monitor Company); the Copenhagen Business School, The International Network of Resource Information Centers (aka the Balaton Group), McKinsey and Company, the Norwegian School of Management, Pugh-Roberts Associates, the Society for Organizational Learning, the Technical University of Denmark, and, of course, the MIT Sloan School of Management.

Special thanks to High Performance Systems, Powersim, SA, and Ventana Systems-and their great people-for providing their simulation software and translations of the models for the CD and website.

The team at IrwidMcGraw-Hill deserves special mention for their enthusiasm, patience, and editorial help, particularly Scott Isenberg, Carol Rose, Jeff Shelstad, and Gladys True.

Cara Barber and Kelley Donovan provided important secretarial support. Kathy Sullivan went beyond the call of duty on library research, data collec-

Finally, the love and support of my family have been constant and essential. tion, editorial changes, and graphics.

Thanks, Cindy, David, and Sarah.

Table of Contents

Preface vii

PART I PERSPECTIVE AND PROCESS 1 1 Learning in and about Complex Systems 3

1.1 Introduction 3 1.1.1

1.1.2 Causes of Policy Resistance 10 1.1.3 Feedback 12 1.1.4 Process Point: The Meaning of Feedback 14 Challenge: Dynamics of Multiple-Loop Systems

Policy Resistance, the Law of Unintended Consequences, and the Counterintuitive Behavior of Social Systems 5

14 1.2 Learning Is a Feedback Process 14 1.3 Barriers to Learning 19

1.3.1 Dynamic Complexity 21 1.3.2 Limited Information 23 1.3.3 Confounding Variables and Ambiguity 25 1.3.4 Bounded Rationality and the Misperceptions

of Feedback 26 1.3.5 Flawed Cognitive Maps 28 1.3.6 Erroneous Inferences about Dynamics 29 1.3.7 Unscientific Reasoning: Judgmental Errors

andBiases 30 Challenge: Hypothesis Testing 30 1.3.8 Defensive Routines and Interpersonal Impediments

to Learning 32 1.3.9 Implementation Failure 33

1.4.1 Improving the Learning Process: Virtues of Virtual Worlds 34

1.4.2 Pitfalls of Virtual Worlds 35 1.4.3 Why Simulation Is Essential 37

1.4 Requirements for Successful Learning in Complex Systems 33

1.5 Summary 39

xiii

xiv Contents

2 System Dynamics in Action 41 2.1 2.2

2.3

2.4

2.5

Applications of System Dynamics 41 Automobile Leasing Strategy: Gone Today, Here Tomorrow 2.2.1 Dynamic Hypothesis 44 2.2.2 Elaborating the Model 48 2.2.3 Policy Analysis 5 1 2.2.4 Impact and Follow-up 54 On Time and Under Budget: The Dynamics of Project Management 55 2.3.1 The Claim 56 2.3.2 Initial Model Development 57 2.3.3 Dynamic Hypothesis 58 2.3.4 The Modeling Process 61 2.3.5 Continuing Impact 64 Playing the Maintenance Game 66 2.4.1 Dynamic Hypothesis 67 2.4.2 The Implementation Challenge 74 2.4.3 Results 76 2.4.4 Transferring the Learning: The Lima Experience 77

42

Summary: Principles for Successful Use of System Dynamics 79

3.1 The Purpose of Modeling: Managers as Organization Designers 84 3.2 The Client and the Modeler 84 3.3 Steps of the Modeling Process 85 3.4 Modeling Is Iterative 87 3.5 Overview of the Modeling Process 89

3 The Modeling Process 83

3.5.1 Problem Articulation: The Importance of Purpose 89 3.5.2 Formulating a Dynamic Hypothesis 94 3.5.3 Formulating a Simulation Model 102 3.5.4 Testing 103 3.5.5 Policy Design and Evaluation 103

4 Structure and Behavior of Dynamic Systems 107 3.6 Summary 104

4.1

4.2

4.3

Fundamental Modes of Dynamic Behavior 4.1.1 Exponential Growth 108 4.1.2 Goal Seeking 11 1 4.1.3 Oscillation 114 4.1.4 Process Point 116 Challenge: Identifying Feedback Structure from System Behavior 117 Interactions of the Fundamental Modes 4.2.1 S-Shaped Growth 118 4.2.2 S-Shaped Growth with Overshoot 121 Challenge: Identifying the Limits to Growth 4.2.3 Overshoot and Collapse 123 Other Modes of Behavior 127 4.3.1 Stasis, or Equilibrium 127

108

11 8

121

Contents xv

4.3.2 Randomness 127 4.3.3 Chaos 129

4.4 Summary 133

PART I1 TOOLS FOR SYSTEMS THINKING 135 5 Causal Loop Diagrams 137

5.1 5.2

5.3

5.4

5.5

5.6

Causal Diagram Notation 137 Guidelines for Causal Loop Diagrams 5.2.1 Causation versus Correlation 141 5.2.2 Labeling Link Polarity 142 Challenge: Assigning Link Polarities 143 5.2.3 Determining Loop Polarity 143 Challenge: Identifying Link and Loop Polarity Challenge: Employee Motivation 147 5.2.4 Name YourLoops 148 5.2.5 Indicate Important Delays in Causal Links 150 5.2.6 Variable Names 152 5.2.7 Tips for Causal Loop Diagram Layout 153 5.2.8 Choose the Right Level ofAggregation 154 5.2.9 Don’t Put All the Loops into One Large Diagram 5.2.10 Make the Goals of Negative Loops Explicit 155 5.2.11 Distinguish between Actual

Process Point: Developing Causal Diagrams from Interview Data 157 Challenge: Process Improvement 158 Conceptualization Case Study: Managing Your Workload 5.4.1 Problem Definition 159 5.4.2 IdentiJLing Key Variables 160 5.4.3 Developing the Reference Mode 160 5.4.4 Developing the Causal Diagrams 163 5.4.5 Limitations of the Causal Diagram 166 Challenge: Policy Analysis with Causal Diagrams Adam Smith’s Invisible Hand and the Feedback Structure of Markets 169 Challenge: The Oil Crises of the 1970s 172 Challenge: Speculative Bubbles 173 Challenge: The Thoroughbred Horse Market 5.5.1 Market Failure, Adverse Selection,

Challenge: The Medigap Death Spiral 176 Explaining Policy Resistance: Traffic Congestion 5.6.1 Mental Models of the Traffic Problem 178 5.6.2 Compensating Feedback: The Response

to Decreased Congestion 18 1 5.6.3 The Mass Transit Death Spiral 185 5.6.4 Policy Analysis: The Impact of Technology 188 5.6.5 Compensating Feedback: The Source

of Policy Resistance 189

141

145

154

and Perceived Conditions 156

159

168

174

and the Death Spiral 174

177

xvi Contents

Challenge: Identifying the Feedback Structure of Policy Resistance 190

5.7 Summary 190

6.1 Stocks, Flows, and Accumulation 191 6 Stocks and Flows 191

6.1.1 Diagramming Notation for Stocks and Flows 192 6.1.2 Mathematical Representation of Stocks and Flows 193 6.1.3 The Contribution of Stocks to Dynamics 195

6.2.1 Units of Measure in Stock and Flow Networks 198 6.2.2 The Snapshot Test 199 Challenge: Identifying Stocks and Flows 201 6.2.3 Conservation of Material in

Stock and Flow Networks 201 6.2.4 State-Determined Systems 202 6.2.5 Auxiliary Variables 202 6.2.6 Stocks Change Only through Their Rates 204 6.2.7 Continuous Time and Instantaneous Flows 206 6.2.8 Continuously Divisible versus Quantized Flows 207 6.2.9 Which Modeling Approach Should You Use? 208 6.2.10 Process Point: Portraying Stocks and Flows

in Practice 209

When Should Causal Loop Diagrams Show Stock and Flow Structure? 210

6.2 Identifying Stocks and Flows 197

6.3 Mapping Stocks and Flows 210 6.3.1

Challenge: Adding Stock and Flow Structure to Causal Diagrams 2 11 Challenge: Linking Stock and Flow Structure with Feedback 6.3.2 Aggregation in Stock and Flow Mapping 213 Challenge: Modifying Stock and Flow Maps Challenge: Disaggregation 214 6.3.3 Guidelines for Aggregation 216 6.3.4 System Dynamics in Action:

6.3.5 Setting the Model Boundary:

6.3.6 System Dynamics in Action: Automobile Recycling 225

212

213

Modeling Large-Scale Construction Projects

“Challenging the Clouds’’ 222

2 18

6.4 Summary 229

7.1 Relationship between Stocks and Flows 232 7 Dynamics of Stocks and Flows 231

7.1.1 Static and Dynamic Equilibrium 232 7.1.2 Calculus without Mathematics 232 7.1.3 Graphical Integration 234 Challenge: Graphical Integration 239 7.1.4 Graphical Diflerentiation 239 Challenge: Graphical Differentiation 24 1

7.2 System Dynamics in Action: Global Warming 241

Contents xvii

7.3 System Dynamics in Action: The War on Drugs 250

7.4 Summary 262

Dynamics of Simple Structures 263

7.3.1 The Cocaine Epidemic after 1990 258

8 Closing the Loop:

8.1 8.2

8.3

8.4 8.5

8.6

First-Order Systems 263 Positive Feedback and Exponential Growth 8.2.1 Analytic Solution for the Linear First-Order System 265 8.2.2 Graphical Solution of the Linear First-Order

Positive Feedback System 266 8.2.3 The Power of Positive Feedback: Doubling Times 268 Challenge: Paper Folding 268 8.2.4 Misperceptions of Exponential Growth 269 8.2.5 Process Point: Overcoming Overconfidence 272 Negative Feedback and Exponential Decay 8.3.1 Time Constants and Half-Lives 279 Challenge: Goal-Seeking Behavior 281 Multiple-Loop Systems 282 Nonlinear First-Order Systems: S-Shaped Growth Challenge: Nonlinear Birth and Death Rates 8.5.1 Formal Definition of Loop Dominance 288 8.5.2 First-Order Systems Cannot Oscillate 290 Summary 290

264

274

285 286

PART I11 THE DYNAMICS OF GROWTH 293 9 S-Shaped Growth: Epidemics, Innovation Diffusion, and the Growth of

New Products 295 9.1 Modeling S-Shaped Growth 296

9.1.1 Logistic Growth 296 9.1.2 Analytic Solution of the Logistic Equation 297 9.1.3 Other Common Growth Models 299 9.1.4 Testing the Logistic Model 300

9.2 Dynamics of Disease: Modeling Epidemics 300 9.2.1 A Simple Model of Infectious Disease 300 9.2.2 Modeling Acute Infection: The SIR Model 303 9.2.3 Model Behavior: The Tipping Point 305 Challenge: Exploring the SIR Model 9.2.4 Immunization and the Eradication of Smallpox 309 Challenge: The Efficacy of Immunization Programs 9.2.5 Herd Immunity 3 12 9.2.6 Moving Past the Tipping Point: Mad Cow Disease 314 Challenge: Extending the SIR Model 9.2.7 Modeling the HIV/AIDS Epidemic 319 Challenge: Modeling HIV/AIDS 321

Modeling New Ideas and New Products 9.3.1

308

3 SO

3 16

9.3 Innovation Diffusion as Infection: 323

The Logistic Model of Innovation DiJj’usion: Examples 325

xviii Contents

9.3.2 Process Point: Historical Fit and Model Validity 328 9.3.3 The Bass Dijfusion Model 332 Challenge: Phase Space of the Bass Diffusion Model 333 9.3.4 Behavior of the Bass Model 334 Challenge: Critiquing the Bass Diffusion Model 334 Challenge: Extending the Bass Model 335 9.3.5 Fad and Fashion:

Challenge: Modeling Fads 341 9.3.6 Replacement Purchases 342 Challenge: Modeling the Life Cycle of Durable Products

Modeling the Abandonment of an Innovation 339

345 9.4 Summary 346

10.1 Path Dependence 349 Challenge: Identifying Path Dep

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