Explains multi-level models of enterprise systems and covers modeling methodology
This book addresses the essential phenomena underlying the overall behaviors of complex systems and enterprises. Understanding these phenomena can enable improving these systems. These phenomena range from physical, behavioral, and organizational, to economic and social, all of which involve significant human components. Specific phenomena of interest and how they are represented depend on the questions of interest and the relevant domains or contexts. Modeling and Visualization of Complex Systems and Enterprises examines visualization of phenomena and how understanding the relationships among phenomena can provide the basis for understanding where deeper exploration is warranted. The author also reviews mathematical and computational models, defined very broadly across disciplines, which can enable deeper understanding.
- Presents a 10 step methodology for addressing questions associated with the design or operation of complex systems and enterprises
- Examines six archetypal enterprise problems including two from healthcare, two from urban systems, and one each from financial systems and defense systems
- Provides an introduction to the nature of complex systems, historical perspectives on complexity and complex adaptive systems, and the evolution of systems practice
Modeling and Visualization of Complex Systems and Enterprises is written for graduate students studying systems science and engineering and professionals involved in systems science and engineering, those involved in complex systems such as healthcare delivery, urban systems, sustainable energy, financial systems, and national security.
Table of Contents:
Preface xi
1 Introduction and Overview 1
Systems Perspectives 2
Systems Movement 3
Philosophical Background 3
Seminal Concepts – Systems Science 5
Seminal Concepts – Economics/Cognition 6
Seminal Concepts – Operations Research 7
Seminal Concepts – Sociology 8
Complexity and Complex Systems 8
Complex Versus Complicated Systems 11
Systems Practice 13
Phenomena as the Starting Point 19
Oveview of Book 20
Chapter 1: Introduction and Overview 20
Chapter 2: Overall Methodology 21
Chapter 3: Perspectives on Phenomena 21
Chapter 4: Physical Phenomena 21
Chapter 5: Human Phenomena 21
Chapter 6: Economic Phenomena 22
Chapter 7: Social Phenomena 22
Chapter 8: Visualization of Phenomena 22
Chapter 9: Computational Methods and Tools 23
Chapter 10: Perspectives on Problem Solving 23
References 23
2 Overall Methodology 27
Introduction 27
Problem Archetypes 29
Deterring or Identifying Counterfeit Parts 29
Financial Systems and Bursting Bubbles 30
Human Responses and Urban Resilience 30
Traffic Control via Congestion Pricing 31
Impacts of Investments in Healthcare Delivery 31
Human Biology and Cancer 31
Comparison of Problems 32
Methodology 33
Summary 35
An Example 36
Supporting the Methodology 40
Conclusions 41
References 41
3 Perspectives on Phenomena 43
Introduction 43
Definitions 43
Historical Perspectives 46
Steam to Steamboats 46
Wind to Wings 47
Electricity to Electric Lights 47
Macro and Micro Physics 47
Probability and Utility 48
Contemporary Perspectives 48
Four Fundamental Forces 48
Computational Fluid Dynamics 49
Integrated Circuit Design 49
Supply Chain Management 50
Summary 50
Taxonomy of Phenomena 50
Behavioral and Social Systems 52
Problems versus Phenomena 54
Visualizing Phenomena 54
Conclusions 58
References 59
4 Physical Phenomena 61
Introduction 61
Natural Phenomena 61
Example – Human Biology 64
Example – Urban Oceanography 67
Designed Phenomena 69
Example – Vehicle Powertrain 73
Example – Manufacturing Processes 75
Deterring or Identifying Counterfeit Parts 76
Conclusions 80
References 80
5 Human Phenomena 83
Descriptive Versus Prescriptive Approaches 84
Models of Human Behavior and Performance 86
Example – Manual Control 87
Example – Problem Solving 89
Example – Multitask Decision Making 90
Traffic Control Via Congestion Pricing 92
Mental Models 95
Team Mental Models 99
Performing Arts Teams 101
Fundamental Limits 104
Conclusions 107
References 107
6 Economic Phenomena 111
Introduction 111
Microeconomics 113
Theory of the Firm 113
Theory of the Market 114
Example – Optimal Pricing 114
Example – Investing in People 118
Summary 119
Macroeconomics 119
Tax Rates Interest Rates and Inflation 120
Macroeconomic Models 126
Summary 128
Behavioral Economics 128
Prospect Theory 131
Risk Perception 132
Attribution Errors 133
Management Decision Making 134
Human Intuition 135
Intuition versus Analysis 136
Summary 137
Economics of Healthcare Delivery 137
Conclusions 139
References 140
7 Social Phenomena 143
Introduction 143
Emergent versus Designed Organizational Phenomena 143
Direct versus Representative Political Phenomena 144
Modeling Complex Social Systems 145
Example – Earth as a System 145
Physics-Based Formulations 149
Example – Castes and Outcastes 151
Network Theory 158
Game Theory 162
Example – Acquisition as a Game 165
Simulation 168
Example – Port and Airport Evacuation 170
Example – Emergence of Cities 171
Urban Resilience 172
A Framework for Urban Resilience 173
Summary 176
Conclusions 176
References 176
8 Visualization of Phenomena 179
Introduction 179
Human Vision as a Phenomenon 180
Basics of Visualization 180
Example – Space Shuttle Challenger 181
Purposes of Visualizations 183
Examples – Co-Citation Networks and Mobile Devices 184
Design Methodology 185
Use Case Illustrations 186
Example – Big Graphics and Little Screens 190
Visualization Tools 193
Data 195
Structure 195
Dynamics 195
Immersion Lab 196
Policy Flight Simulators 198
Background 198
Multilevel Modeling 199
Example – Employee Prevention and Wellness 200
People’s Use of Simulators 203
Conclusions 205
References 206
9 Computational Methods and Tools 209
Introduction 209
Modeling Paradigms 210
Dynamic Systems Theory 212
Control Theory 214
Estimation Theory 216
Queuing Theory 217
Network Theory 218
Decision Theory 221
Problem-Solving Theory 224
Finance Theory 225
Summary 228
Levels of Modeling 228
Representation to Computation 230
Dynamic Systems 230
Discrete-Event Systems 231
Agent-Based Systems 231
Optimization-Based Frame 231
Summary 233
Model Composition 233
Entangled States 233
Consistency of Assumptions 235
Observations 236
Computational Tools 236
Conclusions 237
References 238
10 Perspectives on Problem Solving 241
Introduction 241
What is? Versus What if? 242
Case Studies 243
Business Planning 243
New Product Planning 245
Technology Investments 248
Enterprise Transformation 250
Observations on Problem Solving 253
Starting Assumptions 253
Framing Problems 253
Implementing Solutions 255
Research Issues 255
Decomposition 256
Mapping 256
Scaling 257
Approximation 257
Identification 257
Parameterization 258
Propagation 258
Visualization 259
Curation 259
Conclusions 259
References 261
Index 263
