Modeling and Visualization of Complex Systems and Enterprises: Explorations of Physical, Human, Economic, and Social Phenomena

ISBN-13: 9781118954133 / Angielski / Twarda / 2015 / 296 str.

Ed. William B. Rouse

Opis

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.

This book explains multi–level models of enterprise systems and covers modeling methodology.

Recenzje

"The book 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." (Zentralblatt MATH 2016)

The book is written for graduate students studying systems science and engineering and pro–

fessionals involved in systems science and engineering, those involved in complex systems such

as healthcare delivery, urban systems, sustainable energy, nancial systems, and national se–

curity.

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

William B. Rouse, PhD., is the Alexander Crombie Humphreys Chair of Economics in Engineering at Stevens Institute of Technology, and Director of the university wide Center for Complex Systems and Enterprises. He is also Professor Emeritus of Industrial and Systems Engineering at the Georgia Institute of Technology. He is a member of the National Academy of Engineering.

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.

William B. Rouse, PhD., is the Alexander Crombie Humphreys Chair of Economics in Engineering at Stevens Institute of Technology, and Director of the university wide Center for Complex Systems and Enterprises. He is also Professor Emeritus of Industrial and Systems Engineering at the Georgia Institute of Technology. He is a member of the National Academy of Engineering.

Udostępnij

Spis treści

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

O autorze

William B. Rouse, PhD., is the Alexander Crombie Humphreys Chair of Economics in Engineering at Stevens Institute of Technology, and Director of the university wide Center for Complex Systems and Enterprises. He is also Professor Emeritus of Industrial and Systems Engineering at the Georgia Institute of Technology. He is a member of the National Academy of Engineering.

Blurb

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.

William B. Rouse, PhD., is the Alexander Crombie Humphreys Chair of Economics in Engineering at Stevens Institute of Technology, and Director of the university wide Center for Complex Systems and Enterprises. He is also Professor Emeritus of Industrial and Systems Engineering at the Georgia Institute of Technology. He is a member of the National Academy of Engineering.