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      Social Systems Engineering

      The Design of Complexity

      AvCésar García-Díaz,Camilo Olaya

      Inbunden, Engelska, 2017

      Del i serien Wiley Series in Computational and Quantitative Social Science

      959 kr

      Beställningsvara. Skickas inom 11-20 vardagar. Fri frakt över 249 kr.

      Beskrivning

      Uniquely reflects an engineering view to social systems in a wide variety of contexts of applicationSocial Systems Engineering: The Design of Complexity brings together a wide variety of application approaches to social systems from an engineering viewpoint. The book defines a social system as any complex system formed by human beings. Focus is given to the importance of systems intervention design for specific and singular settings, the possibilities of engineering thinking and methods, the use of computational models in particular contexts, and the development of portfolios of solutions. Furthermore, this book considers both technical, human and social perspectives, which are crucial to solving complex problems.Social Systems Engineering: The Design of Complexity provides modelling examples to explore the design aspect of social systems. Various applications are explored in a variety of areas, such as urban systems, health care systems, socio-economic systems, and environmental systems. It covers important topics such as organizational design, modelling and intervention in socio-economic systems, participatory and/or community-based modelling, application of systems engineering tools to social problems, applications of computational behavioral modeling, computational modelling and management of complexity, and more.  Highlights an engineering view to social systems (as opposed to a “scientific” view) that stresses the importance of systems intervention design for specific and singular settingsDivulges works where the design, re-design, and transformation of social systems constitute the main aim, and where joint considerations of both technical and social perspectives are deemed important in solving social problemsFeatures an array of applied cases that illustrate the application of social systems engineering in different domainsSocial Systems Engineering: The Design of Complexity is an excellent text for academics and graduate students in engineering and social science—specifically, economists, political scientists, anthropologists, and management scientists with an interest in finding systematic ways to intervene and improve social systems.

      Produktinformation

      • Utgivningsdatum:2017-12-22
      • Mått:175 x 246 x 20 mm
      • Vikt:635 g
      • Format:Inbunden
      • Språk:Engelska
      • Serie:Wiley Series in Computational and Quantitative Social Science
      • Antal sidor:312
      • Förlag:John Wiley & Sons Inc
      • ISBN:9781118974452

      Utforska kategorier

      • Elektronik och kommunikationer inom Naturvetenskap och teknik
      • Matematik inom Naturvetenskap och teknik
      • Företagsekonomi inom Ekonomi och Ledarskap

      Mer om författaren

      César García-Díaz, PhD, is an Assistant Professor in the Department of Industrial Engineering, Universidad de los Andes, Bogotá, Colombia. César's expertise is in the field of agent-based social simulation. Camilo Olaya, PhD, is an Associate Professor in the Department of Industrial Engineering, Universidad de los Andes, Bogotá, Colombia. Camilo is a researcher in model-based engineering of private and public systems with more than 15 years of experience in this field.

      Innehållsförteckning

      • List of Contributors xiPreface xiiiIntroduction: The Why, What and How of Social Systems Engineering 1César García-Díaz and Camilo OlayaPart I SOCIAL SYSTEMS ENGINEERING: THE VERY IDEA 111 Compromised Exactness and the Rationality of Engineering 13Steven L. Goldman1.1 Introduction 131.2 The Historical Context 141.3 Science and Engineering: Distinctive Rationalities 201.4 ‘Compromised Exactness’: Design in Engineering 231.5 Engineering Social Systems? 26References 292 Uncertainty in the Design and Maintenance of Social Systems 31William M. Bulleit2.1 Introduction 312.2 Uncertainties in Simple and Complicated Engineered Systems 332.3 Control Volume and Uncertainty 352.4 Engineering Analysis and Uncertainty in Complex Systems 372.5 Uncertainty in Social Systems Engineering 392.6 Conclusions 42References 423 System Farming 45Bruce Edmonds3.1 Introduction 453.2 Uncertainty, Complexity and Emergence 463.2.1 The Double Complexity of CSS 483.3 Science and Engineering Approaches 493.3.1 The Impossibility of a Purely Design-Based Engineering Approach to CSS 513.3.2 Design vs. Adaptation 523.3.3 The Necessity of Strongly Validated Foundations for Design-Based Approaches 533.4 Responses to CSS Complexity 543.4.1 Formal Methods 543.4.2 Statistical Approaches 553.4.3 Self-adaptive and Adaptive Systems 573.4.4 Participatory Approaches and Rapid Prototyping 573.5 Towards Farming Systems 583.5.1 Reliability from Experience Rather Than Control of Construction 583.5.2 Post-Construction Care Rather Than Prior Effort 583.5.3 Continual Tinkering Rather Than One-Off Effort 593.5.4 Multiple Fallible Mechanisms Rather Than One Reliable Mechanism 593.5.5 Monitoring Rather Than Prediction 593.5.6 Disaster Aversion Rather Than Optimizing Performance 593.5.7 Partial Rather Than Full Understanding 593.5.8 Specific Rather Than Abstract Modelling 603.5.9 Many Models Rather Than One 603.5.10 A Community Rather Than Individual Effort 603.6 Conclusion 60References 614 Policy between Evolution and Engineering 65Martin F.G. Schaffernicht4.1 Introduction: Individual and Social System 654.2 Policy – Concept and Process 674.3 Human Actors: Perception, Policy and Action 704.4 Artefacts 734.5 Engineering and Evolution: From External to Internal Selection 764.6 Policy between Cultural Evolution and Engineering 794.7 Conclusions and Outlook 82Appendix: Brief Overview of the Policy Literature 83References 865 ‘Friend’ versus ‘Electronic Friend’ 91Joseph C. PittReferences 99Part II METHODOLOGIES AND TOOLS 1016 Interactive Visualizations for Supporting Decision-Making in Complex Socio-technical Systems 103Zhongyuan Yu, Mehrnoosh Oghbaie, Chen Liu, William B. Rouse and Michael J. Pennock6.1 Introduction 1036.2 Policy Flight Simulators 1046.2.1 Background 1046.2.2 Multi-level Modelling 1056.2.3 People’s Use of Simulators 1066.3 Application 1 – Hospital Consolidation 1086.3.1 Model Overview 1106.3.2 Results and Conclusions 1176.4 Application 2 – Enterprise Diagnostics 1186.4.1 Automobile Industry Application 1196.4.2 Interactive Visualization 1226.4.3 Experimental Evaluation 1256.4.4 Results and Discussion 1256.4.5 Implications 1286.5 Conclusions 128References 1297 Developing Agent-Based Simulation Models for Social Systems Engineering Studies: A Novel Framework and its Application to Modelling Peacebuilding Activities 133Peer-Olaf Siebers, Grazziela P. Figueredo, Miwa Hirono and Anya Skatova7.1 Introduction 1337.2 Background 1347.2.1 Simulation 1347.2.2 Peacebuilding 1357.3 Framework 1377.3.1 Toolkit Design 1387.3.2 Application Design 1427.4 Illustrative Example of Applying the Framework 1437.4.1 Peacebuilding Toolkit Design 1437.4.2 Peacebuilding Application Design 1497.4.3 Engineering Actions and Interventions in a Peacebuilding Context 1537.5 Conclusions 155References 1558 Using Actor-Network Theory in Agent-Based Modelling 157Sandra Méndez-Fajardo, Rafael A. Gonzalez and Ricardo A. Barros-Castro8.1 Introduction 1578.2 Agent-Based Modelling 1588.2.1 ABM Approaches 1598.2.2 Agent Interactions 1608.3 Actor-Network Theory 1608.4 Towards an ANT-Based Approach to ABM 1628.4.1 ANT Concepts Related to ABM 1628.5 Design Guidelines 1638.6 The Case of WEEE Management 1668.6.1 Contextualizing the Case Study 1678.6.2 ANT Applied to WEEE Management in Colombia 1688.6.3 ANT–ABM Translation Based on the Case Study 1728.6.4 Open Issues and Reflections 1738.7 Conclusions 174References 1759 Engineering the Process of Institutional Innovation in Contested Territory 179Russell C. Thomas and John S. Gero9.1 Introduction 1799.2 Can Cyber Security and Risk be Quantified? 1819.2.1 Schools of Thought 1819.3 Social Processes of Innovation in Pre-paradigmatic Fields 1839.3.1 Epistemic and Ontological Rivalry 1839.3.2 Knowledge Artefacts 1849.3.3 Implications of Theory 1849.4 A Computational Model of Innovation 1869.4.1 Base Model: Innovation as Percolation 1869.4.2 Full Model: Innovation with Knowledge Artefacts 1909.4.3 Experiment 1909.5 Discussion 194Acknowledgements 194References 195Part III CASES AND APPLICATIONS 19710 Agent-Based Explorations of Environmental Consumption in Segregated Networks 199Adam Douglas Henry and Heike I. Brugger10.1 Introduction 19910.1.1 Micro-drivers of Technology Adoption 20110.1.2 The Problem of Network Segregation 20210.2 Model Overview 20310.2.1 Synopsis of Model Parameters 20410.2.2 Agent Selection by Firms 20510.2.3 Agent Adoption Decisions 20610.3 Results 20610.3.1 Influence of Firm Strategy on Saturation Times 20710.3.2 Characterizing Adoption Dynamics 20810.3.3 Incentivizing Different Strategies 21010.4 Conclusion 212Acknowledgements 212References 21311 Modelling in the ‘Muddled Middle’: A Case Study of Water Service Delivery in Post-Apartheid South Africa 215Jai K. Clifford-Holmes, Jill H. Slinger, Chris de Wet and Carolyn G. Palmer11.1 Introduction 21511.2 The Case Study 21611.3 Contextualizing Modelling in the ‘Muddled Middle’ in the Water Sector 21711.4 Methods 21911.5 Results 22011.6 Discussion 228Acknowledgements 230References 23112 Holistic System Design: The Oncology Carinthia Study 235Markus Schwaninger and Johann Klocker12.1 The Challenge: Holistic System Design 23512.2 Methodology 23612.3 Introduction to the Case Study: Oncology Carinthia 23812.3.1 Setting the Stage 23812.3.2 Framing: Purpose and Overall Goals (F) 23912.3.3 Mapping the System at the Outset (M) 24012.3.4 A First Model (M) and Assessment (A) 24212.3.5 The Challenge Ahead 24512.3.6 A First Take on Design (D): Ascertaining Levers 24612.3.7 From Design (D) to Change (C) 24812.3.8 Progress in Organizational Design (D) 24912.3.9 The Evolution of Oncology Carinthia (C) 25812.3.10 Results 25912.4 Insights, Teachings and Implications 261Acknowledgements 263Appendix: Mathematical Representations for Figures 12.5, 12.6 and 12.7 263A1: VSM, for any System-in-Focus (one level of recursion; ref. Figure 12.5) 263A2: Recursive Structure of the VSM (ref. Figure 12.6) 264A3: Virtual Teams (ref. Figure 12.7) 264References 26513 Reinforcing the Social in Social Systems Engineering – Lessons Learnt from Smart City Projects in the United Kingdom 267Jenny O’Connor, Zeynep Gurguc and Koen H. van Dam13.1 Introduction 26713.1.1 Cities as Testbeds 26813.1.2 Smart Cities as Artificial Systems 26813.1.3 Chapter Structure 26913.2 Methodology 27013.3 Case Studies 27113.3.1 Glasgow 27113.3.2 London 27413.3.3 Bristol 27713.3.4 Peterborough 27913.4 Discussion 28313.4.1 Push/Pull Adoption Model 28313.4.2 Civic Engagement 28413.4.3 Solutions and Problems 28513.4.4 Metrics, Quantification and Optimization 28513.4.5 Project Scope and Lifecycles 28613.4.6 Collaboration and Multidisciplinarity 28613.4.7 Knowledge-Sharing 28713.5 Conclusion 287References 288Index 291
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