Details

Social Systems Engineering


Social Systems Engineering

The Design of Complexity
Wiley Series in Computational and Quantitative Social Science 1. Aufl.

von: César García-Díaz, Camilo Olaya

70,99 €

Verlag: Wiley
Format: EPUB
Veröffentl.: 25.10.2017
ISBN/EAN: 9781118974421
Sprache: englisch
Anzahl Seiten: 312

DRM-geschütztes eBook, Sie benötigen z.B. Adobe Digital Editions und eine Adobe ID zum Lesen.

Beschreibungen

<p><b>Uniquely reflects an engineering view to social systems in a wide variety of contexts of application</b></p> <p><i>Social Systems Engineering: The Design of Complexity</i> 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.</p> <p><i>Social Systems Engineering: The Design of Complexity</i> 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. </p> <ul> <li>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 settings</li> <li>Divulges 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 problems</li> <li>Features an array of applied cases that illustrate the application of social systems engineering in different domains</li> </ul> <p><i>Social Systems Engineering: The Design of Complexity</i> 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.</p>
<p>List of Contributors xi</p> <p>Preface xiii</p> <p><b>Introduction: The Why, What and How of Social Systems Engineering 1<br /></b><i>César García-Díaz and Camilo Olaya</i></p> <p><b>Part I SOCIAL SYSTEMS ENGINEERING: THE VERY IDEA 11</b></p> <p><b>1 Compromised Exactness and the Rationality of Engineering 13<br /></b><i>Steven L. Goldman</i></p> <p>1.1 Introduction 13</p> <p>1.2 The Historical Context 14</p> <p>1.3 Science and Engineering: Distinctive Rationalities 20</p> <p>1.4 ‘Compromised Exactness’: Design in Engineering 23</p> <p>1.5 Engineering Social Systems? 26</p> <p>References 29</p> <p><b>2 Uncertainty in the Design and Maintenance of Social Systems 31<br /></b><i>William M. Bulleit</i></p> <p>2.1 Introduction 31</p> <p>2.2 Uncertainties in Simple and Complicated Engineered Systems 33</p> <p>2.3 Control Volume and Uncertainty 35</p> <p>2.4 Engineering Analysis and Uncertainty in Complex Systems 37</p> <p>2.5 Uncertainty in Social Systems Engineering 39</p> <p>2.6 Conclusions 42</p> <p>References 42</p> <p><b>3 System Farming 45<br /></b><i>Bruce Edmonds</i></p> <p>3.1 Introduction 45</p> <p>3.2 Uncertainty, Complexity and Emergence 46</p> <p>3.2.1 The Double Complexity of CSS 48</p> <p>3.3 Science and Engineering Approaches 49</p> <p>3.3.1 The Impossibility of a Purely Design-Based Engineering Approach to CSS 51</p> <p>3.3.2 Design vs. Adaptation 52</p> <p>3.3.3 The Necessity of Strongly Validated Foundations for Design-Based Approaches 53</p> <p>3.4 Responses to CSS Complexity 54</p> <p>3.4.1 Formal Methods 54</p> <p>3.4.2 Statistical Approaches 55</p> <p>3.4.3 Self-adaptive and Adaptive Systems 57</p> <p>3.4.4 Participatory Approaches and Rapid Prototyping 57</p> <p>3.5 Towards Farming Systems 58</p> <p>3.5.1 Reliability from Experience Rather Than Control of Construction 58</p> <p>3.5.2 Post-Construction Care Rather Than Prior Effort 58</p> <p>3.5.3 Continual Tinkering Rather Than One-Off Effort 59</p> <p>3.5.4 Multiple Fallible Mechanisms Rather Than One Reliable Mechanism 59</p> <p>3.5.5 Monitoring Rather Than Prediction 59</p> <p>3.5.6 Disaster Aversion Rather Than Optimizing Performance 59</p> <p>3.5.7 Partial Rather Than Full Understanding 59</p> <p>3.5.8 Specific Rather Than Abstract Modelling 60</p> <p>3.5.9 Many Models Rather Than One 60</p> <p>3.5.10 A Community Rather Than Individual Effort 60</p> <p>3.6 Conclusion 60</p> <p>References 61</p> <p><b>4 Policy between Evolution and Engineering 65<br /></b><i>Martin F.G. Schaffernicht</i></p> <p>4.1 Introduction: Individual and Social System 65</p> <p>4.2 Policy – Concept and Process 67</p> <p>4.3 Human Actors: Perception, Policy and Action 70</p> <p>4.4 Artefacts 73</p> <p>4.5 Engineering and Evolution: From External to Internal Selection 76</p> <p>4.6 Policy between Cultural Evolution and Engineering 79</p> <p>4.7 Conclusions and Outlook 82</p> <p>Appendix: Brief Overview of the Policy Literature 83</p> <p>References 86</p> <p><b>5 ‘Friend’ versus ‘Electronic Friend’ 91<br /></b><i>Joseph C. Pitt</i></p> <p>References 99</p> <p><b>Part II METHODOLOGIES AND TOOLS 101</b></p> <p><b>6 Interactive Visualizations for Supporting Decision-Making in Complex Socio-technical Systems 103<br /></b><i>Zhongyuan Yu, Mehrnoosh Oghbaie, Chen Liu, William B. Rouse and Michael J. Pennock</i></p> <p>6.1 Introduction 103</p> <p>6.2 Policy Flight Simulators 104</p> <p>6.2.1 Background 104</p> <p>6.2.2 Multi-level Modelling 105</p> <p>6.2.3 People’s Use of Simulators 106</p> <p>6.3 Application 1 – Hospital Consolidation 108</p> <p>6.3.1 Model Overview 110</p> <p>6.3.2 Results and Conclusions 117</p> <p>6.4 Application 2 – Enterprise Diagnostics 118</p> <p>6.4.1 Automobile Industry Application 119</p> <p>6.4.2 Interactive Visualization 122</p> <p>6.4.3 Experimental Evaluation 125</p> <p>6.4.4 Results and Discussion 125</p> <p>6.4.5 Implications 128</p> <p>6.5 Conclusions 128</p> <p>References 129</p> <p><b>7 Developing Agent-Based Simulation Models for Social Systems Engineering Studies: A Novel</b> <b>Framework and its Application to Modelling Peacebuilding Activities 133<br /></b><i>Peer-Olaf Siebers, Grazziela P. Figueredo, Miwa Hirono and Anya Skatova</i></p> <p>7.1 Introduction 133</p> <p>7.2 Background 134</p> <p>7.2.1 Simulation 134</p> <p>7.2.2 Peacebuilding 135</p> <p>7.3 Framework 137</p> <p>7.3.1 Toolkit Design 138</p> <p>7.3.2 Application Design 142</p> <p>7.4 Illustrative Example of Applying the Framework 143</p> <p>7.4.1 Peacebuilding Toolkit Design 143</p> <p>7.4.2 Peacebuilding Application Design 149</p> <p>7.4.3 Engineering Actions and Interventions in a Peacebuilding Context 153</p> <p>7.5 Conclusions 155</p> <p>References 155</p> <p><b>8 Using Actor-Network Theory in Agent-Based Modelling 157<br /></b><i>Sandra Méndez-Fajardo, Rafael A. Gonzalez and Ricardo A. Barros-Castro</i></p> <p>8.1 Introduction 157</p> <p>8.2 Agent-Based Modelling 158</p> <p>8.2.1 ABM Approaches 159</p> <p>8.2.2 Agent Interactions 160</p> <p>8.3 Actor-Network Theory 160</p> <p>8.4 Towards an ANT-Based Approach to ABM 162</p> <p>8.4.1 ANT Concepts Related to ABM 162</p> <p>8.5 Design Guidelines 163</p> <p>8.6 The Case of WEEE Management 166</p> <p>8.6.1 Contextualizing the Case Study 167</p> <p>8.6.2 ANT Applied to WEEE Management in Colombia 168</p> <p>8.6.3 ANT–ABM Translation Based on the Case Study 172</p> <p>8.6.4 Open Issues and Reflections 173</p> <p>8.7 Conclusions 174</p> <p>References 175</p> <p><b>9 Engineering the Process of Institutional Innovation in Contested Territory 179<br /></b><i>Russell C. Thomas and John S. Gero</i></p> <p>9.1 Introduction 179</p> <p>9.2 Can Cyber Security and Risk be Quantified? 181</p> <p>9.2.1 Schools of Thought 181</p> <p>9.3 Social Processes of Innovation in Pre-paradigmatic Fields 183</p> <p>9.3.1 Epistemic and Ontological Rivalry 183</p> <p>9.3.2 Knowledge Artefacts 184</p> <p>9.3.3 Implications of Theory 184</p> <p>9.4 A Computational Model of Innovation 186</p> <p>9.4.1 Base Model: Innovation as Percolation 186</p> <p>9.4.2 Full Model: Innovation with Knowledge Artefacts 190</p> <p>9.4.3 Experiment 190</p> <p>9.5 Discussion 194</p> <p>Acknowledgements 194</p> <p>References 195</p> <p><b>Part III CASES AND APPLICATIONS 197</b></p> <p><b>10 Agent-Based Explorations of Environmental Consumption in Segregated Networks 199<br /></b><i>Adam Douglas Henry and Heike I. Brugger</i></p> <p>10.1 Introduction 199</p> <p>10.1.1 Micro-drivers of Technology Adoption 201</p> <p>10.1.2 The Problem of Network Segregation 202</p> <p>10.2 Model Overview 203</p> <p>10.2.1 Synopsis of Model Parameters 204</p> <p>10.2.2 Agent Selection by Firms 205</p> <p>10.2.3 Agent Adoption Decisions 206</p> <p>10.3 Results 206</p> <p>10.3.1 Influence of Firm Strategy on Saturation Times 207</p> <p>10.3.2 Characterizing Adoption Dynamics 208</p> <p>10.3.3 Incentivizing Different Strategies 210</p> <p>10.4 Conclusion 212</p> <p>Acknowledgements 212</p> <p>References 213</p> <p><b>11 Modelling in the ‘Muddled Middle’: A Case Study of Water Service Delivery in Post-Apartheid South</b> <b>Africa 215<br /></b><i>Jai K. Clifford-Holmes, Jill H. Slinger, Chris de Wet and Carolyn G. Palmer</i></p> <p>11.1 Introduction 215</p> <p>11.2 The Case Study 216</p> <p>11.3 Contextualizing Modelling in the ‘Muddled Middle’ in the Water Sector 217</p> <p>11.4 Methods 219</p> <p>11.5 Results 220</p> <p>11.6 Discussion 228</p> <p>Acknowledgements 230</p> <p>References 231</p> <p><b>12 Holistic System Design: The Oncology Carinthia Study 235<br /></b><i>Markus Schwaninger and Johann Klocker</i></p> <p>12.1 The Challenge: Holistic System Design 235</p> <p>12.2 Methodology 236</p> <p>12.3 Introduction to the Case Study: Oncology Carinthia 238</p> <p>12.3.1 Setting the Stage 238</p> <p>12.3.2 Framing: Purpose and Overall Goals (F) 239</p> <p>12.3.3 Mapping the System at the Outset (M) 240</p> <p>12.3.4 A First Model (M) and Assessment (A) 242</p> <p>12.3.5 The Challenge Ahead 245</p> <p>12.3.6 A First Take on Design (D): Ascertaining Levers 246</p> <p>12.3.7 From Design (D) to Change (C) 248</p> <p>12.3.8 Progress in Organizational Design (D) 249</p> <p>12.3.9 The Evolution of Oncology Carinthia (C) 258</p> <p>12.3.10 Results 259</p> <p>12.4 Insights, Teachings and Implications 261</p> <p>Acknowledgements 263</p> <p>Appendix: Mathematical Representations for Figures 12.5, 12.6 and 12.7 263</p> <p>A1: VSM, for any System-in-Focus (one level of recursion; ref. Figure 12.5) 263</p> <p>A2: Recursive Structure of the VSM (ref. Figure 12.6) 264</p> <p>A3: Virtual Teams (ref. Figure 12.7) 264</p> <p>References 265</p> <p><b>13 Reinforcing the Social in Social Systems Engineering – Lessons Learnt from Smart City Projects in the United Kingdom 267<br /></b><i>Jenny O’Connor, Zeynep Gurguc and Koen H. van Dam</i></p> <p>13.1 Introduction 267</p> <p>13.1.1 Cities as Testbeds 268</p> <p>13.1.2 Smart Cities as Artificial Systems 268</p> <p>13.1.3 Chapter Structure 269</p> <p>13.2 Methodology 270</p> <p>13.3 Case Studies 271</p> <p>13.3.1 Glasgow 271</p> <p>13.3.2 London 274</p> <p>13.3.3 Bristol 277</p> <p>13.3.4 Peterborough 279</p> <p>13.4 Discussion 283</p> <p>13.4.1 Push/Pull Adoption Model 283</p> <p>13.4.2 Civic Engagement 284</p> <p>13.4.3 Solutions and Problems 285</p> <p>13.4.4 Metrics, Quantification and Optimization 285</p> <p>13.4.5 Project Scope and Lifecycles 286</p> <p>13.4.6 Collaboration and Multidisciplinarity 286</p> <p>13.4.7 Knowledge-Sharing 287</p> <p>13.5 Conclusion 287</p> <p>References 288</p> <p>Index 291</p>
<p><b> César García-Díaz, PhD,</b> 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. <p><b> Camilo Olaya, PhD,</b> 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.
<p><b> Uniquely reflects an engineering view to social systems in a wide variety of contexts of application </b> <p><i> Social Systems Engineering: The Design of Complexity</i> 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. <p><i> Social Systems Engineering: The Design of Complexity</i> 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 modelling, computational modelling and management of complexity, and more. <ul> <li>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 settings</li> <li>Divulges 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 problems</li> <li>Features an array of applied cases that illustrate the application of social systems engineering in different domains</li> </ul> <br> <p><i> Social Systems Engineering: The Design of Complexity</i> 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.

Diese Produkte könnten Sie auch interessieren:

Statistics for Microarrays
Statistics for Microarrays
von: Ernst Wit, John McClure
PDF ebook
90,99 €