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xi | |
Preface |
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xiii | |
Introduction: The Why, What and How of Social Systems Engineering |
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1 | (10) |
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Part I SOCIAL SYSTEMS ENGINEERING: THE VERY IDEA |
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11 | (90) |
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1 Compromised Exactness and the Rationality of Engineering |
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13 | (18) |
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13 | (1) |
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1.2 The Historical Context |
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14 | (6) |
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1.3 Science and Engineering: Distinctive Rationalities |
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20 | (3) |
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1.4 `Compromised Exactness': Design in Engineering |
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23 | (3) |
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1.5 Engineering Social Systems? |
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26 | (5) |
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29 | (2) |
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2 Uncertainty in the Design and Maintenance of Social Systems |
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31 | (14) |
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31 | (2) |
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2.2 Uncertainties in Simple and Complicated Engineered Systems |
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33 | (2) |
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2.3 Control Volume and Uncertainty |
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35 | (2) |
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2.4 Engineering Analysis and Uncertainty in Complex Systems |
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37 | (2) |
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2.5 Uncertainty in Social Systems Engineering |
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39 | (3) |
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42 | (3) |
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42 | (3) |
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45 | (20) |
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45 | (1) |
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3.2 Uncertainty, Complexity and Emergence |
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46 | (3) |
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3.2.1 The Double Complexity of CSS |
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48 | (1) |
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3.3 Science and Engineering Approaches |
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49 | (5) |
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3.3.1 The Impossibility of a Purely Design-Based Engineering Approach to CSS |
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51 | (1) |
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3.3.2 Design vs. Adaptation |
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52 | (1) |
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3.3.3 The Necessity of Strongly Validated Foundations for Design-Based Approaches |
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53 | (1) |
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3.4 Responses to CSS Complexity |
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54 | (4) |
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54 | (1) |
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3.4.2 Statistical Approaches |
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55 | (2) |
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3.4.3 Self-adaptive and Adaptive Systems |
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57 | (1) |
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3.4.4 Participatory Approaches and Rapid Prototyping |
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57 | (1) |
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3.5 Towards Farming Systems |
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58 | (2) |
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3.5.1 Reliability from Experience Rather Than Control of Construction |
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58 | (1) |
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3.5.2 Post-Construction Care Rather Than Prior Effort |
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58 | (1) |
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3.5.3 Continual Tinkering Rather Than One-Off Effort |
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59 | (1) |
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3.5.4 Multiple Fallible Mechanisms Rather Than One Reliable Mechanism |
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59 | (1) |
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3.5.5 Monitoring Rather Than Prediction |
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59 | (1) |
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3.5.6 Disaster Aversion Rather Than Optimizing Performance |
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59 | (1) |
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3.5.7 Partial Rather Than Full Understanding |
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59 | (1) |
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3.5.8 Specific Rather Than Abstract Modelling |
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60 | (1) |
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3.5.9 Many Models Rather Than One |
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60 | (1) |
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3.5.70 A Community Rather Than Individual Effort |
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60 | (1) |
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60 | (5) |
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61 | (4) |
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4 Policy between Evolution and Engineering |
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65 | (26) |
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Martin F.G. Schaffernicht |
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4.1 Introduction: Individual and Social System |
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65 | (2) |
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4.2 Policy -- Concept and Process |
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67 | (3) |
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4.3 Human Actors: Perception, Policy and Action |
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70 | (3) |
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73 | (3) |
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4.5 Engineering and Evolution: From External to Internal Selection |
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76 | (3) |
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4.6 Policy between Cultural Evolution and Engineering |
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79 | (3) |
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4.7 Conclusions and Outlook |
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82 | (9) |
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Appendix: Brief Overview of the Policy Literature |
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83 | (3) |
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86 | (5) |
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5 `Friend' versus `Electronic Friend' |
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91 | (10) |
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99 | (2) |
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Part II METHODOLOGIES AND TOOLS |
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101 | (96) |
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6 Interactive Visualizations for Supporting Decision-Making in Complex Socio-technical Systems |
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103 | (30) |
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103 | (1) |
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6.2 Policy Flight Simulators |
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104 | (4) |
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104 | (1) |
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6.2.2 Multi-level Modelling |
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105 | (1) |
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6.2.3 People's Use of Simulators |
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106 | (2) |
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6.3 Application 1 -- Hospital Consolidation |
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108 | (10) |
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110 | (7) |
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6.3.2 Results and Conclusions |
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117 | (1) |
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6.4 Application 2 -- Enterprise Diagnostics |
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118 | (10) |
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6.4.1 Automobile Industry Application |
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119 | (3) |
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6.4.2 Interactive Visualization |
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122 | (3) |
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6.4.3 Experimental Evaluation |
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125 | (1) |
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6.4.4 Results and Discussion |
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125 | (3) |
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128 | (1) |
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128 | (5) |
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129 | (4) |
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7 Developing Agent-Based Simulation Models for Social Systems Engineering Studies: A Novel Framework and its Application to Modelling Peacebuilding Activities |
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133 | (24) |
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133 | (1) |
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134 | (3) |
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134 | (1) |
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135 | (2) |
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137 | (6) |
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138 | (4) |
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142 | (1) |
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7.4 Illustrative Example of Applying the Framework |
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143 | (12) |
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7.4.1 Peacebuilding Toolkit Design |
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143 | (6) |
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7.4.2 Peacebuilding Application Design |
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149 | (4) |
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7.4.3 Engineering Actions and Interventions in a Peacebuilding Context |
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153 | (2) |
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155 | (2) |
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155 | (2) |
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8 Using Actor-Network Theory in Agent-Based Modelling |
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157 | (22) |
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157 | (1) |
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8.2 Agent-Based Modelling |
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158 | (2) |
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159 | (1) |
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160 | (1) |
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160 | (2) |
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8.4 Towards an ANT-Based Approach to ABM |
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162 | (1) |
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8.4.1 ANT Concepts Related to ABM |
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162 | (1) |
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163 | (1) |
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8.6 The Case of WEEE Management |
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163 | (11) |
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8.6.1 Contextualizing the Case Study |
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67 | (101) |
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8.6.2 ANT Applied to WEEE Management in Colombia |
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168 | (3) |
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8.6.3 ANT--ABM Translation Based on the Case Study |
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171 | (102) |
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8.6.4 Open Issues and Reflections |
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173 | (1) |
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174 | (5) |
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175 | (4) |
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9 Engineering the Process of Institutional Innovation in Contested Territory |
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179 | (18) |
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179 | (2) |
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9.2 Can Cyber Security and Risk be Quantified? |
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181 | (2) |
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181 | (2) |
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9.3 Social Processes of Innovation in Pre-paradigmatic Fields |
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183 | (3) |
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9.3.1 Epistemic and Ontological Rivalry |
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183 | (1) |
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9.3.2 Knowledge Artefacts |
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184 | (1) |
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9.3.3 Implications of Theory |
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184 | (2) |
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9.4 A Computational Model of Innovation |
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186 | (1) |
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9.4.1 Base Model: Innovation us Percolation |
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186 | (4) |
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9.4.2 Full Model: Innovation with Knowledge Artefacts |
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190 | (4) |
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194 | (1) |
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194 | (93) |
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194 | (1) |
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195 | (2) |
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Part III CASES AND APPLICATIONS |
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197 | (2) |
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10 Agent-Based Explorations of Environmental Consumption in Segregated Networks |
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199 | (16) |
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199 | (4) |
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10.1.1 Micro-drivers of Technology Adoption |
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201 | (1) |
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10.1.2 The Problem of Network Segregation |
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202 | (1) |
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203 | (3) |
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10.2.1 Synopsis of Model Parameters |
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204 | (1) |
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10.2.2 Agent Selection by Firms |
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205 | (1) |
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10.2.3 Agent Adoption Decisions |
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206 | (1) |
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206 | (6) |
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10.3.1 Influence of Firm Strategy on Saturation Times |
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207 | (1) |
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10.3.2 Characterizing Adoption Dynamics |
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208 | (2) |
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10.3.3 Incentivizing Different Strategies |
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210 | (2) |
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212 | (3) |
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212 | (1) |
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213 | (2) |
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11 Modelling in the `Muddled Middle': A Case Study of Water Service Delivery in Post-Apartheid South Africa |
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215 | (20) |
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215 | (1) |
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216 | (1) |
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11.3 Contextualizing Modelling in the `Muddled Middle' in the Water Sector |
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217 | (2) |
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219 | (1) |
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220 | (8) |
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228 | (7) |
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230 | (1) |
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231 | (4) |
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12 Holistic System Design: The Oncology Carinthia Study |
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235 | (32) |
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12.1 The Challenge: Holistic System Design |
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235 | (1) |
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236 | (2) |
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12.3 Introduction to the Case Study: Oncology Carinthia |
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238 | (23) |
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238 | (1) |
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12.3.2 Framing: Purpose and Overall Goals (F) |
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239 | (1) |
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12.3.3 Mapping the System at the Outset (M) |
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240 | (2) |
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12.3.4 A First Model (M) and Assessment (A) |
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242 | (3) |
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12.3.5 The Challenge Ahead |
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245 | (1) |
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12.3.6 A First Take on Design (D): Ascertaining Levers |
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246 | (2) |
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12.3.7 From Design (D) to Change (C) |
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248 | (1) |
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12.3.8 Progress in Organizational Design (D) |
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249 | (9) |
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12.3.9 The Evolution of Oncology Carinthia (C) |
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258 | (1) |
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259 | (2) |
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12.4 Insights, Teachings and Implications |
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261 | (6) |
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263 | (1) |
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Appendix: Mathematical Representations for Figures 12.5, 12.6 and 12.7 |
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263 | (1) |
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A1 VSM, for any System-in-Focus (one level of recursion; ref. Figure 12.5) |
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263 | (1) |
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A2 Recursive Structure of the VSM (ref. Figure 12.6) |
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264 | (1) |
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A3 Virtual Teams (ref. Figure 12.7) |
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264 | (1) |
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265 | (2) |
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13 Reinforcing the Social in Social Systems Engineering -- Lessons Learnt from Smart City Projects in the United Kingdom |
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267 | (24) |
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267 | (3) |
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13.1.1 Cities as Testbeds |
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268 | (1) |
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13.1.2 Smart Cities as Artificial Systems |
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268 | (1) |
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269 | (1) |
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270 | (1) |
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271 | (12) |
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271 | (3) |
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274 | (3) |
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277 | (2) |
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279 | (4) |
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283 | (4) |
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13.4.1 Push/Pull Adoption Model |
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283 | (1) |
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284 | (1) |
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13.4.3 Solutions and Problems |
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285 | (1) |
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13.4.4 Metrics, Quantification and Optimization |
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285 | (1) |
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13.4.5 Project Scope and Lifecycles |
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286 | (1) |
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13.4.6 Collaboration and Multidisciplinarity |
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286 | (1) |
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287 | (1) |
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287 | (4) |
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288 | (3) |
Index |
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291 | |