| Preface |
| Overview of Service Science, Management, and Engineering / Chapter 1： |
| What Is SSME? / 1.1： |
| Information and Communication Technology / 1.1.1： |
| ACP Theory / 1.1.2： |
| Why Do We Need SSME? / 1.2： |
| How Do We Benefit from SSME? / 1.3： |
| Transportation System / 1.3.1： |
| Logistics System / 1.3.2： |
| Health Care System / 1.3.3： |
| E-Commerce System / 1.3.4： |
| Financial System / 1.3.5： |
| Summary / 1.4： |
| References |
| Servitization Strategy: Priorities, Capabilities, and Organizational Features / Chapter 2： |
| Introduction / 2.1： |
| Background / 2.2： |
| Context of the PC Industry / 2.2.1： |
| Definitions of Servitization / 2.2.2： |
| Benefits and Challenges of Servitization / 2.2.3： |
| Research Methodology / 2.3： |
| Case Study / 2.3.1： |
| Case Company A / 2.3.2： |
| Case Company B / 2.3.3： |
| Servitization Strategy for PC Industry / 2.4： |
| Strategic Priorities / 2.4.1： |
| Capability Requirements / 2.4.2： |
| Organizational Features / 2.4.3： |
| Managerial and Practical Implications / 2.5： |
| Strategy Priority Depends on Core Competence / 2.5.1： |
| Leadership and Top Management Support / 2.5.2： |
| Industry and Government Development Policy / 2.5.3： |
| Conclusions / 2.6： |
| Acknowledgments |
| Supply Chain Finance: Concept and Modeling / Chapter 3： |
| Inefficient Financial Supply Chain / 3.1： |
| Introduction to SCF Solutions / 3.2： |
| Preshipment Finance / 3.2.1： |
| Transit Finance / 3.2.2： |
| Postshipment Finance / 3.2.3： |
| Mathematical Representations of Supply Chain Finance / 3.3： |
| A Survey / 3.3.1： |
| Approximate Dynamic Programming / 3.3.2： |
| A Three-Stage Supply Chain Finance Modeling Framework / 3.3.3： |
| Future Research / 3.4： |
| Designing and Assessing Participatory Public Services for Emerging Markets / Chapter 4： |
| COCKPIT: A Participatory Service Design Methodology in a European Context / 4.1： |
| Challenges of Service Provision in Emerging Markets / 4.2： |
| Case Study: The National Rural Employment Guarantee Scheme / 4.2.1： |
| Case Study: The Targeted Public Distribution System / 4.2.2： |
| Existence of Corruption and Lack of Transparency / 4.2.3： |
| COCKPIT for Emerging Markets (CEM) / 4.3： |
| CEM Prototype and Implementation / 4.4： |
| Assessing Corruption in Public Services in Emerging Markets / 4.5： |
| Transparency Assessment of Public Services in Emerging Markets / 4.6： |
| Concluding Remarks / 4.7： |
| Appendix |
| Recommendation Algorithms for Implicit Information / Chapter 5： |
| Preliminaries / 5.1： |
| Notation / 5.2.1： |
| Recommendation Framework and Quality Metric / 5.2.2： |
| Neighborhood Models / 5.3： |
| Matrix Factorization Models / 5.4： |
| Matrix Factorization for Explicit Ratings / 5.4.1： |
| Weighted Matrix Factorization for Implicit Ratings / 5.4.2： |
| Weighted Matrix Factorization with Biases / 5.4.3： |
| A Hybrid Model of Implicit and Feature Information / 5.5： |
| Experimental Study / 5.6： |
| Data Description / 5.6.1： |
| Results / 5.6.2： |
| Online Strategies for Optimizing Medical Supply in Disaster Scenarios / 5.7： |
| Related Work / 6.1： |
| Experimental Setup / 6.3： |
| Triage Groups and Penalty Functions / 6.3.1： |
| Data / 6.3.2： |
| Algorithms for Optimization / 6.4： |
| Optimization Problem and Catena / 6.4.1： |
| Optimization Algorithms / 6.4.2： |
| Relaxations / 6.4.3： |
| Experiments and Results / 6.5： |
| Training / 6.5.1： |
| Test / 6.5.2： |
| Future Prospects / 6.6： |
| Evaluating Traffic Signal Control System Based on Artificial Transportation Systems / Chapter 7： |
| Developing an Artificial Transportation System from the Bottom Up / 7.1： |
| The Evaluation Method / 7.3： |
| Building the Evaluation Platform / 7.4： |
| GreenPass System / 7.5： |
| Experiments / 7.6： |
| Scenario 1: Adverse Weather / 7.6.1： |
| Scenario 2: After the Building of a Shopping Mall / 7.6.2： |
| An Approach to Optimize Police Patrol Activities Based on the Spatial Pattern of Crime Hotspots / 7.7： |
| Police Patrolling / 8.1： |
| Crime Hotspots / 8.2.2： |
| Estimators of Spatial Autocorrelation / 8.2.3： |
| Route Optimization / 8.2.4： |
| Strategy for Near-Optimal Patrol Route Planning / 8.3： |
| Overview / 8.3.1： |
| Street Network-Based Patrol Route Model / 8.3.2： |
| Route Optimization Procedure / 8.3.3： |
| A Case Study / 8.4： |
| Study Site / 8.4.1： |
| Data and Analysis / 8.4.2： |
| Conclusions and Prospects / 8.4.3： |
| Limitations and Future Directions / 8.5.1： |
| Chemical Emergency Management Research Based on ACP Approach / Chapter 9： |
| Problems and Challenges / 9.1： |
| A Research Framework: Parallel Emergency Management System / 9.3： |
| Artificial Emergency Systems / 9.3.1： |
| Computational Experiments / 9.3.2： |
| Parallel Execution / 9.3.3： |
| Case Study 1: Chemical Early-Warning Research / 9.4： |
| Case Study 2: Chemical Emergency Response Plans Evaluation / 9.4.2： |
| Bus Arrival Prediction and Trip Planning for Better User Experience and Services / 9.5： |
| Literature Review / 10.1： |
| Bus Arrival Prediction / 10.2.1： |
| Bus Trip Planning / 10.2.2： |
| Factor Analysis / 10.3： |
| Linear Model and Parameter Calibration / 10.3.2： |
| System Overview / 10.4： |
| K-Transfer / 10.4.2： |
| Multiobjective Shortest Path / 10.4.3： |
| Path Patching / 10.4.4： |
| Prototype and Experiments / 10.5： |
| Mass Customization Manufacturing and Its Application for Mobile Phone Production / 10.6： |
| Definitions and Analysis / 11.1： |
| Industrial Practices / 11.1.2： |
| Mobile Phone Production Process Description / 11.2： |
| Mobile Phone Production Processes / 11.2.1： |
| Mobile Phone Production Modes / 11.2.2： |
| Mass Customization Manufacturing Solution / 11.3： |
| Main Manufacturing Phases of Mass Customization / 11.3.1： |
| Order Processing of Mass Customization / 11.3.2： |
| Quality Control of the Solution / 11.3.3： |
| Technical Architecture of the Solution / 11.3.4： |
| Practice Results of the Solution / 11.3.5： |
| ACP Approach-Based Plant Human-Machine Interaction Evaluation / 11.4： |
| Related Research / 12.1： |
| Artificial Human-Machine System / 12.2： |
| Experimental Environment / 12.3： |
| Overview of Boiler Plant Simulator / 12.3.1： |
| Assumed Malfunctions / 12.3.2： |
| Alarm System / 12.3.3： |
| Design of Computational Experiments / 12.4： |
| Failure-Symptom Bipartite Graph / 12.4.1： |
| Abnormal-State-Supervising Procedure / 12.4.2： |
| Task Decomposition and Workload Estimation / 12.4.3： |
| Expected Effects / 12.5： |
| Example of FDI Track / 12.5.1： |
| Example of Workload Estimation / 12.5.2： |
| HMI Evaluation and Improvement / 12.5.3： |
| Cloud of Health for Connected Patients / 12.6： |
| Drivers for Change in Health Care / 13.1： |
| Applications / 13.3： |
| Expert Knowledge-Websites / 13.3.1： |
| Self-Help / 13.3.2： |
| SMS / 13.3.3： |
| Measuring Device Linked by Personal Health Assistant to Expert Systems / 13.3.4： |
| Medical Data on a SIM Card / 13.3.5： |
| Exercise and Rehabilitation / 13.3.6： |
| Links to Nutrition Information Expert Knowledge Systems / 13.3.7： |
| Epilepsy Alert / 13.3.8： |
| Body-Worn Sensors / 13.3.9： |
| Conclusions of Cloud of Health / 13.4： |
| Case Study of SMS Messaging in Health Promotion / 13.5： |
| Characteristics of SMS for Use in Healthcare Promotion / 13.6： |
| K1 Widespread Ownership of Mobile Phones and SMS Usage / 13.6.1： |
| K2 Convenience and Storage / 13.6.2： |
| K3 Personal and Private / 13.6.3： |
| K4 Social Communication / 13.6.4： |
| K5 Speed / 13.6.5： |
| K6 Cost / 13.6.6： |
| K7 Application Integration / 13.6.7： |
| K8 Ease of Administration / 13.6.8： |
| K9 Targeting / 13.6.9： |
| Conclusions of SMS for Use in Healthcare Promotion / 13.7： |
| Construction of Artificial Grid Systems Based on ACP Approach / Chapter 14： |
| ACP Approach / 14.1： |
| Complex Network Characteristics of Power Grids / 14.3： |
| Complex Network Theory / 14.3.1： |
| Complexity of Power Grids / 14.3.2： |
| Construction of Complex Power Grid Network Model / 14.3.3： |
| Some Results of Research on Power Grids Based on Complex Networks / 14.3.4： |
| Construction of Artificial Grid Systems / 14.4： |
| Artificial Grid Systems / 14.4.1： |
| Design and Construction of Artificial Grid Systems / 14.4.2： |
| Influence of Electric Vehicles on After-Sales Service / 14.5： |
| After-Sales Service in the Automotive Industry / 15.1： |
| Stakeholders of the Automotive Aftermarket / 15.2.1： |
| Typical Services in the Automotive Aftermarket / 15.2.2： |
| Changes Due to the Increasing Share of Electric Mobility / 15.3： |
| The Impact on Stakeholders / 15.4： |
| Decreasing Share of Mechanical and Moving Parts / 15.4.1： |
| Fewer Additional Units / 15.4.2： |
| Longer Service Intervals / 15.4.3： |
| Immature Battery Technology / 15.4.4： |
| Limited Self-Service Possibility / 15.4.5： |
| Future Perspectives / 15.5： |
| Service Modeling Optimization and Service Composition QoS Analysis / Chapter 16： |
| BPEL4WS-Based Modeling Optimization / 16.1： |
| Comparison of Modeling of SMEE and Mainstream Methods Based on BPEL4WS / 16.2.1： |
| Definition of SMEE / 16.2.2： |
| Research Method for Converting SMEE Model into BPEL4WS / 16.2.3： |
| Running Performance Evaluation for Generated BPEL4WS Model / 16.2.4： |
| Web Service Composition Quality Analysis with Stochastic Service Times / 16.3： |
| Problem Description / 16.3.1： |
| Analysis of the QoS of Each Kind of BPEL2WS Container / 16.3.2： |
| Analysis of the QoS of an Actual BPEL2WS Model / 16.3.3： |
| Urban Traffic Management System Based on Ontology and Multiagent System / 16.4： |
| LiteratureReview / 17.1： |
| Ontological Technology / 17.2.1： |
| Multiagent Technology / 17.2.2： |
| Ontology of Urban Traffic Management System / 17.3： |
| Road Network / 17.3.1： |
| Environment / 17.3.2： |
| Traffic Information / 17.3.3： |
| Traffic Facility / 17.3.4： |
| Vehicle / 17.3.5： |
| Algorithm / 17.3.6： |
| Time / 17.3.7： |
| Multiagent System Architecture / 17.4： |
| Reference / 17.5： |
| Index |
| Preface |
| Overview of Service Science, Management, and Engineering / Chapter 1： |
| What Is SSME? / 1.1： |
