This volume offers state-of-the-art research in service science and its related research, education and practice areas. It showcases recent developments in smart service systems, operations management and analytics and their impact in complex service systems. The papers included in this volume highlight emerging technology and applications in fields including healthcare, energy, finance, information technology, transportation, sports, logistics, and public services. Regardless of size and service, a service organization is a service system. Because of the socio-technical nature of a service system, a systems approach must be adopted to design, develop, and deliver services, aimed at meeting end users' both utilitarian and socio-psychological needs. Effective understanding of service and service systems often requires combining multiple methods to consider how interactions of people, technology, organizations, and information create value under various conditions. The papers in this volume present methods to approach such technical challenges in service science and are based on top papers from the 2019 INFORMS International Conference on Service Science.

Autorentext
Hui Yang is an Associate Professor in the Harold and Inge Marcus Department of Industrial and Manufacturing Engineering at The Pennsylvania State University, University Park, PA. Dr. Yang's research interests focus on sensor-based modeling and analysis of complex systems for process monitoring, process control, system diagnostics, condition prognostics, quality improvement, and performance optimization.
Robin Qiu is a tenured full Professor of Information Science, teaches a variety of courses including Predictive Analytics, Management Science, Business Process Management, Decision Support Systems, Project Management, Enterprise Integration, Enterprise Service Computing, Software Engineering, Web-based Systems, Distributed Systems, Computer Architecture/SOA, Computer Security, Web Security, Operations Research, and System Engineering. Dr. Qiu's research interests include Big Data, Data/Business Analytics, Smart Service Systems, Service Science, Service Operations and Management, Information Systems, and Manufacturing and Supply Chain Management.
Weiwei Chen is an Associate Professor of Supply Chain Management in Rutgers Business School Newark and New Brunswick at Rutgers University. Dr. Chen's current research interest lies in operations and finance interface, as well as supply chain operations planning and scheduling. He also works on simulation and randomized global optimization methodologies. He has extensive experience working with businesses and public sectors to improve strategic decisions and operational efficiencies using data analytics. He has taught courses in optimization modeling, operations analysis, and lean six sigma.

Inhalt
Chapter 1. Cleaning and Processing on the Electric Vehicle Telematics Data.- Chapter 2. Performance Analysis of a Security-Check System with Four Types of Inspection Channels for High-Speed Rail Stations in China.- Chapter 3. LSTM-Based Neural Network Model for Semantic Search.- Chapter 4. Research on the Evaluation of Electric Power Companies' Safety Capabilities based on Grey Fixed Weight Clustering.- Chapter 5. Analysis of crude oil price fluctuation and transition characteristics at different time scales based on complex networks.- Chapter 6. Understanding of Servicification Trends in China through Analysis of Inter-Industry Network Structure.- Chapter 7. Machine Learning Methods for Revenue Prediction in Google Merchandise Store.- Chapter 8. Predicting Metropolitan Crime Rates Using Machine Learning Techniques.- Chapter 9. Optimizing Ensemble Weights for Machine Learning Models: A Case Study for Housing Price Prediction.- Chapter 10. How do pricing power and service strategy affect the decisions of a dual-channel supply chain?- 11. Designing Value Co-creation for a Free-Floating E-Bike Sharing System.- Chapter 12. Research on Electricity Falling Accident Based on Improved Bode Accident Causation Model.- Chapter 13. Crop Yield Prediction Using Deep Neural Networks.- Chapter 14. Cloud-based Life Sciences Manufacturing System: Integrated Experiment Management and Data Analysis via Amazon Web Services.- Chapter 15. Matching Anonymized Individuals with Errors for Service Systems.- Chapter 16. Developing a Production Structure Model using Service-Dominant Logic A hypergraph-based Modeling Approach.- Chapter 17. Airworthiness Evaluation Model Based on Fuzzy Neural Network.- Chapter 18. Two-Level Trip Selection and Price Incentive Scheduling in Electric Vehicle Sharing System.- Chapter 19. Research on the Method of Identifying Opinion Leaders Based on Online Word-of-Mouth.- Chapter 20. People Analytics in Practice: Connecting Employee, Customer and Operational Data to Create Evidence-Based Decision Making.- Chapter 21. Multiple-Disease Risk Predictive Modeling based on Directed Disease Networks.- Chapter 22. Service Performance Tests on the Mobile Edge Computing Platform: Challenges and Opportunities.- Chapter 23. Study on an Argumentation-Based Negotiation in Human-Computer Negotiation Service.- Chapter 24. On the Uncertain Accuracy of Seller-Provided Information in the Presence of Online Reviews.- Chapter 25. Route planning for vehicles with UAVs based on set covering.- Chapter 26. Frequency-based Contour Selection of Grey Wave Forecasting Model and its Application in Shanghai Stock Market.- Chapter 27. Research on Information Dissemination Model in WeChat-based Brand Community.- Chapter 28. Structure Evolvement and Equilibrium Analysis of International Credit Rating Market.- Chapter 29. Teaching a Man to Fish: Teaching Cases of Business Analytics.- Chapter 30. The study of fresh products supplier's comprehensive evaluation based on Balanced Scorecard.- Chapter 31. Maintenance Architecture Optimization of A Distributed CubeSat Network Based on Parametric Model.- Chapter 32. Study on the Control Measures of MDRO Transmission in ICU Based on Markov Process.- Chapter 33. What makes a helpful online review for healthcare services? An empirical analysis of Haodaifu website.- Chapter 34. Analyzing WeChat Diffusion Cascade: Pattern Discovery and Prediction.- Chapter 35. Study on the Relationship between the Logistics Industry and Macroeconomic Factors in China Based on the Grey Incidence.