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.
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 suppliers 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.
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. Qius research interests include Big Data, Data/Business Analytics, Smart Service Systems, Service Science, Service Operationsand 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. Chens 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.
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