This volume offers the state-of-the-art research and developments in service science and related research, education and practice areas. It showcases emerging technology and applications in fields including healthcare, 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 highlight ways to approach such technical challenges in service science and are based on submissions from the 2018 INFORMS International Conference on Service Science.
表中的内容
Chapter 1. The Inmate Transportation Problem and its Application in the PA Department of Corrections.- Chapter 2. Robust modality selection in radiotherapy.- Chapter 3. Incentive-Based Rebalancing of Bike-Sharing Systems.- Chapter 4. A T-Shaped Measure of Multidisciplinarity in Academic Research Networks: The GRAND Case Study.- Chapter 5. Service Differentiation and Operating Segments: Research Opportunities and Implementation Challenges.- Chapter 6. Higher Education as a Service: The Science of Running a Lean Program in International Business.- Chapter 7. A Hypergraph-based Modeling Approach for Service Systems.- Chapter 8. Zone of Optimal Distinctiveness: Provider Asset Personalization and the Psychological Ownership of Shared Accommodation.- Chapter 9. Data Mining Methods for Describing Federal Government Career Trajectories and Predicting Employee Separation.- Chapter 10. Using the Service Science Canvas to Understand Institutional Change in a Public School System.- Chapter 11. Data-driven capacity management with machine learning: A novel approach and a case-study for a public service office.- Chapter 12. Harnessing Big Data and Analytics Solutions in Support of Smart City Services.- Chapter 13. The Pay Equity Dilemma Women Face Around the World.- Chapter 14. Project and Resource Optimization (PRO) for IT Service Delivery.- Chapter 15. A Unified Framework for Specifying Cost Models of IT Service Offerings.- Chapter 16. Toward a Context-aware Serendipitous Recommendation System.- Chapter 17. Analysis of service execution in the on-line sports gambling industry.- Chapter 18. Decision Modeling in Service Science.- Chapter 19. Predicting call center performance with machine learning.- Chapter 20. Information directed policy sampling for partially observable Markov decision processes with parametric uncertainty.- Chapter 21. Buffered Probability of Exceedance (b POE) Ratings for Synthetic Instruments.- Chapter 22. Service Quality Assessment via Enhanced Data-Driven MCDM Model.- Chapter 23. Estimating the Effect of Social Influence on Subsequent Reviews.- Chapter 24. Product and Service Design for Remanufacturing, Uncertainty and the Environmental Impact in The Closed-loop Supply Chain Network.- Chapter 25. Towards the determinants of successful public-private partnership projects in Jamaica: A proposed methodology.- Chapter 26. Cognitive Solutioning of Highly-Valued IT Service Contracts.- Chapter 27. A Predictive Approach for Monitoring Services in the Internet of Things.- Chapter 28. Managing Clinical Appointments in an Academic Medical Center.- Chapter 29. Factors Influencing E-Procurement Adoption in the Transportation Industry.
关于作者
Hui Yang is the Harold and Inge Marcus Career Associate Professor in the Harold and Inge Marcus Department of Industrial and Manufacturing Engineering at The Pennsylvania State University, University Park, PA. Prior to joining Penn State in 2015, he was an Assistant Professor in the Department of Industrial and Management Systems Engineering at the University of South Florida from 2009 to 2015. 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, 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. He holds a Ph.D. in Industrial Engineering and a Ph.D. (minor) in Computer Science both from The Pennsylvania State University. 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.
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