Smart Service Systems, Operations Management, and Analytics

1. Front Matter

   Pages i-viii

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2. Cleaning and Processing on the Electric Vehicle Telematics Data

   • Shuai Sun, Jun Bi, Cong Ding

   Pages 1-6

3. Performance Analysis of a Security-Check System with Four Types of Inspection Channels for High-Speed Rail Stations in China

   • Chia-Hung Wang, Xiaojing Wu

   Pages 7-16

4. LSTM-Based Neural Network Model for Semantic Search

   • Xiaoyu Guo, Jing Ma, Xiaofeng Li

   Pages 17-25

5. Research on the Evaluation of Electric Power Companies’ Safety Capabilities Based on Grey Fixed Weight Clustering

   • Yijing Wang, Jie Xu, Chuanmin Mi, Zhipeng Zhou

   Pages 27-39

6. Analysis of Crude Oil Price Fluctuation and Transition Characteristics at Different Timescales Based on Complex Networks

   • Jiao Yan, Jing Ma

   Pages 41-53

7. Understanding of Servicification Trends in China Through Analysis of Interindustry Network Structure

   • Yunhan Liu, Dohoon Kim

   Pages 55-64

8. Machine Learning Methods for Revenue Prediction in Google Merchandise Store

   • Vahid Azizi, Guiping Hu

   Pages 65-75

9. Predicting Metropolitan Crime Rates Using Machine Learning Techniques

   • Saba Moeinizade, Guiping Hu

   Pages 77-86

10. Optimizing Ensemble Weights for Machine Learning Models: A Case Study for Housing Price Prediction

    • Mohsen Shahhosseini, Guiping Hu, Hieu Pham

    Pages 87-97

11. How Do Pricing Power and Service Strategy Affect the Decisions of a Dual-Channel Supply Chain?

    • Houping Tian, Chaomei Wu

    Pages 99-111

12. Designing Value Co-creation for a Free-Floating e-Bike-Sharing System

    • Christoph Heitz, Marc Blume, Corinne Scherrer, Raoul Stöckle, Thomas Bachmann

    Pages 113-125

13. Research on Electricity Falling Accident Based on Improved Bode Accident Causation Model

    • Qian Yuanyuan, Xu Jie, Mi Chuanmin, Peng Qiwei

    Pages 127-137

14. Crop Yield Prediction Using Deep Neural Networks

    • Saeed Khaki, Lizhi Wang

    Pages 139-147

15. Cloud-Based Life Sciences Manufacturing System: Integrated Experiment Management and Data Analysis via Amazon Web Services

    • Pei Guo, Raymond Peterson, Paul Paukstelis, Jianwu Wang

    Pages 149-159

16. Matching Anonymized Individuals with Errors for Service Systems

    • Wai Kin (Victor) Chan

    Pages 161-168

17. Developing a Production Structure Model Using Service-Dominant Logic—A Hypergraph-Based Modeling Approach

    • Mahei Manhai Li, Christoph Peters, Jan Marco Leimeister

    Pages 169-182

18. Airworthiness Evaluation Model Based on Fuzzy Neural Network

    • Jie-Ru Jin, Peng Wang, Yang Shen, Kai-Xi Zhang

    Pages 183-194

19. Two-Level Trip Selection and Price Incentive Scheduling in Electric Vehicle-Sharing System

    • Zihao Jiao, Xin Liu, Lun Ran, Yuli Zhang

    Pages 195-207

20. Research on the Method of Identifying Opinion Leaders Based on Online Word-of-Mouth

    • Chenglin He, Shan Li, Yehui Yao, Yu Ding

    Pages 209-222

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.

• Service Science
• Smart Service
• Smart Service and Systems
• Service Systems Modeling
• Service Operations
• Service Operations and Management
• Operations Management
• Service Analytics
• Analytics
• Machine Learning
• Service Research
• Service Management
• Service Systems
• Smart Cities
• Big Data
• Service Science Research

• Harold and Inge Marcus Department of Industrial and Manufacturing Engineering, Pennsylvania State University, University Park, USA

  Hui Yang

• Division of Engineering and Information Science, Pennsylvania State University, Malvern, USA

  Robin Qiu

• Department of Supply Chain Management, Rutgers, The State University of New Jersey, Piscataway, USA

  Weiwei Chen

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 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. 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.

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