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  • Conference proceedings
  • © 2021

AI and Analytics for Smart Cities and Service Systems

Proceedings of the 2021 INFORMS International Conference on Service Science

  • Presents recent advances and rigorously developed papers in service science research, education, and implementation

  • Highlights emerging technology and applications in the state of the art of service research

  • Includes service case studies written by scholars and practitioners worldwide

Part of the book series: Lecture Notes in Operations Research (LNOR)

Conference series link(s): ICSS: INFORMS International Conference on Service Science

Conference proceedings info: ICSS 2021.

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  • ISBN: 978-3-030-90275-9
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Softcover Book USD 249.99
Price excludes VAT (USA)
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Table of contents (31 papers)

  1. Front Matter

    Pages i-vii
  2. Deep Learning and Prediction of Survival Period for Breast Cancer Patients

    • Shreyesh Doppalapudi, Hui Yang, Jerome Jourquin, Robin G. Qiu
    Pages 1-22
  3. Should Managers Care About Intra-household Heterogeneity?

    • Parneet Pahwa, Nanda Kumar, B. P. S. Murthi
    Pages 23-30
  4. Prediction of Gasoline Octane Loss Based on t-SNE and Random Forest

    • Chen Zheng, Shan Li, Chengcheng Song, Siyu Yang
    Pages 43-54
  5. A U-net Architecture Based Model for Precise Air Pollution Concentration Monitoring

    • Feihong Wang, Gang Zhou, Yaning Wang, Huiling Duan, Qing Xu, Guoxing Wang et al.
    Pages 65-75
  6. Algorithm for Predicting Bitterness of Children’s Medication

    • Tiantian Wu, Shan Li, Chen Zheng
    Pages 91-102
  7. Intelligent Identification of High Emission Road Segment Based on Large-Scale Traffic Datasets

    • Baoxian Liu, Gang Zhou, Yanyan Yang, Zilong Huang, Qiongqiong Gong, Kexu Zou et al.
    Pages 103-113
  8. Development of a Cost Optimization Algorithm for Food and Flora Waste to Fleet Fuel (F4)

    • Kate Hyun, Melanie L. Sattler, Arpita H. Bhatt, Bahareh Nasirian, Ali Behseresht, Mithila Chakraborty et al.
    Pages 141-153
  9. Accidents Analysis and Severity Prediction Using Machine Learning Algorithms

    • Rahul Ramachandra Shetty, Hongrui Liu
    Pages 173-183
  10. Estimating Discrete Choice Models with Random Forests

    • Ningyuan Chen, Guillermo Gallego, Zhuodong Tang
    Pages 184-196
  11. Prediction and Analysis of Chinese Water Resource: A System Dynamics Approach

    • Qi Zhou, Tianyue Yang, Yangqi Jiao, Kanglin Liu
    Pages 197-211
  12. Pricing and Strategies in Queuing Perspective Based on Prospect Theory

    • Yanyan Liu, Jian Liu, Chuanmin Mi
    Pages 212-226

Other Volumes

  1. AI and Analytics for Smart Cities and Service Systems

About this book

This book showcases state-of-the-art advances in service science and related fields of research, education, and practice. It presents emerging technologies and applications in contexts ranging from healthcare, energy, finance, and information technology to transportation, sports, logistics, and public services. Regardless of its size and service, every service organization is a service system. Due to the socio-technical nature of service systems, a systems approach must be adopted in order to design, develop and deliver services aimed at meeting end users’ utilitarian and socio-psychological needs alike. Understanding services and service systems often requires combining multiple methods to consider how interactions between people, technologies, organizations and information create value under various conditions. The papers in this volume highlight a host of ways to approach these challenges in service science and are based on submissions to the 2021 INFORMS Conference on Service Science.


  • Service Science
  • Smart Service and Systems
  • Service Systems Modeling
  • Service Operations and Management
  • Service Analytics
  • Artificial Intelligence

Editors and Affiliations

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

    Robin Qiu

  • Faculty of Information (Cross-appointed to Computer Science), Faculty Affiliate, Schwartz Reisman Institute, University of Toronto, Toronto, Canada

    Kelly Lyons

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

    Weiwei Chen

About the editors

Robin Qiu, a full professor of information science, teaches a variety of courses on e.g. 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. His 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.
Kelly Lyons is a professor at the Faculty of Information, University of Toronto with a cross appointment to the Department of Computer Science. Prior to joining the Faculty of Information, she was the program director of the IBM Toronto Lab Centre for Advanced Studies (CAS). Her current research interests include service science, knowledge mobilization, data science, social media, and collaborative work. From 2015 to 2020, she served as an associate dean, Academic at the Faculty of Information. From 2020 to 2021, she is serving as the dean’s advisor on Pandemic Planning and Response. She has co‐authored several papers, served on program committees for conferences, given many keynote and invited presentations, and co‐chaired several workshops. She has received an NSERC Strategic Partnership Grant, NSERC Discovery Grants, an NSERC Collaborative Research and Development Grant with SAP, two NSERC Engage Grants (with ScienceScape and Dell), MITACS Accelerate Grants (with CA, IBM, and Cerebri AI), an SSHRC Knowledge Synthesis Grant, and an IBM Smarter Planet Faculty Innovation Grant, as well as funding from the GRAND Networks of Centers of Excellence (NCE). She is an IBM faculty fellow and a faculty affiliate of the Schwartz Reisman Institute for Technology and Society. She is currently on the Board of CS-Can/Info-Can and on the Board of the Informs Service Science Section. From 2008 to 2012, she was a member‐at‐large of the ACM Council and a member of the Executive Council of ACM‐W. 
Weiwei Chen is an associate professor at Rutgers University. His research interests lie 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 the public sector, especially in energy and healthcare, to improve strategic decisions and operational efficiency using data analytics.

Bibliographic Information

Buying options

eBook USD 189.00
Price excludes VAT (USA)
  • ISBN: 978-3-030-90275-9
  • Instant PDF download
  • Readable on all devices
  • Own it forever
  • Exclusive offer for individuals only
  • Tax calculation will be finalised during checkout
Softcover Book USD 249.99
Price excludes VAT (USA)
Hardcover Book USD 249.99
Price excludes VAT (USA)