Qiu / Lyons / Chen AI and Analytics for Smart Cities and Service Systems

Proceedings of the 2021 INFORMS International Conference on Service Science
1. Auflage 2021
ISBN: 978-3-030-90275-9
Verlag: Springer International Publishing
Format: PDF
Kopierschutz: 1 - PDF Watermark

E-Book, Englisch, 406 Seiten, eBook

Reihe: Business and Management

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.

Zielgruppe

Research

Autoren/Hrsg.

Qiu, Robin

Lyons, Kelly

Chen, Weiwei

Inhaltsverzeichnis

1. Deep Learning and Prediction of Survival Period for Breast Cancer Patients2. Should Managers Care About Intra-Household Heterogeneity?3. Penalizing Neural Network and Autoencoder for the Analysis of Marketing Measurement Scales in Service Marketing Applications4. Prediction of Gasoline Octane Loss Based on t-SNE and Random Forest5. Introducing AI General Practitioners to Improve Healthcare Services6. A U-Net Architecture Based Model for Precise Air Pollution Concentration Monitoring7. An Interpretable Ensemble Model of Acute Kidney Disease Risk 8. Algorithm for Predicting Bitterness of Children's Medication9. Intelligent Identification of High Emission Road Segment Based on Large-Scale Traffic Datasets10. Construction Cost Prediction for Multi-family Housing Projects based on Support Vector Regression11. Evolution of Intellectual Structure of Data Mining Research Based on Keywords12. Development of a Cost Optimization Algorithm for Food and Flora Waste to Fleet Fuel (F4)13. A Comparative Study of Machine Learning Models in Predicting Energy Consumption14. Simulation Analysis on the Effect of Market-Oriented Rental Housing Construction Policy in Nanjing15. Accidents Analysis and Severity Prediction Using Machine Learning Algorithms16. The Use of Binary Choice Forests to Model and Estimate Discrete Choices17. Prediction and Analysis of Chinese Water Resource: A System Dynamics Approach18. Pricing and Strategies in Queuing Perspective Based on Prospect Theory19. Research on Hotel Customer Preferences and Satisfaction Based on Text Mining: Taking Ctrip Hotel Reviews as an Example20. The Power of Analytics in Epidemiology for COVID 19: Prediction, Prevalence, and Vaccine Allocation21. Electric Vehicle Battery Charging Scheduling Under the Battery Swapping Mode22. Information Design for E-Consult Between Vertically Competing Healthcare Providers23. Order Batching Problem in O2O Supermarkets24. Integrating Empirical Analysis into Analytical Framework: An Integrated Model Structure for On-Demand Transportation25. Patient Transfer Under Ambulance Offload Delays: An Approximate Dynamic Programming Approach26. COVID-19 Epidemic Forecasting and Cost-Effectiveness Analysis: A Case Study of Hong Kong27. Crowdsourcing Electrified Mobility for Omni-Sharing Distributed Energy Resources28. Covid-19 Intervention Policy Optimization Using a Multi-Population Evolutionary Algorithm29. Data-driven Joint Pricing and Inventory Management Newsvendor Problem30. Additive Manufacturing Global Challenges in the Industry 4.0 Era31. Broadening the Scope of Analysis for Peer-To-Peer Local Energy Markets to Improve Design Evaluations: An Agent-Based Simulation Approach

Über Autor(innen)

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.