Jintao Ke, Hai Yang, Hai Wang, Yafeng Yin

eBook, ePUB

Supply and Demand Management in Ride-Sourcing Markets (eBook, ePUB)

Beschreibung

Supply and Demand Management in Ride-Sourcing Markets offers a fundamental modeling framework for characterizing ride-sourcing markets by spelling out the complex relationships among key endogenous and exogenous variables in the markets. This book establishes several economic models that can approximate matching frictions between drivers and passengers, describes the equilibrium state of ride-sourcing markets, and more. Based on these models, the book develops an optimum strategy (in terms of trip fare, wage and/or matching) that maximizes platform profit. While the best social optimum solution (for maximizing the social welfare) is generally unsustainable, this book provides options governments can use to encourage second-best solutions. In addition, the book's authors establish models to analyze ride-pooling services, with traffic congestion externalities incorporated into models to see how both new platforms and government designs can optimize operating strategies in response to the level of traffic congestion. - Serves as a foundation for subsequent research studies that investigate ride-sourcing services through mathematical modeling - Offers valuable managerial insights for ride-sourcing platforms and helps them develop more efficient and effective operating strategies - Assists the governments or social planners in designing appropriate regulatory schemes to achieve more sustainable and societally beneficial market outcomes

Technische Details

• Geräte: eReader
• ohne Kopierschutz

Barrierefreiheit

• Text-to-Speech
• E-Mail des Verlags für Barrierefreiheitsfragen: [e-mail]
• E-Mail eines vertrauenswürdigen Mittlers für Barrierefreiheitsfragen: [e-mail]
• Seitennummerierung folgt dem gedruckten Werk
• Mathematische Inhalte in MathML für assistive Technologien
• Text und Medien in logischer Lesereihenfolge angeordnet
• Navigierbarer Index mit direktem Zugriff auf Indexbegriffe
• Navigierbares Inhaltsverzeichnis für direkten Zugriff auf Text und Medien
• Keine Einschränkung der Vorlesefunktionen, außer bei spezifischen Ausnahmen

Autor

Dr. Jintao Ke received his B.S. degree (2016) in civil engineering from Zhejiang University, and his Ph.D. degree (2020) in Civil and Environment Engineering from Hong Kong University of Science and Technology. He is now an Assistant Professor at the University of Hong Kong. His research interests include smart transportation, smart city, urban computing, shared mobility, machine learning in transportation, operational management for transportation studies, etc. He has published over 20 SCI/SSCI indexed research papers in in top-tier transportation journals, such as Transportation Research Part A/B/C/E and IEEE Transactions on Intelligence Transportation System. He serves as an Advisory Board Member of Transportation Research Part C: Emerging Technologies, and referees for a few top transportation journals.Prof. Hai Yang is currently a Chair Professor in the Department of Civil and Environmental Engineering, The Hong Kong University of Science and Technology. He received his Bachelor degree from Wuhan University, China, and PhD from Kyoto University, Japan. Prof. Yang is internationally known as an active scholar in the field of transportation, with nearly 300 papers published in SCI/SSCI indexed journals. He has received a number of national and international awards, including JSCE Outstanding Paper Award (1991); Distinguished Overseas Young Investigator Award from the National Natural Science Foundation of China (2004); National Natural Science Award bestowed by the State Council of China (2011); HKUST School of Engineering Research Excellence Awards (2012); Frank M. Masters Transportation Engineering Award, American Society of Civil Engineers (ASCE) (2020); and 2021 ASCE Francis C. Turner Award. He is an elected permanent member of the International Advisory Committee of the International Symposium on Transportation and Traffic Theory.Dr. Wang is an Associate Professor in the School of Computing and Information Systems at Singapore Management University and a visiting faculty at the Heinz College of Information Systems and Public Policy at Carnegie Mellon University. He received his Bachelors degree from Tsinghua University and his PhD from MIT. His research focuses on methodologies of Analytics and Optimization, data-driven decision-making, and machine learning, and their applications in smart cities, including innovative transportation, advanced logistics, modern e-commerce, and intelligent healthcare. He serves as Associate Editor for Transportation Science and Service Science, Special Issue Editor for Transportation Research Part B, Part C, and Service Science, and Editorial Board Member for Transportation Research Part C and Part E. Dr. Wang was selected as Chan Wu & Yunying Rising Star Fellow in Transportation, received a Lee Kong Chian Research Excellence Award, was nominated for MIT's Top Graduate Teaching Award, and won the Excellent Teaching Award at SMU. During his PhD at MIT, he also served as the Co-President of the MIT Chinese Students' & Scholars Association and a Chair of MIT-China Innovation and Entrepreneurship Forum.

Produktdetails

• Verlag: Elsevier Science & Techn.
• Seitenzahl: 404
• Erscheinungstermin: 30. April 2023
• Englisch
• ISBN-13: 9780443189388
• Artikelnr.: 67865928