Pricing and penalty/compensation strategies of a taxi-hailing platform
Smartphone-based taxi-hailing applications (apps) bring about significant changes to the taxi market in recent years. As platforms that connect customers and taxi drivers, taxi-hailing apps charge different rates for completed orders and penalize reservation-cancellation behaviors with different fines. In this paper, an equilibrium framework is proposed to depict the operations of a regulated taxi market on a general network with both street-hailing and e-hailing modes for taxi services, considering the reservation-cancellation behaviors of e-hailing customers. Based on the proposed equilibrium model, an optimal design problem of taxi-hailing platform’s pricing and penalty/compensation strategies is formulated and solved by the penalty successive linear programming algorithm. To demonstrate the practicability of the proposed solution algorithms and the optimal pricing and penalty/compensation schemes, large-scale numerical examples are presented based on a realistic taxi network of Beijing.
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Availability:
- Find a library where document is available. Order URL: http://worldcat.org/issn/0968090X
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Supplemental Notes:
- Abstract reprinted with permission of Elsevier.
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Authors:
- He, Fang
- Wang, Xiaolei
- Lin, Xi
- Tang, Xindi
- Publication Date: 2018-1
Language
- English
Media Info
- Media Type: Web
- Features: Appendices; Figures; References; Tables;
- Pagination: pp 263-279
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Serial:
- Transportation Research Part C: Emerging Technologies
- Volume: 86
- Issue Number: 0
- Publisher: Elsevier
- ISSN: 0968-090X
- Serial URL: http://www.sciencedirect.com/science/journal/0968090X
Subject/Index Terms
- TRT Terms: Mobile applications; Motivation; Optimization; Pricing; Ridesharing; Smartphones; Taxicabs
- Uncontrolled Terms: Data platform
- Subject Areas: Data and Information Technology; Finance; Highways; Operations and Traffic Management; Public Transportation;
Filing Info
- Accession Number: 01661000
- Record Type: Publication
- Files: TRIS
- Created Date: Feb 22 2018 9:20AM