Research on Order Allocation Strategies for Ride-Hailing Platforms Considering Passenger Order Cancellations During Order Overflow
The rise of ride-hailing services has brought new riding experiences for passengers and exerted a profound impact on the traditional taxi market. To enhance patrol efficiency, increase revenue, and promote sustainable development in the taxi industry, traditional taxis have actively undergone transf...
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MDPI AG
2025-03-01
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| Series: | Applied Sciences |
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| Online Access: | https://www.mdpi.com/2076-3417/15/6/3243 |
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| author | Yan Xia Wuyong Qian Chunyi Ji |
| author_facet | Yan Xia Wuyong Qian Chunyi Ji |
| author_sort | Yan Xia |
| collection | DOAJ |
| description | The rise of ride-hailing services has brought new riding experiences for passengers and exerted a profound impact on the traditional taxi market. To enhance patrol efficiency, increase revenue, and promote sustainable development in the taxi industry, traditional taxis have actively undergone transformation and adopted an integrated “online-offline” operating model, combining online order acceptance with offline order-taking. Meanwhile, a considerable number of orders are canceled by passengers after being accepted, leading to a waste of platform capacity, reduced order dispatch efficiency, and additional empty-running costs for drivers. This issue is particularly prominent during peak hours with order overflow. Based on the changes in taxi order acceptance during order overflow, this paper constructs a model for passenger order cancellation probability during peak hours, examines the relationship between regional order density and the proportion of offline taxi order acceptance, discusses the impact of regional order density changes on the passenger order cancellation probability and stakeholder returns, and proposes optimal order dispatch strategies for ride-hailing platforms with different order densities. Additionally, it analyzes more optimal taxi operating models under varying arrival states. The research findings provide more scientific and efficient operational recommendations for ride-hailing platforms and taxis, promoting sustainable development in the entire travel market and thereby contributing to a greener and more efficient travel environment. |
| format | Article |
| id | doaj-art-23af750fd56648abb269f47d99f09e57 |
| institution | Kabale University |
| issn | 2076-3417 |
| language | English |
| publishDate | 2025-03-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Applied Sciences |
| spelling | doaj-art-23af750fd56648abb269f47d99f09e572025-08-20T03:43:33ZengMDPI AGApplied Sciences2076-34172025-03-01156324310.3390/app15063243Research on Order Allocation Strategies for Ride-Hailing Platforms Considering Passenger Order Cancellations During Order OverflowYan Xia0Wuyong Qian1Chunyi Ji2Business School, Jiangnan University, Wuxi 214122, ChinaBusiness School, Jiangnan University, Wuxi 214122, ChinaBusiness School, Jiangnan University, Wuxi 214122, ChinaThe rise of ride-hailing services has brought new riding experiences for passengers and exerted a profound impact on the traditional taxi market. To enhance patrol efficiency, increase revenue, and promote sustainable development in the taxi industry, traditional taxis have actively undergone transformation and adopted an integrated “online-offline” operating model, combining online order acceptance with offline order-taking. Meanwhile, a considerable number of orders are canceled by passengers after being accepted, leading to a waste of platform capacity, reduced order dispatch efficiency, and additional empty-running costs for drivers. This issue is particularly prominent during peak hours with order overflow. Based on the changes in taxi order acceptance during order overflow, this paper constructs a model for passenger order cancellation probability during peak hours, examines the relationship between regional order density and the proportion of offline taxi order acceptance, discusses the impact of regional order density changes on the passenger order cancellation probability and stakeholder returns, and proposes optimal order dispatch strategies for ride-hailing platforms with different order densities. Additionally, it analyzes more optimal taxi operating models under varying arrival states. The research findings provide more scientific and efficient operational recommendations for ride-hailing platforms and taxis, promoting sustainable development in the entire travel market and thereby contributing to a greener and more efficient travel environment.https://www.mdpi.com/2076-3417/15/6/3243ride-hailing platformtaxiorder allocationorder overflow |
| spellingShingle | Yan Xia Wuyong Qian Chunyi Ji Research on Order Allocation Strategies for Ride-Hailing Platforms Considering Passenger Order Cancellations During Order Overflow Applied Sciences ride-hailing platform taxi order allocation order overflow |
| title | Research on Order Allocation Strategies for Ride-Hailing Platforms Considering Passenger Order Cancellations During Order Overflow |
| title_full | Research on Order Allocation Strategies for Ride-Hailing Platforms Considering Passenger Order Cancellations During Order Overflow |
| title_fullStr | Research on Order Allocation Strategies for Ride-Hailing Platforms Considering Passenger Order Cancellations During Order Overflow |
| title_full_unstemmed | Research on Order Allocation Strategies for Ride-Hailing Platforms Considering Passenger Order Cancellations During Order Overflow |
| title_short | Research on Order Allocation Strategies for Ride-Hailing Platforms Considering Passenger Order Cancellations During Order Overflow |
| title_sort | research on order allocation strategies for ride hailing platforms considering passenger order cancellations during order overflow |
| topic | ride-hailing platform taxi order allocation order overflow |
| url | https://www.mdpi.com/2076-3417/15/6/3243 |
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