Ride acceptance behaviour of ride-sourcing drivers

Ashkrof, Peyman; Correia, Gonçalo Homem de Almeida; Cats, Oded; Arem, Bart van

doi:10.1016/j.trc.2022.103783

Cited by 21 publications

(2 citation statements)

References 49 publications

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“…A recent study investigating ride acceptance behavior in the context of ride-sourcing indicates that part- and full-time drivers have different VoTs, ranging from $35 to $81.6/h ( 60 ). The study also find that full-time drivers have a higher VoT than part-time drivers.…”

Section: Discussionmentioning

confidence: 99%

Does Crowdshipping of Parcels Generate New Passenger Trips? Evidence from the Netherlands

Cebeci,

Tapia,

Nadi

et al. 2023

Transportation Research Record: Journal of the Transportation R

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Crowdsourced shipping or crowdshipping is a promising solution to sustainable parcel delivery, owing to the potential to consolidate freight trips with preexisting passenger trips. Previous literature focuses on these consolidation benefits but does not address the possibility of new activity generation in crowdshipping. In this study, we investigate the willingness of private persons to accept shipments based on a newly generated home-based trip. We compare this to the choices of occasional carriers who build on the daily home–work commute to deliver parcels. Two stated preference experiments are conducted and a multinomial logit choice model and a latent class choice model are employed. These allow us to provide values of time of the occasional carriers, as an original contribution to the literature. The results show that commute-based carrier values of time are higher than those of home-based carriers. Concerning the trip generating power of crowdshipping, we find that low-income groups have a relatively high propensity to generate a home-based pickup and delivery trip. Finally, parcel lockers as delivery points positively influence acceptance of crowdshipping requests, as they allow for more flexibility in delivery times. Together, these results support the notion that crowdshipping can act as a potential trip generator in households.

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Section: Discussionmentioning

confidence: 99%

Does Crowdshipping of Parcels Generate New Passenger Trips? Evidence from the Netherlands

Cebeci,

Tapia,

Nadi

et al. 2023

Transportation Research Record: Journal of the Transportation R

View full text Add to dashboard Cite

show abstract

“…On the other hand, inefficient or improper taxi service management can cause numerous issues such as increased idle time, high costs of operation, and increased CO 2 emissions [16][17][18]. In the case of idle time, there are two types of idle time for the driver, moving idle time and stationary idle time.…”

Section: Introductionmentioning

confidence: 99%

Optimization of Taxi Allocation for Minimizing CO2 Emissions Based on Heuristics Algorithms

et al. 2023

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Recently, the rapid climate change caused by increasing CO2 emissions has become a global concern. Efficient transportation systems are necessary to reduce CO2 emissions in cities. Taxi services are an essential part of the transportation system, both in urban areas with high demand and in rural areas with inadequate public transportation. Inefficient taxi services cause problems such as increased idle times, resulting in increased CO2 emissions. This study proposes a taxi allocation model that minimizes taxi idle time costs for efficient taxi service operation. We also propose three heuristic algorithms to solve the proposed model. At last, we conduct a case study by using real taxi data in Nagaoka, Japan. By comparing the three algorithms, the dynamic greedy algorithm produced the best result in terms of idle time cost and CPU time. The findings indicate that by minimizing idle time costs and reducing the number of taxis, it is possible to achieve a significant 81.84% reduction in CO2 emissions within the transportation sector. Further, in order to estimate the idle time costs the sensitivity of demand is considered.

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Decision support through deep reinforcement learning for maximizing a courier's monetary gain in a meal delivery environment

Zhou,

Fotouhi,

Miller-Hooks

2024

Decision Support Systems

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Ride acceptance behaviour of ride-sourcing drivers

Cited by 21 publications

References 49 publications

Does Crowdshipping of Parcels Generate New Passenger Trips? Evidence from the Netherlands

Does Crowdshipping of Parcels Generate New Passenger Trips? Evidence from the Netherlands

Optimization of Taxi Allocation for Minimizing CO2 Emissions Based on Heuristics Algorithms

Decision support through deep reinforcement learning for maximizing a courier's monetary gain in a meal delivery environment

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