Price optimization for round trip car sharing

Car sharing, car clubs and short-term rentals could support the transition toward net zero but their success depends on them being financially sustainable for service providers and attractive to end users. Dynamic pricing could support this by incentivizing users while balancing supply and demand. We describe the usage of a round trip car sharing fleet by a continuous time Markov chain model, which reduces to a multi-server queuing model where hire duration is assumed independent of the hourly rental price. We present analytical and simulation optimization models that allow the development of dynamic pricing strategies for round trip car sharing systems; in particular identifying the optimal hourly rental price. The analytical tractability of the queuing model enables fast optimization to maximize expected hourly revenue for either a single fare system or a system where the fare depends on the number of cars on hire, while accounting for stochasticity in customer arrival times and durations of hire. Simulation optimization is used to optimize prices where the fare depends on the time of day or hire duration depends on price. We present optimal prices for a given customer population and show how the expected revenue and car availability depend on the customer arrival rate, willingness-to-pay distribution, dependence of the hire duration on price, and size of the customer population. The results provide optimal strategies for pricing of car sharing and inform strategic managerial decisions such as whether to use time- or state-dependent pricing and optimizing the fleet size. • The approach enables real-time price optimization for round-trip car sharing. • Identifies optimal prices based on fleet utilization for realistic fleet sizes. • Queueing model allows a fast evaluation of key performance indicators. • Approach supports strategic (e.g. optimizing fleet size) and operational decisions. • Results provide a better understanding of system behavior for common willingness-to-pay distributions.

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Institutions

Publication Details

Journal
European Journal of Operational Research
Published
2025-07-16
DOI
https://doi.org/10.1016/j.ejor.2025.06.024
Citations
2
Primary Topic
Transportation and Mobility Innovations
Type
article
Field-Weighted Citation Impact
1.37

Funders

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article

Price optimization for round trip car sharing

Beatriz Brito Oliveira, Rym M’Hallah, Christine Currie
2 citations
European Journal of Operational Research
Transportation and Mobility Innovations
1.37
article

Price optimization for round trip car sharing

Beatriz Brito Oliveira, Rym M’Hallah, Christine Currie
article en
2 citations

Abstract

Car sharing, car clubs and short-term rentals could support the transition toward net zero but their success depends on them being financially sustainable for service providers and attractive to end users. Dynamic pricing could support this by incentivizing users while balancing supply and demand. We describe the usage of a round trip car sharing fleet by a continuous time Markov chain model, which reduces to a multi-server queuing model where hire duration is assumed independent of the hourly rental price. We present analytical and simulation optimization models that allow the development of dynamic pricing strategies for round trip car sharing systems; in particular identifying the optimal hourly rental price. The analytical tractability of the queuing model enables fast optimization to maximize expected hourly revenue for either a single fare system or a system where the fare depends on the number of cars on hire, while accounting for stochasticity in customer arrival times and durations of hire. Simulation optimization is used to optimize prices where the fare depends on the time of day or hire duration depends on price. We present optimal prices for a given customer population and show how the expected revenue and car availability depend on the customer arrival rate, willingness-to-pay distribution, dependence of the hire duration on price, and size of the customer population. The results provide optimal strategies for pricing of car sharing and inform strategic managerial decisions such as whether to use time- or state-dependent pricing and optimizing the fleet size. • The approach enables real-time price optimization for round-trip car sharing. • Identifies optimal prices based on fleet utilization for realistic fleet sizes. • Queueing model allows a fast evaluation of key performance indicators. • Approach supports strategic (e.g. optimizing fleet size) and operational decisions. • Results provide a better understanding of system behavior for common willingness-to-pay distributions.

European Journal of Operational ResearchVol. 328(2)
Universidade do Porto (PT), King's College London (GB), INESC TEC (PT), University of Southampton (GB)
Engineering and Physical Sciences Research Council
Openalex Percentile: Top 18%
Transportation and Mobility Innovations
1.37
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