A Tailored Pricing Strategy for Different Types of Users in Hybrid Carsharing Systems

Considering the characteristics of different types of users in hybrid carsharing systems, in which sharing autonomous vehicles (SAVs) and conventional sharing cars (CSCs) coexist, a tailored pricing strategy (TPS) is proposed to maximize the operator’s profit and minimize all users’ costs. The fleet...

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Vydáno v:Algorithms Ročník 15; číslo 5; s. 172
Hlavní autoři: Lu, Rongqin, Zhao, Xiaomei, Wang, Yingqi
Médium: Journal Article
Jazyk:angličtina
Vydáno: Basel MDPI AG 20.05.2022
Témata:
Automobiles
Autonomous vehicles
Car sharing
Case studies
conventional sharing cars
Genetic algorithms
hybrid carsharing systems
Hybrid systems
Incentives
Maintenance costs
Nonlinear programming
Price elasticity
Pricing
Profits
sharing autonomous vehicles
tailored pricing strategy
Travel
user clustering
China
ISSN:1999-4893, 1999-4893
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Shrnutí:Considering the characteristics of different types of users in hybrid carsharing systems, in which sharing autonomous vehicles (SAVs) and conventional sharing cars (CSCs) coexist, a tailored pricing strategy (TPS) is proposed to maximize the operator’s profit and minimize all users’ costs. The fleet sizes and sizes of SAVs’ stations are also determined simultaneously. A bi-objective nonlinear programming model is established, and a genetic algorithm is applied to solve it. Based on the operational data in Lanzhou, China, carsharing users are clustered into three types. They are loyal users, losing users, and potential users, respectively. Results show the application of the TPS can help the operator increase profit and attract more users. The loyal users are assigned the highest price, while they still contribute the most to the operator’s profit with the highest number of carsharing trips. The losing users and potential users are comparable in terms of the number of trips, while the latter still makes more profit.
Bibliografie:ObjectType-Article-1
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ISSN:1999-4893
1999-4893
DOI:10.3390/a15050172