Multi-Criteria Decision Analysis during Selection of Vehicles for Car-Sharing Services—Regular Users’ Expectations

Car-sharing systems, i.e., automatic, short-time car rentals, are among the solutions of the new mobility concept, which in recent years has gained popularity around the world. With the growing interest in services in society, their demands for the services offered to them have also increased. Since...

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Main Author: Katarzyna Turoń
Format: Article
Language:English
Published: MDPI AG 2022-10-01
Series:Energies
Subjects:
Online Access:https://www.mdpi.com/1996-1073/15/19/7277
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author Katarzyna Turoń
author_facet Katarzyna Turoń
author_sort Katarzyna Turoń
collection DOAJ
description Car-sharing systems, i.e., automatic, short-time car rentals, are among the solutions of the new mobility concept, which in recent years has gained popularity around the world. With the growing interest in services in society, their demands for the services offered to them have also increased. Since cars play a key role in car-sharing services, the fleet of vehicles should be properly adapted to the needs of customers using the systems. Due to the literature gap related to the procedure of proper selection of vehicles for car sharing and the market need for car-sharing service operators, this work has been devoted to the selection of car models for car sharing from the perspective of users constantly using the systems (regular users). This paper considered the case of the Polish who are constantly using car-sharing service systems. Vehicle selection was classified as a multi-faceted, complex problem, which is why one of the ELECTRE III multi-criteria decision support methods was used for this study. This study focused on the classification of vehicles from the user’s perspective. Twelve modern and most popular car models in 2021 with internal combustion, electric and hybrid engines were considered. The results indicate that the best choice from the point of view of regular customers is large cars (representing vehicle classes C and D), with a large luggage compartment capacity, the highest possible ratio of engine power to vehicle weight, and the ratio of engine power to energy consumption. Importantly, small urban vehicles, which ideologically should be associated with car-sharing services due to occupying as little urban space as possible, were classified as the worst in the ranking. The results support car-sharing operators during the process of completing or upgrading their vehicle fleets.
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spelling doaj.art-2505932314da4273a6d6f5d7152ee8f42023-11-23T20:16:13ZengMDPI AGEnergies1996-10732022-10-011519727710.3390/en15197277Multi-Criteria Decision Analysis during Selection of Vehicles for Car-Sharing Services—Regular Users’ ExpectationsKatarzyna Turoń0Department of Road Transport, Faculty of Transport and Aviation Engineering, Silesian University of Technology, 8 Krasińskiego Street, 40-019 Katowice, PolandCar-sharing systems, i.e., automatic, short-time car rentals, are among the solutions of the new mobility concept, which in recent years has gained popularity around the world. With the growing interest in services in society, their demands for the services offered to them have also increased. Since cars play a key role in car-sharing services, the fleet of vehicles should be properly adapted to the needs of customers using the systems. Due to the literature gap related to the procedure of proper selection of vehicles for car sharing and the market need for car-sharing service operators, this work has been devoted to the selection of car models for car sharing from the perspective of users constantly using the systems (regular users). This paper considered the case of the Polish who are constantly using car-sharing service systems. Vehicle selection was classified as a multi-faceted, complex problem, which is why one of the ELECTRE III multi-criteria decision support methods was used for this study. This study focused on the classification of vehicles from the user’s perspective. Twelve modern and most popular car models in 2021 with internal combustion, electric and hybrid engines were considered. The results indicate that the best choice from the point of view of regular customers is large cars (representing vehicle classes C and D), with a large luggage compartment capacity, the highest possible ratio of engine power to vehicle weight, and the ratio of engine power to energy consumption. Importantly, small urban vehicles, which ideologically should be associated with car-sharing services due to occupying as little urban space as possible, were classified as the worst in the ranking. The results support car-sharing operators during the process of completing or upgrading their vehicle fleets.https://www.mdpi.com/1996-1073/15/19/7277car sharingcar-sharing servicese-car-sharing systemselectric car sharinghybrid car sharingshort-term car rentals
spellingShingle Katarzyna Turoń
Multi-Criteria Decision Analysis during Selection of Vehicles for Car-Sharing Services—Regular Users’ Expectations
Energies
car sharing
car-sharing services
e-car-sharing systems
electric car sharing
hybrid car sharing
short-term car rentals
title Multi-Criteria Decision Analysis during Selection of Vehicles for Car-Sharing Services—Regular Users’ Expectations
title_full Multi-Criteria Decision Analysis during Selection of Vehicles for Car-Sharing Services—Regular Users’ Expectations
title_fullStr Multi-Criteria Decision Analysis during Selection of Vehicles for Car-Sharing Services—Regular Users’ Expectations
title_full_unstemmed Multi-Criteria Decision Analysis during Selection of Vehicles for Car-Sharing Services—Regular Users’ Expectations
title_short Multi-Criteria Decision Analysis during Selection of Vehicles for Car-Sharing Services—Regular Users’ Expectations
title_sort multi criteria decision analysis during selection of vehicles for car sharing services regular users expectations
topic car sharing
car-sharing services
e-car-sharing systems
electric car sharing
hybrid car sharing
short-term car rentals
url https://www.mdpi.com/1996-1073/15/19/7277
work_keys_str_mv AT katarzynaturon multicriteriadecisionanalysisduringselectionofvehiclesforcarsharingservicesregularusersexpectations