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.

https://www.mdpi.com/1996-1073/15/19/7277/pdf?version=1664862691

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

With the background of implementing carbon peaking and carbon neutralization, identifying methods to realize energy-saving and carbon reduction effectively has become an important issue in the intelligent energy-conservation manufacturing industry. During the process of achieving this goal, determining an optimal location for a low-carbon and intelligent manufacturing industrial park is a foremost decision-making problem for manufacturing corporations’ energy-efficient development. The article established a multi-criteria decision framework to assist manufacturing companies when selecting suitable industrial park sites. To begin with, an evaluation criteria framework is confirmed by literature search. Then, a fuzzy optimization model, which combines the fuzzy Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) and the fuzzy VlseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR) is presented, where fuzzy TOPSIS is used to determine the decision-maker criteria weights. Then, criteria weights are calculated by the optimization model with construction of a Lagrange function. Moreover, the fuzzy VIKOR method is applied to sort alternatives and choose the best alternative location. In addition, five alternative sites for a manufacturing company are evaluated and ranked according to the values of the ranking index as a numerical case to demonstrate the proposed framework’s application. Finally, a comprehensive analysis of diverse methods and sensitivity analyses for the volatility in criteria weights and decision-maker weights is illustrated to confirm that the framework is practicable for the problem of intelligent and sustainable manufacturing industrial park-site selection.

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A Combined Fuzzy Optimization Model for the Location of an Intelligent Energy-Efficient Manufacturing Industrial Park

In the era of upcoming European Union regulations limiting the registration of combustion cars from 2035, the development of various types of alternatives to balancing transport is on the agenda of modern cities. One of these types of services includes automated short-term car rental systems, i.e., car-sharing systems. In recent years, car-sharing services have been gaining more and more interest among operators and municipal authorities. Despite their intense activities, there are still people in society who have not used car-sharing services so far. A lot of research has been devoted to an attempt to answer their needs in the field of car-sharing, but there is a research gap in the field of detailed analyses of the fleet of cars that they would like to use. Noticing this niche, this article is dedicated to the topic of selecting vehicles for car-sharing systems from the point of view of current non-users and indicating the features that, in their opinion, are the most important parameters characterizing the given vehicles. The research was conducted for the Polish car-sharing market. The obtained results indicate that current non-users would be most interested in small, city B-class cars equipped with internal combustion or electric engines, equipped with a large luggage compartment, and meeting the highest safety standards. Interestingly, the issue of the charging time for electric vehicles was not considered crucial. The results showed that the expectations of non-user vehicles are in contradiction to the expectations of current system users. The article supports car-sharing operators who want to properly manage and modernize their fleet of vehicles to encourage the use of car-sharing among those who are currently unconvinced.

/pdf/the-expectations-towards-cars-to-be-used-in-car-sharing-1thp4n6z.pdf

The Expectations towards Cars to Be Used in Car-Sharing Services—The Perspective of the Current Polish Non-Users

Under the background of implementing green travel in response to the national energy conservation and emission reduction policy, the concept of shared travel as a new transportation mode has been promoted. This paper aims at providing a more scientific and quantitative method to explore the shared travel traffic mode and evaluating efficiency with data mining technology. Based on the analysis of the evaluation index system of the existing intelligent shared mobility, this paper firstly points out some issues in reflecting the operation efficiency of a specific shared mobility service. In order to find out the characteristics of passenger flow and propose recommend indicators, this study presents a detail analysis using data in Xiong’an new area from September 2020 to September 2021. Then, this paper proposes a time-series algorithm to identify ridesharing behavior of demand responsive (DR) bus and to recommend indicators on operation efficiency considering capacity, turnover, and time. Moreover, the definition of indicators and calculation of case study are carried out. Results show that the utilization rate of vehicle seat for DR bus was increased by 1.6–2.5 times, and the turnover efficiency was increased by about 2 times compared to private cars and taxi. In general, this paper quantitatively describes the improvement of operation efficiency brought by bus sharing, which shows that this kind of shared mobility has the attributes of public transport in a certain sense. Also, this paper shows that the above indicators are quantifiable and comparable, which is a useful supplement to the existing evaluation index system.

Ruiyao Wang

Papers

Improving bicycle sharing operations: A multi-criteria decision-making approach