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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.

Currently, short-term car rental services (car-sharing) are a solution that is an alternative to individual motorization, which can be used in cities. With the level of sophistication of the relevant systems, there are more and more problems with their proper functioning. However, to understand the essence of some of the problems or properly introduce a new system to the market, it is important to understand how the systems work and the main relationships between the factors affecting car-sharing. This work aims to comprehensively present the most important aspects related to the functioning of car-sharing in light of the current research, as a form of compendium of knowledge about car-sharing. A review of the literature indicates that the leading areas of research in the field of car-sharing are seven topics related to the origin and history of services, the analysis of the functioning of the services market and criteria affecting the development of the relevant systems, the management of vehicle systems and location, issues related to the sustainable development of transport, IT systems, electromobility in car-sharing, and service optimization and modeling. A detailed analysis of the work carried out in this area allowed for the identification of 15 leading factors influencing car-sharing. This article supports the implementation and improvement of car-sharing services. In addition, it supports researchers during literature reviews and the search for a coherent list of the factors influencing car-sharing.

Car-sharing systems, i.e., short-term car rental services, are solutions indicated as an alternative to individual motorization; they can be used in an increasing number of cities around the world. These services, along with their intensive development, are becoming more and more complex. Due to their complexity, they involve not only an increasing number of stakeholders or infrastructure elements, but also indicate numerous links with the functioning of cities, especially smart cities. To properly implement or improve the car-sharing system, both in terms of operational issues regarding the system’s functioning or changes in the vehicle fleet, it is important to be familiar with the elements that make up car-sharing, as well as the factors that affect it. This work aims to present the factors affecting car-sharing, as well as the transport model of car-sharing services. This work fills the research gap stemming from the lack of comprehensive studies and knowledge on car-sharing. A detailed analysis of the literature shows that there are six main groups of factors affecting car-sharing: economic and technical, transport, social, environmental, organizational, and other issues; among these factors, more than 150 quantitative and qualitative criteria can be distinguished. Furthermore, the work also showed factors that are a niche in the literature and can be the basis for further research on car-sharing. Detailed familiarity with these factors could translate into increased profitability and, above all, success in the functioning of on-the-market services. This article supports the implementation and improvement of car-sharing services. In addition, it supports scientists in the preparation of scientific papers and mathematical models in the field of car-sharing and the factors that affect it.

Peer-to-peer car-sharing systems are an evolving branch of urban mobility, aligning with global trends focused on sustainable development and reducing congestion in cities. A research gap has been identified concerning the specific vehicle attributes that would encourage the public to potentially use these services. Addressing this gap, and in the context of launching a new peer-to-peer car-sharing service in Katowice, Poland, this article investigates the technical features influencing the choice of vehicles in peer-to-peer car-sharing systems, particularly from the perspective of individuals who currently do not use such platforms. The study employs Social Network Analysis (SNA) to examine the interrelationships between vehicle attributes. The analysis reveals that key factors influencing users’ decisions include fuel/energy consumption, safety features, and technological advancement, with a particular emphasis on driver assistance systems, including autonomous driving capabilities. The network structure, characterized by a relatively low density (0.2536) and a short average path length (1.872), suggests that a few central vehicle features dominate user decisions, and improvements in these key areas can quickly propagate through the decision-making process, enhancing overall user satisfaction. To validate the findings, a Gradient Boosting Regression (GBR) analysis was conducted, confirming the significance of the key factors identified by the SNA, such as fuel efficiency, battery capacity, and safety systems, thus strengthening the reliability of the results. This study underscores the growing importance of sustainability and technological innovation in the automotive industry, particularly in the context of the sharing economy. It suggests that car-sharing platforms and vehicle manufacturers should prioritize these features to meet user expectations and preferences. These findings provide valuable insights for the strategic and operational management of peer-to-peer car-sharing services, emphasizing the importance of targeted vehicle selection and user-centered innovations to improve platform performance and scalability.

This work studies how the usage of shared mobility services could be influenced by latent factors. An integrated choice and latent variable model is adopted to explore the effects of three attitudinal and perceptual factors on bike- and car-sharing choices while simultaneously investigating the causes associated with each of the latent variables. A group of Chinese commuters’ stated preference mode choice data are collected. It is found that the probability to choose bike-sharing could be positively affected by “willingness to be a green traveler” and “satisfaction with cycling environment,” and car-sharing choice is positively correlated with “advocacy of car-sharing service.” By taking into account the interaction effects between the latent variables and travel time of the two services, a significant difference is discovered on the estimated value of travel time savings (VTTS) compared with other more restrictive model specifications. The finding highlights the importance to derive different VTTS for travelers with differentiated attitudes and perceptions as the tastes toward travel time spent could vary substantially. In other words, there would be different trade-off preferences across attitudinal groups, according to which transport service operators could customize their strategies on prices and levels of service offered.

Shared cars will likely have larger annual vehicle driving distances than individually owned cars. This may accelerate passenger car retirement. Here we develop a semi-empirical lifetime-driving intensity model using statistics on Swedish vehicle retirement. This semi-empirical model is integrated with a carbon footprint model, which considers future decarbonization pathways. In this work, we show that the carbon footprint depends on the cumulative driving distance, which depends on both driving intensity and calendar aging. Higher driving intensities generally result in lower carbon footprints due to increased cumulative driving distance over the vehicle’s lifetime. Shared cars could decrease the carbon footprint by about 41% in 2050, if one shared vehicle replaces ten individually owned vehicles. However, potential empty travel by autonomous shared vehicles—the additional distance traveled to pick up passengers—may cause carbon footprints to increase. Hence, vehicle durability and empty travel should be considered when designing low-carbon car sharing systems. Shared cars are driven more, which could shorten their lifetimes. This could influence carbon dioxide emissions in car manufacturing. Sharing nonetheless reduces carbon footprints. Designing cars for durability can further enhance the benefits

Major cities in developing countries are increasingly becoming motorized. Thus, effective solutions to address the negative impacts that come with rising car-ownership are needed as part of an overall travel demand management strategy. In developed and emerging economies, shared-mobility in the form of car-sharing is becoming popular as potentially low-cost and environmentally sustainable alternative to car-ownership. Yet, our understanding of car-sharing adoption and diffusion factors in developing countries is limited. In this study, we fill this gap by examining car-sharing adoption intentions among young adults aged between 18 and 35 years in Ghana, Sub-Saharan Africa. Using structural equation modelling, we model car-sharing adoption intentions based on a framework that integrates individuals’ perception of the benefits of car-sharing, attitudes towards the environment and technology, trust of stewardship in car-sharing, perception of innovativeness of car-sharing, travel expectations and socio-demographic factors. We found that pro-technology and pro-environmental attitudes correlate positively with perceived benefits of car-sharing. Perceived benefits of car-sharing, in turn, has the largest predictive effect on intentions to car-share. Other factors, including individuals’ previous experience using Uber on-demand taxi services, gender, education, driver’s licensure and expectation of comfortable and fast travel options, all predict car-sharing adoption intentions. While there exists an interest in both station-based and free-floating car-sharing services, more of the would-be users favour the latter than the former. Also, majority of the potential adopters (62%) would join a car-sharing service within the first 1 year of its introduction. An important finding is that dissatisfaction with existing public transit services underpins car-sharing intentions, implying that relying on car-sharing alone to meet travel needs, without a holistic strategy of providing quality and affordable public transit services, could lead to unsustainable outcomes.

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.

There are a number of disruptive mobility services that are increasingly finding their way into the marketplace. Two key examples of such services are car-sharing services and ride-sourcing services. In an effort to better understand the influence of various exogenous socio-economic and demographic variables on the frequency of use of ride-sourcing and car-sharing services, this paper presents a bivariate ordered probit model estimated on a survey data set derived from the 2014–2015 Puget Sound Regional Travel Study. Model estimation results show that users of these services tend to be young, well-educated, higher-income, working individuals residing in higher-density areas. There are significant interaction effects reflecting the influence of children and the built environment on disruptive mobility service usage. The model developed in this paper provides key insights into factors affecting market penetration of these services, and can be integrated in larger travel forecasting model systems to better predict the adoption and use of mobility-on-demand services.

Car-sharing systems, i.e., short-term car rentals, are one of the solutions that can be an alternative to individual motorization in cities. However, these services must adapt well to customers’ needs to develop appropriately. Currently, there have been attempts in scientific research to make numerous optimizations of car-sharing systems, but little emphasis was placed on the type of car fleet used in the systems, which is particularly important at the stage of transformation of the automotive industry towards electric mobility. In response to this research gap, this article was dedicated to the selection of vehicles for car-sharing systems. The work focuses on users of Polish car-sharing systems who use the services of short-term vehicle rental occasionally, i.e., up to five times a year. The research made it possible to determine the types of vehicles (cars with electric, hybrid and internal combustion engines) that the users are interested in and to indicate the specific features that the cars should have. Interestingly, large family vehicles with hybrid engines turned out to be the leading ones. In turn, small city cars, so far dominant in car-sharing, turned out to be the worst choice from the point of view of occasional users. This showed that the current systems are not properly adapted to the needs of society. The results support car-sharing operators who want to upgrade their vehicle fleet accordingly to encourage the public to use car-sharing more often. It is also a guide to identifying a vehicle for fleet modernization towards hybrid and electric vehicles.