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As the sharing economy develops in sustainable transportation, car-sharing platforms improve the allocation efficiency of idle cars to customers. However, as the travel demand increases, and the vehicle type becomes various, the sharing market faces a new challenge to satisfy the customers' diverse needs for quality-differentiated cars. Each customer would like to choose the right car type, while the manufacturing firm and the e-commerce platform should set the right car price for profit maximization. How to match the platform's product line with the customer's choice behavior becomes a problem for all the stakeholders in the sharing economy. From the perspective of customer heterogeneity, we establish a game-theoretic framework to study product line optimization in business-to-consumer (B2C) and consumer-to-consumer (C2C) sharing. We solve the optimal quality decision and the optimal pricing strategy for the manufacturing firm and the e-commerce platform in the sharing economy. In numerical experiments, we investigate how the sensitivity of the quality and the cost can jointly influence the profits of sustainable transportation. Our findings show that within the product line, the firm's selling profit in the C2C sharing is negatively influenced by the sharer's valuation, while the platform's sharing profit in the B2C sharing is independent of either buyer's valuation. We give some policy implications for scholars, practitioners, and policymakers in the sharing economy and point out some limitations and recommendations for the product line design., Author(s): Zichen Zhang (corresponding author) [1,2]; Yuan Wang [3] 1. Introduction The sharing economy has developed rapidly in recent years, especially in developing countries. According to the Chinese National Development [...]

Car sharing helps promote new drive systems to early adopters, and its market share has grown continuously worldwide. However, in rural areas, car sharing still faces challenges, such as sparse populations. In urban areas, previous research has identified underlying factors in the use of car sharing. However, these findings are yet to be transferred to rural areas. Three different methodological approaches were applied in a rural municipality in southern Germany to better understand the acceptance of electric car sharing in rural areas. Firstly, a survey was conducted with 190 participants to provide an overview of underlying factors in the acceptance of electric car sharing. Secondly, interviews were conducted with 21 participants to obtain a deeper insight into these factors. Finally, a cocreation workshop was conducted with 17 participants to identify an electric car sharing model for rural areas. The results showed that performance expectancy, hedonic motivation, and facilitating conditions were the most important factors in the use of electric car sharing in rural areas, at least when presented at a conceptual level. Furthermore, an electric car sharing service with a station-based system and a service provider to distribute vehicles to stations across the municipality's districts was voted as the most suitable model by participants. As the car sharing system was not yet implemented at the time of the survey, future studies should examine the underlying factors in the use of electric car sharing systems in rural areas at later stages of development. Moreover, the economic and technical viability of the developed electric car sharing service should be tested., Author(s): Jan Silberer (corresponding author) [1]; Maja Mrso [1]; Thomas Bäumer [1]; Patrick Müller [1] 1. Introduction Car sharing plays a major role in promoting innovative new drive systems (e.g., [...]

Shared mobility is a service that allows users to share various transportation modes and use them with reservations when necessary. It started with private automotive car-sharing and ride-sharing services. Currently, it operates on a wider range, including personal mobility devices such as electric bicycles and scooters. The purpose of this study is to derive a direction for providing future shared mobility services through analysis of factors affecting the usage intention of both current and prospective users. The survey targets 753 citizens living in Gyeonggi Province, Korea. The survey period is from February 12, 2020, to February 26, 2020. In this study, a logistic regression analysis is conducted to investigate the factors affecting the use intention of shared mobility. The analysis results show that gender, car ownership, and education, among variables reflecting socio-demographic characteristics, have significant effects on intention to use shared mobility. Moreover, we find that experience factors, including mainly used transportation modes, ownership of shared mobility device, past experience in similar services, satisfaction of existing shared mobility services, and distance from the home to the nearest bus stop, are also statistically influential. The analysis results are expected to lay the foundation for the introduction of shared mobility services and can be used as data for planning smart mobility services in the future., Author(s): Eunjeong Ko [1]; Hyungjoo Kim [2]; Jinwoo Lee (corresponding author) [1] 1. Introduction As negative impacts of autoownership have gradually increased, such as significant energy consumption, traffic congestion, inefficient [...]

Shared mobility is a service that allows users to share various transportation modes and use them with reservations when necessary. It started with private automotive car-sharing and ride-sharing services. Currently, it operates on a wider range, including personal mobility devices such as electric bicycles and scooters. The purpose of this study is to derive a direction for providing future shared mobility services through analysis of factors affecting the usage intention of both current and prospective users. The survey targets 753 citizens living in Gyeonggi Province, Korea. The survey period is from February 12, 2020, to February 26, 2020. In this study, a logistic regression analysis is conducted to investigate the factors affecting the use intention of shared mobility. The analysis results show that gender, car ownership, and education, among variables reflecting socio-demographic characteristics, have significant effects on intention to use shared mobility. Moreover, we find that experience factors, including mainly used transportation modes, ownership of shared mobility device, past experience in similar services, satisfaction of existing shared mobility services, and distance from the home to the nearest bus stop, are also statistically influential. The analysis results are expected to lay the foundation for the introduction of shared mobility services and can be used as data for planning smart mobility services in the future., Author(s): Eunjeong Ko [1]; Hyungjoo Kim [2]; Jinwoo Lee (corresponding author) [1] 1. Introduction As negative impacts of autoownership have gradually increased, such as significant energy consumption, traffic congestion, inefficient [...]

This work explores the characteristics of the usage behaviour of station-based car-sharing users based on the actual operation data from a car-sharing company in Gansu, China. We analyse the characteristics of the users' demands, such as usage frequency and order quantity, for a day with 241 h time intervals. Results show that most car- sharing users are young and middle-aged men with a low reuse rate. The distribution of users' usage during weekdays shows noticeable morning and evening peaks. We define two attributes, namely, the latent ratio and persistence ratio, as classification indicators to understand the user diversity and heterogeneity thoroughly. We apply the k-means clustering algorithm to group the users into four categories, namely, lost, early loyal, late loyal, and motivated users. The usage characteristics of lost users, including maximum rental time and travel distance, minimum percentage of same pickup and return station, and low percentage of locals, have noticeable differences from those of the other users. Late loyal users have lower rental time and travel distance than those of the other users. This manifestation is in line with the short-term lease of shared cars to complete short- and medium- distance travel design concepts. We also propose a model that predicts the driver cluster based on the decision tree. Numerical tests indicate that the accuracy is 91.61% when the user category is predicted four months in advance using the observation-to-judgment period ratio of 3 : 1. The results in this study can support enterprises in user management., 1. Introduction The increasing number of vehicles has caused congestion and deterioration of the environment in many large cities worldwide. A new and convenient energy-saving transportation mode called car-sharing with [...]

This study aims to explore factors that affect carsharing demand characteristics in different time periods based on EVCARD transaction data, which is the largest station-based one-way carsharing program in Shanghai, China. Monthly usage intensity and degree of usage imbalance are used as proxies of demand. This study uses three groups of independent variables: carsharing station attributes, built environment (density, diversity, design, and destination accessibility), and transportation facilities. The adaptive elastic net regression is developed to identify factors that influence carsharing usage intensity and degree of usage imbalance after factor selection using extra-randomized-tree algorithm. Finally, a station layout is proposed according to both usage intensity and degree of imbalance. The main results of this study are presented as follows: (1) different effects of built environment and transportation factors cause dynamic demand across different time periods; (2) factors with positive and negative effect on carsharing demand are divided clearly for guidance of the carsharing station layout; (3) public parking space leads to more personal vehicle trip compared to a carsharing trip; and (4) as public transportation, the relationship of the metro and carsharing is complementary. However, the bus stop and carsharing have a competitive relationship. This study provides a carsharing layout method based on both usage intensity and degree of imbalance. Furthermore, several policies concerning carsharing are proposed., 1. Introduction Carsharing service allows users to avoid the money and time cost of car ownership, such as maintenance, insurance, and finding parking space. It offers more flexible car travel [...]