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Title: From the users’ and the operators’ perceptions : the potential of carsharing in Hong Kong
Authors: Ahmed, S 
Xu, M 
Ching, HT 
Issue Date: 2022
Source: ICIT 2021 : proceedings of the 9th International Conference on Information Technology: IoT and Smart City : December 22-25, 2021, Guangzhou, China, p. 545-553
Abstract: Traffic congestion has been a severe issue in Hong Kong. The traffic issues have decreased the satisfaction of living and the quality of the environment. Hence, finding a solution for current issues is a top priority. The emerging trend of car-sharing has attracted attention all over the world. To explore the potential of car-sharing services in Hong Kong, it is essential to understand car-sharing services from the public and the operator's point of view. This study conducts an online survey that aims to identify the factors, such as demographics, driving habits, and car-sharing service attributes, etc., that influence the likelihood of people using carsharing services. The survey collected 213 responses for the multiple regression model to identify the factors that affect people using a car-sharing service. The results indicated that people with less monthly income, fewer owned vehicles, less reliance on public transport, and believe more in car-sharing service is an alternative to car ownership and online booking is an advantage to car-sharing service are more likely to use car-sharing service in Hong Kong. In addition, the attitude toward the carsharing service of most of the respondents is positive. However, the survey results and interview findings show that the publicity of car-sharing is inadequate, and lack of support from the local government is causing low familiarity of the concept, which resulted in low participation of the public in car-sharing services. Therefore, recommendations to the operators are given at the end of this paper to better develop the car-sharing service in Hong Kong.
Keywords: Car-sharing
Multiple linear regression model
Transportation survey
Publisher: Association for Computing Machinery
ISBN: 978-1-4503-8497-1
DOI: 10.1145/3512576.3512669
Rights: © 2021 Association for Computing Machinery. This is the author's version of the work. It is posted here for your personal use. Not for redistribution. The definitive Version of Record was published in ICIT '21: Proceedings of the 2021 9th International Conference on Information Technology: IoT and Smart City, https://doi.org/10.1145/3512576.3512669.
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