• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.15 no.4
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• pp.1-11
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• 2016

The purpose of this study is to analyze the effect of public transit accessibility on the Carsharing use demand. By utilizing the rental historical DB of Greencar which is operated in Suwon city and public transit GIS DB, the use demand models for Carsharing by rental offices are built and analyzed in accordance with public transit accessibility. The result indicates 73% of walking as a majority, 3% cycling, and 20% using buses and urban railways to access Carsharing rental offices. The goodness of fit of Carsharing use models reflecting accessibility to buses and railways is verified as 0.818 which proves that public transit accessibility is a significant variable. Therefore, it is verified that installing Carsharing rental offices where public transit transfer is convenient can possibly increase the use demand. Especially, while accessibility to buses is verified as a significant variable out of other public transit means, the accessibility to urban railways is verified as not significant. This suggests that a variety of complementary policies such as transfer discount policy and one-way transfer return policy are necessary in between urban railways and Carsharing in order to promote mutual use demand in accordance with the other public transit means. This study result is yet the basic research on Carsharing, however it is expected to contribute to improvement of transfer demand in between different public transit means.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.16 no.5
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• pp.49-59
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• 2017

In this study, We analyzed the characteristics of carsharing use and revealed the environmental factors influencing carsharing use using the records of carsharing had been operated in Incheon during 2016. The records show a higher ratio of male users, a big portion of 20s and 30s, and ascending trends in the use of elderly people and short distances compared to the past. We analyzed the relationship between carsharing use and neighborhood environmental factors using the negative binomial regression model. It was found that carsharing was more active in areas where have many public transportation users and higher portion of residential buildings. Therefore, it was concluded that these areas can be suitable candidates for placing new carsharing rental sites to expect more active carsharing use.

• Information Systems Review
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• v.25 no.1
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• pp.75-91
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• 2023

Thanks to information technologies, sharing economy services offer a new way of consumption. Carsharing appeared as a novel type of service that transformed the conventional way of personal transportation, from owning a vehicle to using an on-demand service. Allowing users to use a vehicle without owning a car, carsharing provides various social benefits such as the reduction of resource allocation inefficiencies and the alleviation of transportation problems. To strengthen such positive aspects of carsharing service, it is essential to understand an individual's service usage pattern and reveal factors that affect users' reuse behavior. This study investigates the factors that have an influence on carsharing reuse of users applying RFMC (Recency, Frequency, Monetary, and Clumpiness) model, the popular model for understanding the reuse likelihood of customers. Using data from a leading carsharing service provider in South Korea, we empirically analyze the effect of RFMC on carsharing reuse behavior. The findings show that recency and monetary values are negatively related to reuse while frequency is positively related to carsharing service reuse. Moreover, the impact of recency and monetary value are more salient whereas the impact of frequency is smaller among users with higher clumpiness. Based on these findings, this study elaborates on theoretical and practical implications.

• Journal of Korean Society of Transportation
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• v.30 no.2
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• pp.29-42
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• 2012

Recently, traffic congestion has become serious due to increase of private car usages. Carsharing or other innovative public transportation systems were developed to alleviate traffic congestion and carbon emissions. These measures can make the traffic environment more comfortable, and efficient. Cloud Transportation System (CTS) is a recent carsharing model. User can rent an electronic vehicles with various traffic information through the CTS. In this study, a concept, vision and scenarios of CTS are introduced. And, authors analyzed the location of CTS rental stations and estimated CTS demands. Firstly, we analyze the number of the population, employees, students and traffic volume in study areas. Secondly, the frequency and utilization time are examined. Demand for CTS in each traffic zone was estimated. Lastly, the CTS rental station location is determined based on the analyzed data of the study areas. Evaluation standard of the determined location includes accessibility and density of population. And, the number of vehicles and that of parking zone at the rental station are estimated. The result suggests that Haewoondae Square parking lot would be assigned 11 vehicles and 14.23 parking spaces and that Dongbac parking lot be assigned 7.9 vehicles and 10.29 parking spaces. Further study requires additional real-time data for CTS to increase accuracy of the demand estimation. And network design would be developed for redistribution of vehicles.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.12 no.6
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• pp.22-28
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• 2013

This study aims to propose the location selection method of car-sharing services in Daejeon Metropolitan city. In order to select locations for car-sharing, Daejoen area was divided in $500m{\times}500m$ cell size using GIS Arc/Info 10, and input factors which may affect car-sharing service were determined, and then each input factor was standardized for analysis. The weight for each input factor was determined through experts' survey and index of goodness of fit was estimated in each cell ($500m{\times}500m$ size) using AHP method. Also, This study proposed the method to select 30 service facility location using Location-allocation Model in Network Analysis module. The proposed method for the location selection of car-sharing service in this study can be used for preliminary data for initial car-sharing introduction. Henceforward, appropriate demand forecasting and economic evaluation for the location selection of car-sharing service are needed for the further study.