• KSCE Journal of Civil and Environmental Engineering Research
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• v.43 no.3
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• pp.353-362
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• 2023

In this research, the usage status and characteristics of user big data of Mobike, a dockless bike sharing service introduced in Suwon city, were analyzed, and multiple regression analysis was performed to identify factors influencing the demand for dockless bike sharing service. For analysis, usage data of bike sharing system in Suwon city in 2019 were obtained, and they were organized by areas. As a result of analyzing the characteristics of the influencing factors selected for each area, it was found that the extension of bicycle roads shows high in areas with high demand for bicycles or adjacent areas. Also, the population of 10-30's shows high in areas with high demand for bicycles or adjacent areas. In addition, it was analyzed that the use of bike sharing system is high in areas with high maintenance rate of bicycle roads and large-scale residential and commercial facilities near residential districts and adjacent areas. As a result of the multiple regression analysis, it is analyzed that length of bicycle·pedestrian roads (non-separated), population of 10-30's, number of railway stations, number of schools, number of commercial facilities, number of industrial facilities factors were significant. It is expected that it may be possible to create an environment in which citizens want to use dockless bike sharing service by identifying factors affecting the number of stationless shared bicycles. Also, the results of data analysis are considered to be contributing to policy data to promote the use of dockless bike sharing.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.20 no.6
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• pp.14-25
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• 2021

With the spread of COVID-19 and the government policy of social distancing, the demand for subways and buses is decreasing, whereas the demand for public bicycles and personal transportation is increasing. Hence, research is needed to understand the characteristics of this phenomenon and to prove the statistical reliability of the correlation between the subway and shared bicycle demands. In this study, the correlation between the number of confirmed COVID-19 cases and the replacement rate of subway and public bicycle demands was examined, but the statistical significance was not significant. However, during the period of September to December 2020, in which the number of confirmed COVID-19 cases in Seoul started to increase rapidly, there was a correlation between the number of confirmed COVID-19 cases and the replacement ratio. If the number of confirmed COVID-19 cases increases by more than a certain number, public bicycles are expected to play a significant role as alternates to the subways. It is expected that the role of public bicycles will increase, and that it is possible to suggest the direction of transportation operation and policy establishment for the continuation of COVID-19 countermeasures in field demonstration after elementary technology development. It is also expected that this study will suggest a direction for future development and policymaking.