• 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.