Comparative Analysis of Public Bicycle Usage Patterns between Seoul's 'Ttareungi' and New York's 'Citi Bike'
- Authors
- Sim, W.Y.; Shin, B.; Shin, H.; Lee, G.; Inokuchi, H.
- Issue Date
- Dec-2024
- Publisher
- Institute of Electrical and Electronics Engineers Inc.
- Keywords
- Citi Bike; environmental factors; multiple regression analysis; Public bicycle usage; random forest; regional comparisons; seasonal variations; Ttareungi
- Citation
- 2024 Joint 13th International Conference on Soft Computing and Intelligent Systems and 25th International Symposium on Advanced Intelligent Systems, SCIS and ISIS 2024, pp 1 - 4
- Pages
- 4
- Indexed
- SCOPUS
- Journal Title
- 2024 Joint 13th International Conference on Soft Computing and Intelligent Systems and 25th International Symposium on Advanced Intelligent Systems, SCIS and ISIS 2024
- Start Page
- 1
- End Page
- 4
- URI
- https://scholarworks.bwise.kr/erica/handle/2021.sw.erica/125667
- DOI
- 10.1109/SCISISIS61014.2024.10760230
- Abstract
- This paper analyzes and compares the factors influencing the use of public bicycles in Seoul's 'Ttareungi' and New York's 'Citi Bike,' which operate within distinct cultural, environmental, and regional contexts, enabling a unique comparative study. A multiple regression analysis and a random forest analysis were performed using rental history data from both 'Ttareungi' and 'Citi Bike' as dependent variables. Independent variables included environmental factors such as weather and seasonal conditions. This study assesses the impact of these factors on bicycle usage behavior. Analysis results highlighted the significant influence of seasonal changes and weekend/holiday variables on public bicycle usage. Although both models yielded significant results, the random forest analysis demonstrated better accuracy and revealed distinct patterns in the importance of certain variables. The variation in coefficient values and variable importance between the two areas indicates that while environmental factors similarly affect bicycle usage patterns, regional climatic conditions have distinct influences. This paper proposes that incorporating variables such as personal and economic characteristics in future research could further enhance the analysis and help to develop strategies to promote public bicycle use. © 2024 IEEE.
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