Discovering spatiotemporal usage patterns of a bike-sharing system by type of pass: a case study from Seoul.

ABSTRACT: Determining bike-sharing usage patterns and their explanatory factors on demand is essential for the effective and efficient operation of bike-sharing systems (BSSs). Most BSSs provide different passes that vary with the period of use. However, studies investigating the differences in usage patterns are rare compared to studies conducted at the system level, even though explanatory factors depending on the type of pass may cause different characteristics in terms of usage patterns. This study explores the differences in the usage patterns of BSSs and the impact of explanatory factors on the demand depending on the type of pass. Various machine learning techniques, including clustering, regression, and classification, are used, in addition to basic statistical analysis. As observed, long-te

SUBMITTER: Kim K 

PROVIDER: S-EPMC9942648 | biostudies-literature | 2023 Feb

REPOSITORIES: biostudies-literature