Factors affecting bike-sharing system demand by inferred trip purpose: Integration of clustering of travel patterns and geospatial data analysis

Meesung Lee, Sungjoo Hwang, Yunmi Park, Byungjoo Choi

Research output: Contribution to journalArticlepeer-review

2 Scopus citations

Abstract

Cycling is a sustainable form of transportation that can reduce car usage and benefit both individuals and society. Bike-sharing systems (BSSs) help to position cycling as a daily transportation option and have been widely established in many countries. Previous studies have investigated the association between urban environmental factors and BSSs’ demand to promote the broader use of BSSs and determine whether demand is affected by various factors. However, research on the effects of the urban environment on BSS demand according to the trip purpose (e.g., commuting and leisure) is rare due to the difficulty in understanding users’ trip purposes. In this regard, recent advancements in big data technologies make massive BSSs trip data available to the public, which is useful for in-depth analyzing BSS travel patterns and inferring the trip purposes. This study thus analyzes to what extent demand is affected by urban environmental factors for different trip purposes, focusing on Seoul Bike, through the integration of clustering users’ travel patterns and analyzing geospatial data affecting demand. By observing trip data, BSS trips were clustered into short-distance travel for utilitarian purposes and longer-distance roaming for recreational purposes. The utilitarian trips were more affected by the large floating population and high land-use mix, and they were more concentrated during the rush hours in the crowded areas, while the leisure trips were more concentrated in secluded residential areas and were close to the waterfront. This study can contribute to establishing plans to increase the demand for and optimize the operation of BSSs.

Original languageEnglish
Pages (from-to)847-860
Number of pages14
JournalInternational Journal of Sustainable Transportation
Volume16
Issue number9
DOIs
StateAccepted/In press - 2021

Keywords

  • Bike-sharing system
  • clustering
  • demand analysis
  • geospatial analysis
  • urban big data
  • urban environment

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