The Influences of Built Environment on Public Bike Usage

• Main Authors: Yu-Tong Cheng, 鄭雨桐
• Other Authors: Jen-Jia Lin
• Format: Others
• Language: zh-TW
• Published: 2016
• Online Access: http://ndltd.ncl.edu.tw/handle/59880357917245202559

碩士 === 國立臺灣大學 === 地理環境資源學研究所 === 104 === A public bike system (PBS) is a public transport system and a green mode in urban areas. It can reduce traffic congestions, fossil fuel consumptions, air pollutions and other negative impacts of using motorized modes on public health. In addition, compared with private bikes, using public bikes has several advantages, such as short-time usage, being free of maintaining cost, and easily transferring and parking. The previous PBS studies mostly explored basic features, rental station distribution planning, spatio-temporal analysis, and users’ characteristic; however, affecting of built environment have not been comprehensively explored. This study explored the influences of built environment on metro passagers’ public bike usage via a disaggregate approach. This study reviewed two topics of previous studies including “the influences of built environment on private bike usage” and “affecting factors of public bike usage”, and interviewed various stakeholders to develop hypothetical relationships. To verify the hypotheses, this study selected four metro stations in Xinyi District, Taipei, Taiwan to conduct questionnaire surveys and used principal components analysis, binary logit models and latent class models to analyze the sample data. The empirical evidence reveals that the 7Ds of built environment attributes (density, diversity, design, distance to transit, destination accessibility, daily traffic condition, and distribution of PBS) affected public bike usage, and the effects varied between first mile trips and last mile trips. Latent class model analysis reveals that in whole trips, younger males who did not have driving license of cars but owned bikes were affected more by specific built environment, and in first mile trips and last mile trips, each of they were classified into three and two different groups and were affected by different built environment respectively. Compared with previous studies, this study makes the following contributions. First, the effects of commercial land use, distance to metro stations, travel distance, gender and vehicle ownership on public bike usage are different from that on private bike usage. Second, the 7Ds attributes are more comprehensive than the 5Ds attributes (density, diversity, design, distance to transit, and destination accessibility) in term of explaining PBS usage. Third, the disaggregate approach in this study reaches novel and detailed findings that were never discovered by the aggregate approaches of the previous research. The aggregate approaches mostly conclude that increasing residential density increases PBS usage; however, in light of disaggregate views, it is inconvenient for residents renting and returning public bikes in dense areas and this study found a negative effect existing between residential density to PBS usage. Further, the disaggregate approach can measure built environment further detailed along a commuter’s origin, destination and route. Fourth, the latent class model analysis reveals that the choice preferences of built environment affecting public bike usage are heterogeneous, and that are different from previous studies’ homogenous assumptions. This study not only filled previous research gaps but also applied the results to develop PBS-friendly urban planning strategies for local governments in order to achieve sustainable city developments.