建成環境對公共自行車使用之影響

The Influences of Built Environment on Public Bike Usage

鄭雨桐(Yu-Tong Cheng)

指導教授 ： 林楨家

國立臺灣大學/理學院/地理環境資源學研究所/碩士(2016年)

https://doi.org/10.6342/NTU201600967

摘要

公共自行車系統(public bike system, PBS)作為都市內之公共非機動綠色運具，有助於降低機動運具造成的交通壅塞、石化能源消耗、廢氣排放與公共衛生的負面影響，且相對於一般自行車有短時間租借、不用保養、停放方便和轉乘的優勢。公共自行車過去的研究多是在基本特性、車輛配置與站點選址、流量時空分布和使用者特性方面，對於「建成環境」的影響，則著墨較少。
本研究之目的在於了解建成環境對捷運使用者轉乘使用公共自行車的影響。並使用個體研究取徑探討其影響。首先，針對相關文獻分成「建成環境與私人自行車使用」與「公共自行車使用影響因素」兩個主題進行回顧，之後再進一步透過個案訪談佐證因果關係以提出理論假說。為了驗證假說關係，本研究挑選了臺北市信義區捷運101/世貿站、捷運象山站、捷運永春站和捷運市政府站為調查空間範疇，以問卷調查資料做為樣本，了解實際公共自行車使用的旅運行為。再以主成份分析、二項羅吉特模式和潛在類別模式進行分析。
研究結果證實建成環境7Ds特性(密度、多樣性、設計、離大眾運輸場站距離、迄點可及性、日常交通狀況和公共自行車站分布)會影響公共自行車使用，並且在轉乘的前段旅次和後段旅次的影響效果有所不同。潛在類別模式發現在總旅次中沒有汽車駕照但擁有私人自行車的年輕男性群體較會受到特定的建成環境影響，而在前段旅次和後段旅次上也可分別將樣本分為三個和兩個不同的群體，其分別受到不同的建成環境所影響。與過去相關文獻比較發現，公共自行車受到商業土地使用比例、離捷運站距離、旅次距離、性別和運具持有(私人自行車、機車、汽車)的影響與私人自行車相異；研究結果也證實7Ds特性相較於過去的5Ds(密度、多樣性、設計、離大眾運輸場站距離和迄點可及性)能更完整地顯示影響公共自行車使用的建成環境特徵。本研究使用個體研究取徑，其與過去文獻採用總體研究取徑的相異之處主要呈現在居住密度上，不同於過去總體研究認為居民越多，公共自行車使用越多的論點，個體研究取徑從個人旅運的角度來看，發現借還車的便利性考量，會使得居住密度負向地影響公共自行車使用；此外，個體研究取徑相較於總體，能進一步量測到旅運者在其實際旅行起迄點和旅行路線上之建成環境，以更細緻地探討建成環境對旅運行為的影響關係；最後，透過潛在類別模式的分析，本研究證實個體在建成環境對公共自行車使用的選擇偏好是異質性的，而非過去的同質性假設。除了補足過去文獻的不足之外，本研究依據實證關係進一步提出二項建立公共自行車友善都市的都市規劃策略之建議供市政規劃單位參考，以達到都市永續發展之目的。

關鍵字

建成環境 ； 公共自行車 ； 主成份分析 ； 羅吉特模式 ； 潛在類別模式

並列摘要

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.

並列關鍵字

built environment ； public bike ； principal components analysis ； logit model ； latent class model

參考文獻

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