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題名 臺北市公共自行車使用特性與空間分佈型態之趨勢變化分析
Analysis on the Trend Change of the Use Characteristics and Spatial Distribution Patterns of Public Bicycles in Taipei City作者 鍾凱如
Chung, Kai-Ju貢獻者 白仁德<br>甯方璽
Pai, Jen-Te<br>Ning, Fang-Shii
鍾凱如
Chung, Kai-Ju關鍵詞 公共自行車系統
大數據
空間自相關分析
地理加權迴歸
多尺度地理加權迴歸
Public bike system
Big data
Spatial autocorrelation analysis
Geographically Weighted Regression
Multiscale Geographically Weighted Regression日期 2022 上傳時間 1-Aug-2022 18:22:27 (UTC+8) 摘要 近年來遭受能源消耗與氣候變遷導致之環境衝擊，各國城市積極推動擁有低污染、低耗能、可及性高又兼具運動休閒特性等優勢之公共自行車系統的發展，而我國最為完善且較具規模者為臺北市「YouBike微笑單車」。許多系統營運至今已日漸成熟，掌握時空變化下使用者之租借需求，有效管理供需平衡以提高整體租借量，應為系統長期經營之關鍵。然而，現有關於公共自行車之研究大多透過短期橫斷面數據或以抽樣、問卷調查形式評估其使用特性及影響因素。是故，本研究目的在於運用臺北市YouBike系統自2016年1月至2021年5月之站點資訊與租借資料，瞭解長時間下使用者之租借情況與分佈型態，並考量縱向時間與空間差異概念，建構公共自行車使用需求趨勢模型，評估不同因素對使用量之關係與影響程度，從而提供系統營運規劃與策略建議。本研究首先爬梳文獻且歸納公共自行車有關議題及使用之影響因素，其次以統計分析、空間自相關分析，初步觀察使用量的時間變動趨勢及空間分佈型態變化。最後，根據歷年使用量、平日及假日使用變化量之縱貫性與橫斷面資料型態，分別以追蹤資料模型、全域型與地域型迴歸建構使用需求趨勢模型。實證結果顯示，歷年租借時間趨勢相似且大部分為短程使用，而熱門租借站點與騎乘路線大多鄰近捷運站和學校周邊。另外，公共自行車使用量之顯著影響因素為人口數、從業員工人數、站點數量、假日與降雨天數，而使用變化量之顯著影響因素則為人口數、與捷運站點距離及站點數量。尤其從地域型迴歸模型結果得知，不同變數考量空間特徵下之影響程度和顯著性檢定皆有所差異，且應用多尺度地理加權迴歸可更有效地解釋空間變異下不同因素對於公共自行車使用之影響，據此提出系統站點佈局、容量調整、車輛調度以及自行車道路網規劃等相關策略建議，以期提升整體公共自行車使用量。
In recent years, due to the environmental impact caused by energy consumption and climate change, various cities have actively promoted the development of public bike systems with the advantages of low pollution, low energy consumption, high accessibility and both sports and leisure characteristics. "YouBike" in Taipei City is the most developed and large-scale one. As many systems have become more mature in operation, it should be the key to the long-term operation of the system to grasp the rental needs of users under the change of time and space, and effectively manage the balance between supply and demand to improve the overall rental. However, most of the existing studies on public bicycles evaluate their usage characteristics and influencing factors through short-term and cross-sectional data or in the form of sampling and questionnaire surveys. Therefore, the purpose of this research is to use the site and rental data of the Taipei YouBike system from January 2016 to May 2021 to understand the rental situation and distribution patterns of users over a long period of time. Furthermore, the study considered the concept of longitudinal time and space difference to construct a demand trend model for public bicycle use, and to evaluate the relationship and influence of different factors on the use of bicycles, so as to provide system operation planning and strategic suggestions.The study firstly reviewed the literature and summarized the issues of public bicycles and the influencing factors of the use, then used statistical analysis and spatial autocorrelation analysis to preliminarily observe the temporal trends and spatial distribution patterns of bicycle usage. Finally, according to the longitudinal and cross-sectional data of usage over the years, usage changes on weekdays and holidays, the panel data model, global and regional regressions were used to construct usage demand trend models.The results showed that the trend of rental time over the years is similar and most of them are used for short distances, while popular sites and riding routes are mostly near MRT stations and schools. In addition, the significant factors affecting the use of public bicycles are the population, the number of employees, the number of stations, the number of holidays and rainy days. The significant factors affecting the usage changes are the population, the distance from the MRT station, and the number of stations. Especially from the results of the regional regression model, it is known that the degree of influence and significance test of different variables considering spatial characteristics are different, and the application of multiscale geographically weighted regression can more effectively explain the effect of different factors on the use of public bicycles under spatial variation. 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國立政治大學
地政學系
109257008資料來源 http://thesis.lib.nccu.edu.tw/record/#G0109257008 資料類型 thesis dc.contributor.advisor 白仁德<br>甯方璽 zh_TW dc.contributor.advisor Pai, Jen-Te<br>Ning, Fang-Shii en_US dc.contributor.author (Authors) 鍾凱如 zh_TW dc.contributor.author (Authors) Chung, Kai-Ju en_US dc.creator (作者) 鍾凱如 zh_TW dc.creator (作者) Chung, Kai-Ju en_US dc.date (日期) 2022 en_US dc.date.accessioned 1-Aug-2022 18:22:27 (UTC+8) - dc.date.available 1-Aug-2022 18:22:27 (UTC+8) - dc.date.issued (上傳時間) 1-Aug-2022 18:22:27 (UTC+8) - dc.identifier (Other Identifiers) G0109257008 en_US dc.identifier.uri (URI) http://nccur.lib.nccu.edu.tw/handle/140.119/141225 - dc.description (描述) 碩士 zh_TW dc.description (描述) 國立政治大學 zh_TW dc.description (描述) 地政學系 zh_TW dc.description (描述) 109257008 zh_TW dc.description.abstract (摘要) 近年來遭受能源消耗與氣候變遷導致之環境衝擊，各國城市積極推動擁有低污染、低耗能、可及性高又兼具運動休閒特性等優勢之公共自行車系統的發展，而我國最為完善且較具規模者為臺北市「YouBike微笑單車」。許多系統營運至今已日漸成熟，掌握時空變化下使用者之租借需求，有效管理供需平衡以提高整體租借量，應為系統長期經營之關鍵。然而，現有關於公共自行車之研究大多透過短期橫斷面數據或以抽樣、問卷調查形式評估其使用特性及影響因素。是故，本研究目的在於運用臺北市YouBike系統自2016年1月至2021年5月之站點資訊與租借資料，瞭解長時間下使用者之租借情況與分佈型態，並考量縱向時間與空間差異概念，建構公共自行車使用需求趨勢模型，評估不同因素對使用量之關係與影響程度，從而提供系統營運規劃與策略建議。本研究首先爬梳文獻且歸納公共自行車有關議題及使用之影響因素，其次以統計分析、空間自相關分析，初步觀察使用量的時間變動趨勢及空間分佈型態變化。最後，根據歷年使用量、平日及假日使用變化量之縱貫性與橫斷面資料型態，分別以追蹤資料模型、全域型與地域型迴歸建構使用需求趨勢模型。實證結果顯示，歷年租借時間趨勢相似且大部分為短程使用，而熱門租借站點與騎乘路線大多鄰近捷運站和學校周邊。另外，公共自行車使用量之顯著影響因素為人口數、從業員工人數、站點數量、假日與降雨天數，而使用變化量之顯著影響因素則為人口數、與捷運站點距離及站點數量。尤其從地域型迴歸模型結果得知，不同變數考量空間特徵下之影響程度和顯著性檢定皆有所差異，且應用多尺度地理加權迴歸可更有效地解釋空間變異下不同因素對於公共自行車使用之影響，據此提出系統站點佈局、容量調整、車輛調度以及自行車道路網規劃等相關策略建議，以期提升整體公共自行車使用量。 zh_TW dc.description.abstract (摘要) In recent years, due to the environmental impact caused by energy consumption and climate change, various cities have actively promoted the development of public bike systems with the advantages of low pollution, low energy consumption, high accessibility and both sports and leisure characteristics. "YouBike" in Taipei City is the most developed and large-scale one. As many systems have become more mature in operation, it should be the key to the long-term operation of the system to grasp the rental needs of users under the change of time and space, and effectively manage the balance between supply and demand to improve the overall rental. However, most of the existing studies on public bicycles evaluate their usage characteristics and influencing factors through short-term and cross-sectional data or in the form of sampling and questionnaire surveys. Therefore, the purpose of this research is to use the site and rental data of the Taipei YouBike system from January 2016 to May 2021 to understand the rental situation and distribution patterns of users over a long period of time. Furthermore, the study considered the concept of longitudinal time and space difference to construct a demand trend model for public bicycle use, and to evaluate the relationship and influence of different factors on the use of bicycles, so as to provide system operation planning and strategic suggestions.The study firstly reviewed the literature and summarized the issues of public bicycles and the influencing factors of the use, then used statistical analysis and spatial autocorrelation analysis to preliminarily observe the temporal trends and spatial distribution patterns of bicycle usage. Finally, according to the longitudinal and cross-sectional data of usage over the years, usage changes on weekdays and holidays, the panel data model, global and regional regressions were used to construct usage demand trend models.The results showed that the trend of rental time over the years is similar and most of them are used for short distances, while popular sites and riding routes are mostly near MRT stations and schools. In addition, the significant factors affecting the use of public bicycles are the population, the number of employees, the number of stations, the number of holidays and rainy days. The significant factors affecting the usage changes are the population, the distance from the MRT station, and the number of stations. Especially from the results of the regional regression model, it is known that the degree of influence and significance test of different variables considering spatial characteristics are different, and the application of multiscale geographically weighted regression can more effectively explain the effect of different factors on the use of public bicycles under spatial variation. Based on this, the relevant strategic suggestions on system site layout, capacity adjustment, vehicle scheduling, and bikeway planning are proposed, in order to increase the overall use of public bicycles. en_US dc.description.tableofcontents 第一章 緒論 1第一節 研究動機與目的 1第二節 研究範疇 6第三節 研究方法 8第四節 研究內容與流程 11第二章 文獻回顧 15第一節 公共自行車系統之發展歷程 15第二節 公共自行車使用需求影響因素之相關研究 38第三節 公共自行車使用需求分析之相關研究 53第四節 公共自行車大數據之相關應用 60第五節 小結 66第三章 研究設計 71第一節 研究架構 71第二節 資料來源說明與整理 73第三節 研究模型設定 76第四章 公共自行車使用特性與需求趨勢模型分析 95第一節 公共自行車使用量之時間變動趨勢變化 95第二節 公共自行車使用量之空間分佈型態變化 104第三節 公共自行車使用需求趨勢模型分析 132第四節 模型結果分析與應用 165第五章 結論與建議 171第一節 結論 171第二節 建議 176參考文獻 179附錄一 公共自行車使用量追蹤資料模型結果與診斷 195附錄二 公共自行車使用變化量全域型模型結果與診斷 198附錄三 公共自行車使用變化量地域型模型結果與診斷 202 zh_TW dc.format.extent 22459557 bytes - dc.format.mimetype application/pdf - dc.source.uri (資料來源) http://thesis.lib.nccu.edu.tw/record/#G0109257008 en_US dc.subject (關鍵詞) 公共自行車系統 zh_TW dc.subject (關鍵詞) 大數據 zh_TW dc.subject (關鍵詞) 空間自相關分析 zh_TW dc.subject (關鍵詞) 地理加權迴歸 zh_TW dc.subject (關鍵詞) 多尺度地理加權迴歸 zh_TW dc.subject (關鍵詞) Public bike system en_US dc.subject (關鍵詞) Big data en_US dc.subject (關鍵詞) Spatial autocorrelation analysis en_US dc.subject (關鍵詞) Geographically Weighted Regression en_US dc.subject (關鍵詞) Multiscale Geographically Weighted Regression en_US dc.title (題名) 臺北市公共自行車使用特性與空間分佈型態之趨勢變化分析 zh_TW dc.title (題名) Analysis on the Trend Change of the Use Characteristics and Spatial Distribution Patterns of Public Bicycles in Taipei City en_US dc.type (資料類型) thesis en_US dc.relation.reference (參考文獻) 一、中文參考文獻（一）期刊論文白仁德、劉人華，2014，「大眾運輸導向建成環境特性對捷運運量影響之研究-以臺北捷運為實證對象」，『建築與規劃學報』，15(2/3)：111-128。行政院經濟建設委員會經濟研究處，2008，「永續能源政策綱領－節能減碳行動方案」，『台灣經濟論衡』，6(10)：8-17。江穎慧、莊喻婷、張金鶚，2017，「臺北市公共自行車場站對鄰近住宅價格之影響」，『運輸計劃季刊』，46(4)：399-428。李沃牆、李惠娜、劉雅鳳，2013，「公股銀行放款集中度對經營績效及逾放之影響分析」，朝陽商管評論，12(2)，93-112。李恆綺、楊大輝、楊明德、巫妮蓉，2016，「公共腳踏車使用者特性及偏好分析 -以高雄市 C-Bike 為例」，『運輸計劃季刊』，45(4)：331-356。呂千慈、鍾易詩、馮正民，2018，「環境空間與站點數對公共自行車租借量之影響分析」，『運輸學刊』，30(2)：113-137。李俊毅、王聖鐸，2019，「空氣品質、天氣概況與公共自行車租借行為之關聯性分析：以臺北市為例」，『航測及遙測學刊』，24(3)：161-171。邱皓政，2017，「多元迴歸的自變數比較與多元共線性之影響：效果量、優勢性與相對權數指標的估計與應用」，『臺大管理論叢』，27(3)： 65-108。林宜甲、黃柏霖，2017，「利用空間性局部指標(LISA)分析高雄市C-Bike站點與空間相關性初探」，『經營管理學刊』，12&13：125-141。張國楨，張文菘，曾露儀，2012，「都市土地利用與人口老化對基層醫療資源分布之影響：以台北市為例」，『地理研究』，56：25-40。張凱翔、張立韋、陳亮羽、林長郁，2015，「YouBike微笑單車熱門租借點(以台北市為例)」，『地理資訊系統季刊』，9(4)：26-28。張文菘、陳嘉惠、張國楨，2017，「應用空間統計於桃園地區土地利用變遷因素分析」，『地理研究』，67：137-161。張舜淵、王劭暐、鍾敦沛，2020，「都會區捷運整體路網規劃作業之研究」，『都市交通半年刊』，35(1)：15-42。廖興中、呂佩安，2013，「臺灣縣市政府貪腐現象之空間自相關分析」，『臺灣民主季刊』，10(2)：39-72。趙家芸、王聖鐸，2019，「以開放街圖與開放資料分析公共自行車使用率—以臺北市為例」，『航測及遙測學刊』，24(4)：245-255。蔡佳菁、劉修祥，2010，「高雄成為自行車友善城市之論述」，『城市發展半年刊』，10：34-50。鍾智林、黃晏珊，2016，「開放式數據為基礎之公共自行車營運特性分析－以臺北YouBike為例」，『運輸學刊』，28(4)：455-478。羅孝賢、劉力銘，2010，「接駁型公共自行車租賃系統辦理經驗與未來展望」，『都市交通』，25(1)：56-61。（二）碩博士論文白詩滎，2013，「臺北市公共自行車使用行為特性分析與友善環境建構之研究」，國立政治大學地政學系碩士學位論文。林尚德，2003，「以反應空間不穩定性為基礎之土地估價模型建立」，國立成功大學都市計劃學系碩士論文。余書枚，2009，「公共自行車租借系統選擇行為之研究」，國立交通大學交通運輸研究所碩士學位論文。李舒媛，2018，「以悠遊卡大數據探討YouBike租賃及轉乘捷運之使用者行為」，淡江大學運輸管理學系運輸科學碩士班學位論文。李冠頡，2020，「基於智慧票卡資料探索旅次及活動型態：土地利用與大眾運輸系統空間特性之觀點」，國立臺灣大學土木工程學系碩士論文。李婕瑜，2021，「以個體行為導向模型模擬自行車路網對公共自行車系統使用之影響與環境效益－以臺北市為例」，國立成功大學環境工程學系碩士論文。邱辰，2015，「從空間角度分析公共自行車系統對站點周邊土地活動影響」，國立臺灣大學工學院土木工程學系碩士論文。林浩瑋，2016，「悠遊卡數據應用於大眾運輸乘客旅運型態之研究」，淡江大學運輸管理學系運輸科學碩士班碩士論文。倪如霖，2016，「公共自行車租借量之影響因素分析－地理加權迴歸和函數資 料分析方法之應用」，國立交通大學運輸與物流管理學系碩士論文。張辰尉，2017，「臺北市公共自行車站點需求分析之研究」，國立政治大學地政學系碩士學位論文。黃雅燕，2006，「中國大陸地級城市經濟成長收斂性假說驗證 －空間 Panel 計量的應用」，世新大學財務金融學系碩士學位論文。曾韋齊，2013，「城市公共自行車租賃系統定價研究－以臺北微笑單車為例」，淡江大學運輸管理學系運輸科學碩士班學位論文。楊孝博，2011，「鐵路車站旅客運輸需求之實證性研究－地理加權迴歸之應用」，國立臺灣大學地理環境資源學系碩士學位論文。蔡宛容，2013，「運用地理加權迴歸方法探討都市土地混合使用空間分佈之影響因素」，國立成功大學都市計劃學系碩士論文。蔡宗佑，2017，「公共自行車之替代性與互補性－以臺北都會區為例」，國立交通大學 運輸與物流管理學系。鄭雨桐，2016，「建成環境對公共自行車使用之影響」，國立臺灣大學地理環境資源學系研究所碩士學位論文。戴威，2018，「臺北市YouBike開放大數據為基礎的公共自行車旅次與租賃站特性分析」，淡江大學運輸管理學系運輸科學碩士班學位論文。羅惟元，2008，「以悠遊卡交易資料探索公車路線之旅客起迄」，淡江大學運輸管理學系運輸科學碩士班學位論文。（三）其他水敬心，2020，「YouBike 2.0於臺灣大學校總區試辦計畫營運績效評估與需求分析」，109年2月17日至109年6月30日。李佳倩，2018，「臺北市 YouBike 使用特性報乎你知」，『統計應用分析報告』，臺北市政府交通局統計室。張學聖，2009，「都市地區人為災害空間特性與災害風險區劃設之研究」，補助優秀新進教師學術研究計畫。二、外文參考文獻（一）期刊論文Andreas Kaltenbrunner, Rodrigo Meza, Jens Grivolla, Joan Codina, Rafael Banchs, 2010, “Urban cycles and mobility patterns: Exploring and predicting trends in a bicycle-based public transport system”, Pervasive and Mobile Computing, 6: 455-466.Alexander Rixey, 2013, “Station-Level Forecasting of Bike Sharing Ridership: Station Network Effects in Three U.S. Systems”, Transportation Research Record Journal of the Transportation Research Board, 2387(-1): 46-55.Ahmadreza Faghih-Imani, Naveen Eluru, Ahmed M. 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