隨著共享經濟時代席捲全球，傳統私人運具持有者的特性與認知將因運具的使用權限(access)而有所改變，進而影響其旅運型態與運具選擇。本研究藉由悠遊卡數據分析2016年11月大台北地區Youbike之使用資料，首先了解各租借站點的使用量、起迄對及社群等旅運型態，再運用社會網路分析將平日晨峰與昏峰資料進行比較，並以Gephi進行視覺化方式呈現上述演化關係。此可作為相關單位針對大台北地區Youbike營運管理課題之參考。
To encounter the era of sharing economy worldwide, traditional private vehicle owners are changing their travel patterns and behavior because of use access variations. This study aims at discovering Youbike communities and their travel behavior according to peak hours in the morning and afternoon and different O-D pairs at Youbike stops in Taipei City and New Taipei City by using smart big data from 1st November to 30th November 2016. With the help of social network analysis tool GEPHI, empirical results of Youbike communities segmentation, O-D pairs volume distributions and their travel patterns are demonstrated visually. The results can be used to help Youbike operator to enhance operation and management of bike-sharing service.
