由於地球暖化與能源不足問題，全世界皆致力於節能減碳、推行使用綠色能源，交通運輸方面也積極響應綠色運輸的發展，鼓勵民眾外出減少使用私人機動車輛，盡量採用環保價值較高之非機動車輛(自行車)與大眾運輸系統。由於自行車可彌補大眾運輸系統缺乏可及性問題，大眾運輸系統可作為自行車短程運輸之延伸，故整合自行車與大眾運輸系統為未來都市運輸發展之策略。過去鮮少有文獻著墨於影響「通勤族」使用自行車轉乘大眾運輸系統關鍵因素之研究。因此本研究將採實證分析，以臺北捷運之通勤族旅客為對象，並運用結構方程模式建構通勤族採自行車接駁捷運系統影響因素之架構，探討潛在變數間因果關係。研究對象分為兩類，一為目前採用自行車以外之運具轉乘捷運之乘客，簡稱潛在使用者；另一為目前使用自行車作為捷運接駁運具之乘客，稱為現有使用者。研究結果推測：潛在使用者方面，政策面對於舒適面(0.432)、成本面(0.531)、安全面(0.285)與可及性(0.395)具有直接正向影響效果；舒適面對於成本面(0.268)與便利面(0.588)具有直接正向影響效果；成本面對於便利面(0.306)具有直接正向影響效果；安全面對於可及性(0.297)具有直接正向影響效果。現有使用者方面，環境安全面對於可及性(0.322)與便利面(0.213)具有直接正向影響效果；舒適面對於成本面(0.571)與便利面(0.247)具有直接正向影響效果；可及性對於成本面(0.231)具有直接正向影響效果；號誌控制面對於成本面(0.466)與便利面(0.276)具有直接正向影響效果；成本面對於便利面(0.515)具有直接正向影響效果。 The reason of global warming and insufficient energy, worldwide are dedicating to reduce carbon emissions and promoting the use green energy. On the aspect of transportation, developing green transportation will be a positive orientation. When going outside, encourage people to take public transportation systems or higher environmental value of non-motorized (bikes) vehicles as more as possible instead of private motor vehicle. According to the public transportation and bike could supplement each other, integration of bike and public transportation might be a strategy of urban development. In the past, there were fewer studies to discuss the influence factors of commuters using bike to connect to public transportation systems. Therefore, this research will adopt an empirical analysis of the Taipei MRT commuters travelers as objects, and using Structural Equation Modeling methodology to construct the influence factors of bicycle commuters connecting to MRT transit system, and verify the relationship among these variable. The subjects were divided into two categories, the one is using other modes of transportation (except bike) connecting to MRT transit system passenger, which called potential users another is currently using bike to connect to MRT passenger, called existing users. The empirical results show that potential users, policy is positive relationship between comfort(0.432), cost(0.531), safety(0.285) and accessibility(0.395) comfort is positive relationship between cost(0.268) and convenience(0.588) cost is positive relationship between convenience(0.306) safety is positive relationship between accessibility(0.297). Existing users, environment safety is positive relationship between accessibility(0.322) and convenience(0.213) comfort is positive relationship between cost(0.571) and convenience(0.247) accessibility is positive relationship between cost(0.231) signal control is positive relationship between cost(0.466) and convenience(0.276) cost is positive relationship between convenience(0.515).
