影響高鐵使用因素之分析

Abstract

台灣高鐵運量近幾年以來不斷的成長，而高鐵各區間的成長幅度皆不相同，故本研究以總體的觀點，蒐集高鐵2009年1月至2012年6月的營運資料，分析在不同運輸距離下，利用灰關聯分析和迴歸分析分別討論影響高鐵運量的主要因素為何，其中考慮高鐵特性的內在變數(高鐵優惠措施和高鐵班次數)和社經環境的外在變數(縣市人口數、小客車登記數、二三級產業人數、汽油價格和消費者物價指數)。灰關聯分析中，高鐵短程運輸距離上以高鐵班次數為影響最大的變數，中、長程運輸距離上以汽油價格為影響最大的變數；迴歸分析中，高鐵短程運輸距離，影響顯著的變數有縣市人口數、汽油價格和大專生優惠，高鐵中程運輸距離影響顯著的變數有縣市人口數、小客車登記數、汽油價格和高鐵班次數；高鐵長程運輸距離影響顯著的變數有縣市人口數、小客車登記數、汽油價格、早鳥優惠、大專生優惠和高鐵班次數。

Passenger volume on Taiwan’s high speed rail has been growing in recent years, and its growth rate during each interval has not remained static. Therefore, in order for this study, to provide an overall point of view, grey relational analysis, and regression analysis were employed in analysis of high speed rail use patterns over different transport distances. Several types of data used in the analysis were collected for the time period January 2009 to June 2012. These include operational data affecting high speed railway’s main factors of use, as well as internal factor variables of high speed railway characteristics (high speed railway price promotions and number of flights). In addition, external variables such as socio-economic environment (county population, registered number of small passenger vehicles, number of secondary and tertiary industrial sectors, gasoline prices, and consumer price index) were included. In the grey relational analysis, the greatest impact variables on high speed rail use are the number of flights for short-distance transport, and gasoline prices for transport over medium and long distances. In the regression analysis, variables having significant effects are county population, gasoline prices, and price promotions for college students in short-distance transport; county population, registered number of small passenger vehicles, gasoline prices, and number of flights for medium-distance transport; and county population, registered number of small passenger vehicles, gasoline prices, price promotions for college students and early birds, and number of flights for long-distance transport.