Analyzing Factors Affecting the Usage of High Speed Rail
|關鍵字:||高鐵運量;灰關聯分析;迴歸分析;Passenger volume of high speed rail;Grey relational analysis;Regression analysis|
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.