Analysis of factors affect high speed train ridership in the united states —The acela express case study

In this study, we focus on the Acela Express, and try to find out how selected internal and external factors affect the Acela Express’s ridership. A two-stage least square regression model is introduced in order to eliminate the endogeneity problem caused by price and ridership. Also the Cochrane-Orcutt Procedure is adopted to solve autocorrelation. The result shows that ticket price and train on-time performances, which are used to being thought as important factors affect ridership become insignificant, while other factors like employment of business and professional in the Northeast Corridor areas have higher influence on high speed train ridership. The broader objective of this research is to provide policy suggestions for building of an efficient high-speed rail network that can both be profitable and solve practical problems that the contemporary transportation system faces.

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 Record created 2017-04-01, last modified 2018-01-23

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