Abstract
The shares of the domestic market of public transportation systems in Taiwan have shown a significant change since 2007 when the high-speed rail (HSR) began operating. Specifically, the passenger demands of conventional trains operated by the Taiwan Railways Administration (TRA) have been shrinking in long-distance trips but increasing in short-distance trips after the operation of the HSR system. In Taiwan, passenger rail volumes are highly dependent on the integration conditions of both the HSR and TRA stations. To analyze the impact of station integration/connection conditions on rail passenger demands, random-effects panel data models were calibrated and validated to describe the relationship between rail ridership and a vector of influence factors. Using an 11-year passenger volume dataset of both the HSR and TRA systems, the empirical study results indicated that total employment and the number of daily trains have a positive effect on rail ridership. In contrast, in- and out-of-vehicle travel times are negatively associated with rail ridership. The developed models were applied to investigate the HSR station location problem for a southern extension segment in Taiwan. The results of the scenario analysis led to suggesting that the government establish the HSR Pingtung station connected to a TRA’s minor station to maximize the total revenue of both rail systems. When establishing a new HSR station, the proposed panel data model can be applied to determine the appropriate station integration pattern that maximizes the total volume, revenue of the rail service, or both.
Published Version
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