Abstract
The Taiwan high-speed rail (HSR) markedly reduces the travel time from the north of Taiwan to the south, or vice versa, relative to other modes of public overland transportation. The HSR is faster than those modes, but also more expensive to ride. The pricing of HSR tickets has gained limited public acceptance because it lacks justification, indicating the need for a theoretical method for objectively justifying the ticket prices. With continuing improvements in data analytics, the computational capacity of computers, and visualization techniques, constructing a time–space model of a long-distance transportation system has become increasingly feasible, and such a model can be used to examine the time–space compression of the HSR. The first part of this investigation uses multidimensional scaling to obtain fitting coordinates based on travel times for various combinations of departure/destination HSR stations, and a geographic information system to generate time–space maps of the relative locations of those stations. Through these maps, we can directly estimate the traveling time between pairs of stations. The second part constructs a floating ticket-pricing model that accounts for the riding costs of the HSR. The model's power to explain the prices of HSR tickets is evaluated. Based on the analytical results, suggestions to the current HSR ticket fare were proposed to set the feasible rate concerning the operating, passenger-perceived, and time-space compression costs. Recommendations for future research are made.
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