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Pricing policy of floating ticket fare for riding high speed rail based on time-space compression

机译：基于时空压缩的乘坐高铁浮动车票的定价策略

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摘要

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.
机译：与其他公共陆上交通方式相比，台湾高铁（HSR）显着减少了从台湾北部到南部的旅行时间，反之亦然。高铁比那些模式要快，但是乘坐起来也更昂贵。高铁票价缺乏合理性，因此受到了公众的有限接受，这表明需要一种客观地证明票价合理性的理论方法。随着数据分析，计算机的计算能力和可视化技术的不断改进，构建长途运输系统的时空模型变得越来越可行，并且这种模型可用于检查高铁的时空压缩。本研究的第一部分使用多维缩放比例，基于出发/目的地HSR站点的各种组合的行驶时间获取拟合坐标，并使用地理信息系统生成这些站点的相对位置的时空图。通过这些地图，我们可以直接估计站点对之间的旅行时间。第二部分构建了一个浮动票务定价模型，该模型考虑了高铁的乘坐费用。评估了模型解释高铁票价的能力。根据分析结果，对当前的高铁票价提出了建议，以设定有关运营，乘客感知和时空压缩成本的可行比率。提出了用于未来研究的建议。

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