Temporal transferability: trade-off between data newness and the number of observations for forecasting travel demand
Temporal transferability: trade-off between data newness and the number of observations for forecasting travel demand
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时间可转移性：数据新颖性和预测旅行需求的观测数量之间的权衡
DOI：
10.1007/s11116-016-9707-5
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发表时间：
2017
期刊：
影响因子：
4.3
通讯作者：
三古展弘
中科院分区：
文献类型：
--
作者：
Ryoji Ito and Kenneth C. Gehrt;Ryoji Ito;Ryoji Ito and Kenneth C. Gehrt;伊藤龍史;Ryoji Ito and Kenneth C. Gehrt;Ryoji Ito;Ichiro Furukawa;古川一郎・奥谷孝司;古川一郎;金春姫・古川一郎;古川 一郎;三古展弘;三古展弘;三古展弘
最近的大量数据对于预测旅游需求至关重要。但是，在某些情况下，较旧的时间点可能比最近的时间点具有更多的数据。在时间可转移性的背景下，尚未研究具有大量观测值的旧数据与具有较少观测值的新数据之间的权衡。在本文中，通过利用在日本名古屋收集的重复横截面数据，在旅行到工作模式选择行为的背景下检查了这种权衡。利用在不同时间点（1971年、1981年和1991年）获得的不同观测数量（从50到10,000）估计的模型应用于2001年的行为预测。引导提供了具有统计意义的见解。一项发现是，即使在较旧时间点的观测数量变化很大的情况下，从最近时间点产生的预测所需的最小观测次数在统计上明显优于由较大量观测数据产生的预测，这一最小观测次数出奇地稳定。例如，1981年的300-500个稳定观测产生的预测在统计上明显优于1971年的500-10,000个广泛观测产生的预测。在旅游调查预算不断下降的时代，分析两者之间的取舍有助于确定有效的调查间隔和样本量。
Recent and large amounts of data are crucial for forecasting travel demand. However, in some cases, an older time point may have more data than a more recent time point. A trade-off between older data with a large number of observations and recent data with a smaller number of observations has not been investigated in the context of temporal transferability. In this paper, this trade-off is examined in the context of journey-to-work mode choice behaviours by utilising repeated cross-sectional data collected in Nagoya, Japan. Models estimated utilising different numbers of observations (ranging from 50 to 10,000) obtained at different time points (1971, 1981, and 1991) are applied to the forecasting of behaviours for 2001. Bootstrapping provides insights with statistical meaning. One finding is that the minimum number of observations from a recent time point that is required to produce a forecast statistically significantly better than that produced by older data with a larger number of observations is surprisingly stable, even when the number of observations from the older time point varies considerably. For example, 300–500 stable observations from 1981 produced forecasts that were statistically significantly better than that produced by 500–10,000 wide-ranging observations from 1971. Analysing the trade-off can help determine an efficient survey interval and sample size in an era of declining budgets for travel surveys.