Department of Tourism Science, Tokyo Metropolitan University, Hachioji, Tokyo, Japan.
PLoS One. 2022 Apr 22;17(4):e0267453. doi: 10.1371/journal.pone.0267453. eCollection 2022.
Seasonality of tourism demand witnesses fluctuations over multiple years. The fluctuations and seasonality often cause seasonal pattern changes. This study presents a new seasonal measurement that considers the stability of seasonal patterns. The measurement is based on a seasonal index and expressed interval-valued data, which are a kind of symbolic data. As a case study, the new measurements are calculated from Japanese overnight data from 2011 to 2019 and the results classify the seasonal patterns of 47 prefectures using a hierarchical clustering method for interval-valued data based on Ward's method. The analysis results indicate that there are differences in not only seasonal patterns but also their stability between domestic overnight demand and inbound overnight demand. The analysis procedure suggested in this study could be helpful in organizing numerous other unstable seasonal patterns.
旅游需求的季节性在多年间存在波动。这些波动和季节性通常会导致季节性模式的变化。本研究提出了一种新的季节性度量方法，该方法考虑了季节性模式的稳定性。该度量方法基于季节性指数和表示区间值数据，区间值数据是一种符号数据。作为案例研究，从 2011 年到 2019 年的日本过夜数据中计算出新的度量方法，使用基于 Ward 方法的区间值数据的层次聚类方法对 47 个县的季节性模式进行分类。分析结果表明，国内过夜需求和入境过夜需求的季节性模式及其稳定性存在差异。本研究中提出的分析程序有助于组织其他大量不稳定的季节性模式。
