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Analysing cluster evolution using repeated cross-sectional ordinal data

机译:使用重复的横截面序数数据分析聚类演化

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This study contributes to the existing literature on tourism market segmentation by providing a new matching-clustering procedure that allows patterns of behaviours to be identified using repeated cross-sectional surveys. By extracting equivalent samples over time, the matching method allows inter-temporal cluster analyses to be performed so that a deeper insight into a phenomenon can be obtained beyond the traditional aggregate level of understanding. The paper provides a step-by-step description of the matching-clustering procedure that can be easily replicated, both within and outside the tourism field, when repeated cross-sectional data are available. From a practical and managerial perspective, the proposed procedure helps destination managers and municipalities to describe and verify the efficacy of policy and strategies adopted over years without the necessity to rely on longitudinal surveys, which are often difficult to conduct.
机译:这项研究通过提供一种新的匹配聚类程序,允许使用重复的横截面调查来识别行为模式,从而为有关旅游市场细分的现有文献做出了贡献。通过随着时间的推移提取等效样本,匹配方法可以进行跨时域聚类分析,从而可以超越传统的总体理解水平获得对现象的更深入了解。本文提供了匹配-聚类过程的分步说明,当有重复的横截面数据可用时,可以很容易地在旅游领域内外进行复制。从实践和管理的角度来看,拟议的程序可帮助目的地管理者和市政当局描述和验证多年来采取的政策和策略的有效性,而不必依靠通常难以进行的纵向调查。

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