.png){kind=icon}
返回
Analysing cluster evolution using repeated cross-sectional ordinal data
.png){kind=icon}
OA
AI
DOI：10.1016/j.tourman.2018.06.028.png)
.png){kind=icon}
.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
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.
Keyword:
Repeated cross-sectional data
Matching
Evolution
Ordinal data
Fuzzy data
Fuzzy clustering
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
12.4
论文数:
5.7K
被引数:
3.4W
机构
引用论文
.png){kind=icon}
分享收藏
查看更多内容