土耳其旅游景点与旅游流量关系的空间分析

IF 2.9 Q2 HOSPITALITY, LEISURE, SPORT & TOURISM
D. Karagöz, S. Aktaş, Y. Kantar
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引用次数: 1

摘要

本研究旨在考察旅游景点(自然、文化和历史)与旅游流量之间的关系。在这项研究中,使用了土耳其西南安纳托利亚地区6个省和110个子省的二次数据,当地和外国游客都曾到访过。其中四个省拥有通往爱琴海和地中海的海岸线。在此背景下,110个副省的游客过夜数据以及印刷和在线材料和游客过夜数据被用于识别景点。在本研究中,映射分析、局部和全局Moran’s I、经典回归和空间回归模型均受益匪浅。主要介绍了旅游景点通过地图的溢出效应和旅游流量的分布。当考察旅游景点与旅游流量之间的关系时,我们的分析结果表明,全球莫兰I值为0.25,这110个次省在旅游流量方面可能相似。基于global Moran的I值确定是否存在全局聚类,然后使用光谱聚类方法确定相似的聚类,即旅游流量方面的相似子省。此外,使用局部空间分析指标(LISA)和光谱聚类方法确定了游客流量方面的邻里关系和邻里互动。最后,在研究领域,使用经典回归模型和空间回归模型解释了文化、历史和自然旅游景点与旅游流量之间的关系。与相应的OLS模型相比,基于空间的模型,特别是SEM,提高了模型性能。研究发现,旅游流量与该地区的自然和历史景点呈正相关,而与文化景点呈负相关。讨论了目的地管理的影响。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Spatial analysis of the relationship between tourist attractions and tourist flows in Turkey
This study is intended to examine the relationship between tourist attractions (natural, cultural and historical) and tourist flows. In the study, secondary data for six provinces and 110 sub-provinces in the Southwestern Anatolia region of Turkey, visited by local and foreign tourists, are used. Four of these provinces have a coastline to the Aegean Sea and the Mediterranean. In this context, overnight data of tourists for 110 sub-provinces and the printed and online materials and overnight data of tourists are used to identify attractions. In this study, mapping analysis, local and global Moran’s I, the classical regression and spatial regression models are benefited. Primarily, the spillover of attractions through maps and the distribution of tourist flows are presented in the study. When the relationship between tourist attractions and tourist flows are examined, the results of our analyses show that the Global Moran’s I value is 0.25 and that those 110 sub-provinces could be similar in terms of tourist flow. It was determined whether there is a global clustering based on Global Moran’s I value, and then the similar clusters, that is, similar sub-provinces in terms of tourist flow, were determined using the spectral clustering method. In addition, the neighborhood relationship and neighborhood interactions in terms of tourist flow are determined using local indicators of spatial analysis (LISA) alongside the Spectral Clustering Method. Finally, in the study field, the relationship between cultural, historical, and natural tourist attractions and tourist flow is explained using the classical regression model and the spatial regression model. The spatial-based models, especially the SEM, improve the model performance compared to the corresponding OLS model. In conclusion, it is found that there is a positive correlation between tourist flows and natural and historical attractions of the region, but a negative relationship between tourist flows and cultural attractions. Destination management implications are discussed.
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来源期刊
European Journal of Tourism Research
European Journal of Tourism Research HOSPITALITY, LEISURE, SPORT & TOURISM-
CiteScore
5.00
自引率
8.70%
发文量
50
审稿时长
25 weeks
期刊介绍: The European Journal of Tourism Research is an open access academic journal in the field of tourism, published by Varna University of Management, Bulgaria. Its aim is to provide a platform for discussion of theoretical and empirical problems in tourism. Publications from all fields, connected with tourism such as tourism management, tourism marketing, tourism sociology, psychology in tourism, tourism geography, political sciences in tourism, mathematics, tourism statistics, tourism anthropology, culture and tourism, heritage and tourism, national identity and tourism, information technologies in tourism and others are invited.
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