Cluster-mapping procedure for tourism regions based on geostatistics and fuzzy clustering: example of Polish districts
Justyna Majewska , Szymon Truskolaski
AbstractIn tourism, the phenomenon of spatial agglomeration (concentration of economic activity) spreads beyond the borders of the territorial units. It is referred to as geographic ‘spillovers’ that enhances spatial interdependence and functional relationship of neighbouring regions. Within the standard procedure of cluster-mapping, only concentration inside a territorial unit may be analysed which is a source of biased results in tourism studies. However, tourist agglomeration centres sometimes occur at the juncture of territorial units and the economic entities located in them form spatial clusters with a different degree of membership to several centres of agglomerations located in the neighbourhood. Therefore, we propose to measure ‘inter-regional’ agglomeration in tourism providing modification of spatial autocorrelation measures (regarding neighbourhood and distance). In order to measure neighbourhood more precisely, we use geostatistical information (global positioning system (GPS) coordinates of tourism entities) and geographically weighted fuzzy clustering approach (FGWC). We examine the method on the example of Polish districts (NUTS-4) using database of 131,338 firms registered in section I (accommodation and food services) of Polish Classification of Activity in 2015. The results proved that a novel method of cluster-mapping considering spatial dependency combined with geographic information system (GIS) and FGWC method increases the accuracy of the identification of tourism clusters (inter-regional agglomeration).
|Journal series||Current Issues in Tourism, ISSN 1368-3500, e-ISSN 1747-7603, (N/A 140 pkt)|
|Publication size in sheets||1|
|Keywords in Polish||aglomeracja w turystyce, klastry inter-regionalne, grupowanie rozmyte, geostatystyka, autokorelacja przestrzenna, powiaty w Polsce|
|Keywords in English||Tourism agglomeration; inter-regional clusters; fuzzy clustering; geostatistics; spatial autocorrelation; Polish districts|
|Score||= 140.0, 06-04-2020, ArticleFromJournal|
|Publication indicators||= 0; : 2018 = 2.125; : 2017 = 3.462 (2) - 2017=3.516 (5)|
|Uwagi||First online: 30 Apr 2018|
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