Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/174145 
Year of Publication: 
2016
Citation: 
[Journal:] UTMS Journal of Economics [ISSN:] 1857-6982 [Volume:] 7 [Issue:] 1 [Publisher:] University of Tourism and Management [Place:] Skopje [Year:] 2016 [Pages:] 71-83
Publisher: 
University of Tourism and Management, Skopje
Abstract: 
Tourism seasonality is the major characteristic of tourism industry, a well know but less understood phenomenon. Seasonal fluctuations of tourism demand are implying numerous negative implications affecting tourist destination, tourist operators and tourist demand. Almost every tourist destination is facing seasonality, but the most pronounced seasonal concentration of tourist activities have costal destinations which attract tourist demand motivated primary by the 3S - sun, sand and sea concept. Seasonality in business operation is the most challenging in tourist companies with a large share of fixed capacity, as the hotel accommodating sector. Former research of causes of seasonality, implications of seasonality and potential strategies to combat seasonality had methodological flaw. Tourism product, as a product with seasonal characteristic, requires analysis of performance by season. The objective of this paper is to classify tourist season in coastal tourist destinations regarding hotel occupancy rates. This is the first attempt to empirically classify tourist season. Sample surveys are 218 hotels located in Dalmatia, Croatia. Cluster analysis on hotel occupancy rate date was conducted, whereby the statistical significance between seasons were testes by Friedman test and the statistical significance between destinations were tested by F-test and ANOVA. Further, factor analysis was conducted to test the achieved results. Regarding the research result tourist season can be divided into three seasons: low, medium and high. Low season as the longest consisting of five months: January, February, March, November and December, middle season as the shortest consisting of three months: April, May and October and high season consisting of four months: June, July, August and September. Research findings are a significant contribution to tourism theory and practice.
Subjects: 
tourism seasonality
classification of tourist season
cluster analysis
factor analysis
JEL: 
L83
Document Type: 
Article

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