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Analysing off-season tourist expenditure
Author(s) -
Daniela Soldić Frleta
Publication year - 2017
Publication title -
european journal of tourism research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.467
H-Index - 16
eISSN - 1314-0817
pISSN - 1994-7658
DOI - 10.54055/ejtr.v17i.304
Subject(s) - tourism , sample (material) , regression analysis , psychology , geography , socioeconomics , demographic economics , marketing , business , mathematics , economics , statistics , chemistry , archaeology , chromatography
The majority of researches deal with the issue of micro-level expenditure in the high season, leaving off-season expenditure an under-researched topic. Moreover, the relationship between tourist satisfaction and expenditure has been also rarely explored. Thus, the aim of this study is to determine the factors that influence the off-season expenditure levels of light spenders and heavy spenders. Among the set of predictors, various dimensions of satisfaction were tested as possible off-season expenditure predictors. Descriptive analysis was used for sample profiling, independent t-tests were conducted to determine significant differences between light and heavy spenders in terms of their characteristics, and Principal Components Analysis (PCA) was applied to identify the dimensions of tourist satisfaction with the destination’s offering. In the end, multiple regression analyses were made to identify the expenditure determinants of light and heavy spenders. The main findings indicate that different predictors influence the daily off-season expenditure levels of light and heavy spenders. When it comes to light spenders, among the set of other significant predictors, it was found that those who are more satisfied with the cleanliness and preserved environment tend to spend more in the destination in comparison with those who are less satisfied with this dimension. In the case of heavy spenders, the results revealed that satisfaction with safety, quality and hospitality turned out to be a statistically significant predictor of their daily off-season expenditure.

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