2018
DOI: 10.1016/j.jdmm.2016.07.002
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Destinations and crisis. Profiling tourists' budget share from 2006 to 2012

Abstract: Tourist spending behavior is not only relevant in terms of volume but also in terms of trip budget composition or allocation (share or proportion of total trip budget allocated to transportation, accommodation or activities). This paper aims to profile expenditure patterns before, during and after the economic crisis, and how they affect destinations. Clustering methods and compositional data analysis is used as an appropriate statistical approach to analyze share. Incoming tourists to Spain are segmented by t… Show more

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Cited by 19 publications
(9 citation statements)
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“…The main clustering approaches suggested in the literature to aggregate units characterised by similar behaviour across time are the (1) model-(2) feature-and (3) observation-based approaches (for more details, see Disegna et al, 2017;Caiado et al, 2015) When repeated cross-sectional surveys are used to see how a key relationship has changed over time, a common procedure is to create a pooled dataset aggregating cross-sectional data from different years. Although extensive econometric techniques have been developed for the analysis of pooled cross sectional data (Wooldridge, 2012), in tourism market segmentation the cluster analysis is usually performed on the pooled dataset losing the information on the evolution of the phenomenon (see for instance Ferrer-Rosell & Coenders, 2018). Another common approach adopted in tourism literature, is to compare directly clusters over time, even if samples made by different units are used (see for instance Cang et al, 2017).…”
Section: Statistical Matchingmentioning
confidence: 99%
“…The main clustering approaches suggested in the literature to aggregate units characterised by similar behaviour across time are the (1) model-(2) feature-and (3) observation-based approaches (for more details, see Disegna et al, 2017;Caiado et al, 2015) When repeated cross-sectional surveys are used to see how a key relationship has changed over time, a common procedure is to create a pooled dataset aggregating cross-sectional data from different years. Although extensive econometric techniques have been developed for the analysis of pooled cross sectional data (Wooldridge, 2012), in tourism market segmentation the cluster analysis is usually performed on the pooled dataset losing the information on the evolution of the phenomenon (see for instance Ferrer-Rosell & Coenders, 2018). Another common approach adopted in tourism literature, is to compare directly clusters over time, even if samples made by different units are used (see for instance Cang et al, 2017).…”
Section: Statistical Matchingmentioning
confidence: 99%
“…Typical CoDa examples in the so-called hard sciences are chemical and geological analyses, in which absolute component amounts only tell about the size of the analyzed chemical or geological sample. Typical CoDa examples in management are market share [28], content analysis in advertising [29], spending distribution [30][31][32], and financial statement analysis [33]. In these examples, absolute amounts tell about total market size, advertisement length, total expenditure and firm size, respectively.…”
Section: Compositional Data Analysis (Coda)mentioning
confidence: 99%
“…Value for money when purchasing a flight ticket is a key aspect of that. Such saving behaviours change both expenditure allocation and total trip budget (Ferrer-Rosell and Coenders, 2016). Time will tell if some of the deep changes in tourism expenditure patterns after the crisis will remain structural.…”
Section: Discussionmentioning
confidence: 99%