DUGi

Destinations and crisis: profiling tourists’ budget share from 2006 to 2012

http://dugi.udg.edu/item/http:@@@@hdl.handle.net@@10256@@13499

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 trip budget share using repeated cross-sections of official statistics data (2006-2012). One of the main findings is that segments are heterogeneous in their cutting back on expenditure during the economic crisis, and segments increasing in size during the crisis not only spend less but also have the lowest activity share. Furthermore, the paper identifies one of the segments being particularly attractive for destinations in terms both of total expenditure and expenditure profile, with a high activity expenditure share and usually flying with low-cost airlines. The paper contributes to understanding tourist consumer behavior in terms of expenditure pattern at micro level in times of economic recession and its implications for particular destinations

The authors acknowledge the support of the Catalan Autonomous Government Consolidated Research Group Grant 2014SGR551 funding the research group ‘Compositional and Spatial Data Analysis (COSDA)’; the Spanish Health Ministry Grant CB06/02/1002 funding the research group ‘CIBER of Epidemiology and Public Health (CIBERESP)’; the Spanish Economy and Competitiveness Ministry /FEDER Grants MTM2015–65016-C2–1-R and EDU2015–68610-R funding the projects ‘COmpositional Data Analysis and RElated meThOdS (CODA-RETOS)’ and ‘Assessing Individual and Team Entrepreneurial Potential’; and the University of Girona Grant MPCUdG2016/069 funding the project ‘Statistical and Econometric Modeling’.

Elsevier