Skip to main content

Satisfaction and Tourism Expenditure Behaviour.

D’Urso, P., Disegna, M. and Massari, R., 2020. Satisfaction and Tourism Expenditure Behaviour. Social Indicators Research, 149, 1081-1106.

Full text available as:

[img] PDF
2020SOCI_DDM_proof.pdf - Accepted Version
Restricted to Repository staff only until 14 January 2021.
Available under License Creative Commons Attribution Non-commercial.

378kB

DOI: 10.1007/s11205-020-02272-4

Abstract

In the literature, the quantification of the effect of satisfaction on tourists’ expenditure behaviour has not been extensively studied. This research aims to fill in this gap, providing additional information about this crucial relation by analysing it from a microdata perspective. In particular, the Fuzzy Double-Hurdle model, a new model which combines the well-known Double-Hurdle model and the fuzzy set theory, is suggested and presented, both technically and by means of a real case study. The proposed model gathers the advantages of the Double-Hurdle model and the fuzzy set theory together producing a suitable model for the analysis of censored observations in presence of imprecise data. Specifically, the Double-Hurdle model allows to efficiently estimate the average values of a non-negative, non-normally distributed variable characterised by high frequency of zero values, as tourists’ expenditure can be, considering the two-stages nature of the decision process. On the other end, the inclusion of the fuzzy set theory in the regression model allows to cope with the imprecision of both collected information (i.e. levels of satisfaction) and kind of measurement used (i.e. Liker-type scale). The results will help tourism managers to more accurately evaluate the efficacy of their policies and marketing strategies in enhancing tourists’ satisfaction and, consequently, in increasing the level of spending at the destination.

Item Type:Article
ISSN:0303-8300
Uncontrolled Keywords:Satisfaction; Expenditures behaviour; Imprecise data; Likert-type scale; Fuzzy numbers; Fuzzy regression; Fuzzy Double-Hurdle;
Group:Faculty of Management
ID Code:33522
Deposited By: Unnamed user with email symplectic@symplectic
Deposited On:26 Feb 2020 16:00
Last Modified:06 Jul 2020 12:50

Downloads

Downloads per month over past year

More statistics for this item...
Repository Staff Only -