Drivers of the international tourist's satisfaction with their trip to Spain and its different dimensions
Article Sidebar
Turespaña has conducted a survey on tourist satisfaction aimed at international tourists and applied to them on their way out of the country after their stay. In this article, some of the relationships between overall satisfaction with the trip and several dimensions of it are examined in order to find possible drivers. For that purpose, two multivariate analysis tools were employed: Spearman rank correlation coefficients between pairs of variables and logit regression analysis between factors and a dummy satisfaction variable were calculated and interpreted.
A main finding contained in this article is that none of the dimensions studied (lodging, dining, leisure offerings, environment, infrastructure and transportation in the destination) seem to have a dominant role as a driver of satisfaction with the trip, but one other dimension studied (sustainability) does seem to be more disconnected than the rest with the overall level of satisfaction.
Article Details
Agresti, A (2007). An introduction to Categorical Data Analysis. John Wiley and Sons
Instituto de Turismo de España – Turespaña (2018). Encuesta de Hábitos Turísticos de los Turistas Internacionales (HABITUR) 2016. https://www.tourspain.es/es-es/ConocimientoTuristico/InformesHabitur/Informe%20Habitur%202016%20para%20publicacion.pdf.
Instituto de Turismo de España – Turespaña (2023). Encuesta de Satisfacción de los Viajeros No Residentes 2022. https://conocimiento.tourspain.es/export/sites/conocimiento/.content/Informes/encuesta-satisfaccion/encuesta-satisfaccion-viajeros-no-residentes_v7.pdf
Kennedy, R., Riquier, C. y Sharp. B. (1996). Practical applications of correspondence analysis to categorical data in market research. Journal of Targeting, Measurement and Analysis for Marketing 5(1), 56-70. https://www.researchgate.net/publication/259197416_Practical_Applications_of_Correspondence_Analysis_to_Categorical_Data_in_Market_Research
Matas, A. (2018). Diseño del formato de escalas tipo Likert: un estado de la cuestión. Revista Electrónica de Investigación Educativa, 20(1), 38-47. https://doi.org/10.24320/redie.2018.20.1.1347
Powers, D. A. y Xie, Y. (2000). Statistical Methods for Categorical Data Analysis. Academic Press, Inc.
Rohrer, J.M. (2018). Thinking clearly about correlations and causation: graphical causal models for observational data. Advances in Methods and Practices in Psychological Science 1(1), 27-42. https://psycnet.apa.org/record/2018-67155-004
Tutz, G. (2021). Hierarchical models for the analysis of Likert scales in regression and item response analysis. International Statistical Review, 89(1), 18-35. https://onlinelibrary.wiley.com/doi/full/10.1111/insr.12396