Martín Sevilla-Jiménez

Differences in the economic performance of hotel-based and residential tourist destinations measured by their retail activity. Evidence from Spain

This paper compares the economic performance of holiday and residential tourism destinations in Spain, as measured by the level of retail activity, from a quantitative perspective. Differences between destinations are explored. A positive association between the economic development of destinations and their retail index was expected. However, no significant differences were found between residential/second-home tourism and holiday/leisure tourism destinations. The results obtained contradict the conventional assumptions that holiday destinations perform better economically than residential ones due to a higher level of tourist spending of people accommodated in hotels.

The Effects of Economic Crises on Tourism Success: An Integrated Model

This paper provides a theoretical model of the influence of economic crises on tourism destination performance. It discusses the temporary and permanent effects of economic crises on the global market shares of tourism destinations through a series of potential transmission mechanisms based on the main economic competitiveness determinants identified in the literature. The proposed model explains the non-neutrality of economic shocks in tourism competitiveness. The model is tested on Spains tourism industry, which is among the leaders of the global tourism sector, for the period 1970–2013 using non-linear econometric techniques. The empirical analysis confirms that the proposed model is appropriate for explaining the changes in the market positions caused by the economic crises.

Economic crises and market performance—A machine learning approach

This note analyzes the relationship between economic crises and tourism performance in Spain during the period 1970–2013 using machine learning techniques. Specifically, a regression tree is estimated to confirm that, although the dynamics of Spanish tourism performance is influenced by the general variables established by the literature, the crisis periods disrupt the natural functioning of these dynamics, provoking disturbances that affect the tourism market position of destinations to a greater extent than expected. Conversely, to other econometric techniques, machine learning approach allows us to achieve greater flexibility and enriches the information, estimating the interrelations and thresholds operating in this context.