The concentration of tourists at certain times of the year can damage sensitive environments. The use of peer-to-peer vacation rental websites has increased greatly during the last decade. This system could either reduce seasonality in touristic destinations where the tourist activity takes place throughout the year at a lower price or on the contrary, it could increase the number of visitors at certain times of the year even more. This paper intends to analyze the effect that these platforms have on tourism seasonality in order to calculate if they help reduce or increase the pressure on the destinations. To do so, the Gini Index has been applied to one of the main touristic spots in Europe, the Balearic Islands in Spain. The conclusion is that this type of accommodation has aggravated the problem, generating a greater concentration of tourists and a higher pressure on the resources of the islands.

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This study proposes construction of a synthetic indicator to measure progress toward the objective of economic and social cohesion among the regions of Spain, Greece, Ireland and Portugal within the framework of European Community Regional Policy and the spatial disparities among these countries. Our aim is to integrate, in a single indicator, a large number of variables defined by the European Commission to monitor improvements in regional development, classified according to the objectives of the Europe 2020 Strategy to promote smart, sustainable and inclusive growth. To achieve this goal, we use the Pena distance method for the year 2013.

This study analyzes the changes caused by seasonal trends in the Spanish tourism sector 2007-2016. The methodological originality of the analysis stems from its multi-dimensional index of tourism seasonality, which uses the DP2 indicator. This method enables us to analyze changes in the intensity of destinations’ seasonality and to determine both the variables with the greatest power to explain this phenomenon and the variables with the greatest discriminant value among destinations. The results indicate that urban destinations are the most sensitive to variations in the economic cycle, primarily due to the effect of variations in the arrivals of national tourists.