Competitiveness and overtourism: a proposal for an early warning system in Spanish urban destinations

Abstract

The tourism industry is undergoing accelerated changes that pose significant challenges for both destination and business managers as well as for researchers of the tourism phenomenon. Two of these challenges that are particularly relevant are the emergence of the sharing economy and its influence on the degree of overtourism perceived in the tourist destinations. This paper addresses the subject through the use of machine learning techniques. The findings show that machine learning techniques are especially well-suited tools for dealing with these kinds of tourism issues. The findings also show that for the Spanish case, tourism competitiveness is a key predictor of overtourism.