Abstract

This study provides a methodological contribution in the analysis of tourists’ sustainable behaviour. Traditional methods encounter challenges in addressing the attitude-behaviour gap, prompting the need for new approaches. Using diverse big data sources, the paper introduces a novel methodology for analysing real behaviour patterns, extending Social Network Analysis techniques. The aim is to identify sustainable behaviours that ease overcrowding, distribute visitor flows, and optimize economic diversification. The methodology is valuable for local authorities in monitoring tourist behaviours, aiding in informed decision-making for a more sustainable approach to tourism.

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