Predicting tourism competitiveness with innovation: a machine learning approach

Abstract

This study introduces an analytical model that establishes a connection between the factors that promote innovation in a country and the competitiveness of its tourism destinations. Invoking the international strategic competitiveness theory, this study is among the first to propose and empirically test the predictive roles of innovation facilitators on tourism competitiveness. Utilising longitudinal data from multiple countries from 2013 to 2022, we ran machine learning algorithms. The results show that several innovation facilitators, such as research and development and trade, diversification, and market scale, significantly predict competitiveness in tourism destinations. The results of this investigation enhance our knowledge of innovation and competitiveness in tourism locations globally.