Beyond Travel & Tourism competitiveness ranking using DEA, GST, ANN and Borda count

Travel & Tourism competitiveness rankings are helpful when we wish to consider the issue of how to enrich the global competitiveness of tourism destinations. However, even if a ranking is obtained from a highly reputed institute, it is important to evaluate such a ranking’s trustworthiness, particularly with regard to the possibility that calculation errors and various forms of human bias may be embedded in the ranking result. It is especially a cause for concern that different ranking methods may generate dissimilar results. This paper therefore proposes a solution that involves applying a variety of objective weighting methods, including data envelopment analysis (DEA), grey system theory (GST), and artificial neural network (ANN), to produce sensible rankings, as well as employing Borda count methodology to merge these rankings. By using this method, policy makers and stakeholders can arrive at more prudent and informed decisions than would be the case when solely depending on the original rankings.