Clustering and country destination performance at a global scale: Determining factors of tourism competitiveness

Abstract

Our aim is to evaluate the efficiency of tourist destinations at a global scale, considering 140 countries and drawing on World Economic Forum 2019 data. The approach follows three stages. First, we try to solve the problem of sample heterogeneity through cluster analysis to obtain homogeneous groups of countries. Second, we apply data envelopment analysis to evaluate countries’ efficiency as tourist destinations, considering a territorially based virtual production function which optimizes the flow of revenue from international tourism grounded on a set of inputs such as accommodation capacity, employment of tourist sector and volume of tourist arrivals. Finally, we identify which external factors might determine tourism efficiency by using bootstrap truncated regression analysis. We obtain two groups of countries which evidence differential levels of competitiveness. Rather than natural resources, cultural heritage in a broad sense seems to act as factor that enhances tourism efficiency.