Measuring communities’ efficiencies within the global tourism network

Abstract

Abstract Tourist flows between countries shape the global tourism network, with tightly interconnected nations forming distinct communities. These communities have significant implications for the global tourism patterns. However, existing research on tourism networks rarely provides an in-depth analysis of these communities, particularly lacking systematic and quantifiable methodologies. To address this gap, we apply complex network theory and analyze international tourist flow data from 1995 to 2021 to construct global tourism networks. Using community detection and similarity calculations, we categorize the global tourism network evolution into four distinct stages. Additionally, through theoretical deduction, we develop methods to assess the communities’ structural, performance, and functional efficiency, calculating their efficiencies to reveal evolutionary trends. Finally, utilizing a mixed-effects model, the impact of 11 indicators on community efficiencies has been examined. This study contributes to the theoretical foundation of tourism networks and offers valuable insights for global international tourism organizations.