A complex network analysis of global tourism flows. (1st May 2018)

• Record Type: Journal Article
• Authors: Lozano, Sebastián; Gutiérrez, Ester
• Is Part Of: International journal of tourism research. Volume 20:Number 5(2018)
• Page Start: 588
• Page End: 604
• Publication Date: 2018-05-01
• Subjects: clustered structure -- emergent structure -- geographic homophily -- scale‐free -- small world -- top inbound/outbound flows; Tourism -- Periodicals; 338.4791
• DOI: 10.1002/jtr.2208
• Languages: English
• ISSNs: 1099-2340

Abstract

Abstract: In this paper, the global tourism network (GTN) is studied in order to gain insight about its structure and the interactions between source and destination markets. To concentrate on the main source and destination markets for each country, only its top k inbound and outbound flows are considered. The distribution of these most important ties in international tourism seems to be scale‐free, with some occurrence of reciprocity, large transitivity, and high‐degree centralization. The GTN shows a clustered structure determined by geographical as well as trade and cultural factors. Each major global and regional power seems to have a certain tourism sphere of influence. The network has a small world character and a high degree of geographic homophily, with more links within continents than between continents. Exponential random graph models have been fit to explain the observed global structure of the network based on its local interactions, and a number of significant motifs have been identified. The picture that results is a GTN that emerges from superimposed local processes in which tourism flows between countries is determined from multiple independent individual decisions made at the local level. This insight that global tourism patterns are driven by local processes is a major contribution of this research and can help develop strategic plans and cooperation partnerships at the national and regional levels, involving private and public stakeholders and targeting specific source and destination markets. The indicators computed using network analysis of global tourism flows can also be used to complement and enrich the information provided by current tourism statistics.