What network analysis can reveal about tourism destinations
D. Watts said: "Physicists, it turns out, are almost perfectly suited to invading other people's disciplines". I have invaded the field of Tourism, probably the most important economic activity in today's world, traditionally a prerogative of sociologists, economists and geographers. In this field I have started examining those complex systems known as tourism destinations (TDs) armed with the toolbox of the "network science".
Difficult to define precisely, tourism destinations, basically the place where we head for to spend our time, whether for leisure or business, are agglomerates of many diverse entities (the companies and organisations providing basic tourism services) which are connected by a wide set of relationships, ranging from a simple information exchange to complex economic and technical collaboration agreements. For their importance and the outcomes they can provide in terms of social and economic developments, TDs are considered, by academics and practitioners, a fundamental unit of analysis for the understanding of the whole tourism system.
The first objective of my research is to validate methods and tools and to find how network thinking can be matched with the "common knowledge" in the field. This work concerns the study of two TDs: the island of Elba (Italy) and the Fiji islands. They are quite similar in terms of type (sea, sun, ...) and size (tourist fluxes and number of local tourism operators). Since both areas have well developed Internet infrastructures, I have considered the websites belonging to the tourism destination stakeholders. The idea, common among cyber scholars, is that the relationships between websites represent closely those between the "real" organisations.
The results of the analysis show a very (for both destinations) "sparse" network, with little clustering (density of local agglomerates). This is a sign of little cohesion, or collaborative attitude among the operators, and reconfirms what previous analyses have found, although only from a qualitative point of view. Network metrics can contribute in this assessment by giving also quantitative measurements for this characteristic.
Moreover, the investigation of the distributions of the links has shown some differences which can be interpreted as different stages of evolution of the destinations. Elba is more "mature" than Fiji, a relatively younger tourism system. Again, well in line with the results of the research tradition in the field.
Much more work is undoubtedly needed to confirm these results, to better assess the methodology and to derive, besides the theoretical models, "practical" tools which can allow destination policy makers to cope with the issues of management and development of their destination.
This work is just an initial encouraging attempt. As someone would say: stay tuned for more...