Purpose: The social responsibility of a tourism destination results from the combined efforts of the single stakeholders. This needs coordination and harmonization that cannot be achieved without a deep understanding of the structural and dynamic characteristics of the destination. A tourism destination is a complex dynamic system and requires specific methods to be analyzed and understood in order to better tailor governance actions for steering it along an evolutionary growth path, respectful of the social responsibility towards the community. Many methodological recommendations exist that allow to assess these features, and some have been successfully applied to tourism destinations. This paper aims to explore a new proposal: the visibility graph algorithm (VGA), which is able to provide the required level of information in a fast and simple way. Design/methodology/approach: VGA is a technique to map a time series into a network. The method and its implementation are relatively simple and straightforward. The mapping allows examining the system's properties by using network analytic methods. An example is worked out using data from two destinations: Italy as a country and the island of Elba, one of its most popular areas. Findings: The complexity properties of the two destinations are examined and found in agreement with those obtained by using more complicated approaches, thus strengthening the reliability of the method. Originality/value: This paper provides a new method to examine a tourism destination using a readily available set of data and a simple algorithm. The contribution of this work is mainly methodological. The technique provides insights into the complex structure and dynamics of a tourism destination. This has important implications for those interested in enriching the toolsets used to study a destination from a complex system perspective.
ASJC Scopus subject areas
- Control and Systems Engineering
- Theoretical Computer Science
- Information Systems
- Artificial Intelligence
- Electrical and Electronic Engineering