Mapping time series into networks as a tool to assess the complex dynamics of tourism systems

This paper contributes to filling two gaps: i) the presence of a limited amount of studies focused on tourism demand turning points, ii) the prevalent recourse to linear models in demand analysis, disregarding the complex structure of tourism destinations. The paper uses the Horizontal Visibility Graph Algorithm, a technique able to transform a time series of observations into a network whose topology preserves some fundamental characteristics of the system examined. The empirical work focuses on Livigno, an Italian alpine destination.Findings reveal four turning points in the last 50 years; these changes are built around shifts in the origin market segments. The network's degree distribution confirms the complex structure of the destination and reconfirms the importance of non-linear models and methods for the analysis of tourism demand.