Short Term Dynamics of Tourist Arrivals: What Do Italian Destinations Have in Common?
This work aims to detect the common short term dynamics to yearly time series of 413 Italian tourist areas. We adopt the clustering technique of Abraham et al. (Scand J Stat. 30:581–595, 2003) who propose a two-stage method which fits the data by B-splines and partitions the estimated model coefficients using a k-means algorithm. The description of each cluster, which identifies a specific kind of dynamics, is made through simple descriptive cross tabulations in order to study how the location of the areas across the regions or their prevailing typology of tourism characterize each group.
KeywordsTime Pattern Piecewise Polynomial Tourist Area Tourist Arrival Short Term Dynamic
This research is part of the PRIN 2007 (Project of Relevant National Interest) Mobility of regional incoming tourism. Socio-economic aspects of behaviors and motivations, funded by the Italian Ministry for University and the University of Palermo. We thank the national coordinator of the Project, Prof. Franco Vaccina, for his precious suggestions and cooperation. Many thanks also to Daria Mendola, and the anonymous referees who gave us useful indications for the improvement of the paper.
- Istat (Italian Statistical Office) (2010) Statistiche per politiche di sviluppo. Risorse turistiche. URL http://www.istat.it/ambiente/contesto/incipit/turistiche.html. Cited 14 Jun 2010