Short Term Dynamics of Tourist Arrivals: What Do Italian Destinations Have in Common?

  • Anna Maria Parroco
  • Raffaele Scuderi
Conference paper
Part of the Studies in Classification, Data Analysis, and Knowledge Organization book series (STUDIES CLASS)


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.


Time Pattern Piecewise Polynomial Tourist Area Tourist Arrival Short Term Dynamic 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



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.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  1. 1.Department of Economics, Business and FinanceUniversity of PalermoPalermoItaly

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