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An examination of tourist arrivals dynamics using short-term time series data: a space-time cluster approach

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  • Dogan Gursoy

    ()
    (School of Hospitality Business Management, Washington State University)

  • Anna Maria Parroco

    ()
    (Department of Economics, Business and Finance, University of Palermo)

  • Raffaele Scuderi

    ()
    (Free University of Bolzanoâ€Bozen, School of Economics and Management.)

Abstract

The purpose of this study is to examine the development of Italian tourist areas (circoscrizioni turistiche) through a cluster analysis of short time series. The technique is an adaptation of the functional data analysis approach developed by Abraham et al (2003), which combines spline interpolation with k-means clustering. The findings indicate the presence of two patterns (increasing and stable) averagely characterizing groups of territories. Moreover, tests of spatial contiguity suggest the presence of ‘space–time clusters’; that is, areas in the same ‘time cluster’ are also spatially contiguous. These findings appear to be more robust in particular for those series characterized by an increasing trend.

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Bibliographic Info

Paper provided by School of Economics and Management at the Free University of Bozen in its series BEMPS - Bozen Economics & Management Paper Series with number BEMPS06.

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Length: 26 pages
Date of creation: Jun 2013
Date of revision:
Handle: RePEc:bzn:wpaper:bemps06

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Keywords: cluster analysis; short time series; spline interpolation; K-means; join count test; Italian tourist areas;

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  1. Mark Chiang & Boris Mirkin, 2010. "Intelligent Choice of the Number of Clusters in K-Means Clustering: An Experimental Study with Different Cluster Spreads," Journal of Classification, Springer, vol. 27(1), pages 3-40, March.
  2. Daria Mendola & Raffaele Scuderi & Valerio Lacagnina, 2013. "Defining and measuring the development of a country over time: a proposal of a new index," Quality & Quantity: International Journal of Methodology, Springer, vol. 47(5), pages 2473-2494, August.
  3. C. Abraham & P. A. Cornillon & E. Matzner-Løber & N. Molinari, 2003. "Unsupervised Curve Clustering using B-Splines," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics & Finnish Statistical Society & Norwegian Statistical Association & Swedish Statistical Association, vol. 30(3), pages 581-595.
  4. JG. Brida & M. Pulina, 2010. "A literature review on the tourism-led-growth hypothesis," Working Paper CRENoS 201017, Centre for North South Economic Research, University of Cagliari and Sassari, Sardinia.
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