An Examination of Tourist Arrivals Dynamics Using Short-Term Time Series Data: A Space—Time Cluster Approach

Dogan Gursoy, Anna Maria Parroco and Raffaele Scuderi
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Dogan Gursoy: School of Hospitality Business Management, Washington State University, 340G Todd Hall, PO Box 644736, Pullman, WA 99164–4736, USA
Anna Maria Parroco: Department of Psychology, University of Palermo, Viale delle Scienze ed. 15, 90128 Palermo, Italy

Tourism Economics, 2013, vol. 19, issue 4, 761-777

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.

Keywords: cluster analysis; short time series; spline interpolation; K-means; join count test; Italian tourist areas (search for similar items in EconPapers)
Date: 2013
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Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:sae:toueco:v:19:y:2013:i:4:p:761-777

DOI: 10.5367/te.2013.0318

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