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
Anna Maria Parroco: Department of Economics, Business and Finance, University of Palermo

No BEMPS06, BEMPS - Bozen Economics & Management Paper Series from Faculty of Economics and Management at the Free University of Bozen

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)
JEL-codes: C14 C21 C22 C38 L83 (search for similar items in EconPapers)
Pages: 26 pages
Date: 2013-06
New Economics Papers: this item is included in nep-ecm, nep-tur and nep-ure
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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