Adjunct Lecturer, Department of Regional and Economic Development, Agricultural University of Athens, Greece, Nea Poli, Amfissa, 33100, Greece, Department of Planning and Regional Development, University of Thessaly, Pedion Areos, Volos, 38334, Greece, email@example.com
Ph.D. candidate, Department of Planning and Regional Development, University of Thessaly, Pedion Areos, Volos, 38334, Greece
Professor, Department of Planning and Regional Development, University of Thessaly, Pedion Areos, Volos, 38334, Greece
Tourism seasonality is a complex phenomenon incorporating a temporal, a spatial, and a socioeconomic (ontological) dimension. This paper builds on principal component analysis (PCA) to provide an integrated methodological framework for studying all three dimensions of tourism seasonality. The proposed method classifies the seasonal patterns of tourism demand of the Greek prefectures into regional groups, which are examined in terms of their geographical and socioeconomic characteristics. The study aims to configure distinguishable seasonal profiles in terms of their socioeconomic attributes. The proposed method is applied to monthly data of tourism overnight stays for the period 1998-2018 and detects seven principal components described by diverse socioeconomic attributes. The overall analysis proposes a useful tool for tourism management and regional policy, it advances PCA to be used as a tool of regional classification, and it incorporates a multivariate consideration based on the socioeconomic evaluation of the principal components. The proposed methodology develops an integrated framework dealing with complexity describing socioeconomic research and particularly tourism seasonality.
Keywords: regional development; seasonal classification; spatiotemporal patterns; pattern recognition.
JEL classification: C18, C38, O52, R10, R58, Z30