Detecting determinants in tourist seasonality of greece: A binary logistic regression approach

Abstract

Tourism seasonality is a complex phenomenon ranked as one of the most important and timeless issues for regional and tourism development. This paper builds on binary logistic regression to examine the determinants of tourism seasonality. The proposed method classifies the tourism seasonality of the Greek prefectures into two groups (high seasonality, low seasonality), which are examined in terms of their natural, geographic, and infrastructure characteristics. The study aims to identify the key factors of tourism seasonality, on monthly data of tourism overnight stays for the year 2018, both for foreign and domestic visitors. The overall analysis proposes a useful tool for tourism management, and regional policy because it allows considering in common the different dimensions of the tourism seasonality phenomenon. © 2021, Research Centre in Public Administration and Public Services,cademy of Economic Studies, Bucharest, Romania. All rights reserved.