Detecting Tourism Typologies of Regional Destinations Based on Their Spatio-Temporal and Socioeconomic Performance: A Correlation-Based Complex Network Approach for the Case of Greece

Within the context that tourism-seasonality is a composite phenomenon described by temporal, geographical, and socio-economic aspects, this article develops multilevel method for studying time patterns of in conjunction with its spatial dimension dimension. The study aims to classify temporal seasonality into regional groups configure distinguishable seasonal profiles facilitating tourism policy development. applies pattern recognition approach incorporating time-series assessment, correlation, complex network analysis based on community detection use modularity optimization algorithm, data overnight-stays recorded time-period 1998–2018. reveals four seasonality, which are distinct seasonal, profiles. Overall, supports multidisciplinary synthetic research modeling promotes systems, providing insights physical conceptualization algorithm can enjoy real-world applications.