The Topology of Cultural Destinations’ Accessibility: The Case of Attica, Greece

Abstract

This paper studies the cultural landscape in the prefecture of Attica, Greece, within the context of network science. Tourism is a global and complex phenomenon with a considerable effect on space. Among its diverse forms, cultural tourism stands out, since people often travel to explore different cultures and civilizations. The engagement of different stakeholders in the establishment of policies in regard to tourism development and its relation to cultural heritage demonstrates the need for sustainable spatial planning in cultural tourism areas. According to network science, a modern discipline already contributing to the research in tourism geography, tourism destinations can configure complex spatial networks and be studied in terms of network analysis and statistical mechanics. This paper models the accessibility network of cultural destinations in Attica (ACDN), the capital region of Greece, into a graph, which provides an excellent case study of multilayer network modeling, as is equipped with high quality transportation, accommodation, and cultural infrastructures. The ACDN nodes represent museums and archaeological sites and its edges express possible connections between nodes by different means of transport (car, pedestrian, and public transport). The analysis aims to evaluate the layer’s capacity in the service of the accessibility of the cultural destination tourism market in Greece and reveals two major communities in the structure of ACDN, an urban core and a peripheral, configured by spatial constraints and distinct transportation mode functionality, along with uncovering deficiencies in the public transportation setting of the cultural tourism market of Attica. Overall, this study highlights the requirement for spatial planning and tourism management to be aware of geographical, topological, and functional features of a cultural tourism market and promotes the symbiotic relationship of sustainable tourism development and network science.

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