Mapping Italy’s Tourism Economy: Integrating a Modified Gravity Model and Social Network Analysis
DOI:
https://doi.org/10.70732/tijt.v35i1.81Keywords:
Tourism economy, Modified gravity model, Social Network Analysis, DP2 composite indicator, Regional capitals, ItalyAbstract
Purpose - This study maps the spatial structure of Italy’s tourism economy across the 20 regional capitals. It identifies central hubs, peripheral nodes and territorial disparities, and considers how the resulting network evidence can inform more coordinated tourism development. Design/methodology/approach - A DP2 composite tourism economic quality index (Qi) is combined with a modified gravity model based on multimodal time-distance. The resulting directed city-to-city connection matrix is examined through Social Network Analysis, including in-degree, out-degree, degree, closeness, betweenness, density, global efficiency and total connection strength. Findings: Venice records the highest tourism economic quality score (Qi = 9.42) and total connection strength (Ti = 2,786.65). Florence, Rome, Milan and Naples also occupy prominent positions, whereas Potenza, Bari, Catanzaro and Campobasso remain peripheral on several centrality measures. Global network efficiency is 0.78, but the distribution of strength is highly concentrated: Venice’s Ti is approximately 146 times Campobasso’s. Originality/value: The contribution is primarily contextual and applied. The study transfers an integrated gravity-model and network-analysis framework to a polycentric national tourism system characterised by strong territorial and transport discontinuities, showing how tourism economic quality and multimodal separation jointly shape hub-and-periphery relations. Practical implications: The results support geographically differentiated policies for transport connectivity, interregional destination cooperation, integrated marketing, digital services, workforce development and public-private partnerships, with priority attention to structurally peripheral capitals.
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