Speaker
Description
Tourism is recognized as a powerful driver of sustainable development, generating positive impacts on territorial assets (Ballesta, 2024). However, it is also well-known that tourism can produce negative effects, as highlighted in current policy issues and trends (Zhang et al., 2022).
Positive (e.g. economic value creation) and negative (e.g. resident displacement) effects of tourism have been extensively described by various disciplinary contributions (Eugenio-Martin, Cazorla-Artiles and González-Martel, 2019; Morales-Pérez, Garay and Wilson, 2022), a systemic approach to assess, describe, and evaluate the impact of tourism on a territorial scale is still lacking. While a wide range of approaches to measure sustainable tourism have been developed, significant challenges remain in comparing performance and outcomes across different destinations and scales.
This research introduces a taxonomy for specialized tourism ecosystems, emphasizing its potential in transformative urban and territorial planning. The tourism phenomenon is considered in its territorial complexity thorough systematic approach that integrates the fundamental characteristics according to a clear taxonomic model based on three classes: DA (Destination Areas), TS (Tourism Systems), TES (Tourism Ecosystem) (R.V.Gatto, S. Corrado, 2024-in printing)
The application to a case study in Southern Italy demonstrates its applicability in recognizing territorial components in a territorial system using geodata and providing a comprehensive description of the tourism supply through the Balanced Supply Index and Attractiveness of the DA.
The detailed maps derived from representing spatial entities through Points of Interest (POIs) enable a place-oriented understanding of the relationships among services, moving beyond aggregated spatial similarities that often obscure valuable insights. The taxonomy provides a systematic way of classifying or organizing information by classes placing and linking elements relevant for tourism development in a hierarchical structure.
However, such classification is limited by the reliance of the analytical framework on expert knowledge for input data selection and for assessing results on specific case study without discussion with local actors including policymakers, citizens and operators. A more automated framework can enhance the model's applicability, yielding robust and accountable results.
The proposed framework uses POI data (attractors and amenities) clustered based on proximity to define specific destination areas. Elements of the DAs are further evaluated based on publicly available online reviews to understand service quality. Moving away from traditional approaches, the combination of proximity-based clustering and user generated information can provide insights on a local level to address critical areas, both in the terms of over- and overserving certain areas, as well as in terms of service quality assessment. By applying this data-based approach in the context of spatial planning, this research aligns with Track 11’s goal of fostering efficient, resilient, and inclusive urban systems.
References
Ballesta, S.H. (2024) ‘Collaborative and professional accommodations on Airbnb: Exploring patterns for sustainable tourism management in Spain’, Cities, 154(August), p. 105400. Available at: https://doi.org/10.1016/j.cities.2024.105400.
Eugenio-Martin, J.L., Cazorla-Artiles, J.M. and González-Martel, C. (2019) ‘On the determinants of Airbnb location and its spatial distribution’, Tourism Economics, 25(8), pp. 1224–1244.
Morales-Pérez, S., Garay, L. and Wilson, J. (2022) ‘Airbnb’s contribution to socio-spatial inequalities and geographies of resistance in Barcelona’, Tourism Geographies, 24(6–7), pp. 978–1001.
R.V.Gatto, S. Corrado, F.S. (2024) ‘Taxonomy for specialized Tourism Ecosystems : new geographies for sustainable territorial planning’.
Zhang, Q. et al. (2022) ‘Uneven development and tourism gentrification in the metropolitan fringe: A case study of Wuzhen Xizha in Zhejiang Province, China’, Cities, 121(August 2021), p. 103476. Available at: https://doi.org/10.1016/j.cities.2021.103476.
| Best Congress Paper Award | Yes |
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