Heritage at risk: The impact of tourism and real estate growth on Iloilo City’s cultural landmarks
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Abstract
This study examines how tourism and property development impact Iloilo City’s cultural heritage, emphasizing heritage preservation issues due to rapid urbanization. Following a qualitative systematic review using the PRISMA framework, the study synthesizes literature on real estate development, tourism, and cultural preservation. In addition, focus group interviews (FGDs) with 15 purposively chosen stakeholders—conservationists of heritage, urban planners, government officials, and tourism officers—provided deeper insights into the realities of Iloilo City heritage management. FGD data were coded and analyzed using NVivo software for emerging themes. Results indicated that heritage destruction is driven by unchecked tourism, lax enforcement of protection legislation, and conflict between conservation and commercial interests. Numerous historical buildings are threatened by encroachment, structural alteration, or demolition, undermining Iloilo’s cultural heritage. Stronger policy implementation, heritage conservation in tourism and urban planning, and adaptive reuse of historic buildings were stressed by participants. Strategies for sustainable preservation involve public campaigns, tighter regulatory measures, and public-private collaboration to reconcile economic development with the protection of culture. The study discovers that while tourism and real estate development are needed for the economy of Iloilo City, they must be managed in a way that they do not inflict irreparable damage on heritage sites. Better policies, better community involvement, and sustainable tourism practices are essential. They will ensure that the city’s cultural and historical landmarks are protected for future generations.
Recommended Citation
Oberio, D. C. (2026). Heritage at risk: The impact of tourism and real estate growth on Iloilo City’s cultural landmarks. In Hamdan, R. K. (eds) Integrating Big Data and IoT for Enhanced Decision-Making Systems in Business. Studies in Big Data, 177, 355-362. Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-031-97609-4_30


