Heritage as capital: Professional Airbnb hosts and the spatial pull of cultural monuments in Mexico City

Narciso Salvador Tinoco Guerrero; Gerardo Tinoco Guerrero; José Alberto Guzmán Torres

doi:10.33110/inceptum.v21i41.541

Autores/as

Narciso Salvador Tinoco Guerrero Universidad Michoacana de San Nicolás de Hidalgo
Gerardo Tinoco Guerrero Universidad Michoacana de San Nicolás de Hidalgo
José Alberto Guzmán Torres Universidad Michoacana de San Nicolás de Hidalgo

DOI:

https://doi.org/10.33110/inceptum.v21i41.541

Palabras clave:

Airbnb, Cultural attractions, Gentrification, Geospatial analysis, Professional hosts

Resumen

This study examines spatial distribution patterns of Airbnb listings in Mexico City, comparing professional and non-professional hosts in relation to cultural monuments. Using 26,300 listings and 36 georeferenced cultural points of interest, geospatial and correlation analyses (Haversine formula, Pearson coefficients) were applied across three measures of host professionalization. Results show professional hosts concentrate significantly closer to cultural attractions and central tourist areas, while non-professional hosts are more dispersed across the urban fabric. A robust spatial relationship emerges between listings and cultural monuments, particularly among professional hosts. These asymmetries carry important implications for gentrification, real estate market distortion, and tourist overconcentration, underscoring the need for differentiated public policies addressing these distinct spatial patterns.

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Biografía del autor/a

Gerardo Tinoco Guerrero, Universidad Michoacana de San Nicolás de Hidalgo

Dr. Gerardo Tinoco Guerrero is a researcher at the Universidad Michoacana de San Nicolás de Hidalgo (UMSNH), Mexico, currently completing a postdoctoral fellowship funded by SECIHTI. He holds a doctorate obtained in 2020 and is a Level I member of Mexico's Sistema Nacional de Investigadoras e Investigadores (SNII). His research focuses on numerical methods for partial differential equations, meshless methods, generalized finite differences, and scientific computing applied to environmental fluid dynamics and data science. He collaborates with the Centro Internacional de Métodos Numéricos en Ingeniería (CIMNE).

José Alberto Guzmán Torres, Universidad Michoacana de San Nicolás de Hidalgo

Dr. José Alberto Guzmán Torres is a researcher at the Universidad Michoacana de San Nicolás de Hidalgo (UMSNH), Mexico, and a member of the AULA-CIMNE Morelia network. He holds a doctorate in Engineering Physics with specialisation in data science, machine learning, and deep learning, and completed a postdoctoral fellowship in artificial intelligence applied to civil infrastructure. He is a Level I member of Mexico's Sistema Nacional de Investigadoras e Investigadores (SNII), an Honorary State Researcher of Michoacán, and an active member of the Sociedad Mexicana de Computación Científica y sus Aplicaciones (SMCCA).

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