1# RECORD e4122cbc852a2eb3164aee351201e6331c41cf752# TITLE: Urban Housing Markets as Data-Driven Innovation Systems: Hedonic Price Modeling and Digital Transformation in the Mexican Real Estate Market3# YEAR: 2026.0 VENUE: Revista de Gestão Social e Ambiental DOI: 10.24857/rgsa.v20n5-0044# AUTHORS: G. Uribe; P. López-de-Alba; Francisco J. Villareal-Segoviano; Omar Trejoluna Puente; R. Rodríguez-Carvajal; Juan Oswaldo Robledo López; L. Castellanos5# PAGES: 24 CANDIDATE TABLE PAGES (1-based): []6# ABSTRACT: Objective: This study aims to estimate housing listing values in a residential micro-submarket in Hermosillo, Mexico, by applying a hedonic pricing model. It seeks to understand how digital real estate platforms and data-driven systems reshape property valuation and transaction dynamics. 7 8Theoretical Framework: The research is grounded in the SPIRAL model of innovation systems. It integrates theories on urban innovation ecosystems, where interactions between academia, industry, government, and civil society are transformed by digitalization and technological change. 9 10Method: The methodology utilizes a quantitative approach, applying multiple regression techniques to analyze housing listings obtained from digital real estate platforms. The model examines structural determinants such as built area, number of bedrooms, and parking spaces. 11 12Results and Discussion: The final model demonstrates a high predictive capacity, explaining over 97% of the price variation. The discussion highlights that digital platforms are fundamentally transforming how housing values are generated and communicated within urban innovation systems. 13 14Research Implications: These findings provide insights for innovation management and urban economics. They suggest that econometric models can serve as analytical tools for data-driven governance and sustainable urban planning in the context of digital transformation. 15 16Originality/Value: The study contributes to the literature by interpreting urban housing markets as data-driven innovation ecosystems. Its value lies in linking econometric valuation with the SPIRAL innovation model to analyze the evolution of real estate markets in Latin American cities.171819===== PAGE 1 (score 13, numeric-paren 0, table-words 0, var-words 13) =====2021 22 23 24 25 26 27Rev. Gest. Soc. Ambient. | Miami | v.20.n.5 | p.1-24 | e014421 | 2026. 28 291 30RGSA – Revista de Gestão Social e Ambiental 31ISSN: 1981-982X 32Submission date: 2/9/2026 33Acceptance date: 4/27/2026 34DOI: https://doi.org/10.24857/rgsa.v20n5-004 35Organization: Interinstitutional Scientific Committee 36Chief Editor: Ana Carolina Messias de Souza Ferreira da Costa 37Assessment: Double Blind Review pelo SEER/OJS 38URBAN HOUSING MARKETS AS DATA-DRIVEN INNOVATION SYSTEMS: 39HEDONIC PRICE MODELING AND DIGITAL TRANSFORMATION IN THE 40MEXICAN REAL ESTATE MARKET 41 42 43Gerardo Ramirez Uribe1 44Pedro L. López-de-Alba2 45Francisco J. Villareal-Segoviano3 46Omar Trejoluna Puente4 47Ricardo Rodríguez-Carvajal5 48Juan Oswaldo Robledo López6 49Luis Manuel Orozco Castellanos7 50 51ABSTRACT 52 53Objective: This study aims to estimate housing listing values in a residential micro-submarket in Hermosillo, 54Mexico, by applying a hedonic pricing model. It seeks to understand how digital real estate platforms and data-55driven systems reshape property valuation and transaction dynamics. 56 57Theoretical Framework: The research is grounded in the SPIRAL model of innovation systems. It integrates 58theories on urban innovation ecosystems, where interactions between academia, industry, government, and civil 59society are transformed by digitalization and technological change. 60 61Method: The methodology utilizes a quantitative approach, applying multiple regression techniques to analyze 62housing listings obtained from digital real estate platforms. The model examines structural determinants such as 63built area, number of bedrooms, and parking spaces. 64 65Results and Discussion: The final model demonstrates a high predictive capacity, explaining over 97% of the 66price variation. The discussion highlights that digital platforms are fundamentally transforming how housing 67values are generated and communicated within urban innovation systems. 68 69Research Implications: These findings provide insights for innovation management and urban economics. They 70suggest that econometric models can serve as analytical tools for data-driven governance and sustainable urban 71planning in the context of digital transformation. 72 73Originality/Value: The study contributes to the literature by interpreting urban housing markets as data-driven 74innovation ecosystems. Its value lies in linking econometric valuation with the SPIRAL innovation model to 75analyze the evolution of real estate markets in Latin American cities. 76 77Keywords: Hedonic Pricing Model, Housing Market Analysis, Innovation Ecosystems, Digital Transformation, 78Proptech Platforms, Urban Innovation Systems. 79 80 811 Universidad de Sonora, Sonora, México. E-mail: gerardo.ramirez@unison.mx 82Orcid: https://orcid.org/0000-0001-7036-764X 832 Virtual University of the State of Guanajuato (UVEG), Universidad de Guanajuato (UG), Guanajuato, México. 84E-mail: pllopezdealba@gmail.com Orcid: https://orcid.org/0000-0001-5583-1942 853 Virtual University of the State of Guanajuato (UVEG), Universidad de Guanajuato (UG), Guanajuato, México. 86E-mail: frvillarreal@uveg.edu.mx Orcid: https://orcid.org/0000-0002-6331-2314 874 Universidad de Guanajuato (UG), Guanajuato, México. 88E-mail: omartp@uto.mx Orcid: https://orcid.org/0000-0002-7544-6088 895 Virtual University of the State of Guanajuato (UVEG), Universidad de Guanajuato (UG), Guanajuato, México. 90E-mail: rodriguez.ricardo@ugto.mx Orcid: https://orcid.org/0000-0003-3105-9809 916 Universidad de Guanajuato, Guanajuato, México. E-mail: oswaldo.robledo@ugto.mx 927 Universidad de Guanajuato, Guanajuato, México. E-mail: orozcoz@ugto.mx 93Orcid: https://orcid.org/0000-0002-1621-9539 94