Development of an Innovative Land Valuation Model (iLVM) for Mass Appraisal Application in Sub-Urban Areas Using AHP: An Integration of Theoretical and Practical Approaches

TitleDevelopment of an Innovative Land Valuation Model (iLVM) for Mass Appraisal Application in Sub-Urban Areas Using AHP: An Integration of Theoretical and Practical Approaches
Publication TypeJournal Article
Year of Publication2019
AuthorsBencure, JC, Tripathi, NK, Miyazaki, H, Ninsawat, S, Kim, SMinsun
JournalSustainability
Volume11
ISSN2071-1050
Abstract

Land development in sub-urban areas is more frequent than in highly urbanized cities, causing land prices to increase abruptly and making it harder for valuers to update land values in timely manner. Apart from this, the non-availability of sufficient reliable market values forces valuers to use alternatives and subjective judgement. Land value is critical not only for private individuals but also for government agencies in their day-to-day land dealings. Thus, mass appraisal is necessary. In other words, despite the importance of reliable land value in all aspects of land administration, valuation remains disorganized, with unregulated undertakings that lack concrete scientific, legal, and practical foundations. A holistic and objective way of weighing geospatial factors through expert consultation, legal reviews, and evidence (i.e., news) will provide more realistic results than a regression-based method that does not comprehend valuation factors (i.e., physical, social, economic, environmental, and legal aspects). The analytic hierarchy process (AHP) enables these factors to be included in the model, hence providing a realistic result. The innovative land valuation model (iLVM), developed in this study, is an inclusive approach wherein experts are involved in the selection and weighing of 15 factors through the AHP. The model was validated using root mean squared error (RMSE) and compared with multiple regression analysis (MRA) through a case study in Baybay City, Philippines. Based on the results, the iLVM (RMSE = 0.526) outperformed MRA (RMSE = 1.953).

URLhttps://www.mdpi.com/2071-1050/11/13/3731
DOI10.3390/su11133731