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Automated Valuation Methods through the Cost Approach in a BIM and GIS Integration Framework for Smart City Appraisals

Author

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  • Natale Arcuri

    (Department of Mechanical, Energy and Management Engineering, University of Calabria, 87036 Rende, Italy)

  • Manuela De Ruggiero

    (Department of Environmental Engineering, University of Calabria, 87036 Rende, Italy)

  • Francesca Salvo

    (Department of Environmental Engineering, University of Calabria, 87036 Rende, Italy)

  • Raffaele Zinno

    (Department of Environmental Engineering, University of Calabria, 87036 Rende, Italy)

Abstract

The principle behind sustainable city movements is represented by the idea of “good living”, which is the possibility of having solutions and services that allow citizens to live in an easy, simple, and enjoyable way. Policies for urban quality play a central role in the slow cities manifesto, often suggesting the use of Information and Communication Technologies (ITC) in the development of interactive services for citizens. Among these, an interesting possibility is to offer citizens digital real estate consultancy services through the implementation of automated evaluation methods. An automated appraisal action—which is already complex in itself owing to the need to collect data in a consistent, standardized, but also differentiated way so as to require the adoption of real estate due diligence—collides on the operational level with the concrete difficulty of acquiring necessary data, much more so since the reference market is dark, atypical, and viscous. These operational difficulties are deepened by the epistemological nature of the appraisal discipline itself, which bases its methodology on the forecast postulate, recalling the need to objectify as much as possible the evaluation from the perspective of an intersubjective sharing argument. These circumstances have led, on the one hand, to the definition of internationally accepted uniform evaluation rules (IVS, 2017) and, on the other, to the testing of automated valuation methods aimed at returning computer-based appraisals (AVM). Starting from the awareness that real estate valuation refers essentially to information and georeferences, this paper aims to demonstrate how real estate appraisal analysis can be further improved through information technology (IT), directing real estate valuation towards objectivity in compliance with international valuation standards. Particularly, the paper intends to show the potential of combining geographic information systems (GISs) and building information models (BIMs) in automated valuation methods through the depreciated reproduction cost. The paper also proposes a BIM-GIS semi-automatic prototype based on the depreciated reconstruction cost through an experimentation in Rende (Italy).

Suggested Citation

  • Natale Arcuri & Manuela De Ruggiero & Francesca Salvo & Raffaele Zinno, 2020. "Automated Valuation Methods through the Cost Approach in a BIM and GIS Integration Framework for Smart City Appraisals," Sustainability, MDPI, vol. 12(18), pages 1-16, September.
  • Handle: RePEc:gam:jsusta:v:12:y:2020:i:18:p:7546-:d:412938
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    References listed on IDEAS

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    2. Elena Bykowa & Maria Skachkova & Ivan Raguzin & Irina Dyachkova & Maxim Boltov, 2022. "Automation of Negative Infrastructural Externalities Assessment Methods to Determine the Cost of Land Resources Based on the Development of a “Thin Client” Model," Sustainability, MDPI, vol. 14(15), pages 1-29, July.
    3. Serena Artese & Manuela De Ruggiero & Francesca Salvo & Raffaele Zinno, 2021. "Economic Convenience Judgments among Seismic Risk Mitigation Measures and Regulatory and Fiscal Provisions: The Italian Case," Sustainability, MDPI, vol. 13(6), pages 1-25, March.
    4. Siham El Yamani & Rafika Hajji & Gilles-Antoine Nys & Mohamed Ettarid & Roland Billen, 2021. "3D Variables Requirements for Property Valuation Modeling Based on the Integration of BIM and CIM," Sustainability, MDPI, vol. 13(5), pages 1-22, March.
    5. Sisman, S. & Aydinoglu, A.C., 2022. "Improving performance of mass real estate valuation through application of the dataset optimization and Spatially Constrained Multivariate Clustering Analysis," Land Use Policy, Elsevier, vol. 119(C).

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