Mapping the landscape: a systematic literature review on automated valuation models and strategic applications in real estate

In the rapidly evolving real estate industry, integrating automated valuation models (AVMs) has become critical for improving property assessment accuracy and transparency. Although there is some research on the subject, no thorough qualitative systematic review has been done in this field. This pap...

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Main Authors: El Jaouhari, Asmae, Samadhiya, Ashutosh, Kumar, Anil, Šešplaukis, Audrius, Raslanas, Saulius
Format: Article
Language:English
English
Published: Vilnius Gediminas Technical University 2024
Subjects:
Online Access:https://repository.londonmet.ac.uk/9673/3/Revised%20Manuscript-R2.pdf
https://repository.londonmet.ac.uk/9673/9/22251-Article%20Text-93127-2-10-20240930.pdf
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author El Jaouhari, Asmae
Samadhiya, Ashutosh
Kumar, Anil
Šešplaukis, Audrius
Raslanas, Saulius
author_facet El Jaouhari, Asmae
Samadhiya, Ashutosh
Kumar, Anil
Šešplaukis, Audrius
Raslanas, Saulius
author_sort El Jaouhari, Asmae
collection LMU
description In the rapidly evolving real estate industry, integrating automated valuation models (AVMs) has become critical for improving property assessment accuracy and transparency. Although there is some research on the subject, no thorough qualitative systematic review has been done in this field. This paper aims to provide an up-to-date and systematic understanding of the strategic applications of AVMs across various real estate subsectors (i.e., real estate development, real estate investment, land administration, and taxation), shedding light on their broad contributions to value enhancement, decision-making, and market insights. The systematic review is based on 97 papers selected out of 652 search results with an application of the PRISMA-based method. The findings highlight the transformative role of AVMs approaches in streamlining valuation processes, enhancing market efficiency, and supporting data-driven decision-making in the real estate industry, along with developing an original conceptual framework. Key areas of future research, including data integration, ethical implications, and the development of hybrid AVMs approaches are identified to advance the field and address emerging challenges. Ultimately, stakeholders can create new avenues for real estate valuation efficiency, accuracy, and transparency by judiciously utilizing AVMs approaches, leading to more educated real estate investment decisions.
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spelling oai:repository.londonmet.ac.uk:96732024-10-09T10:10:37Z https://repository.londonmet.ac.uk/9673/ Mapping the landscape: a systematic literature review on automated valuation models and strategic applications in real estate El Jaouhari, Asmae Samadhiya, Ashutosh Kumar, Anil Šešplaukis, Audrius Raslanas, Saulius 330 Economics 600 Technology 650 Management & auxiliary services In the rapidly evolving real estate industry, integrating automated valuation models (AVMs) has become critical for improving property assessment accuracy and transparency. Although there is some research on the subject, no thorough qualitative systematic review has been done in this field. This paper aims to provide an up-to-date and systematic understanding of the strategic applications of AVMs across various real estate subsectors (i.e., real estate development, real estate investment, land administration, and taxation), shedding light on their broad contributions to value enhancement, decision-making, and market insights. The systematic review is based on 97 papers selected out of 652 search results with an application of the PRISMA-based method. The findings highlight the transformative role of AVMs approaches in streamlining valuation processes, enhancing market efficiency, and supporting data-driven decision-making in the real estate industry, along with developing an original conceptual framework. Key areas of future research, including data integration, ethical implications, and the development of hybrid AVMs approaches are identified to advance the field and address emerging challenges. Ultimately, stakeholders can create new avenues for real estate valuation efficiency, accuracy, and transparency by judiciously utilizing AVMs approaches, leading to more educated real estate investment decisions. Vilnius Gediminas Technical University 2024-09-30 Article PeerReviewed text en cc_by_nc_nd_4 https://repository.londonmet.ac.uk/9673/3/Revised%20Manuscript-R2.pdf text en cc_by_4 https://repository.londonmet.ac.uk/9673/9/22251-Article%20Text-93127-2-10-20240930.pdf El Jaouhari, Asmae, Samadhiya, Ashutosh, Kumar, Anil, Šešplaukis, Audrius and Raslanas, Saulius (2024) Mapping the landscape: a systematic literature review on automated valuation models and strategic applications in real estate. International Journal of Strategic Property Management, 28 (5). pp. 286-301. ISSN 1648-9179 https://journals.vilniustech.lt/index.php/IJSPM/article/view/22251 10.3846/ijspm.2024.22251 10.3846/ijspm.2024.22251
spellingShingle 330 Economics
600 Technology
650 Management & auxiliary services
El Jaouhari, Asmae
Samadhiya, Ashutosh
Kumar, Anil
Šešplaukis, Audrius
Raslanas, Saulius
Mapping the landscape: a systematic literature review on automated valuation models and strategic applications in real estate
title Mapping the landscape: a systematic literature review on automated valuation models and strategic applications in real estate
title_full Mapping the landscape: a systematic literature review on automated valuation models and strategic applications in real estate
title_fullStr Mapping the landscape: a systematic literature review on automated valuation models and strategic applications in real estate
title_full_unstemmed Mapping the landscape: a systematic literature review on automated valuation models and strategic applications in real estate
title_short Mapping the landscape: a systematic literature review on automated valuation models and strategic applications in real estate
title_sort mapping the landscape a systematic literature review on automated valuation models and strategic applications in real estate
topic 330 Economics
600 Technology
650 Management & auxiliary services
url https://repository.londonmet.ac.uk/9673/3/Revised%20Manuscript-R2.pdf
https://repository.londonmet.ac.uk/9673/9/22251-Article%20Text-93127-2-10-20240930.pdf
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