Digital Technologies and Their Effect on the Efficiency of the Multi-Family Residential Due Diligence Process

Plieger, Alaïa Yasmin (2023) Digital Technologies and Their Effect on the Efficiency of the Multi-Family Residential Due Diligence Process. Master thesis.

Text Thesis - Alai�a Yasmin Plieger - S5123305 - Accepted Track Changes.pdf Download (1MB)

Abstract

This study investigates the impact of digital technologies, specifically Artificial Intelligence, Blockchain, Property Passports, and Automated Valuation Models, on enhancing the efficiency of the multi-family residential due diligence process. The primary objective is to optimise this process, mitigating the challenges real estate investors face. Employing an inductive qualitative research approach, the study conducts semi-structured expert interviews involving eight participants with specialised expertise in residential real estate. The findings reveal the potential of Artificial Intelligence, Automated Valuation Models, Blockchain, and Property Passports in augmenting the efficiency of the multi-family residential due diligence process. Proactively addressing adoption barriers, including governmental involvement, is identified as crucial. Additionally, establishing a greater level of trust in these technologies emerges as a necessary factor for successful implementation. This study offers a twofold contribution. Firstly, it bridges existing gaps in the limited literature on this subject. Secondly, it provides practical recommendations for companies and government entities on effectively harnessing these technologies and implementing them in practice. Overall, this research provides valuable insights into optimising the multi-family residential due diligence process through the strategic integration of digital technologies. It offers pragmatic guidance and advances knowledge in this field, ultimately fostering more streamlined and efficient real estate investment practices.

Item Type:	Thesis (Master)
Degree programme:	Real Estate Studies
Supervisor:	Daams, M.N.
Date Deposited:	03 Oct 2023 07:59
Last Modified:	03 Oct 2023 07:59
URI:	https://frw.studenttheses.ub.rug.nl/id/eprint/4396

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