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Modelling the drivers of data science techniques for real estate professionals in the fourth industrial revolution era

Osunsanmi, Temidayo; Olawumi, Timothy O.; Smith, Andrew; Jaradat, Suha; Aigbavboa, Clinton; Aliu, John; Oke, Ayodeji; Ajayi, Oluwaseyi; Oyeyipo, Opeyemi


Clinton Aigbavboa

John Aliu

Ayodeji Oke

Oluwaseyi Ajayi

Opeyemi Oyeyipo


The study aims to develop a model that supports the application of data science techniques for real estate professionals in the fourth industrial revolution (4IR) era. The present 4IR era gave birth to big data sets and is beyond real estate professionals' analysis techniques. This has led to a situation where most real estate professionals rely on their intuition while neglecting a rigorous analysis for real estate investment appraisals. The heavy reliance on their intuition has been responsible for the under-performance of real estate investment, especially in Africa.

This study utilised a survey questionnaire to randomly source data from real estate professionals. The questionnaire was analysed using a combination of Statistical package for social science (SPSS) V24 and Analysis of a Moment Structures (AMOS) graphics V27 software. Exploratory factor analysis was employed to break down the variables (drivers) into meaningful dimensions helpful in developing the conceptual framework. The framework was validated using covariance-based structural equation modelling. The model was validated using fit indices like discriminant validity, standardised root mean square (SRMR), comparative fit index (CFI), Normed Fit Index (NFI), etc.

The model revealed that an inclusive educational system, decentralised real estate market and data management system are the major drivers for applying data science techniques to real estate professionals. Also, real estate professionals' application of the drivers will guarantee an effective data analysis of real estate investments.

Numerous studies have clamoured for adopting data science techniques for real estate professionals. There is a lack of studies on the drivers that will guarantee the successful adoption of data science techniques. A modern form of data analysis for real estate professionals was also proposed in the study.

Journal Article Type Article
Acceptance Date Sep 15, 2022
Online Publication Date Jan 6, 2023
Publication Date Mar 22, 2024
Deposit Date Sep 23, 2022
Publicly Available Date Jan 6, 2023
Print ISSN 0263-7472
Publisher Emerald
Peer Reviewed Peer Reviewed
Keywords Data science, decentralised market, fourth industrial revolution, inclusive educational system, real estate professional
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Modelling The Drivers Of Data Science Techniques For Real Estate Professionals In The Fourth Industrial Revolution Era (accepted version) (603 Kb)

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Copyright Statement
This Author Accepted Manuscript (AAM) is deposited under the Creative Commons Attribution Non-commercial International Licence 4.0 (CC BY-NC 4.0) and any reuse is allowed in accordance with the terms outlined by the licence. To reuse the AAM for commercial purposes, permission should be sought by contacting

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