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

IF 16.4 1区化学 Q1 CHEMISTRY, MULTIDISCIPLINARY

Accounts of Chemical Research Pub Date : 2023-01-06 DOI:10.1108/pm-05-2022-0034

T. Osunsanmi, Timothy O. Olawumi, Andrew Smith, S. Jaradat, C. Aigbavboa, John Aliu, Ayodeji Emmanuel Oke, O. Ajayi, O. Oyeyipo

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引用次数: 2

Abstract

PurposeThe 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.Design/methodology/approachThis 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.FindingsThe 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.Originality/valueNumerous 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.

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为第四次工业革命时代的房地产专业人士建模数据科学技术的驱动因素

目的本研究旨在开发一个模型，为第四次工业革命（4IR）时代房地产专业人士应用数据科学技术提供支持。现在的4IR时代催生了大数据集，超出了房地产专业人士的分析技术。这导致了大多数房地产专业人士依赖直觉，而忽视了对房地产投资评估的严格分析。严重依赖他们的直觉是房地产投资表现不佳的原因，尤其是在非洲。设计/方法/方法这项研究利用调查问卷从房地产专业人士那里随机获取数据。使用社会科学统计软件包（SPSS）V24和矩结构分析（AMOS）图形V27软件对问卷进行分析。采用探索性因素分析将变量（驱动因素）分解为有意义的维度，有助于开发概念框架。使用基于协方差的结构方程建模对该框架进行了验证。该模型使用判别有效性、标准化均方根（SRMR）、比较拟合指数（CFI）、归一化拟合指数（NFI）等拟合指数进行了验证。结果表明，包容性的教育系统、去中心化的房地产市场和数据管理系统是将数据科学技术应用于房地产专业人员的主要驱动力。此外，房地产专业人士对驱动因素的应用将保证对房地产投资进行有效的数据分析。原创性/价值许多研究都呼吁房地产专业人士采用数据科学技术。缺乏对驱动因素的研究，这些驱动因素将保证数据科学技术的成功采用。研究中还提出了一种适用于房地产专业人士的现代数据分析形式。

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来源期刊

Accounts of Chemical Research 化学-化学综合

CiteScore

31.40

自引率

1.10%

发文量

312

审稿时长

2 months

期刊介绍： Accounts of Chemical Research presents short, concise and critical articles offering easy-to-read overviews of basic research and applications in all areas of chemistry and biochemistry. These short reviews focus on research from the author’s own laboratory and are designed to teach the reader about a research project. In addition, Accounts of Chemical Research publishes commentaries that give an informed opinion on a current research problem. Special Issues online are devoted to a single topic of unusual activity and significance. Accounts of Chemical Research replaces the traditional article abstract with an article "Conspectus." These entries synopsize the research affording the reader a closer look at the content and significance of an article. Through this provision of a more detailed description of the article contents, the Conspectus enhances the article's discoverability by search engines and the exposure for the research.