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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.

The COVID-19 pandemic came with a lot of stress, uncertainty and disruption for managing the construction supply chain (CSC). The disruption in return caused weak resilience of CSC activities. Unfortunately, the existing models for managing CSC focus on preparedness and recovery while neglecting the visibility perspective of resilience CSC. Towards creating a resilience CSC, this study modelled construction 4.0 as the vaccine for supply chain resilience in the construction industry.

A survey questionnaire was used to collect data randomly from construction stakeholders. The questionnaire was analysed with a structural equation model analysis using SmartPLS while conducting tests such as path coefficient analysis, discriminant analysis and importance-performance analysis.

This study discovered that construction 4.0 is a significant tool and vaccine for ensuring visibility, recovery and adaptation within the supply chain. Construction 4.0 will function as a vaccine for ensuring resilience because of its capacity to optimise CSC management by introducing an evidence-based management approach and less dependent on implicit knowledge. Towards reaping the full potential of construction 4.0, it should be adopted as a moderating variable.

The research is limited by the use of a single methodology (quantitative) without including a qualitative method to understand better and explore the impact of construction 4.0 on CSC resilience. The qualitative part can be carried out by conducting interviews targeted at construction stakeholders.

In spite of the limitations, the findings of this study contributed to building a more responsive and resilient CSC during the pandemic period. Furthermore, this study also presented the crucial construction 4.0 technology capable of ensuring resilience within the CSC.

This paper presents a model for applying construction 4.0 as a vaccine for ensuring CSC resilience during the COVID-19 pandemic period. This study contributed to ensuring that decisions made within the CSC adopt an evidence-based approach.

Construction 4.0 technology has the capabilities for improving the design, management, operations and decision making of construction projects. Therefore, this study aimed at examining the willingness of construction professionals towards adopting construction 4.0 technologies.

The study adopts a survey design, and construction professionals in South Africa are assessed using a convenience sampling technique through a structured questionnaire. The questionnaire was analysed with SPSS while statistical test like; mean score, t-test and principal component analysis was used to present the data.

The findings, from the analysis, revealed that the construction professionals are willing to adopt construction 4.0 technologies for construction project. However, the possibility of fully integrating the technologies into the construction industry is low. This is because the major technologies such as; Internet of things, robotics, human-computer interaction and cyber-physical systems that encourage smart construction site are rated as not important by the construction professionals.

It is believed that the findings emanating from this study will serve as an indicator for investors that are interested in procuring construction 4.0 technologies for the construction industry.

This paper presents a framework for the application of construction 4.0 technologies for the construction industry. It also contributes to the development of digitalising construction industry in South Africa.

Construction industry (CI) has great prominence for the world economy, and it is expected that, with the use of the innovative technologies and approaches of Industry 4.0 (I4.0), the new industrial paradigm, construction can reach higher levels of productivity. This study aims to develop a model (readiness model) to assess the level of use of I4.0 technologies by the construction sector in Brazil and its most relevant applications.

The methodology used was bibliographic research, design-science research and a survey to validate the model, carried out with 162 companies, considered among the main ones in the sector in Brazil. The literature review revealed 13 technologies of I4.0 applied to construction; hence, the views of industry experts were based on these technologies.

The Digital Advancement Within CoNstruction (DAWN) readiness model was proposed, showing that among the 13 evaluated technologies of I4.0 and their applications, the Brazilian construction companies had a low level of utilization; both high and middle-income companies presented this low level of use; some technologies with a greater number of scientific publications were less used in practice in the Brazilian construction.

The originality and theoretical contribution are to present a readiness model to assess the level of use of I4.0 technologies and their most relevant applications in the CI in countries with an economy similar to Brazil’s, making it possible to measure the level of adoption of these technologies.