The construction industry is slow to adopt new technologies. The implementation of digital technologies and remote operations using robots were considered farfetched affairs and unbelievable approaches. However, the effect of COVID-19 on clients and construction companies put high pressure on construction managers to seek digital solutions and justified the need for remote operating or distant controlling technologies. This paper aims to investigate the state of play in construction technology implementation and presents a roadmap for developing and implementing required technologies for the construction industry. The COVID-19 disruption required new methods of working safely and remotely and coincided with the advent of advanced automation and autonomous technologies. This paper aims to identify gaps and 11 disruptive technologies that may lead to upheaval and transformation of the construction sector, perhaps in this decade. A road map for technology implementation can be helpful in developing business strategies at the organizational level as a theoretical measure, and it can facilitate the technology implementation process at the industry level as a practical measure. The roadmap can be used as a framework for policymakers to set industry or company strategies for the next 10 years (2030).

With the outset of Industrial Revolution 4.0 (IR 4.0), every sector is escalating to get enrichment out of it, whether they are research- or industry-oriented. The Architecture Engineering and Construction (AEC) industry lags a bit in adopting it because of its multi-faceted dependencies and unique nature of work. Despite this, a trend has been seen recently to hone the IR 4.0 multitudes in the AEC industry. The upsurge has been seen in the usage of Immersive Technologies (ImTs) as one of the disruptive techniques. This paper studies the literature based on ImTs, which are Virtual Reality (VR), Augmented Reality (AR), and Mixed Reality (MR) integrating with Building Information Modelling (BIM) in the AEC sector. A total number of 444 articles were selected from Scopus following the preferred reporting items for systematic reviews and meta-analysis (PRISMA) protocol of reviewing the literature. Among the selected database, 64 papers are identified as the result of following the protocol, and the articles are divided into eight domains relevant to the AEC industry, namely client/stakeholder, design exploration, design analysis, construction planning, construction monitoring, construction health/safety, facility/management, and education/training. This study adopts both a scientometric analysis for bibliometrics visualization and a critical review using Strength Weakness Opportunity Threat (SWOT) analysis for finding gaps and state of play. The novelty of this paper lies in the analysis techniques used in the literature to provide an insight into the literature, and it provides directions for the future with an emphasis on developing sustainable development goals (SDGs). In addition, research directions for the future growth on the adoption of ImTs are identified and presented based on categorization in immersive devices, graphical/non-graphical data and, responsive/integrative processes. In addition, five subcategories for each direction are listed, citing the limitations and future/needs. This study presents the roadmap for the successful adoption of ImTs for industry practitioners and stakeholders in the AEC industry for various domains. The paper shows that there are studies on ImTs with or without BIM; however, future studies should focus on the usage of ImTs in various sectors such as modular integrated construction (MiC) or emerging needs such as SDGs.

This study features the development of a framework to identify drivers towards increasing adoption of modular integrated construction (MiC) methods for affordable sustainable housing (ASH). The rise of offsite construction (OSC) techniques, especially MiC, has been evident in recent years. MiC’s adoption in ASH is still underdeveloped; however, due to various benefits of MiC over conventional construction methods, it is envisioned to be a significant emerging approach for tackling growing housing demand, and ASH in particular. Although a few prior studies identified some factors for utilization of MiC towards ASH, studies to date have not provided a holistic review of drivers or a comprehensive framework of the interrelationships between such drivers. To address this issue, this study utilizes a three-way process including a systematic literature review, semi-structured interviews and the Total Interpretive Structure Modelling (TISM) method to study the drivers for MiC adoption in ASH. Initially, 111 drivers were extracted from a review of 40 studies in the existing literature. Following that, the significant drivers of MiC adoption for ASH were grouped into cost, time, productivity, quality, environmental, social, policy and demand. Drawing on concepts of systems thinking and graph theory, the TISM model for eight drivers was developed from both the literature review and the interview results. Four levels of hierarchy were found among drivers containing linkage, driving, depending and autonomous. Succeeding the steps of TISM and Reachability Matrix (RM) and Matrice d’ Impacts Croises-Multipication Appliqué a Classement (MICMAC) analysis, social drivers were found to have the highest driving and lowest dependency power, followed by productivity and policy drivers. This signifies the importance of social factors for enhancing MiC adoption for ASH. In addition, a strategic framework of boosting MiC adoption in ASH is also presented, highlighting the key stakeholders and strategies for transformation along with conclusions. This study delivers a wider landscape of drivers for MiC-ASH synergy that may assist practitioners, policy makers and relevant stakeholders to better understand the relationships between the drivers.

Purpose: This study aimed to identify and assess the barriers to implementing modular construction systems (MCS) in developing country's architecture, engineering and construction (AEC) industry, targeting built environment professionals from Nigeria and South Africa.Design/methodology/approach: The study adopted a quantitative research method, using a structured questionnaire to seek the opinions of the professionals on the identified categories of barriers.Findings: Results indicated that all identified categories of barriers were statistically significant using a one-sample t-test at p = 0.05 significance level which indicates they are critical towards the implementation of MCS in developing countries. Assessment of the opinion of the professionals using the Kruskal–Wallis scale showed that they hold similar views on the barriers to the adoption of MCS. Pearson correlation shows a high correlation coefficient amongst the barrier categories and an acceptable level of significance (p = 0.05).Research limitations/implications: This study is limited to two significant African countries (Nigeria and South Africa) selected based on the gross domestic product (GDP). Further studies can consider developing countries outside Africa and investigate broader respondents.Practical implications: The study provides implications on the barriers affecting MCS in developing countries for the academia, industry and government to have an insight into the barriers and make informed decisions and policies.Originality/value: The research satisfies the need to study the barriers affecting the MCS in developing countries that can mitigate housing deficits. This innovative construction method has been adopted and implemented in developed countries, and the result has been positive.

Emerging applications of immersive virtual technologies are providing architects and designers with powerful interactive environments for virtual design collaboration, which has been particularly beneficial since 2020 while the architecture, engineering and construction (AEC) industry has experienced an acceleration of remote working. However, there is currently a lack of critical understanding about both the theoretical and technical development of immersive virtual environments (ImVE) for supporting architectural design collaboration. This paper reviewed recent research (since 2010) relating to the topic in a systematic literature review (SLR). Through the four steps of identification, screening, eligibility check, and inclusion of the eligible articles, in total, 29 journal articles were reviewed and discussed from 3 aspects: ImVE in the AEC industry, ImVE for supporting virtual collaboration, and applications of ImVE to support design collaboration. The results of this review suggest that future research and technology development are needed in the following areas: (1) ImVE support for design collaboration, particularly at the early design stage; (2) cognitive research about design collaboration in ImVE, toward the adoption of more innovative and comprehensive methodologies; (3) further enhancements to ImVE technologies to incorporate more needed advanced design features.

Artificial intelligence (AI), including machine learning and decision support systems, can deploy complex algorithms to learn sufficiently from the large corpus of building information modelling (BIM) data. An integrated BIM-AI system can leverage the insights to make smart and informed decisions. Hence, the integration of BIM-AI offers vast opportunities to extend the possibilities of innovations in the design and construction of projects. However, this synergy suffers unprecedented challenges. This study conducted a systematic literature review of the challenges and constraints to BIM-AI integration in the construction industry and categorise them into different taxonomies. It used 64 articles, retrieved from the Scopus database using the PRISMA protocol, that were published between 2015 and July 2024. The findings revealed thirty-nine (39) challenges clustered into six taxonomies: technical, knowledge, data, organisational, managerial, and financial. The mean index score analysis revealed financial (µ = 30.50) challenges are the most significant, followed by organisational (µ = 23.86), and technical (µ = 22.29) challenges. Using Pareto analysis, the study highlighted the twenty (20) most important BIM-AI integration challenges. The study further developed strategic mitigation maps containing strategies and targeted interventions to address the identified challenges to the BIM-AI integration. The findings provide insights into the competing issues stifling BIM-AI integration in construction and provide targeted interventions to improve synergy.