Sustainable building processes' challenges and strategies : the relative important index approach

Sustainability has been increasingly advocated by the global construction industry due to the need to minimise the industry's adverse impacts. An important area when focusing on sustainability is the issue of project management teams since they are involved from the project's inception to its completion. Many studies have investigated and advocated a wide range of sustainability practices within the construction industry. However, little attention has been geared towards construction project management teams when addressing the issues of sustainability. This study aims to provide an empirical analysis of the challenges and mitigating strategies for enhancing project management teams’ readiness in the adoption of sustainable building processes. It does so by undertaking an extensive critical review of literature resulting in the identification of sixteen challenges and sixteen mitigation strategies and conducted a cross-sectional survey among 200 Ghanaian construction industry professionals. Data obtained from the survey was analysed using descriptive statistics and relative importance index rankings. The study revealed that inadequate training and education, unfamiliarity with green technologies, and higher initial costs of green construction practices and materials are the key challenges that hinder project management teams’ implementation of sustainable building processes. The study further revealed the significant mitigation strategies such as educating stakeholders on the future benefits of green buildings, engaging personnel with green building background, and setting sustainable priorities and goals early in the feasibility study. The value of this paper is to help project management teams to understand these challenges and strategize to turn them into opportunities for the construction industry

Factors affecting reputational damage to organisations due to cyberattacks

The COVID-19 pandemic has brought massive online activities and increased cybersecurity incidents and cybercrime. As a result of this, the cyber reputation of organisations has also received increased scrutiny and global attention. Due to increased cybercrime, reputation displaying a more important role within risk management frameworks both within public and private institutions is vital. This study identifies key factors in determining reputational damage to public and private sector institutions through cyberattacks. Researchers conducted an extensive review of the literature, which addresses factors relating to risk management of reputation post-cyber breach. The study identified 42 potential factors, which were then classified using the STAR model. This model is an organisational design framework and was suitable due to its alignment with organisations. A qualitative study using semi-structured and structured questions was conducted with purposively selected cybersecurity experts in both public and private sector institutions. Data obtained from the expert forum were analysed using thematic analysis, which revealed that a commonly accepted definition for cyber reputation was lacking despite the growing use of the term "online reputation". In addition, the structured questions data were analysed using relative importance index rankings. The analysis results revealed significant factors in determining reputational damage due to cyberattacks, as well as highlighting reputation factor discrepancies between private and public institutions. Theoretically, this study contributes to the body of knowledge relating to cybersecurity of organisations. Practically, this research is expected to aid organisations to properly position themselves to meet cyber incidents and become more competitive in the post-COVID-19 era

Drivers for digital twin adoption in the construction industry : a systematic literature review

Digital twin (DT) is gaining increasing attention due to its ability to present digital replicas of existing assets, processes and systems. DT can integrate artificial intelligence, machine learning, and data analytics to create real-time simulation models. These models learn and update from multiple data sources to predict their physical counterparts’ current and future conditions. This has promoted its relevance in various industries, including the construction industry (CI). However, recognising the existence of a distinct set of factors driving its adoption has not been established. Therefore, this study aims to identify the drivers and integrate them into a classification framework to enhance its understanding. Utilising popular databases, including Scopus, Web of Science, and ScienceDirect, a systematic literature review of 58 relevant DT adoptions in the CI research was conducted. From the review, the drivers for DT adoption in the CI were identified and classified. The results show that developed countries such as the UK, US, Australia, and Italy have been the top countries in advancing DT adoption in the CI, while developing countries have made commendable contributions. A conceptual framework has been developed to enhance the successful adoption of DT in the CI based on 50 identified drivers. The major categories of the framework include concept-oriented drivers, production-driven drivers, operational success drivers, and preservation-driven drivers. The developed framework serves as a guide to propel DT adoption in the CI. Furthermore, this study contributes to the body of knowledge about DT adoption drivers, which is essential for DT promotion in the CI

Barriers to the adoption of digital twin in the construction industry : a literature review

Digital twin (DT) has gained significant recognition among researchers due to its potential across industries. With the prime goal of solving numerous challenges confronting the construction industry (CI), DT in recent years has witnessed several applications in the CI. Hence, researchers have been advocating for DT adoption to tackle the challenges of the CI. Notwithstanding, a distinguishable set of barriers that oppose the adoption of DT in the CI has not been determined. Therefore, this paper identifies the barriers and incorporates them into a classified framework to enhance the roadmap for adopting DT in the CI. This research conducts an extensive review of the literature and analyses the barriers whilst integrating the science mapping technique. Using Scopus, ScienceDirect, and Web of Science databases, 154 related bibliographic records were identified and analysed using science mapping, while 40 carefully selected relevant publications were systematically reviewed. From the review, the top five barriers identified include low level of knowledge, low level of technology acceptance, lack of clear DT value propositions, project complexities, and static nature of building data. The results show that the UK, China, the USA, and Germany are the countries spearheading the DT adoption in the CI, while only a small number of institutions from Australia, the UK, Algeria, and Greece have established institutional collaborations for DT research. A conceptual framework was developed on the basis of 30 identified barriers to support the DT adoption roadmap. The main categories of the framework comprise stakeholder-oriented, industryrelated, construction-enterprise-related, and technology-related barriers. The identified barriers and the framework will guide and broaden the knowledge of DT, which is critical for successful adoption in the construction industry

Technological advancements in green and sustainable construction

This chapter examines the technological advancements in promoting green and sustainable practices in the construction industry. Green and sustainable construction practices have in recent times become topical issues among construction researchers and practitioners. These have become necessary due to the quest to provide responses to mitigate the numerous negative environmental effects of the construction industry. The global construction industry contributes to 5.7 billion tons of carbon emissions, equalling to 23% of global carbon emissions from economic activities. Several global agreements including the Paris Agreement, Kyoto Protocol, and the United Nations Sustainable Development Goals (UNSDGs) all entreat the uptake of measures in minimising environmental impacts resulting from industries. Advancements in technologies such as the Internet of Things (IoT), blockchain, Building Information Modelling (BIM), Digital Twin (DT), Artificial Intelligence (AI), Virtual Reality (VR) and Augmented Reality (AR) are aiding the promotion of green and sustainable practices. These technologies are used in the areas of carbon emissions reduction, energy consumption optimisation, carbon sequestration, construction waste management, whole life cycle costing, among others. Studying the utilisation of technologies relating to the advancement of green and sustainable construction practices provide interesting insights into the innovative processes implemented by researchers in minimising the construction industry’s environmental impacts. The findings of this chapter include the technologies in green and sustainable construction, carbon as a metric for judging sustainability, and state-of-the-art sustainable construction trends to resolve sustainability-related issues. Discussions on the implications of the findings on green and sustainable practices within the construction industry are presented with suggestions for future research

[In Press] Obstacles to green building project financing : an empirical study in Ghana

This study examines the perception of professionals in the Ghanaian construction industry regarding the obstacles to green building project financing. Following an extensive critical comparative review of literature resulting in the identification of ten potential obstacles, a cross-sectional survey was conducted among 520 construction industry professionals. Data obtained from the survey were analysed using both descriptive and inferential statistics. The findings from the study revealed that split incentives, risk related barriers, capital expenditure, lack of incentives, and initial capital cost are the key obstacles that hinder green building project financing. The findings further revealed significant differences in the views of the professionals regarding four obstacles to green building project financing. From the discussion, it was realized that for some of the identified obstacles, the differences resulted from the fact that the different professionals have different interests in green building projects, and those interests depict the kind of risks they are exposed to. The value of this paper is to help built environment professionals to understand these obstacles and find a better way of turning these challenges into opportunities for the construction industry

Digital twin for indoor condition monitoring in living labs: University library case study

Digital twin, a technology bridging the physical and digital domains, has found extensive application in digitally advanced industries. However, its adoption in the construction sector remains limited, hindered by challenges related to construction, integration with real-time data capture, and visualisation platforms. This paper presents a construction industry digital twin that combines Building Information Modelling-based data visualisation with an Internet of Things-driven live data capture platform, outlining a methodology for its development. The digital twin was implemented in a university library embodying the ‘Living Lab’ concept to account for the nuances associated with live environments. It integrates sensors with Building Information Modelling to offer a semiotic representation of the library's internal conditions in digital twin, empowering facility managers to proactively optimize thermal, lighting, and air quality

Digital twin application in the construction industry : a literature review

The construction industry is faced with numerous challenges including low productivity, lack of research and development, and poor technology advancements. Advances in digital technologies such as digital twin (DT) has seen enormous utilisations in digitally advanced industries including the manufacturing and automotive industries. It presents an opportunity for the integration of the physical world to the digital world. DT technology has the potential to transform the construction industry and provide responses to some of its challenges. As a result, the concept of DT has attracted much attention and is developing at a rapid pace. The overarching aim of this study was to analyse the current state of DT applications in the construction industry. This study comprehensively reviews and analyses DT concept, technologies, and application in the construction industry using a systematic review methodology while incorporating the science mapping method. After a complete search of several databases and careful selection in line with the proposed criteria, 22 academic publications about DT application in the construction industry were identified and classified accordingly. The research analysed in detail the status, evolution of the concept, key technologies, and six areas of application in the lifecycle phases of a project: building information modeling, structural system integrity, facilities management, monitoring, logistics processes, and energy simulation. This research shows that there is a high potential for DT to enable solutions to the numerous challenges in the construction industry. Thus, this study raises the level of awareness and need for the application of DT in the construction industry

Obstacles to the implementation of digital twins : a review in the construction of industry

The advent of industry 4.0 gave rise to an array of digital technologies, including digital twins (DTs). DTs present the opportunity to develop digital models, which can be continually updated using several data sources to predict physical assets’ current and future conditions. These models can be simulated for real-time predictions, optimisation, monitoring, controlling and enhanced decision making regarding the status of a physical asset. In addition, DTs utilise other technologies, including artificial intelligence (AI), machine learning and data analytics. Due to the prowess of DTs, the construction industry, with its numerous challenges, have started DTs applications. Technologies such as building information modelling (BIM), Wireless Sensor Networks (WSNs), data analytics, and machine learning are currently supporting the adoption of DTs in the construction industry. Several studies (Boje et al. 2020; Opoku, DGJ et al. 2021; Sacks et al. 2020) have studied DTs in the construction industry and established their relevance. For instance, Opoku, DGJ et al. (2021) indicated that DTs are necessary for facility management since they can be employed in ‘What-if’ analysis in decision making regarding the operation and maintenance of the building. Researchers and practitioners are currently discovering the numerous potentials of DTs in the construction industry. There is, however, a misconception in the construction industry where DTs are likened to BIM due to their similarities (Khajavi et al. 2019). Opoku, D-GJ et al. (2022) and Khajavi et al. (2019) reported their differences based on their purposes, technologies, and end-users. Notwithstanding the advancement of DTs in the construction industry, it is essential to answer the question, “What barriers impede the prompt adoption of DTs in the construction industry?”. Unfortunately, little attention has been geared toward the barriers hindering DTs adoption in the construction industry. Though there have been several reviews (Alshammari et al. 2021; Deng et al. 2021; Opoku, D-GJ et al. 2022; Opoku, DGJ et al. 2021) on DTs in the construction industry, they did not pay enough attention to the barriers to DTs adoption. Thus, there is yet to be a study that comprehensively reviews the literature on the barriers to adopting DTs in the construction industry. This hinders the preparedness to fully embrace DTs in the construction industry. Therefore, this research aims to identify and rank the barriers to adopting DTs in the construction industry to support a roadmap for its adoption in the construction industry