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.

The construction industry has dynamic supply chains with multiple suppliers usually engaged in short-term relationships. Government legislation, novel types of payment agreements, conventional information technology solutions, and supply chain management best practices have endeavoured to solve payment-related financial issues in the construction industry, which are mainly caused by the complexities of the construction supply chain. Nevertheless, payment-related issues persist as one of the key challenges in the industry. Applications of blockchain technology–a trusted, distributed data storing mechanism–along with smart contracts are gaining focus as solutions for complex interorganisational processes. A smart contract is a self-executing script that codifies a set of rules or agreements between multiple parties and runs across the blockchain network. This paper identifies the suitability of blockchain and smart contract technologies in solving payment issues in the construction industry. An expert forum of construction industry stakeholders served as the primary data collection method through a structured questionnaire. The key finding of the paper is that blockchain and smart contract powered solutions can significantly mitigate the payment and related financial issues in the construction industry, including partial payments, nonpayments, cost of finance, long payment cycle, retention, and security of payments.

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, industry-related, 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.

Carbon emissions are categorised as Embodied Carbon (EC) occurring in the production phase and Operational Carbon (OC) occurring in the operational phase of buildings. The current focus on producing zero-carbon buildings, emphasises reducing OC and ignores the importance of reducing EC emissions. This study focuses on EC. Methods available in EC estimating currently produce estimates that often do not complement each other. This makes it important to develop a robust and accurate methodology for estimating EC. Blockchain is an emerging technology that has significant potential for transaction processing in supply chains. The construction industry being the second least digitalised industry, the adoption of innovative technologies is predominantly important. This paper explores the potential application of blockchain for accurate estimation of EC in construction supply chains. A detailed literature review and expert interviews revealed that, compared to traditional information systems, blockchain systems could eliminate issues in EC estimating highlighting its potential credible application for EC estimating. Scalability was identified as a feature that was lacking in a blockchain system, however, for EC estimating, its impact was identified as minimal. It will be difficult to generalise the findings of the study due to interview based qualitative methodology adopted in this study along with the fact that blockchain is an emerging and fairly new technology. However, a similar process could be followed by other studies to compare blockchain with traditional information systems, to evaluate the suitability of blockchain technology to develop prototype systems.

Building information modeling (BIM) plays a critical role in the integration of different parties by acting as a centralized database defining their responsibilities and contractual obligations. However, resolution of conflicts among stakeholders remains a shortcoming of BIM. Blockchain is on a path to disrupt many aspects of businesses that deal with the coordination of information and trust to enable a single source of truth model with multiple control entities. The purpose of this study is to analyze construction supply chain (CSC) data delivery challenges to provide a rationale for the integration of BIM and blockchain enabling a reliable digital deliverable (RDD) for operation. Three systematic reviews and a focus group discussion are used in this study. This is the first study to develop a compelling rationale systematically for the integration of BIM and blockchain and propose an RDD model, paving the way for a single source of truth system. The study enables blockchain to be set in context of both theoretical value transfer and its practical application for CSC data delivery in the form of BIM.