Digital Twin Technology and Social Sustainability: Implications for the Construction Industry

Abstract

To date, a plethora of research has been published investigating the value of using Digital Twin (DT) technology in the construction industry. However, the contribution of DT technology to promoting social sustainability in the industry has largely been unexplored. Therefore, the current paper aims to address this gap by exploring the untapped potential of DT technology in advancing social sustainability within the construction industry. To this end, a comprehensive systematic literature review was conducted, which identified 298 relevant studies. These studies were subsequently analysed with respect to their use of DT technology in supporting social sustainability. The findings indicated that the studies contributed to 8 of the 17 UN Sustainable Development Goals (SDGs), with a strong focus on SDG11 (77 publications), followed by SDG3 and SDG9, with 58 and 48 studies, respectively, focusing on promoting health and well-being and fostering resilient infrastructure and innovation. Other contributions were identified for SDG13 (30 studies), SDG7 (27 studies), SDG12 (26 studies), SDG4 (21 studies), and SDG6 (11 studies), covering areas such as climate action, responsible consumption, affordable energy, quality education, and clean water and sanitation. This paper also proposes future research directions for advancing DT technology to further enhance social sustainability in the construction industry. These include (i) enhancing inclusivity and diversity, (ii) workforce safety and well-being, (iii) training and skill development, (iv) policy and regulatory support, and (v) cross-disciplinary collaboration.

1. Introduction

The alarming depletion of natural and non-renewable resources, in tandem with increased waste and emissions, has triggered a global push towards sustainable practices over the past twenty years [1,2,3]. Although the concept of sustainability is multifaceted and often debated, a common premise in this context is the balance of current needs with the future capacity to meet those needs, as highlighted by the World Commission on Environment and Development (WCED) in 1987 [4]. This further led to the emergence of the concept of ‘sustainable development’, which encompasses three key pillars: economic, environmental, and social sustainability. This paper focuses on social sustainability, a crucial component in achieving the United Nations’ 17 Sustainable Development Goals (SDGs) and their 169 targets aimed at fostering sustainability around the world by 2030 [5]. In this regard, retrospective studies have indicated that 11 of these 17 SDGs involve social aspects in general, underscoring the importance of social sustainability [6].

Social sustainability aims to create environments that enhance well-being, uphold social justice, and respect human dignity by catering to people’s needs in their daily lives and workplaces [1,7,8]. Despite its importance, social sustainability is often seen as the least developed of the three sustainability pillars, with more focus typically placed on the economic and environmental aspects due to their more quantifiable impacts and immediate visibility in policy and industry [9,10]. However, achieving overall sustainability requires establishing robust social structures and commitments. In this regard, a plethora of research aiming to solicit the factors contributing to the hinderance of promoting social sustainability in the construction industry has been undertaken [11,12,13,14]. For example, Zuo et al. [12] highlighted essential social sustainability issues in the construction industry, such as improving occupational health and safety, offering professional development opportunities, ensuring job security, and maintaining diversity. In another study, Choi et al. [11] highlighted ongoing issues such as income inequality and biases related to race, ethnicity, and gender within the construction workforce as the key barriers impeding the attainment of social sustainability in the construction industry. In light of these challenges, the integration of innovative technologies presents a promising avenue for promoting social sustainability in the construction sector. This is echoed in the findings of previous studies [14,15], which attested to the effectiveness and potential of employing innovative technologies to improve social sustainability in the construction industry. For instance, Rostamnezhad and Thaheem [14] emphasised that innovative technologies can play a vital role in supporting social sustainability in the construction industry. They argued that the adoption of innovative technologies can assist with engaging, training, and hiring local labour, businesses, and suppliers, thereby reducing the ecological and social burdens of construction projects.

In this respect, digital twin (DT) technology holds significant potential to support the achievement of the SDGs. A DT is a virtual model that accurately replicates a physical asset, process, or system [16,17]. This technology allows for real-time monitoring, simulation, and analysis, providing valuable insights into the performance and behaviour of the physical counterparts [16,17]. The potential applications of this technology have been explored within the construction industry, including project planning and management [18,19], asset management and maintenance [20,21], safety management [22,23], energy efficiency [24,25], quality control and management [26,27], supply chain management and logistics [28,29], and structural health monitoring [30,31]. Nonetheless, there is a dearth of studies examining the capacity of this technology to achieve the SDGs within the construction industry. Recently, Tzachor et al. [32] published a perspective study discussing the potential and limitations of DT technology in promoting the SDGs. The results highlighted the promising capabilities of this technology; however, its widespread utilisation is still pending, with various challenges that need to be addressed. When it comes to the use of DT technology for realising social sustainability goals, no study has explored this area yet. Hence, there is a significant lack of understanding about the potential of this technology in supporting the construction industry’s transition towards social sustainability. As such, the current study aimed to address this gap by exploring the potential applications of DT technology in promoting social sustainability goals in the construction industry.

This study contributes to the current body of literature by providing a consolidated understanding of how DT technology can be leveraged to achieve social sustainability in the construction industry. The outcomes can be beneficial to multiple target groups. First, researchers can rely on the outcomes of this study as a point of reference for future development in this area. Second, decision-makers can utilise these findings to inform policy and strategy development, ensuring that social sustainability is integrated into construction projects. Finally, practitioners in the construction industry can adopt the insights provided to implement innovative solutions that enhance social sustainability in their projects.

2. Research Methods

This study adopted a comprehensive systematic approach to identify and retrieve materials directly related to the defined scope (Figure 1). The initial step involved compiling a list of keywords that encapsulate the concept of ‘social sustainability’. Given the complexity and multifaceted nature of this pillar of sustainability, selecting the appropriate set of keywords to ensure wide-ranging coverage of related publications posed a significant challenge. To address this, the current paper used the SDGs [5] as a foundation for developing a comprehensive search syntax. Therefore, all 17 SDGs, along with their 169 corresponding targets, were first qualitatively analysed to identify those goals that align with social sustainability. The analysis revealed that 14 SDGs are related to social sustainability (see Supplementary Materials for detailed information). This is, to a large extent, in alignment with the findings of previous studies [33,34]. The next step involved developing sets of keywords to identify materials relevant to each identified SDG. An initial list of keywords was compiled through a detailed thematic analysis of the 14 identified SDGs and their associated targets. This list underwent multiple review iterations by the authors to ensure full coverage of the relevant topics. Each iteration included reviewing the keywords’ effectiveness by conducting preliminary searches in key databases and adjusting the terms to improve both precision and recall of materials. The final keyword sets, presented in

Table 1. Keywords used to retrieve publication materials.

SDG No.	SDG	Keywords Related to the Identified Goals
1	End poverty in all its forms everywhere.	[“poverty” OR “vulnerable” OR “social protection” OR “economic” OR “income inequality”]
3	Ensure healthy lives and promote well-being for all at all ages.	[“health” OR “safety” OR “workplace safety” OR “pollution reduction” OR “healthy environments” OR “occupational health” OR “ergonomic” OR “public health”]
4	Ensure inclusive and equitable quality education.	[“vocational skills” OR “technical education” OR “employment skills” OR “youth training” OR “gender equality in education” OR “inclusive education” OR “vocational training” OR “skills development” OR “education access” OR “learning” OR “pedagogy”]
5	Achieve gender equality and empower all women and girls.	[“gender equality” OR “non-discrimination” OR “women’s empowerment” OR “equal rights” OR “workplace equity” OR “women’s leadership” OR “equal opportunities”]
6	Ensure availability and sustainable management of water and sanitation for all.	[“water access” OR “equitable water distribution” OR “water infrastructure” OR “affordable water” OR “sustainable water management” OR “hygiene infrastructure” OR “sanitation services” OR “sewage” OR “sewerage system”]
7	Ensure access to affordable, reliable, sustainable, and modern energy for all.	[“energy access” OR “affordable energy” OR “energy infrastructure” OR “sustainable energy” OR “renewable energy” OR “energy mix” OR “renewable sources” OR “green energy” OR “energy transition” OR “clean energy”]
8	Promote sustained, inclusive, and sustainable economic growth.	[“Economic Growth”; “Inclusive Growth”; “Sustainable Economy”; “Job Creation”; “Decent Work”; “Economic Resilience”; “Poverty Reduction”; “Equitable Growth”; “Innovation”; “Sustainable Industry”; “Resource Efficiency”; “Green Economy”; “Productivity”; “Employment Opportunities”; “Global Value Chains”; “Sustainable Investments”; “Economic Diversification”; “Fair Trade”]
9	Build resilient infrastructure, promote inclusive and sustainable industrialisation, and foster innovation.	[“Resilient Infrastructure” OR “Inclusive Industry” OR “Infrastructure Development” OR “Sustainable Technology” OR “Smart Infrastructure” OR “Green Technology” OR “Sustainable Construction” OR “Industrial Innovation” OR “Inclusive Development” OR “Digital Infrastructure” OR “Infrastructure Investment” OR “Urban Infrastructure” OR “Resilient Economy”]
10	Reduce inequality within and among countries.	[“Social Equality” OR “Income Inequality” OR “Economic Inequality” OR “Gender Equality” OR “Social Inclusion” OR “Equitable Development” OR “Wealth Distribution” OR “Poverty Reduction” OR “Equal Opportunity” OR “Inclusive Growth” OR “Global Inequality” OR “Social Justice” OR “Human Rights” OR “Discrimination” OR “Marginalized Communities” OR “Economic Disparity” OR “Social Mobility” OR “Equity” OR “Global Development” OR “Access to Resources”]
11	Make cities and human settlements inclusive, safe, resilient, and sustainable.	[“Affordable Housing” OR “Urban Planning” OR “Inclusive Development” OR “Sustainable Housing” OR “Community Engagement” OR “Heritage Protection” OR “Air Quality” OR “Urban Sustainability” OR “Pollution Control” OR “Public Spaces” OR “Green Spaces” OR “Inclusive Infrastructure” OR “Community Spaces” OR “Urban Accessibility” OR “Disaster Resilience” OR “Disaster Risk Management” OR “Urban Governance”]
12	Ensure sustainable consumption and production patterns.	[“resource efficiency” OR “sustainable management” OR “natural resources” OR “resource conservation” OR “sustainable production” OR “supply chain” OR “waste management” OR “pollution control” OR “environmental health” OR “recycling” OR “reuse” OR “corporate sustainability” OR “sustainable practices” OR “corporate responsibility” OR “sustainable development” OR “circular economy” OR “green technology”]
13	Take urgent action to combat climate change and its impacts.	[“climate resilience” OR “adaptive capacity” OR “disaster preparedness” OR “natural disasters” OR “climate adaptation” OR “climate policy” OR “national planning” OR “climate measures” OR “sustainable strategies” OR “policy integration” OR “climate education” OR “mitigation strategies” OR “carbon reduction” OR “green technology” OR “Paris Agreement” OR “emission control” OR “climate management”]
16	Promote peaceful and inclusive societies for sustainable development.	[“Social Inclusion” OR “Peacebuilding” OR “Human Rights” OR “Justice” OR “Conflict Resolution” OR “Social Justice” OR “Inclusive Governance” OR “Community Cohesion” OR “Violence Prevention” OR “Gender Equality” OR “Access to Justice” OR “Institutional Integrity” OR “Good Governance” OR “Public Trust” OR “Civil Rights” OR “Equity” OR “Humanitarian Aid”]
17	Strengthen the means of implementation and revitalise the global partnership for sustainable development.	[“Global Partnership” OR “Capacity Building” OR “International Cooperation” OR “Financial Resources” OR “Technology Transfer” OR “Knowledge Sharing” OR “Policy Coherence” OR “Multi-Stakeholder Collaboration” OR “Global Governance” OR “Public-Private Partnerships” OR “Innovative Financing” OR “Development Aid” OR “Trade Facilitation” OR “Institutional Capacity” OR “Monitoring and Evaluation” OR “Accountability” OR “Sustainable Financing” OR “North-South Cooperation” OR “South-South Cooperation” OR “Inclusive Partnerships” OR “Global Solidarity”]

, managed to capture the multifaceted nature of social sustainability, incorporating a broad range of terms that reflect its multiple aspects.

The next step involved combining the keywords formulated for each SDG (see Table 1) with the following keywords related to DT technology [“digital twin” OR “digital replica” OR “virtual twin” OR “digital model” OR “virtual model” OR “cyber-physical system”], as well as keywords related to the construction industry [“construction industry” OR “building sector” OR “AEC” OR “Architecture Engineering and Construction”]. This process was carried out iteratively for each of the 14 SDGs. For each SDG, the corresponding set of keywords was combined with the keywords related to DT technology and the construction industry, and then applied to search Web of Science (WoS) and Scopus. The selection of these databases was based on their extensive coverage of high-quality, peer-reviewed research across multiple disciplines, ensuring a thorough retrieval of relevant literature [35,36]. The initial results yielded 453 publications on 3 July 2024.

To weed out irrelevant materials, this study applied multiple selection criteria to ensure the inclusion of only those studies directly related to the research scope. First, non-English publications were excluded to maintain consistency and accuracy in the analysis. Additionally, the filtering functions of the databases were utilised to remove publications from fields outside the study’s focus (e.g., agricultural science and medical science). This filtering process reduced the initial dataset to 368 publications. Next, the shortlisted studies were qualitatively reviewed based on their titles, abstracts, and conclusions to assess their suitability for inclusion. The primary criterion was that the studies must have applied DT technology for a purpose aligned with one of the SDGs listed in Table 1. Consequently, studies that used DT technology for objectives not connected to social sustainability or that failed to provide sufficient details were excluded. This further reduced the number of selected studies to 298. Finally, the identified materials were downloaded for further analysis.

3. Results and Analysis

Figure 2 provides an overview of the studies identified through the systematic literature review. As shown, the review failed to identify any study examining the application of DT technology in relation to SDG1, SDG5, SDG8, SDG10, SDG16, and SDG17. The majority of the studies found were concentrated on SDG11, with 77 publications focusing on the use of DT technology in designing urban environments that are inclusive, safe, resilient, and sustainable. This was followed by SDG3 and SDG9, which had the second and third highest number of studies related to DT application to achieve these specific SDGs.

These findings also highlight both the strengths and gaps in current research trends, revealing where DT technology has been effectively applied and where further exploration is needed. One promising area for future research lies in investigating the potential of DT technology to ameliorate inclusivity in the construction industry, addressing various aspects such as age, gender, physical well-being, and cultural background. There has long been debate that the construction industry is predominantly male-dominated and favours able-bodied individuals, leading to potential discrimination against those with diverse gender identities and cultural backgrounds [37,38]. In this regard, DT technology can enhance inclusivity in the construction industry by integrating diverse perspectives into design processes and simulating spaces that ensure accessibility, gender equity, and overall user comfort. This could help minimise design biases and create more equitable environments, presenting a compelling area for future exploration.

3.1. Current Digital Twin Applications for Social Sustainability in Construction

This section aims to provide a comprehensive analysis of the applications of DT in promoting social sustainability within the construction industry. The identified studies related to each of the SDGs are discussed to evaluate their contribution to enhancing inclusivity, equity, and well-being in construction practices, while also identifying gaps and opportunities for future research.

3.1.1. DT Technology and SDG3

SDG3 is to ensure “healthy lives and promote well-being for all at all ages” [5]. The construction industry can contribute to this goal by enhancing workplace safety, creating healthier living environments, and reducing harmful environmental impacts [33]. Construction sites are among the most dangerous workplaces, responsible for one in six fatal workplace accidents [39]. Based on the International Labour Organization, over 60,000 fatalities occur annually on construction sites around the world [39]. In this regard, DT technology can help improve the safety, well-being, and overall health outcomes within the construction industry, thereby contributing to the achievement of SDG3.

The review identified 58 studies that utilised DT technology to improve safety conditions on construction sites. These studies were classified into four groups, based on the similarity of their focus areas and approaches and are discussed accordingly.

• Safety and risk management. This refers to the use of DT technology to identify, assess, and mitigate potential hazards on construction sites. Studies in this group leveraged DT technology to enhance workplace safety by simulating scenarios leading to fatalities on construction sites, considering parameters such as fire safety and fall hazards [40,41,42], monitoring real-time site conditions such as workers’ behaviour [22,23,43,44,45], improving safety and risk management practices on sites [46,47,48,49], and examining DT applications for monitoring the safety of equipment such as cranes and structures on construction sites [50,51,52,53,54]. These studies also used DTs to monitor and control noise emissions from heavy machinery, aiming to improve the on-site environmental and safety conditions [55]. The use of DT technology enables construction projects to proactively address safety concerns, reduce accident rates, and create safer environments for workers through data-driven insights and preventative measures.
• Cyber–physical integration and automation. This group explored the integration of DT technology with cyber–physical systems (CPSs) to enhance automation and safety in construction processes. Studies in this group employed DTs to synchronise real-time data for improved planning, scheduling, and execution in precast on-site assembly [56], and to enhance the safety of mobile cranes through a CPS-based approach [57,58]. Some studies also investigated the use of CPSs for monitoring temporary structures on construction sites [59,60], as well as the application of DT technology for site implementation and planning the operation of mobile cranes [61,62]. This group contained research that combined CPSs with DTs for comprehensive safety management on smart construction sites, enabling real-time synchronisation of data to improve operational decision-making [63]. These applications demonstrate the potential of integrating DT technology with CPSs, improving both the operational efficiency and safety on construction sites through real-time data analysis and automation, which can ultimately lead to minimising human errors and enhancing decision-making.
• Safety training. This research area used DT technology to enhance safety training in construction by simulating realistic, risk-free environments for workers to develop skills and improve safety awareness. Studies in this group investigated how DTs can create personalised virtual training environments tailored to specific needs [64] and used virtual reality (VR) games for safety training [65]. DT technology has also been applied to support instructor-led training, such as in the use of excavators [66] and to generate VR environments for enhanced training simulations [67]. These applications demonstrate the significant potential of DT technology in transforming traditional safety training methods by providing interactive, adaptable, and immersive learning experiences. By enabling workers to practice in virtual environments that replicate real-world conditions without the associated risks, DT technology can help reduce accidents, improve response times, and increase overall workforce preparedness. As construction projects become more complex, the continued integration of DT technology into safety training programs can play a crucial role in fostering a safer, more informed workforce.
• Infrastructure and structural health monitoring. This cluster addresses the use of DT technology for monitoring the health and safety of critical infrastructure and ensuring their long-term performance. Studies in this group have applied DT technology to assess vulnerability and perform risk-based maintenance of infrastructure, particularly bridges, under extreme conditions [68]. DT technology was also used to enhance the safety and security of buildings throughout their lifecycle by providing real-time data for monitoring structural integrity [69]. In addition, frameworks for bridge management systems utilising DT were developed to ensure that the infrastructure is regularly inspected and maintained [70]. Another application involved the creation of health maps to monitor construction worker safety, contributing to overall project health and structural performance [44]. These studies highlight the capacity of DT technology in providing proactive monitoring, identifying potential risks, and extending the lifespan of critical infrastructure.

The results of this review showed that the application of DT technology in the construction industry offers considerable advancements in promoting safety, well-being, and overall health outcomes, directly contributing to the achievement of SDG3. By enabling proactive hazard identification, improving operational efficiency through cyber–physical integration, enhancing safety training programs, and facilitating the long-term monitoring of infrastructure, DT technology has proven to be a versatile tool in addressing the critical safety challenges of the construction industry. As DT technology continues to evolve, its role in fostering safer, more sustainable construction environments will likely expand, making it a vital component in advancing both industry standards and global health and safety goals.

3.1.2. DT Technology and SDG4

SDG4 focuses on ensuring “inclusive and equitable quality education” [5], and the construction industry can support achieving this goal by offering skill development opportunities and promoting equal access to training and employment for all, regardless of gender, cultural background, and physical attributes. In this regard, DT technology can support the key agenda of SDG4 by facilitating accessible, immersive training environments that allow workers to develop essential skills through virtual simulations.

The review identified 21 studies that utilised DT technology to enhance educational methods, improve training environments, and develop skills for future professionals in construction. The studies were organised into four categories, grouped by the similarity of their focus and methodologies, and are discussed below.

• Pedagogical change and integration of DT technology in education. This group focused on the integration of DT technology into educational frameworks, aiming to revolutionise pedagogical approaches and develop digital literacy among students. For example, one study explored combining DT technology with BIM and mixed reality to transform facility management education by simulating real-world operations for better training outcomes [71]. Another study discussed how DT technology can be applied in urban planning education, providing new ways to teach city planning and management through digital twin cities [72]. In an interdisciplinary approach, Wahbeh et al. [73] examined the use of DT technology to enhance interdisciplinary education in architecture, civil engineering, and geomatics. The results demonstrated the potential of DT technology in supporting applied research and project-based learning, providing students with practical experience in managing complex, data-driven systems. In another study, Gade et al. [74] explored the development of digital literacy to support the long-term implementation of DT technology in construction education. The study used focus groups to assess how students integrate DT technology into their learning, emphasising the importance of both technical and conceptual competencies. The findings highlighted that improving digital literacy is essential for effective use of DT technology in the construction industry. These studies collectively demonstrate that DT technology can bring about meaningful pedagogical changes by integrating digital literacy and immersive experiences into construction and engineering education.
• Interactive and immersive learning environments. This group examined how DT technology is used to create immersive and interactive learning environments, enhancing the practical learning experience for students. The research showed how immersive DT environments helped maximise the students’ learning by simulating real-world architectural and construction scenarios, bridging the gap between theory and practice [75]. In one study, Goedert et al. [76] developed a Virtual Interactive Construction Education (VICE) framework that uses DT technology to create immersive, simulation-based learning environments for construction education. The VICE platform simulates real-world construction processes, allowing students to optimise time, costs, and resources while making decisions in a virtual setting. This study demonstrated how DT-based simulations can enhance student learning by providing hands-on experience with construction management tasks, improving both practical skills and decision-making abilities. Similarly, Harichandran et al. [65] discussed how DT technology can be applied to create VR-based safety games, allowing students to safely experience dangerous scenarios. Sepasgozar [77] also used DT technology in combination with web-based virtual gaming technologies to enhance online education, offering interactive platforms for construction management training.
• Skill development and workforce training. The studies in this group focused on the potential of DT technology in developing the practical skills needed for future workforce demands in the construction and engineering industries. For instance, Hazrat et al. [78] explored how DT technology can equip students with the skills needed to meet future industry demands by offering real-time simulations and data-driven training. Podder et al. [79] also investigated how DT technology can create specialised immersive environments focused on energy-efficient construction, providing trainees with relevant hands-on experience. In another study, Martínez-Gutiérrez et al. [80] proposed combining DT technology with VR to enhance training for digital operators, with a focusing on improving their skills for Industry 4.0 applications. Similarly, DT technology was used to generate personalised safety training tailored to individual workers’ specific needs, improving their preparedness for real-world risks [64]. These studies illustrate how DT technology can play a crucial role in developing a skilled and well-trained workforce that is prepared to meet the evolving needs of the construction and engineering industries.
• Monitoring and safety in educational and training settings. This group focused on the use of DT technology for safety monitoring and improving risk management in both educational and practical training settings. The research showed how DT technology, paired with augmented reality, enables students and workers to interact with and monitor construction machinery in real time, enhancing both safety and operational understanding [81]. Kamari et al. [82] used DT technology to assess and manage safety risks related to job site debris, particularly in relation to nearby structures, providing a safer learning and working environment. In another example, Wu et al. [83] proposed integrating DT technology with mixed reality to provide real-time visual warnings for construction workers, improving on-site safety conditions. DT technology was also applied to monitor ergonomic risks, helping workers adjust their behaviours to prevent injuries [84]. Collectively, these studies show how DT technology can be applied to monitor and manage safety, making both educational and real-world training environments safer and more efficient.

These studies demonstrate the promising potential of DT technology in transforming educational practices, enhance immersive learning environments, and equip future professionals with practical skills in the construction and engineering industries. By integrating DT technology with tools like VR, augmented reality, and real-time data, these studies highlight the versatility of DT technology in improving pedagogical approaches, skill development, and safety training.

3.1.3. DT Technology and SDG6

SDG6’s target is to “ensure the availability and sustainable management of water and sanitation for all” [5]. The construction industry can contribute to this target by developing sustainable water and sanitation infrastructures and improving resource management practices [33]. DT technology, when applied within the construction industry, can be supportive of SDG6 by enabling efficient management, monitoring, and optimisation of water and sanitation systems, ensuring sustainable resource use [85,86].

This review identified 11 papers that utilised DT technology to advance water and sanitation management in alignment with SDG6. These studies explored how DT technology can be leveraged to improve the efficiency and governance of water distribution systems, such as integrating DT technology with blockchain to enhance water governance and transparency [87], and applying virtual sensors for real-time monitoring of building water systems [88]. For instance, Ciliberti et al. [89] explored the use of DT technology for managing Water Distribution Networks (WDNs). They developed Digital Water Services (DWSs) on GIS platforms to improve decision-making in WDN management by integrating hydraulic modelling and AI. The study demonstrated the effectiveness of DWSs in enhancing both short-term and long-term management tasks for real-world water systems. Conejos Fuertes et al. [90] also developed a DT for managing the water distribution network in Valencia. The outcomes outlined the key requirements and challenges for maintaining the DT and demonstrated its benefits in daily operations, positioning it as a valuable tool for future smart cities.

Further research applied DT technology to smart pumping stations to optimise infrastructure management and improve operational efficiency [91,92]. In one study, Feng et al. [91] developed a high-precision DT model tailored for pumping stations to address the lack of established standards in infrastructure systems. Their model, applied to the East–West Water Transfer Project in China, integrated physical entities and operational processes, achieving 100% automatic inspection and significant cost savings. The use of DT technology for geospatial data acquisition for underground utility tunnels was also explored to enhance water management by Lee et al. [93]. They proposed a step-by-step methodology for implementing DT technology in underground utility tunnels, focusing on data acquisition, modelling, and service configuration. This approach aims to improve disaster response and facility management in critical urban infrastructure. Other studies focused on the role of DT technology in analysing water infrastructure impacts during crises such as the COVID-19 pandemic [94], and the potential for DT technology to improve the sustainability and efficiency of urban water systems [85]. The use of DT platforms in water treatment plants [95] and high-fidelity DT models for anomaly detection in smart water grids [86] further highlight the transformative role of this technology in achieving sustainable water management.

The results of reviewed studies attested to the great potential of DT technology in supporting the achievement of SDG6. From improving decision-making in WDNs to optimising infrastructure like smart pumping stations, DT technology has proven to be an effective tool for enhancing operational efficiency and resource management. However, while this technology shows promise in improving sustainability and resilience in water systems, further research is needed to address challenges such as standardisation and large-scale implementation. As DT technology continues to evolve, its role in supporting sustainable water and sanitation management will likely expand, contributing to the broader objective of ensuring access to clean water and sanitation for all.

3.1.4. DT Technology and SDG7

SDG7 focuses on ensuring “access to affordable, reliable, sustainable, and modern energy for all” [5]. The construction industry can potentially contribute to achieving this goal by developing energy-efficient infrastructure and incorporating renewable energy solutions [33,34]. In particular, DT technology can play a critical role in facilitating the achievement of this goal in different ways.

This review found 27 studies that used DT technology to improve energy efficiency, manage renewable energy integration, and optimise energy systems in both buildings and urban environments. The studies were classified into three main groups based on their approach to using DT technology and are discussed below.

• Renewable energy integration. This group of studies explored the application of DT technology to enhance the integration of renewable energy sources into energy systems. Studies in this group utilised DT technology to manage renewable energy-based power grids and optimise energy service provision, often through the integration of artificial intelligence (AI) and the Internet of Things (IoT) [96,97]. For instance, Fan and Li [96] proposed a fog computing model for managing renewable power grids using DT technology for precise energy monitoring. They applied an AI-based Whale Optimization Algorithm (WOA) to optimise load balancing in the fog layer, demonstrating a 5% improvement in performance over other algorithms. DT technology was employed to develop and simulate renewable energy systems, such as wind farms [98] and solar energy-based systems [99], enabling real-time monitoring and predictive analysis for fault detection and energy optimisation. In another study, Li et al. [100] integrated DT models with blockchain and IoT to optimise the management of hybrid connected microgrids (HMGs). Their approach used the WOA for energy management and applied blockchain to enhance power trading security, which indeed demonstrated the effectiveness of their networked HMG-EM structure. The implementation of DT technology was also shown to be effective in improving the efficiency of regional energy systems in smart cities [101]. These applications demonstrate how DT technology supports the transition toward renewable energy by enabling real-time control and improving decision-making processes.
• Development of low-carbon urban environments. This set focused on the role of DT technology in supporting net-zero energy buildings and the development of low-carbon urban environments. Several studies applied DT technology to evaluate and improve the energy performance of existing buildings, particularly those transitioning to a near-zero-energy status [102,103]. DT technology was also used to model urban resource management toward the creation of net-zero smart cities, considering renewable energy uncertainties and other urban constraints. For instance, Zhao and Zhang [104] utilised DT technology to model urban microgrid management, addressing renewable energy uncertainties and enhancing energy efficiency. Their approach integrated Non-Intrusive Load Monitoring (NILM) and smart metering for demand response, while also leveraging advanced forecasting techniques for real-time energy optimisation. This model supports the creation of net-zero smart cities by improving urban resource management and system resilience. Furthermore, research has demonstrated the use of DT simulations to integrate renewable energy sources into smart homes and urban landscapes [105], contributing to sustainable energy transitions at the city scale. These studies illustrate the capacity of DT technology to assist in achieving energy-efficient urban development through better planning and resource management.
• Smart grids and microgrids. This collection examined the application of DT technology in managing energy systems at the grid level, including both large-scale smart grids and smaller microgrids. Some studies explored the use of DT technology for predictive power control in microgrids [106], as well as fault detection, classification, and location in large-scale solar energy systems [99]. Additionally, DT simulations were used for real-time power generation predictions in microgrids, demonstrating the ability of DT technology to enhance the efficiency and reliability of these energy systems [107]. Other studies integrated climate data into national-scale energy systems through DT technology, allowing for a more comprehensive evaluation of energy systems at different scales. For instance, Savage et al. [108] applied DT technology to create a Universal Digital Twin, integrating energy supply data and climate information for the UK. Their approach used a knowledge graph to unify complex, heterogeneous domains, enabling real-time data interpretation and interactive visualisations. This model enhances urban resource management by dynamically linking energy and climate systems, supporting the development of net-zero smart cities. These applications highlight the role of DT technology in making energy systems more resilient and responsive to changing demands.

All in all, the application of DT technology in energy systems demonstrates significant potential for advancing SDG7 by improving energy efficiency, integrating renewable sources, and optimising energy management at various scales. Through real-time monitoring, AI-driven optimisation, and the incorporation of IoT and blockchain, DT technology has proven effective in both urban planning and smart grid management. As cities move towards net-zero emissions and renewable energy reliance, DT technology will play an increasingly important role in supporting sustainable and resilient energy solutions.

3.1.5. DT Technology and SDG9

The construction industry can contribute to realising SDG9 by advancing technological innovations; improving infrastructure development, particularly in developing regions; and expanding access to modern communication and information technologies [33,34]. This review identified 48 studies that applied DT technology in infrastructure management. These studies were classified into four groups and are discussed based on their focus on infrastructure resilience and maintenance, disaster management and emergency response, smart city and urban infrastructure management, and the integration of AI and IoT in infrastructure systems.

• Infrastructure resilience and maintenance. This group focused on the use of DT technology in enhancing the resilience and maintenance of infrastructure systems. Studies in this group explored how DT technology can be applied to improve the resilience of critical infrastructure such as bridges, railways, and road networks by facilitating real-time monitoring and predictive maintenance [109,110]. For instance, Wenner et al. [111] proposed a DT model for the Köhlbrandbrücke bridge in Hamburg to optimise infrastructure maintenance. By integrating sensors, IoT, and structural health monitoring, the DT enables real-time monitoring, allowing for predictive maintenance and early detection of structural issues. This approach improves maintenance efficiency and can be applied to other critical infrastructure systems to enhance their resilience and longevity. This review also found studies that employed DTs for improving resilience in civil infrastructure systems by integrating data from various sources, such as track geometry and component defects, into railway infrastructure maintenance [112,113]. For instance, Sresakoolchai and Kaewunruen [112] explored how integrating deep reinforcement learning (DRL) with DT technology can enhance railway infrastructure maintenance. The study focused on improving maintenance efficiency by developing a reinforcement learning model using real-world data from a 30 km railway section, optimizing the track geometry and defect management. Their approach demonstrated a significant reduction in both maintenance activities (by 21%) and defects (by 68%), showcasing the potential of DT technology and DRL in predictive maintenance for railway systems. These applications demonstrate the ability of DT technology to revolutionise infrastructure maintenance by enabling real-time monitoring and predictive decision-making.
• Disaster management and emergency response. This research area examined the application of DT technology for managing infrastructure systems during disasters and emergencies. Studies in this group applied DTs to enhance the management of transportation infrastructure and urban systems during events such as hurricanes and floods, improving the response times and recovery efforts [114,115]. For example, Braik and Koliou [116] proposed a novel DT framework aimed at improving the resilience of electric power infrastructure systems subjected to hurricanes. Their approach combines both physics-based and data-driven models, utilising a Dynamic Bayesian network that can be updated in near real-time through data sensing. The framework was applied to Galveston Island’s electric power network, and its ability to provide accurate and detailed estimations for decision-making, particularly in community resilience planning and infrastructure recovery, was demonstrated. This review further found studies that utilised DT systems for disaster management in smart cities, incorporating real-time data and predictive modelling to mitigate the impacts of extreme weather events like floods [117,118]. An example of such is the study conducted by Ford and Wolf [117] that proposed a conceptual model for smart cities with digital twins (SCDTs) specifically aimed at disaster management. Their study highlighted the integration of sensing and simulation across different infrastructure systems to support disaster response and recovery. Ford and Wolf [117] emphasised the importance of continuous information loops to enhance decision-making during disasters, demonstrating how SCDTs can improve the resilience of urban communities by forecasting the impacts of management strategies.
• Smart city and urban infrastructure management. This group highlighted the role of DT technology in managing and optimising urban infrastructure for smarter cities. Several studies in this group demonstrated the use of DT technology in urban planning, integrating IoT and AI for more efficient management of civil infrastructure [119,120]. For instance, Leplat et al. [121] developed NorDark-DT, a DT designed to support urban lighting infrastructure planning and analysis. Their model aimed to address the challenges of balancing human needs, wildlife conservation, and energy consumption. By integrating various research domains, NorDark-DT offers a 3D visualisation tool that allows stakeholders to simulate and evaluate different lighting scenarios, helping them to improve decision-making processes for sustainable lighting interventions in urban green spaces. In another study, Niaz et al. [122] applied DTs for road infrastructure safety and monitoring, supporting smarter cities’ development through data-driven decision-making. These applications of DT technology in urban environments underline the potential of this technology in creating more sustainable and efficient cities by enabling smarter infrastructure management.
• Integration of AI and IoT in infrastructure. This group explored the integration of AI and IoT with DT technology to improve the management of infrastructure systems. Studies in this group focused on combining AI and IoT to provide more intelligent and autonomous solutions for infrastructure systems, such as bridges and tunnels [123,124]. For example, AIoT-enabled DTs were applied to improve communication and decision-making in bridge maintenance [123]. Other research developed cognitive DTs for infrastructure health monitoring, particularly in areas such as pavement management [125]. DTs were also applied to smart city IoT applications, such as road infrastructure safety and monitoring, enabling real-time data exchange for more efficient urban management [125]. These studies highlight the transformative potential of AI and IoT in advancing DT technology for more resilient and intelligent infrastructure systems.

The application of DT technology in infrastructure management presents a profound opportunity to drive innovation, improve resilience, and foster sustainability, aligning with the goals of SDG9. By enabling real-time data analysis, predictive maintenance, and intelligent decision-making, DT solutions are reshaping how critical infrastructure systems are managed and maintained. From enhancing disaster response capabilities to advancing smart city development, these technologies are paving the way for more adaptive, resilient, and sustainable urban environments. As DT technology continues to evolve, its role in transforming infrastructure management will be pivotal in building more resilient and sustainable cities.

3.1.6. DT Technology and SDG11

SDG11 aims to “make cities and human settlements inclusive, safe, resilient, and sustainable” [5], and the construction industry can play a key role in achieving this goal [33,34]. This review identified 77 studies that applied DT technology to enhance urban planning, improve infrastructure resilience, optimise resource management, and support sustainable development in cities. These studies were categorised into four major groups, based on their scopes and similarity in their approaches to using DT technology and are discussed accordingly.

• Urban planning and sustainability. This group explored the application of DT technology to enhance urban planning and sustainability efforts. Several studies focused on how DT technology can be used for more efficient city infrastructure management and planning [126,127]. For instance, Bibri et al. [128] examined the convergence of AI, AIoT, and Urban Digital Twin (UDT) technologies in sustainable smart cities. Their study highlights how these technologies can enhance data-driven urban planning and resource management to address environmental challenges. Bibri et al. [129]’s research offers a framework for integrating AI and AIoT within UDT systems for improved decision-making and urban resilience. Other studies also utilised DTs to monitor and manage urban walkability, offering insights for creating more accessible and liveable city environments [130,131]. Sharma et al. [131] also explored the application of DT technology in urban planning to assess the impact of planning interventions on land values. Their study underscores the capacity of DT in simulating urban scenarios and generating land value uplift maps, which can further lead to providing insights into the economic sustainability of cities. By evaluating the long-term effects of planning decisions, Sharma et al. [131] showed how DT technology can support more informed and sustainable urban development strategies. In a recent study, Omrany and Al-Obaidi [132] proposed a seven-layer framework named REFLECT to address Urban Heat Island (UHI) mitigation through UDT technology. Each layer is designed to streamline the process of collecting and analysing urban data, creating a systems-based model that incorporates urban greenery optimisation, resilience in urban planning, and high-fidelity simulations. This framework aims to mitigate UHI effects by offering decision-makers actionable insights for urban cooling strategies and data-driven planning interventions.
• Cultural heritage preservation. This group focused on the use of DT technology to manage, preserve, and protect cultural heritage sites [133,134,135,136]. Studies in this group applied DT models to document and monitor the structural integrity of historical monuments [137,138], such as the Notre-Dame de Paris [139]. For instance, Yiğit and Uysal [140] conducted a study that utilised UAV photogrammetry to create a 3D DT of cultural heritage buildings for structural monitoring. Their method used machine learning to automatically detect and assess cracks, offering improved precision compared to traditional inspection techniques. This approach demonstrated the effectiveness of DT technology in enhancing the accuracy and efficiency of heritage building assessments. In another study, Massafra et al. [141] proposed a workflow that integrates Heritage Building Information Modelling and Building Performance Simulation tools to enhance the energy efficiency of modern buildings, particularly listed heritage assets. Their study focused on improving thermal demand through energy intervention strategies in historic Italian buildings, while maintaining architectural integrity. By utilising multi-criteria analysis, they were able to identify optimal renovation solutions, contributing to more sustainable heritage management practices.
• Disaster management and urban resilience. The studies in this group examined the role of DT technology in disaster management and enhancing urban resilience. The research showed that DT systems can be employed to improve real-time disaster prevention and mitigation efforts in cities [142,143,144,145]. For example, DTs were developed to simulate urban infrastructure responses to extreme weather events, such as floods, and support city-wide disaster management systems [146,147]. In another application, Wang et al. [145] proposed a framework using DT technology to enhance urban resilience by simulating disasters within a virtual environment. Their approach connects real-world data with virtual simulations, focusing on three aspects: data acquisition from reality to virtuality, disaster simulation, and translating virtual insights into disaster prevention strategies. This method addresses the limitations of traditional experimental approaches and offers dynamic disaster prediction, pre-disaster planning, real-time emergency assessments, and post-disaster recovery strategies, making it a valuable tool for building disaster-resilient cities. These applications highlight the role of DT technology in improving the preparedness and resilience of urban areas in the face of climate-related and other disasters.
• Smart cities and citizen engagement. This group explored how DT technology can foster smarter, more interactive urban environments, with a focus on citizen participation [148,149,150,151]. Several studies have demonstrated the use of DT technology for gathering and analysing citizen feedback in real-time to support urban governance and city planning [151,152]. For instance, the City of Zurich’s DT was used for urban planning and to engage citizens in shaping urban development projects [150]. In another study, White et al. [151] proposed a DT system for smart cities, focusing on integrating citizen feedback into urban planning processes. Their study demonstrated the potential of DT technology to simulate urban environments and collect real-time data from IoT devices, enabling enhanced decision-making. They applied this approach to the Docklands area in Dublin, and illustrated how citizens can interact with a virtual model to provide feedback on infrastructure developments, ensuring transparency and public involvement in urban planning. Lee et al. [153] proposed a geospatial platform for managing large-scale individual mobility within an UDT environment. Their platform, developed using the Unity3D engine, integrates both static and dynamic geospatial data, allowing for real-time management and visualisation of individual mobility, including vehicles and pedestrians. By incorporating data from public CCTV and ensuring privacy through anonymisation techniques, the platform enables enhanced urban planning and mobility management, contributing to more efficient and responsive UDT applications. These applications demonstrate the capacity of DT technology to create more inclusive, responsive, and intelligent urban systems by engaging citizens in the development of their communities.

The application of DT technology offers significant potential in advancing SDG11 by supporting sustainable urban development, cultural heritage preservation, disaster resilience, and citizen engagement. DT solutions have demonstrated their effectiveness in enhancing urban planning, optimizing resource management, and enabling real-time data integration for more informed decision-making. By leveraging AI, IoT, and advanced modelling techniques, DT systems are not only improving the resilience of cities but also fostering greater public involvement in shaping urban environments. These advancements mark an important step towards building inclusive, resilient, and sustainable cities.

3.1.7. DT Technology and SDG12

SDG12 aims to “ensure sustainable consumption and production patterns” [5], and the construction industry can contribute to this goal in various ways, such as managing resources efficiently, reducing waste, adopting sustainable practices, and promoting environmental responsibility throughout the supply chain [33,34]. This review identified 26 studies whose approach to using DT technology aligns with the overarching goals of SDG12, with a focus on improving sustainability in construction processes and resource management. These studies were grouped as follows:

• Circular economy and sustainable construction. This group focused on the role of DT technology in supporting the circular economy and enhancing sustainability in construction. This review found several studies that explored the capacity of DT technology in facilitating the recycling and reuse of materials to promote a more sustainable construction cycle [154,155,156]. For instance, Züst et al. [156] developed a graph-based Monte Carlo simulation to support the use of DT technology for the curatorial management of excavation and demolition material flows. Their model integrates the Monte Carlo method with a DT system to simulate various material flows in construction, with a focus on optimizing the recycling process of materials and reducing the reliance on primary resources. The study highlighted how DT technology can enhance decision-making for sustainable material management, with a focus on minimising landfill use and promoting recycling within the construction sector. In another study, Chen et al. [157] proposed a framework for estimating embodied carbon in buildings by integrating DT technology with life cycle assessments (LCAs). Their approach was based on utilising real-time data from DT systems to enhance the accuracy of carbon estimation throughout a building’s life cycle. The framework was also capable of streamlining communication between BIM and LCA databases, enabling more reliable carbon assessments during early design stages. The research also demonstrated the potential of DT technology in urban mining, enabling the sustainable reuse of products and materials within the construction industry [158]. Other studies focused on digital ecosystems, such as the Circular Twin Framework, to enable circular building processes [159]. These applications illustrate how DT technology can contribute to reducing waste and optimising material use in alignment with the circular economy.
• Supply chain and logistics management. This group examined how DT technology is being applied to enhance supply chain efficiency and logistics within construction projects [160,161,162,163]. Some of the studies developed DT-enabled platforms to improve supply chain coordination in modular construction, ensuring better visibility and traceability of building materials [162,164]. For instance, Yevu et al. [163] developed a DT-enabled framework to address challenges in the prefabrication supply chain, focusing on smart construction and real-time carbon emissions monitoring. By integrating RFID, GPS, and laser scanners, the study enhanced the real-time tracking of materials and processes during production and on-site assembly. This approach highlights DTs’ potential in optimising prefabrication and reducing carbon emissions throughout the construction process. Other research integrated blockchain with DT technology to support accountable information sharing and improve collaboration in the construction supply chain [28,165]. By addressing the challenges of supply chain management, DT technology has demonstrated its potential in optimising logistics, improving material tracking, and reducing inefficiencies in construction projects.
• Blockchain integration and advanced construction techniques. This study area focused on the integration of blockchain and other advanced technologies with DT technology in construction projects. The research showed that combining DT technology with blockchain can enhance the traceability and accountability of materials in fit-out operations, ensuring transparency across construction processes [166]. Blockchain-enabled DT platforms were also proposed to improve collaboration in modular integrated construction, where information sharing between stakeholders is critical for project success [165]. Additionally, one study explored the use of DT technology and blockchain to manage risks in ready-mix concrete production, showcasing their ability to mitigate operational risks and improve efficiency in construction processes [167]. These integrations highlight the transformative potential of DT technology in advancing construction practices through secure and transparent digital ecosystems.

The review showed that DT technology plays a crucial role in supporting SDG12 by promoting resource efficiency, reducing waste, and enhancing sustainability in construction processes. The reviewed studies highlight DTs’ potential in improving material management, optimising supply chains, and integrating advanced technologies like blockchain to ensure transparency and accountability. These applications demonstrate the potential of DT technology in driving sustainable practices across the construction industry, aligning with the goals of SDG12.

3.1.8. DT Technology and SDG13

SDG13 focuses on taking “urgent action to combat climate change and its impacts” [5]. The construction industry can contribute to this goal in various ways such as enhancing resilience to climate hazards, integrating climate considerations into planning, and improving the capacity for climate change mitigation and adaptation [33]. This review found 30 studies whose approaches to using DT technology align with the overarching objectives of SDG13. These studies were categorised as follows:

• Climate resilience and adaptation. This group explored how DT technology can support the construction industry in enhancing climate resilience and enabling better adaptation to climate change. Several studies highlighted the potential of DT technology in creating climate-resilient urban regeneration plans and managing critical infrastructure under climate-related risks [168,169]. For instance, Chang et al. [170] proposed a simulation-based evacuation framework aimed at enhancing disaster preparedness and response strategies. This framework, known as the Stochastic Pedestrian Cell Transmission Model (SPCTM), integrates real-time data and simulations to model pedestrian evacuations in post-disaster urban environments. By leveraging the capabilities of a DT, the system provides real-time updates and predictive analyses that inform decision-makers during critical situations, significantly improving response times and overall evacuation efficiency in earthquake-prone regions. Another study focused on using DT technology to optimise water management and disaster risk reduction, transforming climate data into actionable information [171]. The research also demonstrated that DTs can be used to simulate disaster scenarios, enabling cities to develop more effective evacuation strategies and improve response times during emergencies [172,173]. Kwon et al. [174] explored the use of DTs in flood forecasting and early warning systems, utilising real-time data to enhance emergency planning and minimise the impact of natural disasters. These studies showcase the value of DT technology in transforming disaster risk management, providing cities with the tools to better respond to climate-related emergencies and reduce vulnerabilities.
• Carbon emissions reduction and decarbonisation. This group focused on the role of DT technology in supporting decarbonisation efforts and reducing carbon emissions in building operations and urban planning. Studies in this group explored DT-enabled strategies for managing energy consumption and reducing greenhouse gas emissions, particularly in ageing residential buildings [175,176]. For example, Mohamad Zaidi et al. [177] explored the use of DT technology in mitigating energy consumption and carbon emissions in Bertam City, Penang. They utilised the Intelligent Communities Lifecycle–Intelligent Community Design (iCL-iCD) software to create a DT model of the residential areas to estimate the baseline energy consumption and carbon emissions. The use of a DT model enabled them to comprehensively demonstrate the possibility of achieving a 37.3% reduction in energy consumption and carbon emissions through adopting energy-efficient measures. In another study, Ohueri et al. [178] endeavoured to employ DTs to decarbonise building operations through retrofitting via applying IoT-based sensors to optimise energy use and cut operational carbon. These studies demonstrate how DT technology can play a pivotal role in achieving climate neutrality by providing real-time data and actionable insights for decarbonisation strategies.
• Energy efficiency and renewable energy integration. This group examined the use of DT technology for optimising energy efficiency in buildings and integrating renewable energy into urban environments [179]. Some studies showed that DTs can be leveraged to improve building energy benchmarking and enhance energy management in smart cities [180,181]. For instance, Tariq et al. [182] developed a DT model for building-integrated solar chimneys aimed at optimising ventilation, energy efficiency, and environmental impact across four different climatic zones. Their study leveraged AI techniques such as multilayer perceptron artificial neural networks (MLP-ANNs) for predictive modelling and optimisation. The research demonstrated significant improvements in air changes per hour and energy efficiency, especially in tropical and dry climatic zones, highlighting the potential of solar chimneys as a sustainable passive cooling solution in both developed and developing regions. In another study, Cao and Zhou [179] proposed a resilient microgrid model integrated with DT technology to enhance grid stability and performance under both normal and extreme conditions. Their approach combines stochastic robust optimisation with Monte Carlo simulation to account for uncertainties such as fluctuations in wind and photovoltaic power generation. This study highlighted the use of IoT devices for real-time monitoring, which enables the DT to simulate various worst-case scenarios, improving the resilience of smart grids. This framework showed promise in effective energy management and strengthening the microgrid’s adaptability to disruptions.

The findings of this section showed that DT technology plays a critical role in supporting SDG13 by enhancing climate resilience, reducing carbon emissions, and integrating renewable energy solutions. Through the use of real-time data and predictive models, DT technology enables more effective planning, disaster management, and energy optimisation. These applications show how DT technology can drive the construction industry’s contribution to climate change mitigation and adaptation.

3.2. Future Directions

The outcomes of this review showed that DT technology can support the achievement of social sustainability across many of the SDGs set out by the UN. However, it was also realised that DT technology has not been utilized to its fullest potential for several SDGs, leaving significant opportunities for further research and development to unlock its full capabilities. This section aims to highlight key future directions for advancing the application of DT technology in promoting social sustainability within the construction industry (Figure 3).

• Enhancing inclusivity and diversity. Future research could explore how DT technology can be used to create more inclusive construction practices, addressing issues such as age, gender, physical well-being, and cultural background. DT technology can help enhance accessibility, gender equity, and inclusive design by simulating diverse user experiences and needs, ensuring that construction spaces are designed to cater to all individuals, regardless of their physical or social attributes. This technology can also address cultural variability by providing a comprehensive training and learning platform that is both interactive and adaptable. By simulating real-world scenarios, DT technology allows users to become familiar with the cultural norms and expectations of the industry, promoting a more inclusive working environment.
• Workforce safety and well-being. Given the current focus on safety applications, future research could advance DT technology by integrating real-time data from wearable devices to continuously monitor workers’ health and safety. This would allow for the early detection of fatigue, exposure to hazardous environments, and potential safety violations. DTs can predict and prevent accidents by analysing real-time and historical data, offering proactive safety interventions. This technology could also be used to monitor and improve mental well-being by tracking stress levels and workload, providing timely support and adjustments to reduce burnout. Such advancements would not only enhance the physical safety of workers but also promote a more holistic approach to health by considering mental well-being in high-stress construction environments.
• Training and skill development: DT technology has significant potential to revolutionise training practices in the construction industry. Future research could focus on developing immersive, personalised training environments using VR and augmented reality that mimic real-world construction scenarios. These platforms can be tailored to the specific needs of workers, especially those from marginalised or underrepresented groups, enabling them to gain hands-on experience in a risk-free environment. By simulating complex tasks and workflows, DT technology can accelerate skill development, provide individualised feedback, and bridge knowledge gaps. This approach not only improves safety and efficiency but also ensures that a wider, more diverse workforce has access to high-quality training, thus fostering inclusivity and upskilling within the industry.
• Policy and regulatory support: Future research could focus on exploring how DT technology can be integrated into policy-making processes in order to enhance social sustainability. DTs have the potential to inform and shape regulations by providing real-time data and predictive insights that ensure fair wages, equal opportunities, and adherence to health and safety standards. By using DT simulations, policymakers could model the social impact of different regulatory frameworks and construction practices, allowing for more informed decision-making.
• Cross-disciplinary collaboration: To unlock the full social sustainability potential of DTs, collaboration between construction professionals, urban planners, sociologists, and policymakers is crucial. Future research could emphasise the need for building partnerships across these disciplines to align technology-driven advancements with broader social goals. Such cross-disciplinary collaboration would ensure that DT implementations are designed not just for technical efficiency, but also to address societal needs, such as improving community resilience, enhancing workforce diversity, and promoting equitable urban development.

The potential of DT technology can be stretched even beyond the directions recommended above. For instance, DT technology can support Industry 4.0 and 5.0 and assist the construction industry in transitioning toward greater sustainability, operational efficiency, and technological innovation. In Industry 4.0, DT technology could contribute to enhancing automation and the interconnection of cyber–physical systems, enabling real-time monitoring, predictive maintenance, and data-driven decision-making [183,184]. This capacity aligns directly with sustainable development goals by improving resource efficiency, reducing waste, and lowering carbon footprints across industries [184,185]. As Industry 5.0 emerges, with human–robot collaboration and personalised production at its core [184,185,186], DT technology continues to foster synergy between humans and machines, facilitating socially inclusive and environmentally responsible production practices. By integrating AI and sustainable practices, DT technology not only supports operational efficiency, but also contributes to SDGs focused on reducing inequalities, ensuring healthy workplaces, and promoting inclusive economic growth. This capacity makes DT technology a key enabler in realising the future goals of sustainable development, industrial efficiency, innovation, and environmental responsibility, all while supporting the evolving principles of Industry 4.0 and 5.0 across the construction sector. Future research can explore how DT technology can further integrate AI and data analytics to enhance its impact across these areas.

4. Conclusions

As the construction industry increasingly embraces digital solutions, the role of DT technology is becoming more central to addressing global sustainability challenges. To date, there has been a plethora of research undertaken to investigate the potential of DT technology across multiple domains, including the construction industry. However, no studies have been conducted to uncover the capacity of this technology in improving social sustainability in the construction industry. Hence, this study is the first of its kind, as far as the authors are aware, and endeavours to address this gap by systematically reviewing the literature on understand how DT technology can contribute to enhancing social sustainability in the construction industry.

As a result, 298 studies were identified that implemented DT technologies, contributing to 8 of the 17 SDGs. The majority of these studies focused on SDG11, with 77 publications highlighting the use of DT technology in designing urban environments that are inclusive, safe, resilient, and sustainable. SDG3 and SDG9 followed, with 58 and 48 studies, respectively, focusing on promoting health and well-being and fostering resilient infrastructure and innovation. Other contributions were identified for SDG13 (30 studies), SDG7 (27 studies), SDG12 (26 studies), SDG4 (21 studies), and SDG6 (11 studies), covering areas such as climate action, responsible consumption, affordable energy, quality education, and clean water and sanitation.

The results also showed that DT technology holds considerable potential for advancing social sustainability across various SDGs in the future. However, it is clear that this potential has yet to be fully realised, presenting significant opportunities for further research and development. Future work could focus on enhancing inclusivity and diversity by using DTs to simulate diverse user experiences, ensuring that construction designs cater to different ages, genders, physical abilities, and cultural backgrounds. DTs can also improve workforce safety and well-being by integrating real-time data from wearable devices to monitor health, detect fatigue, and manage stress levels. In terms of skill development, immersive DT-based training environments tailored to marginalised groups can help close skill gaps and promote inclusivity in the workforce. DT technology could also play a critical role in shaping policy by providing real-time insights that inform regulations promoting fair wages, equal opportunities, and safety standards. Finally, cross-disciplinary collaboration between construction professionals, urban planners, sociologists, and policymakers will be crucial for aligning DT advancements with broader social sustainability goals.

Despite the efforts undertaken to ensure a comprehensive scope, there are several limitations associated with the paper that should be highlighted. First, the review was restricted to studies published in English, potentially excluding relevant research in other languages. Additionally, the analysis primarily focused on peer-reviewed articles, which may have led to the exclusion of grey literature or industry reports that could offer practical perspectives. Nevertheless, the study still managed to provide a strong foundation for understanding the role of DT technology in supporting the realisation of social sustainability within the construction industry.