Editorial: Digital transformation and smart technologies for sustainable built environment: innovations, applications and future pathways

Despite its significant impact on industrial employment (representing approximately 6% of total UK employment) and contribution of over £141 billion in gross value added to the economy in 2023 (ICAEW, 2025; ONS, 2024), the UK Architecture, Engineering and Construction (AEC) industry has been continuously criticised for its fragmentation for over 6 decades, resulting in numerous major industry reports. The industry currently employs approximately 2.05 million workers as of Q3 2025, though this represents a decline of 1.6% year-on-year and remains 12% lower than pre-pandemic levels (BCIS, 2025). The knowledge gap between design and construction continues to be identified as a major reason for this persistent discontinuity, with fragmentation, adversarial relationships and ineffective integration across the project lifecycle remaining central issues highlighted in successive reports from Latham (1994) and Egan (1998) through to the Farmer (2016) and recent government construction strategies (HM Government, 2011; Strategic Forum for Construction, 2002).The world has never been exposed to such a paradigm shift prior to the emerging Industry 4.0 revolution – the governing foundations for shaping and delivering progressive changes for addressing issues embracing Society, Knowledge, Economy and People (Rahimian et al., 2021; Sheikhkhoshkar et al., 2025a). Scientific advances and innovative technologies in architecture, engineering and construction (AEC) are key factors in this process, the tenets of which can help countries move towards developing smarter and more sustainable communities (Najafi and Rahimian, 2025). The European Commission’s Industry 5.0 framework extends this evolution by integrating human-centric innovation, resilience and sustainability, to align technological advancements with societal and environmental needs (Najafi et al., 2025). In this respect, the nine pillars supporting Industry 4.0 are widely accepted by the research and practice communities to include: the integration of eXtended Reality (XR=VR/AR/MR) (Potseluyko et al., 2022; Rahimian et al., 2019); where Digital Twins (Adu-Amankwa and Rahimian, 2025; Bakhshi et al., 2024; Meng et al., 2025) and mainstream Building Information Models (Bakhshi et al., 2022) in particular are seen as a vehicle for addressing such issues as industry fragmentation, value-driven solutions, decision making, client engagement and design/process flow to name but a few.Advanced Simulation (Seyedzadeh et al., 2020), Computer Vision (Pour Rahimian et al., 2020), Internet of Things (IoT) (Okonta et al., 2025), Blockchain (Basheer et al., 2024), Machine Learning (Seyedzadeh et al., 2020), Deep Learning (Lee et al., 2021) and Linked Data (Matarneh et al., 2022) all provide immense opportunities for dealing with these challenges; more importantly, perhaps, provide real tangible (evidenced-based) innovative solutions that until now, have never been possible before. These technologies, alongside Large Language Models (LLMs) (Zhou and Xue, 2025) and Natural Language Processing (NLP) (Salimi et al., 2025), provide unprecedented opportunities to tackle challenges and drive tangible, evidence-based innovations in the built environment (Sheikhkhoshkar et al., 2025b). They are perceived as the “true” enablers of future practice. Examples from other industries such as automotive, aerospace and oil and gas have provided a showcase of solutions using advanced technologies. However, until relatively recently, AEC has only started to recognise terms such as “golden key” and “golden thread” as part of Digital Twins processes and workflows, recognising their potential in creating interconnected, transparent and resilient systems.This collection brings together seventeen research contributions published in Smart and Sustainable Built Environment that collectively demonstrate how digital technologies are reshaping the design, construction, operation and management of sustainable built environments across diverse global contexts. The papers span multiple continents and countries, including Australia, the United Arab Emirates, Turkey, Finland, Nigeria, South Africa, Saudi Arabia, Pakistan, Sri Lanka, New Zealand and the United States. This geographic diversity reflects both the universal challenges facing the built environment and the context-specific nature of digital transformation strategies. This collection employs varied methodological approaches, from machine learning-aided systematic reviews and neural network modelling to behavioural studies and case-based investigations, collectively offering a comprehensive view of the current state and future trajectories of digital sustainability.Several papers address the fundamental challenge of organisational adaptation to digital technologies. Ershadi and Lijauco (2026) present a comprehensive framework for digitalising construction businesses, identifying eighteen selective codes across four critical dimensions: organisation, stakeholders, infrastructure and business environment. Their systematic review emphasises that successful digital transformation requires horizontal, vertical and end-to-end integration across the entire value chain, moving beyond isolated technical adoption toward systems thinking. This perspective is reinforced by Razmak and Farhan (2026), who propose a Digital Transformation Model specifically tailored for implementation by digital leaders in the UAE context, demonstrating that leadership competency and cultural change are as crucial as technological capability. Their research reveals that leaders aged 30–40 and those over 60 show higher orientation toward digital transformation constructs, while organisations that initiated digitalisation before COVID-19 implemented strategies significantly faster.Aliu et al. (2026) explore the significant “awareness-adoption gap” in Nigeria's construction sector, where high familiarity with digital platforms fails to translate into professional usage due to risk-averse industry culture. Their application of Diffusion of Innovation theory reveals that LinkedIn and WhatsApp have the highest awareness scores, yet Pinterest shows the highest mean gap (1.38), indicating platforms that are well-known but rarely used professionally. These studies collectively emphasise that digital transformation is fundamentally a socio-technical phenomenon requiring alignment between technology, people, processes and institutional frameworks.A substantial cluster of papers focuses on leveraging digital technologies to address the energy performance gap and enhance indoor environmental quality. Moradi et al. (2026) introduce the Collaborative and Life Cycle-based Project Delivery Model, which integrates project and product lifecycles to ensure accountability for actual operational performance rather than designed intent alone. Their research identifies fragmented delivery processes as a primary cause of energy performance gaps, with late involvement of HVAC contractors and maintenance experts contributing to suboptimal outcomes in Finnish building projects.Tomrukcu et al. (2026) demonstrate that strategic short-term data acquisition, combined with Building Energy Simulation, can achieve precise calibration without lengthy longitudinal studies. Their case study of Istanbul schools improved the predicted average internal temperature from 19.5°C to 21.3°C through systematic parameter adjustment. In the Australian context, Lu et al. (2026) examine compliance behaviour with seven-star energy ratings, revealing that only 5.73% of new Victorian houses currently exceed this rating. Their application of the Theory of Planned Behaviour identifies that most practitioners adhere only to minimum standards due to a “bottom-line mentality,” despite evidence that higher standards do not significantly increase costs. This behavioural dimension underscores that technical solutions alone are insufficient without addressing the human factors influencing decision-making.Indoor air quality emerges as another critical concern. Jung et al. (2026) demonstrate that while excellent-grade eco-friendly materials reduce toluene emissions by 97% in UAE high-rise buildings, furniture remains a dominant source of formaldehyde, often offsetting the benefits of sustainable construction materials. Karaiskos et al. (2026) advance this field further by developing LSTM neural network models that provide day-ahead predictions of safe occupancy intervals for naturally ventilated fitness facilities. Their model, trained on 77,520 data points collected over three months, demonstrates how artificial intelligence can surpass human capacity in processing complex environmental data for real-time decision support, with TVOC showing the highest availability percentage (92.8%) for safe occupancy.The integration of the Internet of Things, blockchain and artificial intelligence is a recurring theme across multiple contributions. Hassanain et al. (2026) identify data security and privacy as the primary barriers to IoT adoption in Saudi Arabian facilities management, with a high consensus (Spearman's correlation of 0.79) between facilities managers and IoT specialists regarding these concerns. Despite IoT's potential to contribute to the UN Sustainable Development Goals, staff resistance to changing traditional work methods remains a significant organisational hurdle.Ullah et al. (2026) reveal through their scoping review that Green IoT, which specifically addresses the energy consumption of digital hardware itself, remains an overlooked dimension with only thirty-three scholarly articles identified globally. Their research establishes five themes: smart cities/buildings, computing, sustainability, waste management and tracking/monitoring, while projecting that G-IoT has massive revenue potential exceeding $1.05 trillion by 2030. Ranasinghe and Rodrigo (2026) examine blockchain implementation for solar energy trading, highlighting a critical sustainability paradox: while blockchain enables transparent peer-to-peer trading without intermediaries, the technology itself is highly energy-intensive, presenting a sustainability trade-off. Their systematic review identifies Australia and China as top contributors to blockchain-based solar research, with scalability and high investment costs remaining the most cited technical challenges. This tension exemplifies the broader challenge of ensuring that digital solutions do not inadvertently undermine the environmental goals they aim to achieve.Several papers demonstrate how Building Information Modelling integrated with lifecycle assessment tools enables more informed material selection and sustainability evaluation. Sajid et al. (2026) show how BIM combined with tools like Autodesk Insight 360 and One Click LCA can swiftly identify optimal materials for a hospital project in Lahore, revealing that lightweight expanded clay aggregate offers 5.4% lower costs and 2.8% lower CO2 emissions compared to second-place alternatives, while AAC blocks perform best for reducing acidification. Fernando et al. (2026) advocate for machine learning as a superior methodology for mapping the vast landscape of green construction research, successfully filtering 5,462 relevant papers from a pool of 10,739 using Multinomial Naive Bayes classifiers. Their analysis identifies four major research clusters: green building materials, techniques, assessment and management, with assessment and techniques being the most prevalent themes, while management and technology remain the least explored.The papers also extend beyond conventional building components to nature-based solutions. Aghimien et al. (2026) explore blue-green roofs for South African contexts, identifying through Fuzzy Synthetic Evaluation that the overall impact of hindrances is rated 3.16 out of 5.00, indicating “somewhat high” barriers. Their research reveals that only 21.2% of surveyed professionals had participated in a blue-green roof project, with “fear of the unknown” and lack of exemplar projects identified as primary hindrances, despite strong motivations for stormwater management and climate change adaptation. Hashemi et al. (2026) provide a systematic review of outdoor thermal comfort in Australia and New Zealand, demonstrating that tree canopies can effectively decrease surface temperatures by 1°C in winter and 3°C in summer. Their research notes that Melbourne has the highest number of microclimatic studies in the region, though they identify significant research gaps in winter conditions and a heavy bias toward summer-based investigations.The collection importantly foregrounds social sustainability alongside technological and environmental considerations. Alsherfawi Aljazaerly et al. (2026) compare urban neighbourhoods in Istanbul, revealing how spatial organisation influences residents' experiences of safety and social interaction. Their comparative assessment of Balat (organic form) and Rasimpasa (gridded form) demonstrates that accessibility ranked highest (73–78%) and participation lowest (53–55%) in both neighbourhoods, with Balat scoring higher for social interaction while Rasimpasa provided a better sense of safety. Their finding that participation ranked lowest across both neighbourhood forms suggests persistent global weaknesses in collaborative decision-making mechanisms.Mawed (2026) explores the evolution of the UAE facilities management market from service bundling toward “business productivity,” with the market value reaching US$5.4 billion in 2019. The research identifies key trends, including Total Facilities Management and the integration of IoT and Big Data for real-time monitoring, positioning facility management as a strategic driver of smart city integration. Major threats include a shortage of skilled local labour and extreme weather affecting worker productivity, emphasising the human interface with digital building systems.The collection demonstrates important methodological advances in the generation and synthesis of sustainability knowledge. Fernando et al. (2026) argue convincingly that traditional manual literature reviews are ineffective for the massive volume of sustainability data, and that their machine-learning approach achieves 80.0% accuracy in relevancy prediction using supervised algorithms. This represents a significant leap in research efficiency, enabling comprehensive mapping of research landscapes that would be impractical through conventional methods.Similarly, Karaiskos et al. (2026) demonstrate that LSTM recurrent neural networks can process complex multi-parameter environmental data to identify safe time-slots for building occupancy with high precision, a task that exceeds human cognitive capacity given the volume and velocity of sensor data streams. These methodological innovations suggest that the field is entering a new phase where AI-assisted research synthesis and decision support become standard practice rather than experimental applications.Collectively, these seventeen papers advance knowledge by demonstrating that successful digital transformation in the built environment requires moving beyond isolated technical solutions toward integrated frameworks that combine technological innovation with organisational change management, behavioural understanding and context-specific adaptation. The research reveals several critical tensions: between universal standards and local adaptation, between the sustainability goals of digital technologies and their own environmental footprint, and between economic imperatives and environmental performance.Several important gaps and future directions emerge from this collection. First, there is a clear need for longitudinal studies that track the sustained outcomes of digital interventions beyond initial implementation. Tomrukcu et al. (2026) demonstrate that precise short-term calibration is possible, yet Jung et al. (2026) show that pollutant concentrations do not always stabilise over extended periods (185 days), making definitive reduction rates difficult to calculate. Second, the energy intensity of digital technologies themselves requires urgent attention through the development of green-by-design hardware and software solutions, as highlighted by the paradox identified in blockchain applications by Ranasinghe and Rodrigo (2026).Third, the persistent awareness-adoption gap documented by Aliu et al. (2026) suggests that research must extend beyond technical feasibility studies toward implementation science that addresses organisational culture, risk perception and change management. The behavioural determinants identified by Lu et al. (2026) – attitudes, subjective norms, perceived behavioural control and personal norms – provide a useful framework for understanding compliance behaviour that extends beyond the Australian energy rating context to broader technology adoption challenges.Fourth, the geographic concentration of research in specific regions calls for expanded investigation in underrepresented contexts. Hashemi et al. (2026) note that while temperate cities such as Melbourne and Sydney are well-documented, tropical or highly humid locations such as Darwin remain neglected. Similarly, research in developing economies, as represented by studies in Nigeria and South Africa, reveals context-specific barriers, including limited financial resources and shortages of skilled labour that may not be adequately addressed by frameworks developed in advanced economies.The papers also highlight the importance of middle-out actors, occupant engagement and behavioural determinants in realising the potential of digital technologies. Technical capabilities must be matched by shifts in organisational culture, governance mechanisms, regulatory frameworks and capacity-building initiatives. The transition to sustainable built environments through digital transformation is thus revealed as fundamentally multidimensional, requiring coordinated action across technology developers, researchers, policymakers, industry practitioners and building occupants.Looking ahead, the integration of multiple digital technologies – BIM, IoT, AI, blockchain and Digital Twins – presents both opportunities and challenges for creating truly intelligent, responsive and sustainable built environments. The papers in this collection provide valuable empirical evidence, theoretical frameworks and methodological innovations that will inform this ongoing transformation. As Ershadi and Lijauco (2026) emphasise, success depends on systems thinking that recognises the interdependencies across organisational, stakeholder, infrastructural and business environment dimensions. Only through such holistic approaches can the built environment sector realise the full potential of digital transformation in the service of global sustainability imperatives.