This editorial draws on the inspiration from Verhagen et al. (2024) who observed that traditionally, editorials are reflections of a journal’s editor on selected articles, a specific theme or a prominent topic that should be addressed. Therefore, for this issue 7, these [reflections] are structured around the following sections: Geographical and authorship composition; Topics and themes; Research design; Theoretical perspectives; Research outputs and activities; impact; and implications. This is achievable by deploying some methods from acceptable techniques such as Systematic Literature Reviews (SLR) and bibliometric analysis albeit without much scientific rigour such as needing bibliometric software such as Gephi, Leximancer, VOSviewer, and scientific databases such as Scopus and Web of Science (Donthu et al., 2021), but just enough to distil the geographical and authorship metrics of the 12 papers using frequencies analysis and some abridged version of thematic analysis to identify the main themes and topics in the issue. As noted by Donthu et al. (2021), bibliometric analysis whilst a popular and rigorous method, does require large volumes of scientific data. Hence, some descriptive analysis akin with SLR which categorises the published articles under the country of study, location of authors, research methodology adopted and research outputs (see Hosseini et al., 2018) for the detailed reporting on the SLR descriptive statistics, and how to conduct SLR (Pati and Lorusso, 2018).
Geographical and authorship composition: This issue consists of twelve articles from a combined total of 36 authors drawn from nine countries, both developing and developed and spread across four out of the seven continents as follows: Asia (China, India, United Arab Emirates and Vietnam); Africa (Ghana, Nigeria, Egypt and South Africa);South America (Brazil) and Europe (U.K). Vietnam dominates by the number of authors (n = 11; 30.56%) and papers (n = 5) followed by UAE with 5 authors (13.89%) and India (n = 4; 11.11%). The issue also draws on studies from two of the most populous countries in Asia namely, India with a population of 1,476,625,576, and China (ranked 2nd with 1,412,914,089 inhabitants). Interestingly, both countries’ including South Africa and Brazil belong to the original BRICS (Brazil, Russia, India, China, and South Africa) which has since expanded its membership to 11 countries including the United Arab Emirates. The inclusion of these two countries is critical as the construction activities in China alone, generate substantial air pollutants and greenhouse gas emissions, contributing heavily to ambient PM2.5 exposure and associated mortality worldwide (Wang et al., 2026). Likewise, India is the fourth-largest construction market in the world (Konar, 2026). Collectively, according to Chapungu et al. (2022), BRICS countries are among the countries with the greatest contribution of emissions into the atmosphere. Moreso, the importance of the original BRICS is that they are responsible for significant sustainable impacts on a global scale, eliciting interest in the practices they undertake to promote sustainability (Hluszko et al., 2024), and they are facing both environmental and natural resource stresses due to their rapid economic growth (Tian et al., 2020). From the digital transformation perspective, the compelling case of Nigeria’s inclusion as an area of study is provided by Adepoju and Aigbavboa (2020) who acknowledges it [Nigeria] as one of the largest and fastest growing construction markets in Africa, yet one that faces significant digital transformation challenges, and Osuizugbo et al. (2026) study in this issue offers justifiable reasons for investigating current state of proficiency and application of AI skills due to its offering of unprecedented opportunities to enhance decision making, innovation, and productivity.
As stated in Chileshe (2026a, 2026b), this huge population comes with its own challenges in achieving the Sustainable Development Goals. Further, population growth leads to urbanisation (people moving into cities), to gain resources and opportunities (Wang et al., 2019). In summation, the papers and geographical spread of the authors, and in particular the inclusion of the countries from the expanded BRICS further enhances the readers understanding of issues affecting the emerging economies as well as aligning with the Journal’s scope and mission of expanding the boundaries of knowledge in these fields and provide an international forum for the interchange of information and current issues from around the world, whilst responding to the grand challenges as identified in Ferraro et al. (2015). Whilst Europe as in Northern Ireland is represented geographically in the A. Mohy et al. (2026), the other co-authors were drawn from Egypt and the data set for this study was sourced from the U.S. OSHA Fatality and Catastrophe Investigation Summaries (FARs). Hence, the implications drawn from this research around bridging the gap between algorithmic multi-model forecasting and on-site safety management are based on insights from the U.S.
Topics and themes: Issue 6 has papers drawn from the following 7 themes of Artificial Intelligence and digitalisation; Health, safety and wellbeing; Value engineering; Sustainability; Risk Management; Building Information Modelling (BIM); and Procurement. More specifically, the topic areas are around risk management, organisational culture, sustainable supply chain management practices, intelligent construction programs, cost estimating, employee workplace mental ill-health, coping strategies for work stress, construction safety, artificial intelligence skills, green BIM readiness, falls-from-height (FFHs) risks, waste management, and value engineering. Some of the topics and themes are well aligned with grand challenges. For instance, artificial intelligence is acknowledged as a way and a tool to solve grand challenges (Uğur et al., 2024). However, Nasir et al. (2023) found the connections of artificial intelligence to be heavily skewed towards addressing SDG 9 (Industry Innovation and Infrastructure). Further, according to Thomson et al. (2021), circular economy, safety and digital construction are other example which responds to the grand challenges, albeit from the urban transition perspective. Building on from Issue 5 (Chileshe, 2026b), the significance of the Sustainable Development Goals (SDGs) is evident in this issue as 3 out of 6 papers all drawn from Vietnam are aligned with the SDG 3 of “Good health and well-being” which is aimed ensure healthy lives and promote well-being for all at all ages (Nguyen and Le, 2026; Nguyen and Do, 2026; Nguyen et al. (2026). The other papers reported have some links with SDGs such as SDG 8 of “Decent work and economic growth” through the productivity studies (Osuizugbo et al., 2026) and enhancing safety standards (A. Mohy et al., 2026; Khanh et al., 2026). Studies such as Ozili (2025) have explored the role of AI in achieving the 17 sustainable development goals. However, in this issue, the more pronounced synergy is that by Osuizugbo et al. (2026) as increasing AI skills would enable the undertaking of SDG 4 activities such as access to quality education (Ozili, 2025). Finally, the innovative practices such as sustainability-oriented contract models, material reuse strategies, and stage-specific tool adoption, demonstrating the ongoing evolution of VE from a traditional cost-reduction mechanism into a holistic driver of resource efficiency, resilience, and long-term value creation as demonstrated in Venu Jaya et al (2026) are well aligned with the following SDG 9: Industry, Innovation and Infrastructure; SDG 11: Sustainable Cities and Communities; SDG 12: Responsible Consumption and Production; and SDG 13: Climate Action. The issue demonstrates the relevance of addressing these SDGs as noted by Ika et al. (2024), addressing the SDGs are good examples of grand challenges. Collectively, these studies provide important insights into organisational and work-environment factors that affect employee mental health; investigates key sources of occupational stress amongst construction employees; and identifies and prioritises the mental ill-health risk factors of construction employees. As reported in vol 24, issue 5’s editorial (Chileshe, 2026b), and acknowledged by Wickert et al. (2021), SDGs capture societal grand challenges. Further, the topics included in this issue arise from several practical, theoretical and spotting gaps which Lim (2026) describes as the 3Us of unexplored, underdeveloped and uncertain areas.
Research design: The focus here is on provision of reflections on the selected research design, data collection and analysis techniques. As opined by the seminal study Bono and McNamara (2011), selected designs should match the research questions, and challenges around measurement and conceptualisation, inappropriate adaptation and application of existing measures, common method variance and model specification should be addressed. All the 12 papers in this issue used cross sectional data, from the data analysis perspective, most of the studies such as Anh and Nguyen (2026), Nguyen and Le (2026), and Nguyen et al. (2026) used Fuzzy Synthetic Evaluation (FSE) method. Other techniques applied were principal component analysis (PCA), correlation, and ordinal logistic regression (OLR) (Ajayi et al., 2026; Khanh et al., 2026) and A. Mohy et al. (2026) employed Graph Neural Networks, whereas Chacko et al. (2026) used Failure Mode and Effects Analysis (FMEA) and Interpretive Structural Modelling (ISM) to determine critical risk factors with greater influence. Only one study by Venu Jaya et al. (2026) employed a qualitative approach using the thematic analysis to analyse the interview data. Even so, the qualitative analysis discussed and contextualised the quantitative prioritisation results derived from the quantitative approach (survey). So, most of the studies were quantitative in nature. The adaptation and application of existing measures is welcome and evident in some papers such as Nguyen and Le (2026) which investigated key sources of occupational stress among employees in Vietnamese ADFs and verified and revised the instruments with Vietnamese experts. Likewise, Nguyen and Le (2026) adapted an existing instrument by having three items which were slightly renamed to enhance clarity and expression in Vietnamese.
Theoretical perspectives: The call for papers contributing to ether theory building or development continues in this issue and reinforced by Wickert et al. (2021), who acknowledged that scholars should contribute more substantially to broader societal concerns. For more details on how theory is described and evaluated, see Batunek and Lei (2026), whereas Makadok et al. (2018) offers a taxonomy of possible contributions to theory. Theoretical framework are identified in literature as pathway for offering new or application of existing theories that explain relations between actors and outcomes (Dale et al., 2019), therefore, papers in this issue employ various theoretical lenses, frameworks, and models including Technology Acceptance Model (TAM), Diffusion of Innovations (DOI) theory, fuzzy set theory, fuzzy logic theory, Job Demands-Resources model and Conservation of Resources theory, Maslow’s theory, Institutional theory, Social Exchange Theory (SET), Herzberg’s Two-Factor Theory, Risk perception theory, Socio-Technical Systems (STS) Theory, Organisational climate theory, Value Engineering theory, Reason’s Swiss Cheese Model and dynamic systems theory. This application of theory is commendable as theory guides the acquisition of knowledge (Lim, 2026). Hence, Osuizugbo et al. (2026), the DOI theory complements TAM by explaining how AI skills and applications spread within the AEC sector, whereas Anh and Nguyen (2026) employ Fuzzy Synthetic Evaluation (FSE) which is grounded in fuzzy logic theory. Whilst it is encouraging with the level of engagement and incorporation of theory in the reported studies, some justification, consideration and explanations around the choice of the selected theory how the findings can lead to research impact is warranted. Hollebeek et al. (2025) is a useful source of guidance towards this endeavour as the study has developed a set of six guidelines the selection of an appropriate macro-foundational theory for research impact. The framework is abbreviated as “IMPACT” which represents Interestingness, Matching, Parsimony, Applicability, Conceptual rigor, and Testability.
Research outputs and activities: Drawing on Romme and Reymen (2018) study, the five types of research outputs are described as values, constructs, models, principles and practices. Romme and Reymen (2018) study built on the seminal study by March and Smith (1995) which proposed a research framework for IT systems and identified the following the following four different types of research outputs: constructs, model, method and instantiation and mapped these to research activities of build, evaluate, theorise and justify. Romme and Reymen (2018) further differentiates these research activities into creating and evaluation (together: design) and theorising and justifying (together: validation). Dale et al. (2019) further classifies these frameworks into conceptual, management and theoretical. Thus, management frameworks are more prominent in this issue, and these are more focussed on bridging the policy-practice divide. Further, these management frameworks should include specific sets of steps, instructions and or implementation guidelines. The reported research outputs in this issue are varied and includes intelligent construction programs, frameworks such as predictive, regulatory, performance oriented circular construction, and MIT90s for assessing Green BIM readiness. Principles are evident in Venu Jaya et al. (2026) which illustrates how circular economy CE principles can be integrated into value engineering. Likewise, the Brazilian study by Barra et al. (2026) is well aligned with this requirement as the proposed and developed framework provides structured guidance for practitioners and researchers on selecting, applying, and enhancing BIM tools for quantity take-off and cost estimation. Khanh et al. (2026) proposed a model for supporting more effective Falls-from-height (FFH) risks control and management in practice and fits into the research outputs as described and represents situations as problem and solution statements. Equally, Anh and Nguyen (2026) proposed framework translates readiness assessment into actionable organisational strategies. Finally, a method as a research output is evident in A. Mohy et al. (2026) study which applied natural language processing and semantic clustering to define a validated hazard taxonomy from unstructured narratives. This fits with the March and Smith (1995) description of a method as a set of steps (an algorithm or guideline).
Impact: There is a growing need for undertaking impactful research leading to different forms of impact such scholarly, practical, societal, policy and education (Wickert et al., 2021). All the papers in this issue addresses this by reporting on one or more of the identified impacts. Other examples include reporting on the societal, scholarly and industry impact by demonstrating how societal impact is offered beyond isolated site-level interventions, modelling spatiotemporal hazard dynamics which offers profound macroeconomic implications (A. Mohy et al., 2026). The societal impact is also reported in the Venu Jaya et al (2026) of how 3R-driven VE extends beyond business and operational advantages. The study notes how the proposed paradigm enhances material efficiency, promotes reuse, and supports lifecycle-oriented decision-making, thereby reducing reliance on landfills, lowering the carbon intensity of building operations, and improving environmental health outcomes in urban communities. The reported impact could further be viewed and dissected using the “IMPACT” framework as proposed by Hollebeek et al. (2025).
Implications: The relevance of the findings to policy (Purtle et al., 2023), and need, the practical and need for theoretical implications being in manuscripts (Geletkanycz and Tepper, 2012) are observed in this issue. For instance, Yu et al. (2026) study aimed at the provision of empirical evidence of the development of intelligent construction programs by addressing research questions, and proposed policy recommendations for emerging engineering education efforts, and provides educators and policymakers with public insights into current developmental challenges. Likewise, Anh and Nguyen (2026) suggest policy developments where policy makers are included in the coordinated including the firms and stakeholders for construction firms to enhance their readiness for Green BIM. More pronounced is the expectation of policymakers to provide support through guidelines, incentives, and capacity building programs. Equally, Osuizugbo et al. (2026) demonstrated that adoption of AI could be achieved through to leveraging global best practices through responsive policy frameworks. Most importantly, the findings would aid policymakers in shaping digital transformation strategies. The importance of promoting collaborative frameworks and institutional arrangements that support cooperation among construction firms are also highlighted. Similarly, Ajayi et al. (2026) recommends that policymakers and industry regulators may consider promoting frameworks that encourage cooperative relationships among supply chain actors, as these are critical for effective sustainability implementation. From the United Arab Emirates (UAE) perspective, Venu Jaya et al. (2026), demonstrates how policy interventions can accelerate the institutionalisation of sustainable VE by shifting industry practices from isolated sustainability initiatives towards standardised, performance oriented circular construction frameworks. Overall, the papers in this issue are all significant as they contribute to the growing body of knowledge by providing empirical evidence in several themed areas from both developed, emerging and developing economies context.
In the first of the five papers from Vietnam, Nguyen and Le (2026) used the two continua model (TCM) to develop and validate the Construction Employee’s Workplace Mental Health Questionnaire (CEWMHQ) in the Vietnamese construction context. The study adopted a mixed-methods approach to strengthen the development and validation of the measurement instrument. From the findings, four mental health states supporting early detection of hidden psychological risks emerged, employee mental health was deemed as a multidimensional which could not be understood using a single continuum. The results also reinforced the theoretical proposition that wellbeing and mental illness represent distinct but related constructs. Emergent implications were that construction firms could apply the CEWMHQ to monitor employee mental health systematically across project environments. Some implications were observable – At a broader level, the classification framework may inform sector-wide mental health monitoring systems. Policymakers may use these insights to develop industry guidelines that promote both psychological safety and wellbeing. Overall, the study is significant as it advances previous research by offering a systematic method for identifying distinct mental health states among construction employees.
In the second Vietnamese study, Nguyen and Do (2026) investigated the key sources of occupational stress among employees in Vietnamese architectural design firms (ADFs) using the Occupational Sources of Stress (OSS) framework. Data collected via questionnaire was analysed using the Fuzzy Synthetic Evaluation (FSE) method. The findings showed that the most impactful stressors are work overload, tight deadlines, client change pressure, conflicting demands, and role ambiguity, respectively. The research is significant as it extends the application of the OSS framework in ADFs and highlight how Vietnam’s cultural and organisational characteristics shape workplace stress. This study offers important implications for theory, practice, policy, and society. The findings confirm that the OSS framework effectively captures the multidimensional nature of occupational stress in ADFs. It demonstrates that task-related and role-related stressors dominate stress experiences in design-based professional environments. For practice, the results suggest that organisations should prioritise managing workloads and clarifying roles before addressing other stressors. Policy-wise, improved governance practices may further reduce role-related stress and job insecurity.
In UAE, Venu Jaya et al. (2026) examined how Value Engineering (VE) could be aligned with the 3R principles-Reduce, Reuse, and Recycle, to advance sustainable construction practices, and empirically investigated the key drivers, challenges, benefits, and enabling tools and techniques influencing the adoption of 3R-driven VE across various construction project lifecycle stages. A mixed-methods approach was employed and the findings revealed that supportive government policies, early integration of VE during project planning, and structured functional analysis are the most influential drivers of 3R-driven VE adoption. Major challenges include limited awareness of economic and sustainability benefits, shortage of skilled professionals, and lack of standardized tools for sustainable material management. The study offers an environment for practitioners and policymakers to integrate 3R methods into VE, facilitated by digital technologies and incentive-based contracts, thus promoting cost-effective, waste reducing, and resilient building methodologies. This study enhances VE theory by illustrating how CE principles, specifically the 3R strategies, can be integrated into VE as a systematic decision-making framework rather than as supplementary sustainability elements.
In addressing the limitations of lagging indicators and static risk assessments, A. Mohy et al. (2026) developed an automated framework to model the dynamic nature of construction accident causation. Semantic clustering and temporal Graph Neural Networks were employed with the methodology successfully transforming unstructured accident narratives into an initiative-taking link-prediction tool. The findings showed that the GraphSAGE architecture equipped with CBAM attention yielded the highest predictive performance, outperforming baseline models. Temporal features were identified as the primary driver of predictability, outweighing static structural associations. The model successfully mapped high-probability hazard chains, such as the progression from demolition to structural and struck-by incidents. The implications are that the predictive framework enables safety managers, regulators, and planners to anticipate imminent risks and deploy targeted interventions, optimising resource allocation and site inspection schedules before sequential accidents occur. This research bridges the gap between algorithmic multi-model forecasting and on-site safety management. Integrating these predictive pathways into existing Safety Management Systems enables site managers to transition from reactive compliance to proactive, targeted interventions.
In response to the rapid evolution of artificial intelligence (AI) in redefining professional practices across industries, Osuizugbo et al. (2026) examined the current state of proficiency and application of AI skills among construction professionals in a developing country using Nigeria as a case study. Informed by the Technology Acceptance Model (TAM) and Diffusion of Innovations (DOI) theory, survey data from the constructional professionals was analysed using descriptive and inferential statistics. The findings reveal uneven digital competency levels among respondents, with stronger skills in data handling and Building Information Modelling, but significantly weaker proficiency in advanced AI-related competencies such as automation and digital project management. Overall proficiency remains low, constrained by limited formal education, curriculum-industry misalignment, and a persistent knowledge-practice gap. The study is one of the first detailed evaluation of AI skill proficiency and application in Nigeria. It also provides a clarion call to researchers, policymakers, and industry leaders to address this shortfall through targeted research, responsive policy frameworks, and innovative construction practices. In their study, Chacko et al. (2026) identified the more consequential risks affecting high-rise residential construction projects. A mixed approach comprising a structured literature review and questionnaire survey was used FMEA and Interpretive Structural Modelling (ISM) employed to determine critical risk factors with greater influence. The findings showed proved that risks at the earlier stages of project definition and project planning, if not mitigated, can give rise to secondary risks which affect the design execution. These findings advance current understanding of design-related risks by considering both their criticality and interrelationships to reflect a systemic or network-oriented perspective, which facilitates a more comprehensive approach to risk management. Further, the findings augment industry performance through a deeper understanding of project failure and facilitate the development of best practices for risk management. The study results promote a comprehensive understanding of risks impacting DM by converting uncertainty into actionable outcomes.
In the third Vietnamese study, Nguyen et al. (2026), identified and prioritised the mental ill-health risk factors of construction employees by applying Maslow’s hierarchy of needs as a theoretical framework. The research methods included data collection through a structured questionnaire survey. Fuzzy Synthetic Evaluation method was employed and the findings revealed that physiological needs, esteem needs, and self-actualisation are the top three priorities for construction employees. In contrast, safety needs and social belonging needs were ranked lower. The emergent recommendations are that construction firms should prioritise improving basic working conditions which includes ensuring fair wages, reasonable working hours, and adequate rest periods. Reducing excessive workload is essential to protect employee wellbeing. Organisations should strengthen recognition systems and career development pathways. Additionally, management practices should shift from productivity-focused approaches to employee-centred strategies. The study has some theoretical contributions as it makes methodological advances in measuring mental health levels in construction. The key take home lesson from this study is that mental health risks are multidimensional and context dependent.
In the fourth paper from Vietnam and arising from the importance of Green Building Information Modelling (Green BIM) and its offerings of significant potential for advancing sustainable construction practices, Anh and Nguyen (2026) assessed the readiness of construction firms in Vietnam to implement Green BIM. Fuzzy Synthetic Evaluation method was used to determine readiness levels across firms of varied sizes from the collected data. The findings highlighted that firm size plays a significant role in shaping readiness with large firms demonstrating the highest readiness, followed by medium-sized firms. Small firms showed the lowest levels across all five dimensions. The differences in the readiness were attributed to having clearer strategies, better-defined structures, and stronger technical infrastructure (large firms). In contrast, small firms faced resource, planning, and workforce-capability constraints. Implications for policy are practice are evident in that theoretically; the study extends the MIT90s framework for assessing Green BIM readiness. From a practical perspective, the framework proves effective in identifying internal readiness dimensions beyond technical capabilities.
In addressing an existing gap between talent cultivation and industry demands, and the lack of public opinions which make it challenging for educators to advance intelligent construction programs, Yu et al. (2026) explored public opinions on intelligent construction programs and find out key factors behind them. Informed by the DOI theory, the study employed the Bidirectional Encoder Representations from Transformers based natural language processing model to conduct topic clustering on social media posts and sentiment analysis on comments related to intelligent construction programs. From the findings, the following four mains on topic clustering of posts emerged: intelligent construction industry, intelligent construction programs, intelligent construction technologies, and intelligent construction scenarios. The study is significant as it provides public-perspective insights into intelligent construction and civil engineering education research, contributing to fostering future engineers capable of responding to the digital transformation of the construction industry. In addition, the current findings effectively explain public opinions based on the perceived intrinsic characteristics, providing educators and policymakers with public insights into current developmental challenges.
In their research, Barra et al. (2026) developed a framework for quantity takeoff from BIM models based on the requirements identified in the literature for the process and evaluated the ability of the main BIM software available on the market to meet the requirements proposed in the framework. The adopted a five-stage approach: bibliographic research; identification of BIM 5D applications and categorisation of verified approaches, development of the framework; analysis of the framework; and comparative analysis of BIM software. The results of the validation and evaluation of the framework did not significantly alter the framework’s structure but rather complemented it. and its application in a case study, through performance in a real project provided empirical validation of its use and efficiency, complementing and reinforcing the apparent validation from the experts’ responses and comments on the questionnaire. The framework has some practical implications as it provides structured guidance for practitioners and researchers on selecting, applying, and enhancing BIM tools for quantity takeoff and cost estimation.
In response to an empirical gap of where previous studies have largely focused on resource-based perspectives with limited attention to imitable and transferable practices within supply chains, Ajayi et al. (2026) investigated the relationship between organisational culture (OC) and sustainable supply chain management (SSCM) practices in Nigerian construction companies, using the competing values framework. A quantitative approach (surveys) was employed for data collection, and descriptive statistics, principal component analysis (PCA), correlation, and ordinal logistic regression (OLR) analyses were used. The findings revealed that construction companies primarily display a clan culture, followed by a market culture. The PCA identified two components of SSCM practices: inter-organisational and intra-organisational. From a practical perspective, the findings provide important insights for managers and policymakers. Construction managers are encouraged to adopt and strengthen clan-oriented cultural attributes, including trust, collaboration, and employee engagement, to support inter organisational sustainability practices. This research is significant as it bridges the knowledge gap regarding how diverse cultural profiles influence SSCM implementation.
In the last and fifth Vietnamese paper, and in understating the principal causes of life-threatening accidents in the construction industry, Khanh et al. (2026) developed models to evaluate stakeholders’ perceptions of Falls-from-height (FFH) risks. Survey data was analysed using principal analysis tools, including mean scores, Spearman’s rank correlation, and exploratory factor analysis. The findings showed that although stakeholders exhibit a high consensus in ranking the FFH risks, their assessments differ significantly. Contractors assigned the lowest average rating compared with consultants and owners, highlighting a concerning gap in FFH risk perception. Across all factors, the critical risks were found to be: “unstable scaffolding and ladders” and “slippery surfaces”. Emergent implications are that a shared understanding of FFH risks among stakeholders is essential, as it supports a systematic approach to controlling FFHs throughout the design, construction, and on-site safety management phases. The study is significant as it contributes to the literature by systematically evaluating behavioural, organisational, and environmental risk factors for each stakeholder group. Further, the study’s findings provide insights for prioritising interventions and developing stakeholder specific safety strategies.
Moving forward and based on the reported research outputs in this issue, there is a greater need of employing the design science research (DSR) methodology when dealing with the grand and societal challenges affecting the built environment. The rationale is that constructs, models, methods, and implementations as reported in this issue are all products of design science (March and Smith, 1995), and DSR can bridge theory and practice by designing and validating artefacts (Brown et al., 2021), provide the opportunity for engaging the research activities of creative design and scientific validation (Romme and Reymen, 2018), and according to Töhönen et al. (2020), design science can also solve construction or improvement problems in a given context. There is now traction in the usage of DSR in construction management and economics research (Tommelein, 2020), and design is acknowledged as a key activity in fields like architecture, engineering and planning (March and Smith, 1995).
