Purpose The use of Environmental, Social and Governance (ESG) criteria has become crucial for investment decision-making. However, industry-to-industry ESG assessment criteria has become a daunting task because of the peculiarities of industry practices. This study contributes to this research domain by identifying ESG assessment criteria of public-private partnership (PPP) projects and assessing their resultant effects on project sustainability. Design/methodology/approach The study followed the PRISMA guidelines and conducted systematic review of 47 peer-reviewed articles from Scopus database and organisational reports. Comprehensive search is done using keywords such as social sustainability, corporate social responsibility, environmental sustainability, and governance sustainability for PPP projects. Identified articles are evaluated using descriptive analysis to identify PPPs ESG assessment criteria. Findings The results show that the long-term impact of infrastructure development projects on ecosystems, green solid waste reduction and natural resource conservation are critical environmental criteria. Also, with social criteria, how PPPs prioritize worker health and safety, PPP tendering and stakeholder engagement are key criteria. Furthermore, how PPP projects outline a defined plan for reaching commercial and financial close of a project, how it improves supply chain planning process, and ensuring due diligence with tender documents and drafted PPP contracts are realised governance practices. The findings from the study establishes industry-specific adaptable ESG criteria that promises positive project sustainability. Originality/value The study establishes a theoretical checklist of forty-six PPP ESG assessment criteria for PPP investment decision-making.
Purpose Delays in the construction industry continue to be a challenge in India, which has been mainly caused by a lack of proper planning, ill-defined decision-making and inability to adapt to technological advancements. The proposed research work aims to analyze the impact of the use of specific, measurable, achievable, relevant and time-bound (SMART) project management techniques, in partnership with Internet of Things (IoT), to improve delay management in the Indian construction industry. Design/methodology/approach The approach was qualitative and expert-driven. Sixteen dimensions of delay, identified from the literature using a political, economic, social, technological, environmental and legal (PESTEL) analysis, were verified by eight senior experts from industry, government, technology supply and academia. Total interpretive structural modeling (TISM) was performed to generate the relationship between identified variables. Fuzzy Matrixy Impacts Croisés Multiplication Appliquée á un Classement (MICMAC) analysis was performed to classify variables based on their driving power and dependence into independent, dependent, linkage and autonomous categories. Findings Issues of disputes, negotiations, lack of communication, planning, lack of clear contract procedures and scope creep were identified as the most probable delay causes. The adoption of smart philosophy in monitoring allows better coordination, decision-making and provides a clear avenue for eliminating process inefficiencies. Originality/value This study integrates SMART project management, IoT and a PESTEL–TISM–Fuzzy MICMAC framework to analyze construction delays in India. It advances prior research by modeling interdependencies and prioritizing delay drivers based on systemic influence, linking macro-environmental factors with organizational practices to inform managerial and policy-level interventions for improved project performance.
Purpose This study aims to systematically identify, categorize and prioritize barriers to the adoption of artificial intelligence (AI) in circularity-driven smart cities. By framing the analysis through the lens of the circular economy (CE), the research addresses the knowledge gap in understanding the technological, governance, socio-technical and infrastructural barriers that hinder AI integration in sustainable urban contexts.Design/methodology/approach A picture fuzzy Z-analytic hierarchy process (PF Z-AHP) approach is employed to capture expert judgments under uncertainty and prioritize the identified barriers. The methodology integrates picture fuzzy sets with the analytic hierarchy process within a multi-expert decision-making framework to systematically evaluate and rank barriers related to digital infra-structure, governance and policy, socio-technical engagement and urban technological capacity.Findings The results show that socio-technical and community engagement barriers hold the highest overall category weight, followed by circularity-enabling digital and data infrastructure barriers. At the individual level, skills gap and resistance to change emerges as the most critical barrier, highlighting the importance of human capital readiness in facilitating artificial intelligence-enabled circular transitions in smart cities.Originality/value This research contributes to the literature by integrating fuzzy-based multi-criteria decision-making to examine AI adoption in circular economy-oriented smart cities. The study presents a novel application of PF Z-AHP for evaluating barriers under uncertainty, offering a replicable methodological framework for advancing sustainable, AI-driven circular urban transformations.
PurposeIncremental innovation is widely perceived as essential for construction firms seeking to sustain competitiveness, enhance project performance capabilities and adapt to changing industry demands. However, it has received limited attention compared to radical innovation, which emphasises disruptive change. Existing studies often examine individual enablers in isolation, with a limited understanding of how incremental innovation can be systematically supported. This paper addresses this gap by synthesising past studies to identify the enablers that support incremental innovation in construction firms. Design/methodology/approachA systematic literature review guided by preferred reporting items for systematic reviews and meta-analyses 2020 was conducted on 60 articles published between 2015 and 2025. Using the human-technology-organisation (HTO) framework, the review identified 8 key enablers with 18 sub-enablers that explain how incremental innovation can be effectively supported within construction firms. FindingsThe analysis shows that the human, technological and organisational categories of the HTO framework are interdependent in fostering incremental innovation. Among these, teamwork emerged as the main key enabler, while collaboration emerged as the most cited sub-enabler and is frequently associated with the successful implementation of incremental innovation in construction firms. Originality/valueDespite increasing attention, enablers of incremental innovation remain underexplored and inconsistently categorised. This paper offers practical guidance on elements that can support the growth of incremental innovation in construction firms. By consolidating fragmented insights, it provides a foundation for future empirical studies and offers guidance for practitioners seeking to foster incremental innovation in their firms, with potential implications for improved collaborative practices in construction projects.
Purpose The heating, ventilation and air conditioning (HVAC) systems are vital for maintaining indoor air quality and patient safety in healthcare facilities. However, the inconsistent asset data and inadequate documentation are some critical issues that challenge the repair and maintenance (R&M) processes of such systems. This research aims to address these challenges by creating a HVAC-centric building information model focused on the R&M of a healthcare centre. Design/methodology/approach A design science research approach is adopted, which involves the creation, demonstration and evaluation of a BIM to enhance the R&M processes of HVAC systems in a healthcare centre. Findings The created HVAC-centric building information model supports collaboration with the manufacturer, preventive maintenance, workforce planning, fault diagnosis, decision support, cost savings and inspection and audit. Collectively, these benefits will help the maintenance teams optimise the R&M performance. Practical implications The strategic professionals emphasise R&M history and preventive maintenance schedules as crucial information. Managerial staff require warranty, spare parts and location data. Meanwhile the tactical personnel focus on manufacturer details. This role-specific information need, which has been largely neglected by past studies, indicates that both system and user-level customisation are required when creating BIM. Originality/value This research addresses a critical gap by creating a HVAC-centric building information model tailored to the operational challenges of healthcare facilities, thereby delivering a data-rich, practice-ready tool that will assist maintenance professionals in managing R&M tasks effectively.
Purpose This study systematically analyzes existing research at the intersection of Industry 4.0 (I4.0) and the emerging Industry 5.0 (I5.0) paradigm in construction materials. It identifies dominant themes, temporal trends and research gaps, with particular attention to performance, sustainability and digital technologies. Design/methodology/approach This study offers a thematic analysis of 1,797 documents sourced from Scopus and Google Scholar. This method is followed based on Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guideline and analyzed by Biblioshiny approaches within 2016–2025. The analysis is suggested based on co-occurrence networks, thematic maps and temporal Sankey diagrams. Findings Although compressive strength (203 occurrences) and mechanical properties (143 occurrences), including compressive, split tensile and flexural strengths, are still essential for I4.0, there is an increasing focus on sustainability and resiliency. However, the human centricity is still unexplored since the I5.0 is in the very early stage, and its impacts on human factors are yet in the steady phase. Thematic mapping results suggest emerging areas including machine learning, graphene, basalt fiber, composites and sustainable building. Practical implications The results provide essential insights for academics, practitioners and policymakers informing policy development, guiding material innovation and shaping regulatory standards. Originality/value The work offers, for the first time, the relationship between I4.0 with construction material context from basic compressive strength and mechanical properties to emerging technological and social aspects.
Purpose This study investigates how adaptive gyroscopic systems can improve indoor environmental quality (IEQ) and support low-energy building performance in Sub-Saharan Africa. The region faces persistent heat stress and unreliable electricity, and most buildings rely on passive strategies that cannot adjust to changing conditions. The study addresses the lack of research connecting gyroscopic mechanisms to climate-responsive design in this context. Design/methodology/approach A bibliometric review supported by the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) protocol was conducted using Scopus publications from 2003 to 2024. Keyword co-occurrence, citation mapping, and thematic clustering were used to examine research on thermal comfort, ventilation, adaptive shading, energy use, and emerging gyroscopic or AI-assisted control systems. Findings The analysis shows growing interest in adaptive environmental control, though direct building applications of gyroscopic systems remain limited. Two main clusters emerged: one focused on IEQ performance (thermal comfort, ventilation, energy efficiency) and another on regional sustainability themes. Evidence suggests that gyroscopic mechanisms, especially when paired with lightweight AI tools, can support airflow regulation, sun-responsive shading, and simple energy-management functions suited to low-energy buildings. Research limitations/implications Further prototype development and real-world testing are needed. Practical implications Gyroscopic systems can strengthen passive strategies without relying on mechanical cooling. Social implications More stable indoor conditions can improve comfort and daily well-being in heat-stressed communities. Originality/value This study is among the first to link adaptive gyroscopic systems with IEQ and low-energy performance in Sub-Saharan Africa.
Purpose Prior studies report inconsistent findings regarding the effects of project management practices and accounting information systems (AIS) on project performance (PP). Meanwhile, limited research explains how these relationships vary under high-risk construction conditions. Accordingly, this study examines whether project risk (PR) moderates the effects of cost management (CM), schedule management (SM), quality management (QM) and AIS on PP in Iraq's construction sector. Design/methodology/approach A quantitative cross-sectional survey was conducted using structured questionnaires administered to 333 experienced professionals from large registered construction firms across major Iraqi regions. Data were analysed using WarpPLS 8.0, and interaction term analysis was used to test the moderating effect of PR. Findings PR significantly moderates the relationships between CM, SM, AIS and PP. The positive effects of CM and SM are stronger under lower-PR conditions, whereas AIS contributes more strongly to PP as PR increases. QM maintains a stable positive relationship with PP across varying PR levels. Practical implications Construction firms should align budgeting and scheduling controls with prevailing PR conditions, adopt greater flexibility in high-risk projects, strengthen AIS capabilities to support timely decisions under uncertainty and maintain consistent QM routines regardless of PR level. Originality/value This study extends the project management and AIS literature by explaining why managerial and technological controls yield uneven PP under varying PR conditions. This study conceptualises PR as a boundary condition that shapes the effectiveness of CM, SM, QM and AIS. The findings also provide practical insights for managing construction projects in high-PR, institutionally unstable environments, such as Iraq.
Purpose Fire risk assessments in existing building assets are constrained by static, paper-based methods and the absence of Building Information Modelling (BIM), limiting the identification and communication of spatial vulnerabilities. Despite advances in digital technologies, current approaches do not adequately support in situ, inspection-oriented fire risk evaluation. This study aims to develop a mobile augmented reality (AR)-based framework to enhance the visualisation, prioritisation, and communication of fire risks in BIM-absent contexts. Design/methodology/approach A qualitative research design was adopted, combining a literature review, synthesis of international fire safety codes, and ISO 31010:2019-based qualitative risk evaluation. Critical spatial fire risk factors were identified and assessed using a likelihood-consequence matrix and mapped to ARKit functionalities including Simultaneous Localisation and Mapping (SLAM), plane detection, object recognition, and Light Detection and Ranging (LiDAR) based mesh reconstruction. Findings Critical spatial fire risks were found to concentrate in circulation and wayfinding systems, with corridors, stairwells, and emergency signage identified as very high-risk factors, and atria, compartmentation gaps, and interior obstructions as high- to medium- risk factors. The MARsFRE framework illustrates how AR functionalities may support hazard visualisation, inspection-based assessment, and communication of spatial vulnerabilities, indicating the potential of mobile AR to enhance in situ fire risk identification and prioritisation. Originality/value The study reconceptualises mobile AR as a proactive, inspection-oriented fire risk assessment approach. It provides an integration of ISO 31010:2019 qualitative risk assessment with AR-enabled inspection capabilities of ARKit and proposes a conceptual framework tailored to BIM-absent buildings, addressing a critical gap in digital fire risk management.
PurposePoor material lifecycle data management prevents construction industry circular economy transformation. Stakeholders cannot reliably verify secondary material quality despite massive embedded material stocks in existing buildings. Current material passport (MP) frameworks operate in isolation, with blockchain providing verification but lacking real-time monitoring, while digital twins offer dynamic tracking without cryptographic security. This study aims to systematically review blockchain-digital twin integration in MP research to inform digital product passport (DPP) implementation strategies in construction material lifecycle management. Design/methodology/approachThis systematic literature review follows the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) framework. A bibliometric analysis was conducted on 62 publications and content analysis on 29 studies from Scopus and Web of Science. The methodology was limited by database selection and English-language publications, potentially excluding some relevant studies. FindingsIntegration creates synergistic effects where blockchain ensures data integrity while digital twins provide dynamic material intelligence, transforming static documentation into intelligent responsive systems. However, significant barriers exist including technical interoperability issues, data storage conflicts, performance limitations and standardization deficits. Current isolated deployments fail to address comprehensive requirements of dynamic material lifecycle management. Future research should focus on developing standardized integration frameworks, addressing real-time synchronization challenges and conducting comprehensive performance evaluations across diverse construction contexts to support DPP regulatory compliance. Originality/valueThe study establishes theoretical foundations for MP integration research that informs DPP deployment, demonstrating how integrated systems can serve as foundational mechanisms connecting blockchain verification capabilities with digital twin intelligence for regulatory compliance preparation.
PurposeMachine learning (ML), a subset of artificial intelligence (AI), is increasingly transforming construction project management (CPM) processes, yet a significant gap exists between research advancements and practical implementation. This study synthesizes empirical findings and proposes a framework to bridge the research-practice divide. Design/methodology/approachA systematic review was conducted using Scopus and Web of Science databases, following PRISMA guidelines. 64 peer-reviewed studies published between 2015 and 2025 were selected and coded using open and axial methods. The analysis was guided by systems theory, complexity theory, and dynamic capabilities theory to develop the Machine Learning–Enabled Construction Project Management (MLCPM) framework. FindingsML use in CPM aligns with three core areas: (1) planning tasks like cost estimation and scheduling, (2) execution tasks such as progress tracking and risk detection and (3) monitoring activities including cost control, delay prediction and performance tracking. The MLCPM framework offers a four-layer architecture consisting of data, ML processing, integration and output, with feedback and retraining loops to support scalable deployment. Furthermore, a quantitative synthesis of ten comparative studies revealed that hybrid and ensemble methods achieved superior performance in cost estimation (cost) (e.g. LightGBM and DNN-SVR), tree-based ensembles (random forest (RF) and gradient boosted trees (GBTs)) showed optimal accuracy for duration forecasting (duration) and hybrids with metaheuristic optimization outperformed single algorithms in delay prediction (delay). Originality/valueThis review consolidates existing literature on ML applications in CPM and introduces a comprehensive MLCPM Framework. Additionally, a quantitative subset synthesis of comparative evaluations extracts task–method performance patterns, enhancing decision relevance. We provide practical, theory-grounded guidance for adopting ML in construction.
PurposeConstruction projects often suffer from delays, cost overruns, and fragmented control due to isolated implementation of Computer Vision (CV), Internet of Things (IoT), Building Information Modelling (BIM), and Machine Learning (ML). This study addresses this gap by proposing a comprehensive Digital Twin framework that integrates these technologies into a unified system for real-time monitoring and predictive control of labor, material, equipment, and activity (LMPA). Design/methodology/approachA four-phase bibliometric approach was followed: (1) retrieving 2,032 studies (2014–2024) from the search database; (2) screening through multi-level filtering to retain 534 relevant papers; (3) network analysis and mapping keywords in Gephi and forming thematic clusters using the Louvain algorithm; and (4) identifying the research gap of fragmented CV, IoT, BIM, and ML applications and developing a Digital Twin framework for real-time LMPA control. FindingsNineteen functional clusters were identified across the four domains: CV (Visual Understanding, Edge Hardware, Metrics, LMPA Algorithms, Analytics), IoT (Sensors, Transmission, Edge Devices, Signal Processing, Dashboards), BIM (Foundations, 4D/5D Control, Progress Tracking, As-Built Alignment), and ML (Data Preparation, Model Training, Forecasting, Optimization, Real-Time Feedback). These form a Digital Twin framework for real-time, closed-loop project monitoring and control. Originality/valueUnlike prior reviews focusing on single technologies or static visualisation, this study integrates CV, IoT, BIM, and ML into a single, evidence-based Digital Twin framework tailored to closed-loop LMPA control.
Purpose As economic activities grow, clients demand more efficient building facilities. Smart buildings, which integrate technology, user interaction and adaptability, offer a solution, yet their adoption in developing countries like Sri Lanka remains limited. Although frameworks exist, most originate in developed contexts and emphasise individual attributes rather than integrated assessment. This study develops a Sri Lanka-specific smartness assessment model to evaluate modern buildings and motivate improvements in efficiency and sustainability. Design/methodology/approach This article employs a mixed-methods design to develop a smartness assessment model comprising 11 attributes and 41 variables, derived from the literature and subsequently validated and weighted by experts. Sixteen selected buildings in the Colombo suburbs were assessed; cases were selected by convenience sampling. Data were collected through site observations, document review and interviews with responsible professionals. Scores were computed using a four-level subgrades and weighted aggregation to produce Smartness Ratings, which were summarised descriptively. Findings Across 16 buildings, the mean Smartness Rating is 42%. By type, commercial average 48.35%, hotels 45% and apartments 34%, with CB4 (61.34%) and CB5 (57.79%) leading the sample. Higher Smartness Ratings are associated with deeper building management systems coverage, central-plant control and sensor-based monitoring, whereas lower Smartness Ratings reflect fragmented integration. At the attribute level, occupant control and safety and security are consistently strong; energy efficiency and environment and sustainability sit in the mid-range; and adaptability and learning are largely absent. Originality/value This article introduces a comprehensive, validated smartness assessment tailored to Sri Lankan buildings and demonstrates its application to a real-world sample.
Purpose Quantifying embodied carbon (EC) is essential for mitigating climate change impacts and reducing excessive use of natural and non-renewable materials. Yet, many Global South countries face several challenges such as data limitations, technical capacity gaps and limited use of EC assessment tools, particularly at early design stage where the greatest reduction potential exists. This study therefore aims to develop an accessible early design stage EC assessment model to support more effective EC management. Design/methodology/approach This study employs a mono-method quantitative approach using secondary data from 25 office building projects in Sri Lanka. Data for model development were extracted from architectural drawings and bills of quantities (BOQs) to determine material quantities, while EC coefficients were obtained from Inventory of carbon and energy (ICE) v3.0. Model development integrated multiple linear regression (MLR) technique with life cycle assessment (LCA) principle. Findings The findings indicate that the developed model provides accurate and reliable EC estimates using a limited set of early design parameters. Gross internal floor area (GIFA) and external wall area (EWA) were found to be the most influential in determining EC estimations. Practical implications The model provides built environment professionals with a practical and time-efficient tool for estimating EC at the early design stage, supporting informed design decisions, wider adoption in data-scarce contexts, and improved carbon management in the Global South. Originality/value This study is distinctive in providing an accessible EC assessment model specifically tailored to the constraints of Global South contexts, where limited data and technical capacity often hinder effective carbon management.
Purpose In both research and practice, the lack of explicit, actionable project-level sustainability management hinders the translation of high-level strategies into effective project-lifecycle practices. This paper addresses this gap by developing a holistic and process-based management framework for managing sustainability in construction projects.Design/methodology/approach This study used a qualitative, exploratory design with design science research to develop and validate a sustainability management framework for construction projects. It was built from literature and best practice synthesis, then validated through interviews and quantitative evaluations with 14 industry experts, enabling refinement and ensuring theoretical and practical relevance.Findings The resulting framework, GEPAS, comprises five interlinked components: A1-Define sustainability goals, A2-Enhance the project team, A3-Plan sustainability, A4-Assess sustainability and A5-Manage stakeholders. Evaluation indicated that GEPAS offers clear, structured and practical guidance for integrating sustainability into construction project management.Practical implications GEPAS enables project managers and stakeholders to define, implement and monitor sustainability objectives systematically, fostering collaboration, informed decision-making and greater stakeholder empowerment through clear roles, shared ownership and active engagement. Its alignment with established standards allows integration into existing practices with minimal disruption, while helping projects deliver measurable contributions to relevant SDGs.Originality/value This research is the first to develop and validate a process-based framework that holistically embeds sustainability principles into all stages of the construction project lifecycle, while aligning with existing project management standards. It advances theory by operationalising sustainability as a core project objective and offers practitioners a practical tool to overcome common barriers to sustainable delivery.
Purpose Although work engagement has been widely studied, limited research has explored the psychological mechanisms underlying engagement in developing countries. This study examines how first-order psychological capital (self-efficacy, optimism, hope, and resilience) mediates the relationship between psychological empowerment and work engagement among construction engineers in Myanmar. Amid evolving political and socio-economic challenges, enhancing engagement through psychological resources is crucial for sustaining productivity. This study addresses a gap by exploring how these resources support engagement in unstable contexts. Design/methodology/approach A quantitative, cross-sectional research design was used to assess psychological empowerment, psychological capital, and work engagement. Data were collected from 266 construction engineers in Yangon, Myanmar using a structured questionnaire. Participants were required to have a minimum of two years of construction experience and at least six months in their current organization. Path analysis of Structural Equation Modeling (SEM) with AMOS, was used to test the research hypotheses. Findings The results indicate a significant positive impact of psychological empowerment on work engagement, with optimism and resilience serving as notable mediators. In contrast, self-efficacy and hope showed limited predictive power in this context. These findings suggest that socio-economic challenges may influence how specific psychological resources affect engagement. Originality/value This study contributes to construction management by testing the mediation of specific PsyCap dimensions (self-efficacy, hope, optimism, resilience) in the relationship between psychological empowerment and work engagement in Myanmar's developing construction sector. The finding also suggests that the different components of PsyCap have unequal effects on engagement under uncertainty.
Purpose The purpose of this paper is to examine how configurations of project structure, risk allocation, and procurement competition influence the financing capacity of U.S. toll-road public-private partnership (PPP) investments.Design/methodology/approach The relationships among capital value, concession term, construction risk, traffic risk, and competition level are analyzed using fuzzy-set Qualitative Comparative Analysis (fsQCA) of 24 U.S. transportation PPP projects delivered over the past 2 decades. Project attributes are calibrated into fuzzy membership scores based on financial and contractual data and evaluated against three financing outcomes: reduced equity return, reduced debt spread and maximized leverage ratio.Findings Results suggest that financing performance does not depend on isolated variables but on specific combinations of conditions. High competition, low traffic risk, and manageable construction exposure are consistently associated with lower equity costs, narrower debt spreads, and higher leverage. When equity sponsors also act as builders, construction risk is internalized through construction profit, reallocating returns within the project rather than raising the cost of equity. Traffic risk remains the principal constraint for lenders. Two configurations associated with financing failure are also identified, particularly small-scale projects combining short concession terms and high traffic exposure.Originality/value The paper contributes to PPP finance research by reframing financing capacity as a configurational outcome emerging from interacting contractual and market conditions rather than a linear response to individual risk factors. It provides systematic cross-case evidence identifying both successful financing pathways and "no-deal" structures in U.S. transportation PPPs, offering practical guidance for structuring financially viable concessions.
Purpose This study addresses the lack of structured, data-driven approaches to infrastructure asset management, demonstrating how integrating building information modelling (BIM) and digital twin methodologies can enhance the maintenance and lifecycle management of railway tunnels.Design/methodology/approach A structured data-to-BIM workflow was co-developed with Infraestruturas de Portugal (IP), using inspection and monitoring data from 79 railway tunnels. The workflow includes automated data acquisition and systematisation, algorithmic generation of structured, data-rich BIM models, and a centralised digital twin platform for lifecycle monitoring.Findings Implementation enabled real-time data manipulation, predictive maintenance and improved decision-making. Key outputs include standardised data exchange protocols, product data templates, BIM object classes for tunnel components and digital twinning algorithms. Benefits observed include improved collaboration, automatic anomaly detection and enhanced visualisation of tunnel condition.Research limitations/implications Further research is needed to improve the algorithm's performance, minimise manual interventions and validate the workflow's scalability across diverse asset typologies and operational contexts.Originality/value The research presents a framework for integrating digital twins into infrastructure asset management, demonstrating the operational value of computational methods in transforming conventional maintenance and lifecycle management workflows and supporting data-driven decision-making.
Purpose This study applies critical success factors (CSF) theory to address collaboration challenges in Ghana's building information modeling (BIM) construction projects, where stakeholder engagement is hindered by fragmentation, misaligned expectations, and limited digital integration. It identifies and prioritizes CSF influencing stakeholder collaboration and proposes structured strategies that align with Sustainable Development Goals (SDG) 9 and SDG 11.Design/methodology/approach A two-round Delphi method was conducted with 17 experts in the first round and 13 in the second, selected through purposive sampling for their BIM expertise in Ghana. The iterative process facilitated expert consensus on the most critical collaboration challenges and success factors in BIM-enabled construction.Findings The study identifies 16 CSF for BIM stakeholder collaboration. Seven were ranked as very highly influential (VHI: 9.00-10.00), including communication, collaborative attitudes, early involvement, coordination, joint decision-making, BIM infrastructures and fostering trust, mutual respect and understanding. The remaining nine were categorized as highly influential (HI: 7.00-8.99). These findings support SDG 9 by promoting digital innovation in infrastructure and SDG 11 by enhancing inclusive and sustainable urban development.Originality/value This research integrates CSF theory with collaborative delivery models such as integrated project delivery (IPD) and lean project delivery (LPD), offering a validated framework for improving stakeholder collaboration in BIM projects. It contributes to both academic understanding and practical implementation of BIM in developing contexts.
Purpose This study aims to develop a practical method for evaluating how Performance-Based Contracting (PBC) features are embedded in the design of Public-Private Partnership (PPP) road contracts in China. It addresses a gap in understanding how performance expectations are structured, specified, and enforced during contract formulation. Design/methodology/approach A qualitative document analysis was conducted using all 26 road PPP projects recorded in China's National PPP Project Information System. A unified three-tier Key Performance Indicator (KPI) framework was developed through iterative coding and consolidation of contract content. A structured scoring method was then created to evaluate contracts across three dimensions: breadth (coverage of performance domains), depth (granularity of indicators), and clarity and enforceability (precision and legal operability). The approach was applied to a representative case to demonstrate its practical utility. Findings The study presents two core outputs: a benchmark KPI framework and a conceptual scoring method aligned with PBC features. These tools enable systematic and transparent evaluation of how well PPP contracts articulate and support performance expectations. The case application illustrates how contractual provisions can be assessed for structural coverage, operational detail, and enforceability. Originality/value This paper contributes a replicable framework for diagnosing performance system design in infrastructure contracts. It advances the literature by translating PBC features into measurable contract features and provides practical tools for cross-project comparison, contract template improvement, and policy alignment. The approach supports more consistent integration of performance logic into PPP governance.
