Purpose Land acquisition is widely recognised as one of the most delay-prone activities in infrastructure project delivery. This study empirically evaluates whether transparent and fair land acquisition reforms improve schedule performance of publicly procured infrastructure projects, focusing on India's Right to Fair Compensation and Transparency in Land Acquisition, Rehabilitation and Resettlement (RFCTLARR) Act. Design/methodology/approach The analysis is based on a dataset of 481 completed highway projects implemented between 2000 and 2019, covering both pre- and post-reform periods. Mean comparison analysis, ordinary least squares (OLS) and seemingly unrelated regression (SUR) models were employed to examine the association between the reform and the three indicators of schedule performance: estimated unit time, actual unit time and time overruns, while controlling for project-specific, governance and state-level factors. Findings The results consistently show that projects implemented after the RFCTLARR Act had lower estimated and actual unit times and significantly lower time overruns. These findings suggest that enhanced procedural fairness, through improved compensation mechanisms, mandatory social impact assessments and structured rehabilitation and resettlement measures, is associated with reduced uncertainty, disputes and execution risk, thereby improving project schedule performance. Originality/value This study advances institutional theory by demonstrating that procedural fairness in land acquisition serves as a governance mechanism that improves schedule performance of infrastructure projects. It provides empirical evidence from a large dataset that institutional reform in land acquisition is associated with measurable reductions in planned duration, actual execution time and time overruns for highway projects in India.
Purpose Despite rapid advances in Artificial Intelligence (AI), and specifically Generative Artificial Intelligence (GenAI) for urban planning, a gap persists between these innovations and their applicability in African contexts shaped by informality, data scarcity, limited capacity and climate vulnerability. This study examines how GenAI is reshaping urban planning globally and assesses its relevance, adaptability and risks in African contexts, identifying pathways for inclusive, legitimate and context-sensitive deployment. Design/methodology/approach A systematic literature review used a Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA)-guided framework extended through PRALSMA (Preferred Reporting of AI-integrated Literature Search and Meta-Analysis), a reporting extension for transparent AI-assisted reviews. Peer-reviewed articles (2020–2025) from Web of Science and OpenAlex, with selected grey literature, gave 82 sources analysed through manual review and AI-assisted tools, with all outputs verified and triangulated for robustness and traceability. Findings GenAI is transforming urban planning through multimodal workflows enabling rapid scenario generation, visualisation and communication, but effectiveness depends on localisation, bias mitigation, institutional capacity and legitimacy. Without these, GenAI risks misleading or exclusionary “blueprint” solutions, underscoring the need for context-sensitive adaptation. Originality/value The study integrates creativity-in-design, relational agency and democratic design to frame GenAI as a socio-technical participant rather than an autonomous planner, offering an Africa-relevant agenda for responsible, human-centred implementation aligned with equity, sustainability and resilience.
Purpose Traditional Critical Path Method (CPM) based heuristics are insufficient for managing resource overallocation and meeting deadlines in repetitive projects such as highways and multi-bridge repairs. Despite their inefficiencies, they are still being used due to the lack of simple heuristic scheduling tools that help project managers and stakeholders cater to these projects' needs, such as crew continuity. The study aims to fill this gap and develop a unified framework that extends CPM heuristics to optimize scheduling for both repetitive and nonrepetitive projects. Design/methodology/approach A unified heuristic optimization (UHO) framework was developed, integrating CPM-based cost-resource allocation and time-cost trade-off procedures with the first-come-first-served repetitive scheduling methodology. An Excel-based automated scheduling tool based on the proposed framework was developed as a proof of concept and tested against cases from the literature. Findings This article presented a novel scheduling framework that generalizes CPM procedures to be applicable for repetitive projects, resolving any deadline or resource allocation constraints. Applied to a literature case study, the produced schedule achieved the same overall project deadline while having more efficient resource utilization. Originality/value This study introduces a unified heuristic approach that simplifies and enhances scheduling for repetitive infrastructure projects. By bridging the gap between CPM-based tools and the unique demands of repetitive scheduling, it supports project managers in managing the schedule and resources of large-scale repetitive projects.
Purpose The built environment is a major contributor to global carbon emissions, making the transition to zero-carbon buildings essential. Achieving this transition depends on construction professionals' awareness and readiness to implement zero-carbon initiatives (ZCIs). However, empirical evidence on their preparedness in the Nigerian construction industry remains limited. This study assesses Nigerian construction professionals' knowledge and awareness of ZCIs supporting the zero-carbon transition. Design/methodology/approach A quantitative research design was adopted using a structured questionnaire administered to 225 Nigerian construction professionals. The questionnaire was validated through expert review and pilot testing. Purposive sampling was used to ensure representation of key industry stakeholders, and data were subsequently analyzed using descriptive statistical techniques. Findings The results reveal substantial awareness and capacity gaps among Nigerian construction professionals. Awareness of international climate agreements, national climate policies, and industry-led ZCIs was generally low. Familiarity, experience, and training in carbon assessment, building performance assessment, life cycle assessment, and energy modelling were also limited. These deficiencies indicate inadequate sectoral preparedness for the effective implementation of ZCIs in Nigeria's construction industry. Originality/value This study provides one of the first empirical assessments of Nigerian construction professionals' awareness of zero-carbon policies and initiatives alongside their preparedness to implement zero-carbon building practices. By identifying critical gaps in policy awareness, technical knowledge, practical experience, and professional training, it contributes context-specific evidence on zero-carbon transitions in developing economies and highlights the need for targeted capacity-building and institutional support.
Purpose The implementation of situated learning (SL) in project-based settings is hindered by a lack of empirical research on its success factors (SFs). This paper addresses this gap by investigating the SFs for cultivating SL in construction projects, with the aim of providing insights into effective implementation strategies. Design/methodology/approach Purposive sampling method was utilized to obtain a sample size of 203 respondents and data solicited through a structured questionnaire survey. The data set was analyzed using a four-level analytical protocol. These include – pretesting the data set, mean score ranking, exploratory factor analysis (EFA) and fuzzy synthetic evaluation (FSE). Findings Fuzzy synthetic evaluation revealed that SFs at the team level had the highest criticality index (4.292), followed by organizational-level (4.202) and individual-level factors (4.193), all exceeding the 3.50 threshold. Although individual-level factors explained the greatest variance (22.587%), team dynamics were perceived as most decisive for SL outcomes. Mean ranking identified participatory decision-making (M = 4.47), ease of information flow (M = 4.45), team composition (M = 4.44), team leadership (M = 4.43) and behavioral conditioning (M = 4.35) as the top five critical SFs. The results indicate that team-level factors constitute the primary mechanism for cultivating SL, supported by organizational enablers and individual capacities. Originality/value This study provides the first empirical validation of SFs for cultivating situated learning in projects, addressing a gap in literature dominated by cognitive knowledge management models.
