Purpose The purpose of this paper is to provide a high-level summary of the results of region-specific studies pertaining to the interaction between transportation and property market. The authors intend to do so by studying the relationship between transportation volume/construction and housing market indicators at the national level, in this case, the USA. Design/methodology/approach This paper, through a combination of Granger causality test and vector error correction model (VECM), explores the time-lagged impact of fluctuation in volume of air transportation, vehicular transportation, passenger rail, public transit and transportation construction on housing value, supply and market hotness. Findings Impulse-response analysis generated via VECM indicated that shocks in transportation volume and related construction value added is associated with long-run negative responses with housing value/supply/market hotness. Development-type-specific analysis indicated that transportation volume escalation harmed exclusively the supply of development of five units and more. The findings governing location-specific studies, specifically property markets declining with higher demand for travel and access to mobility facilitating migration from dense areas to lower density communities, are expandable as national level phenomenon. Originality/value The paper’s findings contradict that of many studies done on regional contexts: although access to transportation stimulates local property market, at the national level additional transportation provides population migration options and may shift total surplus to the consumer’s side and cause seller’s side to cool.
PurposeIn Vietnam, delays in disbursement for state-funded construction projects remain a persistent challenge, directly impacting stakeholder performance. This study aims to identify significant risks contributing to these delays and proposes a multi-criteria model to mitigate them.Design/methodology/approachAdopting a hybrid method that integrates literature review and expert surveys, the study identifies 17 risk factors grouped into three categories: human-related, policy-related and performance-related. Data was collected through a structured questionnaire and analyzed using Cronbach's alpha, mean score analysis, Spearman's rank correlation, Exploratory Factor Analysis and Fuzzy Synthetic Evaluation (FSE).FindingsThe analysis highlights the limited authority of investors, frequent legal policy changes and delays in site clearance as the most critical causes of slow disbursement. Human-related risks were found to have the greatest influence on this disbursement. Respondents with similar work experience shared consistent assessments, while those in different roles or positions showed divergent views. The FSE results confirm that these risks significantly hamper the disbursement process in public construction projects.Research limitations/implicationsEvaluating disbursement delays and developing a corresponding model are essential for future research on enhancing project performance. Nevertheless, further in-depth study is needed to understand the full impact of these delays.Practical implicationsStakeholders should prioritize improving the qualifications and authority of staff and managers involved in the disbursement process. Doing so will accelerate payment procedures and contribute to more stable cash flow for all parties, especially contractors.Originality/valueThe study's findings provide valuable insights for stakeholders, particularly contractors, to manage financial planning better in the face of disbursement delays.
PurposeThe purpose of this study is to identify the specific causes of variation orders that affect project costs, as perceived by relevant stakeholders, including contractors, consultants, and clients. Variation orders are considered one of the significant contributors to cost overruns in construction projects. That is why various research efforts have addressed this issue to tackle its impact on construction projects. However, most of these studies have focused on various project types, giving little attention to large-scale infrastructure projects such as bridges. As a result, to address this gap, this study adopts a structural equation modeling (SEM) to investigate the primary causes of variation orders that lead to cost overruns in construction bridge projects. This is accomplished by identifying variation order causes through a comprehensive literature review, in addition to collecting data from eight actual bridge projects in Egypt.Design/methodology/approachThe research methodology involves the identification of the main causes of variation orders on cost overrun in bridge construction projects using an extensive literature review and structured questionnaires. First, an initial set of 51 potential variation order causes was identified. Then, interviews were conducted with eight experts to discuss the relevance of the identified causes to the cost overruns in bridge construction projects in Egypt. Consequently, the refined list of 51 causes served as the foundation for a structured questionnaire survey, which was distributed to 95 experienced professionals specializing in bridge projects in Egypt. Consequently, the responses were analyzed to identify the most significant causes, which consist of thirty main causes, using mean scores as the criterion for ranking. To investigate the underlying relationships among these causes, SEM was conducted using AMOS software. This analysis determined the correlations and interactions of latent variables within a multidimensional performance framework, providing deeper insights into how these causes collectively contribute to project cost overruns.FindingsUsing SEM, 19 key variation order causes were identified as significantly affecting bridge construction cost overruns. The aforementioned causes were classified into four latent variables, which form the foundation for eight hypotheses aimed at examining both the interactions among the variables and their impact on cost overruns. The analysis confirms the importance of 19 factors contributing to rising project costs, underlining the complex nature of variation orders in Egyptian bridge construction. Additionally, a case study of a real bridge project is provided that illustrates how these latent factors impacted the cost overruns. This case study acts as a tangible example highlighting the importance of these factors in managing cost performance in bridge construction.Originality/valueThis study uses structural equation modeling to identify the primary causes of variation orders resulting in cost overruns within Egyptian bridge construction projects. In contrast to previous research efforts that focused on various types of construction projects, with minimal attention given to bridge construction projects, this research specifically examines bridge projects by integrating practical insights, expert evaluations and thorough statistical analyses. Its value lies in providing assistance to practitioners in improving decision-making, reducing risks and enhancing cost management in bridge projects.
PurposeThe purpose of this study is to evaluate that prefabricated buildings (PBs), which offer environmental, economic and logistical benefits, are constrained by substantial capital requirements. PB construction's complex, gray-box supply chain creates uncertainty in the bank's financing decisions. Recent advances in blockchain-driven supply chain finance can resolve trust issues to spawn a feasible multilevel finance system.Design/methodology/approachA blockchain-enabled financing model for the PB supply chain was established to characterize the interactions among contractors, suppliers and banks. An evolutionary game model was developed to analyze their strategic behaviors and equilibrium conditions under different incentive and penalty scenarios. A system dynamics simulation, using real project data, was conducted to verify the theoretical model and evaluate the effects of key parameters on system stability.FindingsThe proposed blockchain model effectively mitigates information asymmetry and lowers supplier financing costs within the prefabricated construction supply chain. Under conventional static incentive mechanisms, the tripartite evolutionary game lacks a stable equilibrium, leading to persistent behavioral fluctuations among contractors, suppliers and banks. By implementing a dynamic incentive mechanism that adjusts subsidies and penalties based on real-time compliance performance, the system converges to a stable state in which all participants consistently adhere to blockchain-based strategies. This approach not only enhances operational transparency and trust but also safeguards the interests of all stakeholders while promoting the practical adoption of blockchain technology.Originality/valueThe results provide theoretical support and practical guidance for refining financing arrangements for the complex PB supply chain.
PurposeAlthough artificial intelligence (AI) technologies are increasingly adopted worldwide, their diffusion in the Nigerian construction industry (NCI) remains limited. This study aims to investigate the transformative opportunities presented by AI and the critical challenges hindering its adoption in the NCI, framed by the technology acceptance model (TAM) and organisational change management theory (OCMT).Design/methodology/approachUsing a quantitative approach within a positivist paradigm, data were collected via an electronic survey distributed through convenience sampling to professionals across government agencies, consulting firms and contractors. The data were analysed using descriptive and inferential statistics.FindingsResults reveal AI's potential to revolutionise operational efficiency and decision-making within the NCI. However, adoption is constrained by insufficient digital infrastructure and limited technical expertise. Addressing these barriers, particularly from the perspectives of individual acceptance (TAM) and organisational readiness (OCMT), is essential to fully harness AI's transformative capabilities.Originality/valueThis study uniquely examines the socio-economic, technical and cultural factors shaping AI adoption in the NCI. By offering context-specific knowledge and strategic interventions, it informs policymakers, consultants and contractors of practical pathways for AI integration. The research contributes to the global discourse on AI in construction, especially in developing economies, providing a framework to foster innovation and sustainability in comparable contexts.
