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This research aims to systematically review studies on significant risks for Critical Infrastructure Projects (CIPs) from selected top-tier academic journals from 2011 to 2023.

In this research, a three-step systematic literature review methodology was employed to analyse 55 selected articles on Critical Infrastructure Risks (CIRs) from well-regarded and relevant academic journals published from 2011 to 2023.

The findings highlight a growing research focus on CIRs from 2011 to 2023. A total of 128 risks were identified and grouped into ten distinct categories: construction, cultural, environmental, financial, legal, management, market, political, safety and technical risks. In addition, literature reviews combined with questionnaire surveys were more frequently used to identify CIRs than any other method. Moreover, oil and gas projects were the subjects most often explored in the reviewed papers. Furthermore, it was observed that publications from Iran, the USA and China dominated CIRs research, making significant contributions, accounting for 49.65% of the analysed articles.

This research specifically focuses on five types of CIPs (i.e. roadways, bridges, water supply systems, dams and oil and gas projects). Other CIPs like cyber-physical systems or electric power systems, were not considered in this research.

Governments and contracting firms can benefit from the findings of this study by understanding the significant risks associated with the execution of CIPs, irrespective of the nation, industry or type of project. The results of this investigation can offer construction professionals valuable insights to formulate and implement risk response plans in the early stages of a project.

As a novel literature review related to CIRs, it lays the groundwork for future research and deepens the understanding of the multi-faceted effects of these risks, as well as sets practical response strategies.

The Logistics Performance Index (LPI), published by the World Bank, is a key measure of national-level logistics performance. It comprises six indicators: customs, infrastructure, international shipments, service quality, timeliness, and tracking and tracing. The objective of this study is to explore temporal dependencies among the six LPI indicators while operationalizing the World Bank’s LPI framework in terms of mapping the input indicators (customs, infrastructure, and service quality) to the outcome indicators (international shipments representing cost, timeliness, and tracking and tracing representing reliability).

A Bayesian Belief Network (BBN)-based methodology was adopted to effectively map temporal dependencies among variables in a probabilistic network setting. Using forward and backward propagation features of BBN inferencing, critical variables were also identified. A BBN model was developed using the World Bank’s LPI datasets for 2010, 2012, 2014, 2016, 2018, and 2023, covering the six LPI indicators for 118 countries.

The prediction accuracy of the model is 88.1%. Strong dependencies are found across the six LPI indicators over time. The forward propagation analysis of the model reveals that “logistics competence and quality” is the most critical input indicator that can influence all three outcome indicators over time. The backward propagation analysis indicates that “customs” is the most critical indicator for improving the performance on the “international shipments” indicator, whereas “logistics competence and quality” can significantly improve the performance on the “timeliness” and “tracking and tracing” indicators. The sensitivity analysis of the model reveals that “logistics competence and quality” and “infrastructure” are the key indicators that can influence the results across the three outcome indicators. These findings provide useful insights to researchers regarding the importance of exploring the temporal modeling of dependencies among the LPI indicators. Moreover, policymakers can use these findings to help their countries target specific input indicators to improve country-level logistics performance.

This paper contributes to the literature on logistics management by exploring the temporal dependencies among the six LPI indicators for 118 countries over the last 14 years. Moreover, this paper proposes and operationalizes a data-driven BBN modeling approach in this unique context.

Policymakers are developing government-level pandemic response strategies (GPRS) to assist architecture, engineering and construction (AEC) enterprises. However, the effectiveness of the GPRS has not been assessed. Therefore, this study aims to investigate the interrelationships between GPRS and AEC enterprises. To achieve that aim, the study objectives are to compare GPRS effectiveness between small-medium and large AEC enterprises, develop groupings to categorize interrelated GPRS and evaluate the effectiveness of the GPRS and interrelated constructs.

A systematic literature review and semi-structured interviews with 40 AEC industry professionals were carried out, generating 22 GPRS. Then, questionnaire survey data was collected among AEC professionals. In total, 114 valid survey answers were received and analyzed using the Kruskal–Wallis H test, normalized mean analysis, factor analysis and fuzzy synthetic evaluation.

Small-medium enterprises have four distinct critical GPRS: “form a special task force to provide support in maneuvering COVID-19,” “provide infrastructure investment budgets to local governments,” “develop employee assistance programs that fit all types of working groups” and “diversify existing supply chain.” Large enterprises have two distinct critical GPRS: “provide help in digitalizing existing construction projects” and “mandate COVID-19 as force majeure.” Eighteen GPRS can be categorized into the following five constructs: “market stability and financial aid,” “enterprise capability management,” “supply chain improvement,” “law and policy resources” and “information and workforce management.” The former two constructs are more effective than other GPRS constructs.

This is the first paper that evaluates the effectiveness of GPRS for AEC enterprises, providing new evidence to policymakers for well-informed decision-making in developing pandemic response strategies.

The Afghan construction industry faces resource shortages and heavily relies on foreign aid to fund public projects on the path to recovery and reconstruction. While the resource constraints demand cost-efficient delivery of construction projects, many Afghan public projects experience delays and cost overruns. This study aims to evaluate various attributes and factors influencing cost performance in public construction projects in Afghanistan.

The literature review and Delphi method identified 30 cost performance attributes relevant to the context of Afghanistan. Next, a questionnaire survey was conducted with construction management professionals working in the public sector in the Afghan construction industry to evaluate these attributes.

This study found that the lack of resources, poor project management skills and corruption in procurement are the leading causes behind cost overruns in Afghan public projects. This study also identified five latent factors influencing cost performance in public projects in Afghanistan: competency of the project team, socioeconomic and political support, governance and public procurement, planning and risk management and project characteristics.

The exploratory factor analysis did not reveal the relative significance of different cost performance success factors. Moreover, the ranking of cost performance attributes is based on the responses from the public sector construction professionals only.

The construction industry in Afghanistan significantly contributes to the country’s social and economic growth and employment. This study’s findings will help researchers, project sponsors, government departments and industry practitioners interested in improving the cost performance in Afghan public projects.

Given the scarcity of research in war-affected and conflict-sensitive regions, this study fills a research gap on project cost performance by providing insights into the cost performance success factors in public projects in Afghanistan.

Construction industry is one of the worst affected sectors due to the impact of the current coronavirus disease 2019 (COVID-19) outbreak. Therefore, the purpose of this study was to identify the key competencies that should be demonstrated by the contractors in the post-COVID-19 scenario to make them resilient to the adverse impact of pandemic outbreaks.

A survey instrument was developed using an extensive literature review and was tested using a pilot study. It was then administered online using survey monkey to 900 respondents, out of which 324 complete responses were obtained. The data analysis was performed using exploratory factor analysis and second-order confirmatory factor analysis.

After analyzing the data, it was identified that the most critical competence was managing site safety (standard factor loading (SFL) = 0.91), followed by leadership skills (SFL = 0.88), technical competence (SFL = 0.81), managing supply chain disruption (SFL = 0.73) and financial stability (SFL = 0.48) that were found to be less essential from the respondents’ point of view.

The study is first of its kind to identify the core competencies that should be demonstrated by the contractors to cope with COVID-19-induced disruptions. The findings of this article can be used by the practitioners to develop policies and procedures for selection of contractors.

Firms in the architectural, engineering, construction and operations (AECO) sector continue undertaking projects in a disruptive environment due to the coronavirus disease 2019 (COVID-19) pandemic. This study aims to explore environmental turbulence in the AECO project delivery space and suggest mechanisms for enhancing resilience against future pandemics.

The study adopts the quantitative approach by administering 110 survey questionnaires to participants comprising project managers, site engineers, quantity surveyors, contractors and subcontractors.

The study identifies 24 COVID-19 disruptions linked to environmental turbulence categorised as scheduling, performance and productivity, project budget, supply chain, resource allocation and technological and regulatory. The study suggested resilient mechanisms for surviving in future pandemics.

This study enhances the understanding of environmental turbulence from the perspective of COVID-19 disruptions in AECO project delivery, while the implementation of the resilient mechanisms improves capability of AECO firms against future pandemics.

This study aims to explore the critical application areas of radio frequency identification (RFID) technology for sustainable buildings.

The quantitative research approach was adopted through a structured questionnaire administered to relevant stakeholders of construction projects. The data collected were analysed with the exploratory factor analysis, relative importance index (RII) and fuzzy synthetic evaluation (FSE).

The study’s results have categorised the crucial areas of application where construction industry stakeholders should focus their attention. These areas are divided into four categories: management technologies, production technologies, sensing technologies and monitoring technologies. The findings from the FSE indicate that monitoring technologies represent the most significant category, whereas management technologies rank as the least significant. Moreover, the RII analysis highlights that tools management stands out as the most important application of RFID, while dispute resolution emerges as the least significant RFID application.

The study establishes the core areas of RFID application and their benefits to sustainable buildings. Consequently, it helps stakeholders (consultants, clients and contractors) to examine the RFID application areas and make informed decision on sustainable construction. Furthermore, it provides systematic proof that can aid the implementation of RFID in developing countries.

The study provides an insight into the possible application areas and benefits of RFID technology in the construction industry of developing countries. It also developed a conceptual frame for the critical application areas of RFID technology in the construction industry of developing countries.

Perceived benefits of building information modelling (BIM) have been discussed for some time, but cost–benefit benchmarking has been inconsistent. The purpose of this paper is to investigate BIM feasibility and evaluate investment worth to elucidate and develop the current understanding of BIM merit. The aim of the study is to propose a research agenda towards a more holistic perspective of BIM use incorporating quantifying investment return.

An in-depth examination of research patterns has been conducted to identify challenges in the assessment of the investment value and return on investment (ROI) for BIM in the construction industry. A total of 75 research articles were considered for the final literature review. An evaluation of the literature is conducted using a combination of bibliometric analysis and systematic reviews.

This study, which analysed 75 articles, unveils key findings in quantifying BIM benefits, primarily through ROI calculation. Two major research gaps are identified: the absence of a standardized BIM ROI method and insufficient exploration of intangible benefits. Research focus varies across phases, emphasizing design and construction integration and exploring post-construction phases. The study categorizes quantifiable factors, including productivity, changes and rework reduction, requests for information reduction, schedule efficiency, safety, environmental sustainability and operations and facility management. These findings offer vital insights for researchers and practitioners, enhancing understanding of ’BIM’s financial benefits and signalling areas for further exploration in construction.

The ’study’s outcomes offer the latest insights for researchers and practitioners to create effective approaches for quantifying ’BIM’s financial benefits. Additionally, the proposed research agenda aims to improve the current limited understanding of BIM feasibility and investment worth evaluation. Results of the study could assist practitioners in overcoming limitations associated with BIM investment and economic evaluations in the construction industry.

The construction industry (CI) has been identified as one of the most challenging sectors for stakeholders to achieve organizational success. Although previous studies had examined both organizational leadership (OL) and employee well-being (EWB) in the CI, a bibliometric and systematic analysis of published articles is hitherto lacking. Therefore, this paper aims to conduct a bibliometric and scientometric review of published articles related to OL and EWB in the CI between 2008 and 2022.

A three-step method consisting of a bibliometric analysis, a scientometric analysis and an in-depth discussion were used. A total of 1,114 articles met the inclusion criteria. All articles were retrieved from the Scopus database.

The results present an in-depth discussion of the research publication trends, keywords co-occurrence analysis, document analysis and countries/regions analysis. This review paper identified three main research gaps in OL and EWB in the CI, namely, project management, technology innovation and people orientation. It also proposes “OL-EWB in the CI”' mechanisms and a theoretical framework to guide future research directions.

This review paper theoretically fills the gap in the lack of research summarizing OL and EWB in the CI and provides research gaps and trends for achieving a win-win situation for both companies and employees.

The purpose of this paper is to seek an efficient method to tackle the energy provision problem for smart grid with sparse constraints and distributed energy and storage devices.

A complex smart grid is first studied, in which sparse constraints and the complex make-up of different energy consumption due to the integration of distributed energy and storage devices and the emergence of multisellers are discussed. Then, a real-time pricing scheme is formulated to tackle the demand response based on sparse bilevel programming. And then, a bilevel genetic algorithm (BGA) is further designed. Finally, simulations are conducted to evaluate the performance of the proposed approach.

The considered situation is widespread in practice, and meanwhile, the other cases including traditional model without the sparse constraints can be seen as its extensions. The BGA based on sparse bilevel programming has advantages of “no need of convexity of the model.” Moreover, it is feasible without the need to disclose the private information to others; therefore, privacies are protected and system scalability is kept. Simulation results validate the proposed approach has good performance in maximizing social welfare and balancing system energy distribution.

In this paper, the authors consider the sparse constraints due to the fact that each user can only choose limited utility companies per time slot. In reality, there exist some other sparse cases, which deserve further study in the future.

To the best of the authors’ knowledge, this is one of the very first studies to address pricing problems for the smart grid with consideration of sparse constraints and integration of distributed energy and storage devices.