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Evaluating the implementation of environmental management plans (EMPs) in highway construction projects is essential to avoid climate change. Public evaluations can help ensure that the EMP is implemented correctly and efficiently. To allow public evaluation of EMP implementations, this study aims to investigate performance indicators (PIs) for assessing EMP implementation in highway construction projects. To that end, the study objectives are to compare the critical PIs between environment auditors (EAs) and environment officers (EOs) and among the main project stakeholders (i.e. clients, contractors and consultants), create components for the critical PIs and assess the efficiency of the components.

The paper identified 39 PIs from interviews with environmental professionals and a systematic literature review. Then a questionnaire survey was developed based on the PIs and sent to EAs and EOs. The data were analyzed via mean score ranking, normalization, agreement analysis, factor analysis and fuzzy synthetic evaluation (FSE).

The analyses revealed 21 critical PIs for assessing EMP implementation in highway construction projects. Also, the critical PIs can be grouped into four components: ecological, pollution, public safety and ecological. Finally, the overall importance of the critical PIs from the FSE is between important and very important.

To the best of the authors’ knowledge, this paper is the first-of-its-kind study on the critical PIs for assessing EMP implementation in highway construction projects.

This study aims to review recent advances towards the implementation of ANN and NLP applications during the budgeting phase of the construction process. During this phase, construction companies must assess the scope of each task and map the client’s expectations to an internal database of tasks, resources and costs. Quantity surveyors carry out this assessment manually with little to no computer aid, within very austere time constraints, even though these results determine the company’s bid quality and are contractually binding.

This paper seeks to compile applications of machine learning (ML) and natural language processing in the architectural engineering and construction sector to find which methodologies can assist this assessment. The paper carries out a systematic literature review, following the preferred reporting items for systematic reviews and meta-analyses guidelines, to survey the main scientific contributions within the topic of text classification (TC) for budgeting in construction.

This work concludes that it is necessary to develop data sets that represent the variety of tasks in construction, achieve higher accuracy algorithms, widen the scope of their application and reduce the need for expert validation of the results. Although full automation is not within reach in the short term, TC algorithms can provide helpful support tools.

Given the increasing interest in ML for construction and recent developments, the findings disclosed in this paper contribute to the body of knowledge, provide a more automated perspective on budgeting in construction and break ground for further implementation of text-based ML in budgeting for construction.

The construction industry is complex, human-intensive and driven by monetary values. Hence, disputes are widespread. Initial conflicts among parties may develop into a disastrous dispute that costs the project success and good relationships and affects stakeholders' expectations. There has been a focus on causes of construction-related disputes, and studies over the past three decades have attempted to identify a more comprehensive list of reasons for disputes. Some of these studies' limitations were geographical, project delivery methods and project types. The purpose of this study is to identify the most recent and conclusive list of causes of disputes based on current literature by undertaking a systematic literature review (SLR).

Considering the large number of studies that focused on causes of disputes, this study aims to develop a comprehensive list of causes, using a SLR, as it ensures that all previous articles in multiple databases are reviewed to produce a comprehensive outcome. A six-stage SLR was followed from background study to analysis and reporting.

Not surprisingly, the number of publications has increased over time, most from the Middle East region. The interconnected nature of the causes was widely emphasised. The SLR has produced eight common core causes of disputes. They are: poor contractual arrangements, employer-initiated scope changes, unforeseen site changes, poor contract understanding and administration, contractor’s quality of works, the inability of the contractor to achieve time targets, non- or delayed payments and poor quality of design. The majority of previous authors realised that disputes could be avoided by parties’ involvement during the early stages, avoiding being opportunistic and acting collaboratively.

Even though numerous studies have been carried out to identify the causes of disputes in the construction industry, none did a SLR. This study aggregates all the previous studies that focused on construction-related disputes systematically. Categorising causes based on the party primarily responsible help various stakeholders by providing a distinct list of factors to avoid that contribute to disputes.

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.

Sources highlight that lack of systematic labour training components results in low performance and productivity of labour, which leads the construction industry of many countries to face various challenges. This study aims to quantify the variations in the performance and productivity levels of labour in building construction projects through the applications of effective work-based training components.

A comprehensive literature review and a series of experts’ discussions with action-oriented communication approaches were conducted to develop a set of practices related to labour training, performance assessment and productivity measurements within a framework. The developed practices were applied to around 100 labourers working on nine building construction projects through a construction supervisory training programme.

The study presents the detailed patterns of the significant changes in labour performance and productivity levels. The majority of trained labourers have grown to perform the work process with some relevant theoretical and operational knowledge and skills. The overall results spotlight the significant behavioural changes that can be observed in workforce operations by improving labour performance, which resulted in implementing effective labour-rewarding practices within a framework.

Although the study findings were limited to the Sri Lankan context, the proposed practices can be applied to the industry practices of the construction sector of other developing countries and the other developing industries in similar ways/scenarios.

The study outcomes contribute to uplifting the work qualities of labourers with life-long learning opportunities and unlocking the potential barriers for expanding the local labour supply while controlling the excessive inclination of the local firms towards foreign labour. This paper describes further implications and future scopes of the study elaborately.

The study provides generalised mechanisms and practices that transform the labour characteristics and add new attributes for strengthening the values of construction supervision practices to obtain well-improved work outputs. The study outcomes reinforce the chain relationships among the training elements, labour performance and productivity levels, leading to upgrading current planning and operational management practices, especially adding constructive mechanisms in resource levelling and productivity benchmarking practices.

Rebar is the prime component of reinforced concrete structures, and rebar monitoring is a time-consuming and technical job. With the emergence of the fourth industrial revolution, the construction industry practices have evolved toward digitalization. Still, hesitation remains among stakeholders toward the adoption of advanced technologies and one of the significant reasons is the unavailability of knowledge frameworks and implementation guidelines. This study aims to investigate technical factors impacting automated monitoring of rebar for the understanding, confidence gain and effective implementation by construction industry stakeholders.

A structured study pipeline has been adopted, which includes a systematic literature collection, semistructured interviews, pilot survey, questionnaire survey and statistical analyses via merging two techniques, i.e. structural equation modeling and relative importance index.

The achieved model highlights “digital images” and “scanning” as two main categories being adopted for automated rebar monitoring. Moreover, “external influence”, “data-capturing”, “image quality”, and “environment” have been identified as the main factors under “digital images”. On the other hand, “object distance”, “rebar shape”, “occlusion” and “rebar spacing” have been highlighted as the main contributing factors under “scanning”.

The study provides a base guideline for the construction industry stakeholders to gain confidence in automated monitoring of rebar via vision-based technologies and effective implementation of the progress-monitoring processes. This study, via structured data collection, performed qualitative and quantitative analyses to investigate technical factors for effective rebar monitoring via vision-based technologies in the form of a mathematical model.

Productivity increase is correlated with profitability, sustainability and competitiveness of the construction firms. Recent studies reveal that the primary causes of productivity decline are poor usage of scientific and technological advances, ineffective supervision strategies and poor apprenticeship facilities/opportunities. Accordingly, the purpose of this study was to evaluate how well construction supervisors can utilise fundamental science and technological concepts/ideas to increase the efficiency and productivity of construction activities.

A new strategic layout was designed with the use of potential training guide tools. Based on the designed layout, a new supervisory training programme was developed, and 62 construction supervisors were selected, trained and evaluated in line with six parts of competencies and the relevant learning domains. An assessment guide with different levels of descriptions and criteria was developed through literature analysis and expert interviews. The research tools were verified using comprehensive approaches.

The overall mean values of supervisors’ performance scores indicate proficient-level grades in the competency characteristics related to taking measurements, generating drawings/designs using manual techniques and computer-aided tools, involving Bill of Quantities (BOQ) preparations and preparing training plans/materials for improving the competencies of labourers on estimation, measurements and understanding drawings. Their proficiency was notably lower in the use of information and communication technology application tools in construction tasks compared to others. The findings point to a modern generalised guideline that establishes the ranges of supervisory attributes associated with science and technology-related applications.

The study outcomes produce conceptualised projections to restructure and revalue the job functions of various working categories by adding new definitions within the specified scope. This may result in constructive benefits to upgrading the current functions associated with urbanisation, sustainability and society. The implementation of the study’s findings/conclusions will have a significant impact on present and future practices in other developing nations and developing industries, even if they are directly applicable to the Sri Lankan construction industry.

Up to certain limits/stages, the study fills not only the knowledge gap in the field of creating protocols and application techniques connected to lifelong learning and skill enhancement/upgrading but also the existing gaps in work attributes and roles of construction supervisors associated with the utilisation of fundamental science and technological concepts/ideas towards reinforcing sustainable and productive site operations.

Despite the popularity of the entrepreneurial ecosystem (EE) concept, research on its value-adding activities receives less attention. Thus, in this article, the authors investigate the role of EEs in supporting global value chain (GVC) activities.

The authors employ the fuzzy-set qualitative comparative analysis (fsQCA) technique to identify practical configurations of EE’s framework and systemic conditions spurring GVC activities in 80 countries.

The findings suggest different configurations of EE`s framework and systemic conditions necessary for various GVC activities regarding input-output structure, geographical scope, upgrading, and forward and backward participation.

This study contributes to the extant literature by pioneering the EE approach to explaining GVC development. Moreover, the findings provide novel insights for understanding the EE – GVC interplay. As a result, the study offers a more nuanced understanding of how the EE supports GVC activities.

Establishing a more sustainable built environment is an increasing global concern for the construction industry. Despite the intrinsic and extrinsic obstacles the stakeholders face, huge efforts are required to transition to a smooth, sustainable construction (SC) practice. This study identifies and discusses cogent obstacles to SC in developing nations.

The Preferred Reporting Item for systematic reviews and Meta-Analysis (PRISMA) approach was employed to establish research work in SC for developing countries. The databases used were Scopus and Web of Science. Meta-analysis of keywords was analysed thematically. The initial broad search returned 8,420 publications which were filtered and reviewed in-depth to fit the aim of the study, produced only 21 relevant publications from the years 2000–2021.

The four identified themes of obstacles to SC in developing countries are as follows: construction professional training and education, clients' attitudes and awareness, construction industries' culture and capacity and governments' regulation, policies and economy. The key barriers identified from the meta-analysis include inadequate training and education amongst construction professionals, poor execution of sustainability ethics, poor populace attitude towards sustainability, poor awareness and understanding, dearth of precise data and integrated study and inappropriate priorities about sustainability.

The originality in this study are themes drawn from millennium development goals (MDGs) and sustainable development goals (SDGs) publications related to SC. Consequently, the final framework presented a holistic approach to surmounting the established limitations and aided recommendations for future studies. Thus, setting a background for developing strategies to overcome the limitations and further attain sustainable development (SD).

Digital twin (DT) and building information modeling (BIM) are interconnected in some ways. However, there has been some misconception about how DT differs from BIM. As a result, industry professionals reject DT even in BIM-based construction projects due to reluctance to innovate. Furthermore, researchers have repeatedly developed tools and techniques with the same goals using DT and BIM to assist practitioners in construction projects. Therefore, this study aims to assist industry professionals and researchers in understanding the relationship between DT and BIM and synthesize existing works on DT and BIM.

A systematic review was conducted on published articles related to DT and BIM. A total record of 54 journal articles were identified and analyzed.

The analysis of the selected journal articles revealed four types of relationships between DT and BIM: BIM is a subset of DT, DT is a subset of BIM, BIM is DT, and no relationship between BIM and DT. The existing research on DT and BIM in construction projects targets improvements in five areas: planning, design, construction, operations and maintenance, and decommissioning. In addition, several areas have emerged, such as developing geo-referencing approaches for infrastructure projects, applying the proposed methodology to other construction geometries and creating 3D visualization using color schemes.

This study contributed to the existing body of knowledge by overviewing existing research related to DT and BIM in construction projects. Also, it reveals research gaps in the body of knowledge to point out directions for future research.