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In construction projects, underpayments can be recognised as one of the significant drawbacks that impact the success of a project. Research into underpayments is considered ambiguous and provides a limited reflection of the issue, which makes it complicated to trace how it originates in the first place. This study aims to examine the causes that lead to underpayments and develop a holistic synthesis of underpayments for subcontractors in the lifecycle of a construction project.

An open-ended and closed-ended questionnaire was used to collect the data using purposeful sampling with 28 construction stakeholders who ranged from main contractors, subcontractors and others (Small medium enterprises SMEs, Consultancies, Clients etc.). Data collected was analysed to trace drivers and the impact of underpayment and suggested mitigation strategies to be identified whilst viewing the perspectives of a main contractor and subcontractor.

The findings show that the most prominent driver for underpayments is variation disputes followed by cash flow. The research also suggests mitigation strategies such as collaborative working, more robust budget control and early identification of risks as potential remedies to overcome the underpayment issue. The research concludes with a framework that elicits the complexity underlying underpayments for subcontractors in construction projects.

The research evolves the understanding that underpayment is a complex phenomenon, relying heavily on the data/information exchange mechanism between the main contractor and subcontractors. This research provokes the need to understand underpayment further so it can be mitigated.

Previous studies have established to a great extent that regulatory frameworks and, in particular, procurement approaches – that are common in a particular context – have a major impact on the success of building information modelling (BIM) implementation in construction projects. Despite the close links between these two concepts, research on the effect of procurement approaches on BIM implementation is scarce. To address this gap, this paper aims to investigate the barriers that affect BIM implementation through the lens of procurement approaches.

A mixed-method approach was adopted using a questionnaire survey (n = 116) and interviews with key stakeholders (n = 12) in Jordan. The outcomes of the quantitative parts were augmented with findings from interviews.

It was revealed that the deployment of unfavourable construction procurement approaches represents a major hurdle towards BIM implementation. Though essential for enhancing BIM implementation, it is revealed that a fundamental change from the common design-bid-build (DBB) to more collaborative procurement approaches remains infeasible in view of the realities that govern the construction industry.

It was revealed the deployment of unfavourable construction procurement approaches represents a major hurdle towards BIM implementation. Though essential for enhancing BIM implementation, it is revealed that a fundamental change from the common DBB to more collaborative procurement approaches remains infeasible given the realities that govern the construction industry.

As the first of its kind, a set of recommendations for establishing supportive, workable procurement that does not deviate significantly from common procedures and practices is presented. Rather than advocating a shift to procurement approaches that are aligned with BIM, the findings offer novel insight into the necessity of developing a framework within the boundaries of the current and widely adopted procurement approaches to address the identified construction procurement issues and facilitate BIM implementation.

The purpose of this paper is to develop a building information modelling (BIM)-based multi-objective optimization (MOO) framework for volumetric analysis of buildings during early design stages. The objective is to optimize volumetric spaces (3D) instead of 2D spaces to enhance space utilization, thermal comfort, constructability and rental value of buildings

The integration of two fundamental concepts – BIM and MOO, forms the basis of proposed framework. In the early design phases of a project, BIM is used to generate precise building volume data. The non-sorting genetic algorithm-II, a MOO algorithm, is then used to optimize extracted volume data from 3D BIM models, considering four objectives: space utilization, thermal comfort, rental value and construction cost. The framework is implemented in context of a school of architecture building project.

The findings of case study demonstrate significant improvements resulting from MOO of building volumes. Space utilization increased by 30%, while thermal comfort improved by 20%, and construction costs were reduced by 10%. Furthermore, rental value of the case study building increased by 33%.

The proposed framework offers practical implications by enabling project teams to generate optimal building floor layouts during early design stages, thereby avoiding late costly changes during construction phase of project.

The integration of BIM and MOO in this study provides a unique approach to optimize building volumes considering multiple factors during early design stages of a project

While the COVID-19 pandemic has impacted the construction industry, it is still unclear from prior studies about adequately positioning the quality assurance (QA) for the post-pandemic era and future pandemics, especially cross-border construction logistics and supply chain (Cb-CLSC). Thus, this study aims to develop a managerial framework to position the QA of Cb-CLSC during pandemics and post-pandemics by taking lessons from how COVID-19 has impacted the existing QA systems and has been managed successfully.

This is achieved pragmatically through an embedded mixed-method design involving a literature review, survey and interview from experts within the Hong Kong SAR–Mainland China links, typically known as the world’s factory. The design is further integrated with the partial least squares structural equation modelling (PLS-SEM) approach.

The study revealed 10 critical managerial practices (MPs) to position the QA to be adequate for the post-pandemic and during future pandemics, with the top three including “strict observance of government regulations (MP1)”, “planning ahead the period of quality assurance with the quarantine days in host countries (MP6)” and “modification of contract to cater for uncertainties (MP4)”. This attained a relatively good percentage agreement of 53% between the industry and academia. However, the top four MPs regarded as very effective include “implementing digital collaborative inspections with subcontractors and trades (MP8)”, “implementing a digital centralized document and issue management system (MP7)”, “strict observance to government regulations, including vaccination of workers, social distancing, use of prescribed nose masks, etc. (MP1)” and “planning ahead the period of quality assurance with the quarantine days in host countries (MP6)”. Two underlying components of the MPs were revealed as policy-process (PP)-related practices and people-technology-process (PTP)-related practices, and these can be modelled into a managerial framework capable of effectively positioning the QA to be adequate during pandemics through to the post-pandemic era.

The findings of this study depicted significant theoretical and practical contributions to the proactive management of QA activities during pandemics through to the post-pandemic era. It could empower organisations to pay attention to smartly and innovatively balancing people, processes, pandemic policy and technology to inform decisions to effectively position the QA for the post-pandemic era and survive the risks of future pandemics.

The study contributes to the body of knowledge in that it develops a managerial framework to position the QA of Cb-CLSC during pandemics and post-pandemics by taking lessons from how COVID-19 has impacted the existing QA systems and has been managed successfully. It is original research with invaluable primary data in the form of surveys and interviews from experts within the Hong Kong SAR–Mainland China links, typically known as the world’s factory.

The COVID-19 outbreak reached a critical stage when it became imperative for public health systems to act decisively and design potential behavioral operational strategies aimed at containing the pandemic. Isolation through social distancing played a key role in achieving this objective. This research study examines the factors affecting the intention of individuals toward social distancing in India.

A correlation study was conducted on residents from across Indian states (N = 499). Online questionnaires were floated, consisting of health belief model and theory of planned behavior model, with respect to social distancing behavior initially. Finally, structural equation modeling was used to test the hypotheses.

The results show that perceived susceptibility (PS), facilitating conditions (FC) and subjective norms are the major predictors of attitude toward social distancing, with the effect size of 0.277, 0.132 and 0.551, respectively. The result also confirms that the attitude toward social distancing, perceived usefulness of social distancing and subjective norms significantly predict the Intention of individuals to use social distancing with the effect size of 0.355, 0.197 and 0.385, respectively. The nonsignificant association of PS with social distancing intention (IN) (H1b) is rendering the fact that attitude (AT) mediates the relationship between PS and IN; similarly, the nonsignificant association of FC with IN (H5) renders the fact that AT mediates the relationship between FC and IN.

The results of the study are helpful to policymakers to handle operations management of nudges like social distancing.

The research is one of its kind that explores the behavioral aspects of handling social nudges through FC.

The application of integrated project delivery (IPD) in conjunction with building information modeling (BIM) and Lean Construction (LC) as the efficient method for improving collaboration and delivering construction projects has been acknowledged by construction academics and professionals. Once organizations have fully embraced BIM, IPD and LC integration, a measurement tool such as a maturity model (MM) for benchmarking their progress and setting realistic goals for continuous improvement will be required. In the context of MMs literature, however, no comprehensive analysis of these three construction management methods has been published to reveal the current trends and common themes in which the models have approached each other.

Therefore, this study integrates systematic literature review (SLR) and thematic analysis techniques to review and categorize the related MMs; the key themes in which the interrelationship between BIM, IPD and LC MMs has been discussed and conceptualized in the attributes; the shared characteristics of the existing BIM, IPD and LC MMs, as well as their strengths and limitations. The Preferred Reporting Items for Systematic Reviews (PRISMA) method has been used as the primary procedure for article screening and reviewing published papers between 2007 and 2022.

Despite the growth of BIM, IPD and LC integration publications and acknowledgment in the literature, no MM has been established that holistically measures BIM, IPD and LC integration in an organization. This study identifies five interrelated and overlapping themes indicative of the collaboration of BIM, IPD and LC in existing MMs' structure, including customer satisfaction, waste minimization, Lean practices and cultural and legal aspects. Furthermore, the MMs' common characteristics, strengths and limitations are evaluated to provide a foundation for developing future BIM, IPD and LC-related MMs.

This paper examines the current status of research and the knowledge gaps around BIM, IPD and LC MMs. In addition, the highlighted major themes serve as a foundation for academics who intend to develop integrated BIM, IPD, and LC MMs. This will enable researchers to build upon these themes and establish a comprehensive list of maturity attributes fulfilling the BIM, IPD and LC requirements and principles. In addition, the MMs' BIM, IPD and LC compatibility themes, which go beyond themes' intended characteristics in silos, increase industry practitioners' awareness of the underlying factors of BIM, IPD and LC integration.

This review article is the first of a kind to analyze the interaction of IPD, BIM and LC in the context of MMs in current AEC literature. This study concludes that BIM, IPD and LC share several joint cornerstones according to the existing MMs.

The oil and gas industry form the main resource of economy in Iraq and constructing any project in such sectors requires a huge amount of expenses due to the unique requirements that oil and gas facilities required in such projects. Therefore, adopting an appropriate technological approach such as building information modeling (BIM) which is unfortunately not adopted yet in Iraq is essential to successfully deliver these projects. Thus, this paper aimed to introduce BIM to Iraq through Basra Oil Company (BOC) which is one of the biggest public oil and gas companies in Iraq.

The related literature of journals articles, conference proceedings and published reports have been reviewed. As a result, firstly: a hypothesis has been derived that is “If Basra Oil Company (BOC) adopts and applies BIM approach instead of the 2D approach currently used to manage its projects, the company can overcome several constraints in managing its projects that associated with such 2D traditional approach”; secondly: homogenous, consistence and reliable web-based questionnaire has been designed as its Cronbach’s alpha equal to 0.897 and 0.711 for BIM benefits and barriers, respectively. This questionnaire distributed to the BOC related professionals to test such hypothesis by investigating their readiness and accepting of BIM approach and to rank BIM barriers based on five-point Likert scale.

Based on the analysis using IBM SPSS Statistics 26 of 115 responses, almost 50% of the respondents had experience 11–15 years, while 22.6% had experience more than 15 years in oil and gas industry construction projects. Those participants were from diverse engineering majors that are: 4.3% Architectural Engineers, 31.3% Civil Engineers, 20% Mechanical Engineers, 22.6% Electrical Engineers and 21.7% from other engineering majors. The respondents’ departments demography was 16.5% of design department, 12.2% of construction department, 20.9% of Project Management Department, 12.2% of Maintenance department, 4.3% of HSE Department, 13% of Production Department and 20.9% of “Other Department.” The study resulted in 1: accepting BIM approach to be an alternative of current 2D-traditional approach used by the company to manage and construct its projects, since mean of collected data is (4.4332), Kruskal–Wallis H test significance values were 0.398 and 0.372; and ANOVA test significance values were 0.433 and 0.599 among Engineering Majors groups and Company’s Department groups, respectively. 2: Disclosed and sequenced BIM barriers in the company based on their criticality. 3: verifying reliably how BIM attributes are important to oil and gas construction projects in Iraq, 4: the company top management and company policies are the most critical potential factors to hinder or adopt and implement BIM in the company, 5: while cost is not seen a critical barrier to implement BIM in the oil and gas sector.

The limitation of this study is the excluding of decision makers of BOC, thus more profound future studies need to be conducted where top management and decision makers are involved, particularly the present study demonstrated that support of company top management is the most critical factor which can help the company to adopt (BIM).

The study concludes that BIM approach is valuable for managing projects in oil and gas sector in Iraq and identify the originality in output by using the research method. This noble study provides a leverage for enhanced research to adopt and implement building information modeling (BIM) in Iraq as the study originally demonstrates benefits and identifies the critical barriers in BIM implementation to push the boundaries toward adopt Digitalization and reduce CO2 emission in Iraqi oil and gas sector. The study can be used as evidence and platform to encourage professionals and practitioners to present more sophisticated tools of BIM in the oil and gas industry, especially for facility and operation management. These findings achieved via oil and gas experts, and it is first time to achieve such findings from a case study in Iraqi oil and gas sector.

Practitioners have reported a minimal and non-use of building information modelling (BIM), especially in small and medium-sized organisations and BIM infant construction industries. This development calls for a reappraisal of organisations’ strength in capabilities required for BIM uptake towards the target of global construction digitalisation. This study aims to assess the BIM Level 2 uptake capability of organisations in a BIM infant construction industry and identify the underlying interactions between the capability criteria.

The study used a multivariable analysis of fifteen descriptors identified from the people, process, policy, finance and technology domain. Data collection was done in the BIM infant construction industry in Nigeria. Verification of the descriptors and an evaluation of BIM uptake capability in organisations was done. Seventy-three responses were received within the selected context, and data analysis was done with mean weighting and exploratory factor analysis. Maximum Likelihood extraction and Direct Oblimin rotation were used.

Factor analysis revealed three factors that explained 53.28% of the total variance in the BIM Level 2 uptake capability of construction organisations. The factors are workforce capacity and continuous development, an affinity for innovation and strength in physical and operational facilities.

This study provides an overarching and insightful discussion on BIM uptake capability and construction digitalisation with evidence from a BIM-infant construction industry.

The findings of this study are a piece of valuable empirical evidence on Level 2 BIM uptake capability. This empirical situation analysis will inform the advocacy for the advancement of BIM and enhanced utilisation of building information. Evidence on the capability performance of the BIM infant industry has been revealed.

The outcome is expected to stir debate on the preparedness of organisations to further exploit the benefits of BIM in the BIM infant construction industry. Examination of the capability for a particular phase of BIM is scanty in the literature.

Prefabricated building has been widely applied in the construction industry all over the world, which can significantly reduce labor consumption and improve construction efficiency compared with conventional approaches. During the construction of prefabricated buildings, the overall efficiency largely depends on the lifting sequence and path of each prefabricated component. To improve the efficiency and safety of the lifting process, this study proposes a framework for automatically optimizing the lifting path of prefabricated building components using building information modeling (BIM), improved 3D-A* and a physic-informed genetic algorithm (GA).

Firstly, the industry foundation class (IFC) schema for prefabricated buildings is established to enrich the semantic information of BIM. After extracting corresponding component attributes from BIM, the models of typical prefabricated components and their slings are simplified. Further, the slings and elements’ rotations are considered to build a safety bounding box. Secondly, an efficient 3D-A* is proposed for element path planning by integrating both safety factors and variable step size. Finally, an efficient GA is designed to obtain the optimal lifting sequence that satisfies physical constraints.

The proposed optimization framework is validated in a physics engine with a pilot project, which enables better understanding. The results show that the framework can intuitively and automatically generate the optimal lifting path for each type of prefabricated building component. Compared with traditional algorithms, the improved path planning algorithm significantly reduces the number of nodes computed by 91.48%, resulting in a notable decrease in search time by 75.68%.

In this study, a prefabricated component path planning framework based on the improved A* algorithm and GA is proposed for the first time. In addition, this study proposes a safety-bounding box that considers the effects of torsion and slinging of components during lifting. The semantic information of IFC for component lifting is enriched by taking into account lifting data such as binding positions, lifting methods, lifting angles and lifting offsets.