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This study evaluates the enablers and barriers for modular concrete construction in Lebanon. The purpose of this paper is to investigate various factors (time, cost, technical know-how, organizational, sustainability, etc.) and their influence on the choice of the construction method. The paper examines the different assessments of designers, manufacturers, and contractors regarding precast construction in comparison to traditional in-situ methods, and highlights the major differences in their views.

Structured face-to-face surveys were conducted with top management personnel of precast manufacturers, architectural and engineering firms, and contracting companies in Lebanon. In addition, a case study from the largest precast project in Lebanon was used to provide a deeper understanding of factors encouraging the use of precast concrete, and to highlight major onsite issues associated with its implementation.

On the one hand, the findings highlight technical, logistical, organizational, and cultural factors that inhibit the use of precast concrete as a construction method. On the other hand, results reveal that cost, time, sustainability, and flexibility factors are the main enablers for increasing the uptake of modular concrete construction.

The main contribution to knowledge is that this study presents different stakeholders’ perspectives on precast concrete construction. Moreover, this is the first research addressing precast concrete construction in the Middle East and Lebanon. The results of the study provide valuable global insights and recommendations that may help increase the uptake of precast concrete construction. They can also guide project stakeholders to properly match project characteristics and precast concrete as a construction method.

The paper aims to provide a door-to-door holistic perspective on the state of a production system based on several metrics and their relationships, to utilize a combination of tools and techniques and to develop a unique model for production system assessment. The study addresses the limitations of narrow approaches by proposing a new metric as a single indicator of the production system’s overall state.

The research methodology adopted is design science research. It proposes a framework that combines value stream mapping, simulation and fuzzy logic to study the impact of different lean interventions on the overall state. An offsite construction facility was used as a case study. Data were gathered using methods such as ethnography, interviews, time and motion studies, shopfloor observations, video surveillance and database exploration.

The paper highlights how some interventions can have local improvements but lead to negative impacts on the overall system state. It emphasizes the importance of having a holistic approach to analyze and improve the true state of a production system.

The study excludes impacts of the supply chain and assumes the system to be confined within the shopfloor. Researchers are encouraged to include those variables in future studies.

The study presents a practical framework and tool that can be tailored to any production system and be used to improve its performance.

This paper proposes a unique framework and a new metric for system state assessment and improvement.

In academics and industry, significant efforts have been made to lead planners and control teams in evaluating project performance and control. In this context, numerous control metrics have been devised and put into practice, often with little emphasis on analyzing their underlying concepts. To cover this gap, this research aims to identify and analyze a holistic list of control metrics and their functionalities in the construction industry.

A multi-step analytical approach was conducted to achieve the study’s objectives. First, a holistic list of control metrics and their functionalities in the construction industry was identified. Second, a quantitative analysis based on social network analysis (SNA) was implemented to discover the most important functionalities.

The results revealed that the most important control metrics' functionalities (CMF) could differ depending on the type of metrics (lagging and leading) and levels of control. However, in general, the most significant functionalities include managing project progress and performance, evaluating the look-ahead level’s performance, measuring the reliability and stability of workflow, measuring the make-ready process, constraint management and measuring the quality of construction flow.

This research will assist the project team in getting a comprehensive sensemaking of planning and control systems and their functionalities to plan and control different dynamic aspects of the project.

This study aims to enhance productivity monitoring and control in the construction industry by integrating data-driven analytics with expert insights.

A novel framework combines expert knowledge and data analysis to identify productivity trends and devise improvement strategies. A machine learning model predicts productivity ranges using historical data and project-specific factors’ evaluated by surveys, supported by a warning dashboard for proactive decision-making.

The findings reveal that integrating expert insights with data analytics significantly enhances the ability to monitor and control productivity, leading to proactive strategies for construction stakeholders. The machine learning model demonstrates robust accuracy in forecasting productivity ranges, allowing for early identification of potential issues. The dashboard system proves invaluable, offering semi-real-time alerts and facilitating swift action to prevent productivity lapses. These results highlight the effectiveness of the proposed approach in detecting trends, predicting outcomes and enabling timely interventions, thereby contributing to the overall productivity improvement of construction projects.

There are also limitations to consider, including potential data availability, constraints in the expert pool, implementation challenges and the need for long-term evaluation; these factors should be considered when interpreting the study’s findings and applying the proposed framework to construction projects. Future research can focus on expanding the application of this framework to different types of construction projects and evaluating its scalability.

This study introduces a framework with a warning dashboard for early detection of issues, combining expert insights and data analysis for improved project outcomes. This research suggests a shift toward more expert, data-driven, insightful decision-making in construction, aiming for enhanced performance and reduced disruptions. An important implication of this research is the need to balance digital tools and expert judgment. Project managers are advised to use a holistic strategy that ensures informed and comprehensive decision-making.

This research introduces a unique methodology that blends traditional expertise with modern analytics to address construction productivity challenges. It offers a practical solution for stakeholders to enhance decision-making, resource allocation and project planning, marking a significant contribution to construction management literature.

Compressing the schedule by using overlapping activities is a commonly adopted approach for accelerating projects. However, this approach might channel a variety of risks into the construction processes. Risks imply waste; still, evaluating the effects of using overlapping activities on schedule quality has been a looming gap in construction research. Therefore, this paper aims to study the quality of overlapping in terms of emerging waste and to demarcate the boundaries of the overlapping envelope.

This study presents a method for assessing the consequences of implementing overlapping activities in a schedule on two types of waste namely waiting time and variation gap. A critical path method (CPM) network including eleven activities is modeled stochastically where the durations of individual activities are sampled as beta-distributions. Using program evaluation and review technique (PERT) assumptions to calculate the schedule dates, the network is simulated for various amounts of overlapping and the corresponding waste is quantified each time.

Results show that not only the returns on overlapping are diminishing after a certain overlap percentage, but also waste in the production system increases. Particularly, results reveal that compressing the schedule leads to a decrease in variation gaps, but at the same time, it leads to a larger increase in waiting times, which creates more waste.

The presented study shows through simulation how overlapping activities affects productivity by identifying wastes. It shows that despite the apparent gains, overlaps should be used with caution, and while considering the side-effects of increased waste which introduces a need for increased managerial awareness.

The research introduces means for improving premanufacturing processes (design, procurement and bidding) by leveraging digitalisation in offsite construction. Specifically, this paper proposes a framework that provides measures for the planning and implementation of digitalisation in offsite construction by positioning building information modelling (BIM) as the key technology and lean principles to add value and reduce waste.

The paper follows the design science research approach to develop the proposed framework and attain the aforementioned objective. The developed framework includes data collection, value-stream mapping and simulation to assess current processes, develop and propose improvements. An empirical implementation is employed to demonstrate the applicability of both the framework and the measures used to evaluate the outcomes.

The application of the proposed three-stage framework resulted in 9.45%–23.33%-time reduction per year for the various improvement categories in premanufacturing phases. Employing simulation and applying the developed measures provide incentive for upper management to adopt the suggested improvements. Additionally, while the empirical implementation was tested on a modular construction company, the methods used indicate that the framework, with its generic guidelines, could be applied and customized to any offsite company.

While several studies propose that BIM-Lean integration offers an advantage in the context of production systems, this paper focuses on the initial design and planning phases, which are mostly overlooked in the literature. Moreover, the present study provides quantitative evidence of the benefits of data integration through BIM technology.

In a public-private partnership (PPP), the private sector is represented by a company termed the special purpose vehicle (SPV), which combines different stakeholders including designers, contractors and service providers under one umbrella. Correct SPV team selection is critical to ensure PPP success as the SPV must act as an integrated entity. In fact, unless the SPV takes an active role in developing trust and promoting integration principles, segmentation of interests, highly adversarial atmospheres, loss of value and economic inefficiency will prevail. Absence of awareness of such principles among stakeholders and the scarcity of literature investigating SPV stakeholder integration create great risks that jeopardize project success. Accordingly, to mitigate the aforementioned risks and provide stakeholders with both the knowledge and the tools to instigate and maintain integration, this paper aims to develop and test a framework to measure SPV stakeholder integration, inspired by the correlation between integrated project delivery (IPD) and SPV operations.

Following a design science research approach, a structured review is conducted to develop the SPV integration metrics and framework. The framework is then validated through face validation by a panel of industry and academic experts to assess its applicability in measuring SPV integration. Finally, the framework is tested on a well-recognized international PPP project to measure the SPV integration level, and the outcomes are discussed and analyzed.

The framework was able to assess the integration level of the studied SPV highlighting several areas of low-integration settings and providing guidance for achieving better integration.

This research is the first that develops a model to investigate the SPV’s integration level, from a holistic IPD perspective, to enable successful relationship management and enhance collaboration success. This study inspires practical recommendations for PPP practitioners to reduce the risks of segregated SPVs and their contribution to PPP failure.

This study investigates the extent to which the popular forms of contract adopted in the Middle East (ME) address collaboration. The purpose of this paper is to assess how collaboration features weaved into the construct of integrated project delivery (IPD) may impact projects in the ME. In this context, the study identifies features in IPD and existing delivery methods that may enable or inhibit collaboration and evaluates their impact on project success from the perspective of various contract managers in the ME.

The study employs structured face-to-face interviews with 41 construction industry practitioners in top contract management positions in the ME to evaluate the significance of collaboration features in IPD. Data collected from the structured interviews/surveys were analyzed using statistical tools in R and Excel.

Results reveal that while experts recognize the collaboration benefits which IPD features may contribute to a project, the current contractual environment of the industry does not optimally encompass these features. The current status of project delivery does not favor IPD implementation nor does it enable its collaborative features.

This study contributes to the growing international body of knowledge addressing the application of collaborative contracts in construction projects, and it is innovative in evaluating collaboration features within IPD and exiting project deliveries in the ME.

With tower cranes being the site hubs, thoroughly planning and managing their operations can result in better construction performance. As urban spaces become more constricted, overlapping working radii of tower cranes becomes inevitable. While project planners are concerned with safety hazards, research has not comprehensively addressed workload distribution and synchronization of overlapping cranes. Therefore, this study aims at exploring the impact of overlapping cranes, used on high-rise buildings, on operational flexibility which is the balance between schedule duration, crane utilization and safety.

A simulation model was developed and applied on a real project to analyze and compare the impacts of different overlap sizes. Seven scenarios of different overlap sizes, i.e. different number of tasks falling in the overlap space, were executed in the model; their results were plotted and analyzed.

The outcomes result from several compounded factors such as the experience of planners and crane operators, the sequencing of critical versus non-critical activities and the overall effort and care taken when planning operations of overlapping cranes. Increasing overlap size can be beneficial or unfavorable depending on how properly planners allocate overlapping cranes to workload demand, keeping in mind that there are certain trade-offs while achieving operational flexibility.

While project planners are concerned with safety hazards associated with crane overlaps, research has not been comprehensively nor proactively addressing the workload distribution and synchronization of overlapping crane processes. This study contributes to science by addressing the need to harness the flexibility in using overlapping tower cranes while minimizing the resulting interruptions and safety risks. This study sheds light on the potential benefits of allowing cranes to overlap while considering their collision free operations. Operational flexibility is seen as the balance between achieving shorter schedule durations and higher crane utilizations while maintaining collision free motion paths.