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The deviant behavior (DB) of construction workers has always been a troubling event in project management. Although scholars continue to search for the main causes of this behavior to curb it at the source, the authors know less about the role and contribution of the team. This study aims to uncover the mechanisms and conditions under which collective moral judgment focus on self (CMJS) effectively enhances DB.

Adopting Chinese construction enterprises as samples, a hierarchical linear model (HLM) is used to test the results of the hypothesis. Moderated mediating effects are used to analyze the potential mechanisms and boundary conditions of DB.

The results of the HLM analysis show that CMJS could directly and significantly induce DB, and moral disengagement (MD) plays a mediator role in this association. In addition, the positive relationship between MD and DB is stronger when performance-avoidance goal orientation (PaGO) or overqualification (Overq) is higher.

The conditions and mechanisms that influence DB are not unique. Future study could examine the explanatory and weighting mechanisms of DB from other perspectives or to construct a framework and summarize the factors that may influence DB.

This study provides a rich theoretical basis for the prevention and correction of construction workers' DB in Chinese construction firms from the perspective of CMJS. In addition, objective moral judgments contribute to guiding employees' moral cognitive processes and positive work.

This study extends existing research on DB and advances the practical outcomes of construction project governance. It not only illustrates that CMJS has a direct impact on DB but also clarifies the mechanisms and conditions that predispose to the generation of DB, filling the research gap on construction workers' DB from cross-level mechanisms and also enriching the theoretical system for preventing this behavior.

This paper aims to present a highly accessible and affordable tracking model for earthmoving operations in an attempt to overcome some of the limitations of current tracking models.

The proposed methodology involves four main processes: acquiring onsite terrestrial images, processing the images into 3D scaled cloud data, extracting volumetric measurements and crew productivity estimations from multiple point clouds using Delaunay triangulation and conducting earned value/schedule analysis and forecasting the remaining scope of work based on the estimated performance. For validation, the tracking model was compared with an observation-based tracking approach for a backfilling site. It was also used for tracking a coarse base aggregate inventory for a road construction project.

The presented model has proved to be a practical and accurate tracking approach that algorithmically estimates and forecasts all performance parameters from the captured data.

The proposed model is unique in extracting accurate volumetric measurements directly from multiple point clouds in a developed code using Delaunay triangulation instead of extracting them from textured models in modelling software which is neither automated nor time-effective. Furthermore, the presented model uses a self-calibration approach aiming to eliminate the pre-calibration procedure required before image capturing for each camera intended to be used. Thus, any worker onsite can directly capture the required images with an easily accessible camera (e.g. handheld camera or a smartphone) and can be sent to any processing device via e-mail, cloud-based storage or any communication application (e.g. WhatsApp).

This paper systematically reviewed research work on drivers of teamwork, which will reinforce construction work teams to enhance workers’ safety performance. This study adds to the existing but limited understanding of teamwork drivers on construction workers’ safety performance. This paper presents scholars and industry-based professionals with critical initiatives that have to be implemented in organisations to get positive results in safety while working in teams with an emphasis on systems drivers of teamwork on safety performance at the organisational level, which will help in providing information on the functioning of the teams and contribute towards improved safety performance of team workers.

This study aims to systematically examine the existing body of knowledge on drivers of teamwork by analysing 53 publications from the years 1997–2021. The Scopus search engine was used to conduct a systematic review and germane publications were collated.

According to the findings of the review, since 1997, there has been a burgeoning concern in the research of drivers of teamwork and its impact on workers’ safety performance. After performing a systematic review, 37 drivers of teamwork were identified. The top five drivers are effective communications, team workers’ relations, leadership, shared knowledge and information, and team training. Moreover, it was noted that the United States and Australia have been the international regions of focus for most of the research in the area of drivers of teamwork from the years 1997–2021. The 37 drivers of teamwork are distributed into six major socio-technical components: people drivers; culture drivers; metrics drivers; organisational and management practices and procedures drivers; infrastructure drivers and technology drivers.

The results reported present research scholars and professional practitioners with an overview of the drivers of teamwork that could be implemented in the construction industry to streamline potential implementations and improve safety performance of construction workers.

A list of teamwork drivers has been developed to ratify potential empirical research in the area of construction safety. The results would contribute to the existing but restricted understanding of drivers of teamwork in the construction industry.

In repetitive projects, repetition offers more possibilities for activity scheduling at the sub-activity level. However, existing resource-constrained repetitive scheduling problem (RCRSP) models assume that there is only one sequence in performing the sub-activities of each activity, resulting in an inefficient resource allocation. This paper proposes a novel repetitive scheduling model for solving RCRSP with soft logic.

In this paper, a constraint programming model is developed to solve the RCRSP using soft logic, aiming at the possible relationship between parallel execution, orderly execution or partial parallel and partial orderly execution of different sub activities of the same activity in repetitive projects. The proposed model integrated crew assignment strategies and allowed continuous or fragmented execution.

When solving RCRSP, it is necessary to take soft logic into account. If managers only consider the fixed logic between sub-activities, they are likely to develop a delayed schedule. The practicality and effectiveness of the model were verified by a housing project based on eight different scenarios. The results showed that the constraint programming model outperformed its equivalent mathematical model in terms of solving speed and solution quality.

Available studies assume a fixed logic between sub-activities of the same activity in repetitive projects. However, there is no fixed construction sequence between sub-activities for some projects, e.g. hotel renovation projects. Therefore, this paper considers the soft logic relationship between sub-activities and investigates how to make the objective optimal without violating the resource availability constraint.

Due to its longer length compared to other construction materials and distinctive stacking patterns, obtaining construction steel bars in congested construction sites with limited storage capacity becomes challenging. Lack of storage space in crowded places prompts the need for building steel bar storage choice optimization. Therefore, this study aims to optimize the construction steel bar procurement plan by providing when and how much rebar to order and how to stack different sizes of rebar considering limited storage capacity.

A novel approach has been presented in this paper by integrating 4D building information modelling (BIM) and mixed-integer linear programming (MILP). This technique uses BIM to retrieve material quantities, including rebar, during the design phase. Following that, activities are scheduled depending on the duration determined by crew productivity data and material quantity. Then, based on the prior price, the price of each unit of rebar is projected for the duration of construction using the exponential smoothing method. After that, the MILP approach is used to generate an optimal steel bar procurement plan for limited storage space following the scheduled rebar-related operations.

The developed strategy minimizes overall procurement costs and ensures the storage of rebar as per standard guidelines. An optimal rebar procurement and storage plan to construct a six-storied RC frame has been presented in this paper as a demonstrative example to show the effectiveness of the proposed method.

This work partially satisfies a long-sought research need for establishing a comprehensive construction steel bar procurement system, making it a very useful source of information for practitioners and researchers. The proposed method can be used to minimize a key performance limitation that the conventional rebar procurement practice for crowded building sites may experience.

The COVID-19 pandemic offered a unique glimpse into the resilience of construction projects, shedding light on several learning opportunities. The purpose of this paper is to develop propositions for the improvement of resilient performance in construction in the post-pandemic era.

The propositions were developed based on an empirical study in Brazil. Data collection involved the analysis of regulations, interviews with health experts, managers, and workers, in addition to non-participant observations of the use of 37 control practices in 39 construction sites comparing the work-as-imagined and the work-as-done. The practices were classified in a hierarchy of controls.

Seven propositions for the improvement of resilient performance were developed, addressing collaboration between construction companies, slack resources, new health and safety practices, production planning and control, digital technologies, visual management, and organizational culture. These propositions emphasize organizational support for resilience. This is in contrast to the nature of most observed practices (57%) that relied on administrative controls and personal protective equipment, which are measures dependent on behaviors that resemble resilience at the individual level.

Although much has been studied on COVID-19 implications for construction projects, previous empirical studies have not adopted the organizational resilience perspective as the main theoretical background.

The workforce management model conceptualised for the effective management of the construction workforce was subjected to expert scrutiny to determine the suitability and applicability of the identified practices and their attributed variables to the construction industry. In achieving this, a Delphi approach was adopted using experts from construction organisations in South Africa. These experts comprised workforce management personnel and construction professionals in senior management positions. The data were analysed using appropriate statistical tools such as interquartile deviation, Kendell’s coefficient of concordance, and chi square to determine consensus among these experts. After a two-round Delphi, the seven constructs proposed in the conceptualised workforce management model were adjudged to be important and worthy of adoption by construction organisations seeking to improve workforce management in the current fourth industrial revolution era.

Previous research regarding shaping factors and major causes behind accidents in the construction field is reviewed. In particular, a hypothetical model is established to correlate activity time, cost and safety in the context of construction activity acceleration planning. Two demonstration cases are presented to illustrate the proposed theoretical model in the context of critical activity expedition planning. Further, a third case uses a 100-activity project to perform the global level total project time and cost analysis, identifying specific activity acceleration plans that would materialize the shortened total project time at the lowest total project cost.

This research proposes a safety-centric application framework to guide construction acceleration planning at both activity and project levels while taking sufficient preventive measures against safety hazards and accidents. As planning construction acceleration by factoring in safety constraints inevitably drives up cost, it is imperative to control increases in activity costs at the local level in connection with schedule acceleration planning while at the same time not compromising on safety. This research also addresses this critical question through performing global level total project time and cost analysis.

An application framework is proposed for guiding a planner through identifying accident shaping factors, obeying schedule acceleration rules and accounting for safety-related costs in attempts to mitigate hazardous situations on-site at both activity level (local) and project level (global), resulting in (1) minimizing the increase of total project cost in schedule acceleration while at the same time not compromising on safety at individual activities; (2) producing specific execution plans on each individual activity in terms of the amount of time to crash and the associated activity cost.

This study is original in developing theories and methods for evaluating the impact of safety constraints upon construction time and cost in activity acceleration planning and project time-cost analysis. The research fills a gap in knowledge in terms of how to factor in sufficient safety constraints while achieving project time and cost objectives on construction acceleration planning at both activity and project levels.

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.

Tracking physical resources at the construction site can generate information to support effective decision-making and building production control. However, the methods for conventional tracking usually offer low reliability. This study aims to propose the integrated Smart Twins 4.0 to track and manage metallic formworks used in cast-in-place concrete wall systems using internet of things (IoT) (operationalized by radio frequency identification [RFID]) and building information modeling (BIM), focusing on increasing quality and productivity.

Design science research is the research approach, including an exploratory study to map the constructive system, the integrated system development, an on-site pilot implementation in a residential project and a performance evaluation based on acquired data and the perception of the project’s production team.

In all rounds of requests, Smart Twins 4.0 registered and presented the status from the formworks and the work progress of buildings in complete correspondence with the physical progress providing information to support decision-making during operation. Moreover, analyses of the system infrastructure and implementation details can drive researchers regarding future IoT and BIM implementation in real construction sites.

The primary contribution is the system proposal, centralized into a mobile app that contains a Web-based virtual model to receive data in real time during construction phases and solve a real problem. The paper describes Smart Twins 4.0 development and its requirements for tracking physical resources considering theoretical and practical previous research regarding RFID, IoT and BIM.