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High-level labor waste is a major challenge in construction projects. This paper aims to identify, quantify and categorize labor waste in the context of Iranian housing construction projects.

This research uses a case study approach, with empirical data collected through direct observations and semi-structured interviews.

Having triangulated the findings from the literature review and empirical studies, a list of eight types of waste was derived for the thirteen observed laborers in ten case study projects. The empirical studies allowed the labor waste identified from the literature to be verified and refined by considering it in the context of the observed activities, and led to two new types of waste being identified which were not considered in the literature. Findings indicate that nearly 62% of laborers' time is spent on non-value-adding activities. It appeared that “unnecessary movement,” “waiting” and “indirect work” make up the highest labor waste.

This research focuses only on onsite resource flows in a housing construction site. It does not include offsite flows such as material delivery to site.

The findings have provided substantial evidence on type and amount of labor waste and provide a solid basis to stimulate construction actors to participate in reducing labor waste and improving productivity.

In the construction sector, site excavation is one of the most dangerous and challenging activities. Proper training can be an effective way to mitigate excavation hazards. Virtual reality (VR) has been used as an effective training tool to enhance safety performance in various industries. However, little attention has been paid to the potential of this technology for construction excavation safety training.

This study proposes an immersive VR training system for excavation safety and hazard identification. The proposed VR training system was compared with a health and safety manual via a controlled experiment.

Results based on scores obtained immediately after training indicate that VR training significantly enhanced practical performance, knowledge acquisition and self-efficacy. Results also show that knowledge was retained four weeks after training. In addition, VR training outperformed health and safety manuals regarding knowledge retention.

This study measures the practical performance to evaluate the effectiveness of the proposed VR training system. Also, this study compares the VR training system with a traditional training method by measuring knowledge acquisition and retention. The results demonstrate the potential of VR as a training tool for excavation safety and hazards.

The versatility of customer relationship management (CRM) systems has kept these technologies popular over the years. These solutions have been integrated into organizations of all sizes, from large corporations to small- and medium-sized enterprises. Similarly, CRM systems have also found applications in all types of industries and business sectors. All this has been the driving force behind the proliferation of CRM solutions around the world. In this chapter, the author not only reflects on the impact and democratization of CRM systems on business management and marketing strategies but also explores how these technologies can determine the company's income. In particular, the author presents an experiment that analyzes the extent to which the volume of annual investment in CRM solutions can be used to predict annual net income in a sample of companies. Using time series analysis and applying the autoregressive integrated moving average modeling technique, the researcher examines a sample of 10 companies from different industries, and countries, over a 20-year period. The results show the efficiency of the predictive models developed in nine of the 10 companies analyzed. The findings of this study allow us to conclude that there seems to be an association between the investments made in CRM solutions and the income of the companies that invest in these technologies.

Quality management barriers have been discovered in construction small- and medium-sized enterprises (SMEs), determining their long-term survival. Despite the recognition of Lean Six Sigma (LSS) as a valuable quality management technique for addressing the barriers faced by SMEs, LSS implementation within the construction SME context is alarmingly low. Therefore, this study aims to investigate the barriers for implementing LSS within construction SMEs and to determine the most effective strategies for overcoming these barriers.

A quantitative research approach was used, and data was collected in two stages: a questionnaire survey with 44 construction professionals and an expert opinion survey with 12 LSS specialists. The collected data was then analysed using the fuzzy TOPSIS method, achieving a higher degree of sensitivity.

The findings revealed the 15 most significant LSS barriers that need to be addressed. In addition, the ten most important strategies to be implemented in overcoming the identified barriers before LSS implementation were discovered and thematised, most notably the hiring of LSS specialists for project monitoring and the formation of a committee for strategic planning through LSS.

Previous research on LSS examined barriers and strategies for SMEs in general, but to the best of the authors’ knowledge, this study is the first of its kind, focusing especially on the construction SME context and involving the unique fuzzy TOPSIS approach.

Dynamic planning and scheduling forms a widely adopted smart strategy for solving real-world problems in diverse business systems. This paper uses deductive content analysis to explore secondary data from previous studies in dynamic planning and scheduling to draw conclusions on its current status, forward action and research needs in construction management.

The authors searched academic databases using planning and scheduling keywords without a periodic setting. This research collected secondary data from the database to draw an objective comparison of categories and conclusions about how the data relates to planning and scheduling to avoid the subjective responses from questionnaires and interviews. Then, applying inclusion and exclusion criteria, we selected one hundred and four articles. Finally, the study used a seven-step deductive content analysis to develop the categorisation matrix and sub-themes for describing the dynamic planning and scheduling categories. The authors used deductive analysis because of the secondary data and categories comparison. Using the event types represented in a quadrant mapping, authors delve into where, when, application and benefits of the classes.

The content analysis showed that all the accounts and descriptions of dynamic planning and scheduling are identifiable in an extensive research database. The content analysis reveals the need for multi-hybrid (4D BIM-Agent based-discrete event-discrete rate-system dynamics) simulation modelling and optimisation method for proffering solutions to scheduling and planning problems, its current status, tools and obstacles.

This research reveals the deductive content analysis talent in construction research. It also draws direction, focuses and raises a question on dynamic planning and scheduling research concerning the five-integrated model, an opportunity for their integration, models combined attributes and insight into its solution viability in construction.

The dispute resolution process in the construction industry is known for delays in settlement, with some cases even escalating to complex arbitration and litigation. To avoid conflicts turning into disputes, the parties need to be proactive in identifying and resolving conflicts in their nascent stages. It is here that innovative lean construction practices can potentially act as a game-changer to avoid disputes, and this study aims to attempt to understand this phenomenon empirically.

A questionnaire-based empirical study, followed by semi-structured interviews, is conducted to understand the relevance of key tenets of lean principles in dispute avoidance.

Although stakeholders agree on the usefulness and practicality of lean principles in dispute avoidance, the extent of agreement is lesser when it comes to its implementation practicality. Moreover, there is a demographic influence observed on lean tenets such as “open communication”, “stakeholder collaboration” and “constraint identification”.

The results point towards an approach that combines contractual mandate, training and awareness creation to iron out the differences in the usefulness and practicality of lean approaches to avoid disputes.

Lean implementation is widely discussed in many construction contexts, such as sustainability, productivity improvement and planning. However, a discussion on lean philosophy’s role in dispute avoidance is muted. Therefore, this study assumes significance.

The chapter explored integrating smart construction techniques in achieving stealth construction objectives, emphasising the development of building cross-sections, visibility management, energy transmission optimisation, and countermeasure implementation. It delved into the multifaceted aspects of smart construction towards achieving stealth construction goals, including environmental protection, enhanced construction safety, accelerated construction duration, cost-effectiveness, and aesthetic considerations. Furthermore, the chapter underscores the importance of leveraging innovative approaches and advanced technologies to meet the evolving demands of stealth construction projects and pave the way for sustainable, safe, and aesthetically pleasing built environments.

Construction projects usually suffer delays, and the causes of these delays and its cost overruns have been widely discussed, the weather being one of the most recurrent. The purpose of this paper is to analyze the influence of climate on standard construction work activities through a case study.

By studying the extent at which some weather variables impede outdoor work from being effectively executed, new maps and tables for planning for delays are presented. In addition, a real case regarding the construction of several bridges in southern Chile is analyzed.

Few studies have thoroughly addressed the influences of major climatic agents on the most common outdoor construction activities. The method detailed here provides a first approximation for construction planners to assess to what extent construction productivity will be influenced by the climate.

Although this study was performed in Chile, the simplified method proposed is entirely transferable to any other country, however, other weather or combinations of weather variables could be needed in other environments or countries.

The implications will help reducing the negative social, economic and environmental outcomes that usually emerge from project delays.

Climatic data were processed using extremely simple calculations to create a series of quantitative maps and tables that would be useful for any construction planner to decide the best moment of the year to start a project and, if possible, where to build it.

This research article proposes a quantitative method for analyzing planning reliability and risk evaluation in construction projects through probabilistic numerical simulation models. The aim is to assess the combined time-based variability of activities across the project and its impact on planning reliability in various production management systems.

The study examines different methods for comparing the impact of production management strategies, specifically standardization and lean construction practices, on project reliability. The article introduces Monte Carlo, importance sampling and first-order-second moment methods as quantitative tools for decision-making and continuous improvement in construction projects.

The utilization of multiple numerical simulation models demonstrates how the variability in activity durations directly affects planning reliability, leading to uncertainty and increased risk in construction projects. The study highlights the significance of lean construction principles and industrialized processes, such as standardization of processes and construction methods, in reducing variability and improving the average duration of activities. Furthermore, it quantifies the differential impact of various production management systems on project performance and planning reliability.

This study is based on a limited number of case studies, which may affect the generalizability of the findings. The results are specific to the construction projects analyzed in Colombia. Expanding the research to include a broader range of projects will improve the applicability of the findings. Developing more comprehensive numerical models can also enhance understanding of planning reliability across different construction management systems.

Currently, there are limited quantitative methods available for project managers to evaluate the impact of industrialized construction practices and production management strategies on planning reliability as well as quantifying the associated risk level in project delays. Consequently, the adoption of innovative construction methods is often limited to a few pilot projects, as managers lack numerical evidence to support the implementation of new methodologies that require changes in traditional operational practices.

A variety of buffer allocation methods exist to distribute an aggregated time buffer among project activities. However, these methods do not pay simultaneous attention to two key attributes of disruptive events that may occur during the construction phase: probability and impact. This paper fills this research gap by developing a buffer allocation method that takes into account the synergistic impact of these two attributes on project activities.

This paper develops a three-step method, calculating the probability that project activities are disrupted in the first step, followed by measuring the potential impact of disruption on project activities, and then proposing a risk-informed buffer allocation index by simultaneously integrating probability and impact outputs from the first two steps.

The proposed method provides more accurate results by sidestepping the shortcomings of conventional fuzzy-based and simulation-based methods that are purely based on expert judgments or historical precedence. Further, the paper provides decision-makers with a buffer allocation method that helps in developing cost-effective buffering and backup strategies by prioritizing project activities and their required resources.

This paper develops a risk-informed buffer allocation method that differs from those already available. The simultaneous pursuit of the probability and impact of disruptions distinguishes our method from conventional buffer allocation methods. Further, this paper intertwines the research domains of complexity science and construction management by performing centrality analysis and incorporating a key attribute of project complexity (i.e. the interconnectedness between project activities) into the process for buffer allocation.