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The purpose of this paper is to propose a model for planning and controlling the design process in companies that design, manufacture and assemble prefabricated engineer-to-order (ETO) building systems. This model was devised as an adaptation of the Last Planner® System for ETO multiple-project environments.

Design science research, also known as prescriptive research, was the methodological approach adopted in this research. An empirical study was carried out at the design department of a leading steel fabricator from Brazil, in which the proposed model was implemented in six different design teams.

The main benefits of the proposed model were shielding design work from variability, encouraging collaborative planning, creating opportunities for learning, increasing process transparency, and flexibility according to project status. Two main factors affected the effectiveness of the implementation process commitment and leadership of design managers, and training on design management and project planning and control core concepts and practices.

Some limitations were identified in the implementation process: similarly to some previous studies (Ballard, 2002; Codinhoto and Formoso, 2005), the success of constraint analysis was still limited; some of the metrics produced (e.g. ABI, causes of planning failures) have not been fully used for process improvement; and systematic feedback about project status was not properly implemented and tested.

The main contributions of this study in relation to traditional design planning and control practices are related to the use of two levels of look-ahead planning, the introduction of a decoupling point between conceptual and detail design, the proposition of new metrics for the Last Planner® System, and understanding the potential role of visual management to support planning and control.

The construction industry has considerably evolved in the recent two decades due to the emergence of sustainability, lean construction (LC) and building information modelling (BIM). Despite previous research efforts, there is still a gap concerning the multidimensional nature of their integration. Hence, this study aims to fill the mentioned knowledge gap through exploring and comparing the challenges, enablers, techniques as well as benefits of integrating LC with BIM and sustainability in building construction projects.

A systematic literature review was conducted to fulfill the purpose of this study.

The findings reveal and compare the challenges, enablers, techniques and benefits of integrating LC with BIM and sustainability in building construction projects. The results suggest that there are eight common challenges for integrating LC with BIM and sustainability, including high initial cost, lack of collaboration, lack of professionals and lack of compatible contractual framework. The discovered challenges, enablers, techniques and benefits seem to be mostly routed in people. The findings also suggest that the synergistic benefits of integrating LC with BIM and sustainability can overcome the common challenges (safety, reliability, productivity, collaboration and quality) in construction projects.

The findings contribute to the literature and practice concerning the integration of LC with BIM and sustainability by exploring, comparing and discussing the relevant challenges, enablers, techniques as well as benefits. Moreover, the findings reveal the significance of the development of people in construction industry, besides processes and technology, as people are always subject of activities in construction while processes and technology are always objects.

The coronavirus disease 2019 (COVID-19) pandemic has affected the global economy and, thus, the global construction industry. This paper aims to study the impact of COVID-19 on construction project performance in the United Arab Emirates (UAE).

This study adopted a qualitative and exploratory approach to investigate the impact of COVID-19 and its policies on project performance in the UAE construction industry in critical areas of the project management body of knowledge (e.g. schedule, cost, resources and contracts). Semi-structured interview questions were asked from ten construction professional to obtain valuable insights into the pandemic’s effects on the UAE construction industry and the effectiveness of policies implemented to rectify the damage and identify the industry’s new normal.

The findings indicate that the construction industry faced several challenges such as schedule delays, disrupted cashflows, delayed permits, approvals and inspections, travel restrictions, serious health and safety concerns, material and equipment shortages, among others which hindered the timely delivery of construction projects. It also indicates that efforts made by the government institutions and the construction industry of the UAE such as economic support programs, digitization of processes, fee and fine waivers, health facilities, among other statutory relaxations proved effective in supporting the construction industry against the adverse effects of the pandemic.

The research findings are limited to the literature review and ten semi-structured interviews seeking an expert’s opinion from industry professionals working in the UAE construction industry. The research team did not get access to project documents, contracts and project progress reports which may be required to validate the interview findings, and to perform an in-depth analysis quantifying the impact of COVID 19 on construction projects performance, which is a limitation of this research.

The implication is that, owing to the imposed lockdowns and strict precautionary measures to curb the rapid spread of the pandemic, smooth execution of the construction project across the country was affected. The government institutions and stakeholders of the construction projects introduced and implemented various techniques and solutions which effectively handled the implications of the COVID-19 pandemic on the construction industry of the UAE.

This study has identified the challenges faced by the construction industry of the UAE in the context of the management of project schedule, project cost, construction contracts, health and safety of construction employees and other related aspects of the construction projects. This study also identified the techniques and solutions adopted by various public and private institutions of the country and their implications on construction projects. Therefore, this study provides guidelines for policymakers and future research studies alike.

This paper aims to present a preliminary experimental result on a large-scale experiment on a cyber-physical hybrid discussion support environment in a panel discussion session in an international conference.

In this paper, the authors propose a hybrid (cyber-physical) environment in which people can discuss online and also offline simultaneously. The authors conducted a large-scale experiment in a panel discussion session in an international conference where participants can discuss by using their online discussion support system and by physical communications as usual.

The authors analyzed the obtained date from the following three viewpoints: participants’ cyber-physical attention, keywords cyber-physical linkage and cyber-physical discussion flow. These three viewpoints indicate that the methodology of the authors can be effective to support hybrid large-scale discussions.

Online large-scale discussion has been focused as a new methodology that enable people to discuss, argue and make consensus in terms of political issues, social complex problems (like climate change), city planning and so on. In several cases, the authors found that online discussions are very effective to gather people opinions and discussions so far. Moreover, this paper proposes a hybrid (cyber-physical) environment in which people can discuss online and also offline simultaneously.

The present paper aims to address challenges associated with path planning and obstacle avoidance in mobile robotics. It introduces a pioneering solution called the Bi-directional Adaptive Enhanced A* (BAEA*) algorithm, which uses a new bidirectional search strategy. This approach facilitates simultaneous exploration from both the starting and target nodes and improves the efficiency and effectiveness of the algorithm in navigation environments. By using the heuristic knowledge A*, the algorithm avoids unproductive blind exploration, helps to obtain more efficient data for identifying optimal solutions. The simulation results demonstrate the superior performance of the BAEA* algorithm in achieving rapid convergence towards an optimal action strategy compared to existing methods.

The paper adopts a careful design focusing on the development and evaluation of the BAEA* for mobile robot path planning, based on the reference [18]. The algorithm has remarkable adaptability to dynamically changing environments and ensures robust navigation in the context of environmental changes. Its scale further enhances its applicability in large and complex environments, which means it has flexibility for various practical applications. The rigorous evaluation of our proposed BAEA* algorithm with the Bidirectional adaptive A* (BAA*) algorithm [18] in five different environments demonstrates the superiority of the BAEA* algorithm. The BAEA* algorithm consistently outperforms BAA*, demonstrating its ability to plan shorter and more stable paths and achieve higher success rates in all environments.

The paper adopts a careful design focusing on the development and evaluation of the BAEA* for mobile robot path planning, based on the reference [18]. The algorithm has remarkable adaptability to dynamically changing environments and ensures robust navigation in the context of environmental changes. Its scale further enhances its applicability in large and complex environments, which means it has flexibility for various practical applications. The rigorous evaluation of our proposed BAEA* algorithm with the Bi-directional adaptive A* (BAA*) algorithm [18] in five different environments demonstrates the superiority of the BAEA* algorithm.

The rigorous evaluation of our proposed BAEA* algorithm with the BAA* algorithm [18] in five different environments demonstrates the superiority of the BAEA* algorithm. The BAEA* algorithm consistently outperforms BAA*, demonstrating its ability to plan shorter and more stable paths and achieve higher success rates in all environments.

The originality of this paper lies in the introduction of the bidirectional adaptive enhancing A* algorithm (BAEA*) as a novel solution for path planning for mobile robots. This algorithm is characterized by its unique characteristics that distinguish it from others in this field. First, BAEA* uses a unique bidirectional search strategy, allowing to explore the same path from both the initial node and the target node. This approach significantly improves efficiency by quickly converging to the best paths and using A* heuristic knowledge. In particular, the algorithm shows remarkable capabilities to quickly recognize shorter and more stable paths while ensuring higher success rates, which is an important feature for time-sensitive applications. In addition, BAEA* shows adaptability and robustness in dynamically changing environments, not only avoiding obstacles but also respecting various constraints, ensuring safe path selection. Its scale further increases its versatility by seamlessly applying it to extensive and complex environments, making it a versatile solution for a wide range of practical applications. The rigorous assessment against established algorithms such as BAA* consistently shows the superior performance of BAEA* in planning shorter paths, achieving higher success rates in different environments and cementing its importance in complex and challenging environments. This originality marks BAEA* as a pioneering contribution, increasing the efficiency, adaptability and applicability of mobile robot path planning methods.

This study’s fundamental objective is to assess climate change impact on reference evapotranspiration (ET_o) patterns in Egypt under the latest shared socioeconomic pathways (SSPs) of climate change scenarios. Additionally, the study considered the change in the future solar radiation and actual vapor pressure and predicted them from historical data, as these factors significantly impact changes in the ET_o.

The study utilizes data from the Coupled Model Intercomparison Project Phase 6 (CMIP6) models to analyze reference ET_o. Six models are used, and an ArcGIS tool is created to calculate the monthly average ET_o for historical and future periods. The tool considers changes in actual vapor pressure and solar radiation, which are the primary factors influencing ET_o.

The research reveals that monthly reference ET_o in Egypt follows a distinct pattern, with the highest values concentrated in the southern region during summer and the lowest values in the northern part during winter. This disparity is primarily driven by mean air temperature, which is significantly higher in the southern areas. Looking ahead to the near future (2020–2040), the data shows that Aswan, in the south, continues to have the highest annual ET_o, while Kafr ash Shaykh, in the north, maintains the lowest. This pattern remains consistent in the subsequent period (2040–2060). Additionally, the study identifies variations in ET_o , with the most significant variability occurring in Shamal Sina under the SSP585 scenario and the least variability in Aswan under the SSP370 scenario for the 2020–2040 time frame.

This study’s originality lies in its focused analysis of climate change effects on ET_o, incorporating crucial factors like actual vapor pressure and solar radiation. Its significance becomes evident as it projects ET_o patterns into the near and distant future, providing indispensable insights for long-term planning and tailored adaptation strategies. As a result, this research serves as a valuable resource for policymakers and researchers in need of in-depth, region-specific climate change impact assessments.