Developing a WELL building model for office environments.

Many reported cases of occupants in modern office buildings suffer from severe health risks, negative impacts on well-being, and productivity loss. Existing building standards often prioritize energy performance and green environments over human sustainability. Moreover, office buildings have a distinct group of occupants that require extra attention. Hence, the study aims to develop a WELL building model specifically for office buildings to support occupants' well-being, health, and productivity (i.e., WELL). To achieve that objective, this study developed a list of physical indoor building features through a systematic literature review and semi-structured interviews. Then, the features were inserted into a survey and sent to office building occupants and built environment professionals. The collected data was analyzed using the analytic hierarchy process (AHP) and confirmatory factor analysis (CFA). The findings suggest twelve new features applicable for supporting WELL in office buildings: workspace privacy, sufficient space, office layout, cleanliness, efficiency in building services, individual control, building automation system, Information Technology (IT) infrastructure, Wireless Fidelity (WiFi) risk, security system, safety at parking lots, and safe design. Also, three new concepts for supporting WELL in office buildings were established: office space, building services and maintenance, and smart systems. The new concepts and features lay a foundation for designing office buildings that comprehensively target occupants' WELL. Finally, this study is unique as it accentuates the development of a WELL building model specifically for office buildings.

Construction 4.0 technology evaluation using fuzzy TOPSIS: comparison between sustainability and resiliency, well-being, productivity, safety, and integrity.

This study aims to compare the impact of Construction 4.0 technologies on different organizational core values, focusing on sustainability and resiliency, well-being, productivity, safety, and integrity. To achieve that aim, the study objectives are the following: (i) identify the critical Construction 4.0 technologies between core values; (ii) appraise overlapping critical Construction 4.0 technologies between core values; (iii) examine the ranking performance of Construction 4.0 technologies between core values; and (iv) analyze the interrelationships between Construction 4.0 technologies and core values. First, twelve Construction 4.0 technologies were identified from a national strategic plan. Then, the fuzzy technique for order of preference by similarity to ideal solution (TOPSIS) that incorporates subjective and objective weights was used to evaluate the impact of the Construction 4.0 technologies on the five core values. Finally, the collected data was analyzed using the following techniques: fuzzy TOPSIS, normalization, overlap analysis, agreement analysis, sensitivity analysis, ranking comparison, and Spearman correlation. The study findings reveal four critical Construction 4.0 technologies that enhance all five core values: building information modeling (BIM), Internet of Things (IoT), big data and predictive analytics, and autonomous construction. Also, there is a high agreement on the Construction 4.0 technologies that enhance well-being and productivity. Lastly, artificial intelligence (AI) has the highest number of very strong relationships among the core values. The originality of this paper lies in its comprehensive comparison of the impact of Construction 4.0 technologies on multiple organizational core values. The study findings provide valuable insights in making strategic decisions in adopting Construction 4.0 technologies.

Modeling COVID-19 Impacts and Response Strategies in the Construction Industry: PLS-SEM Approach.

Policymakers are developing response strategies to reduce the impacts of COVID-19. However, developing response strategies without considering their relationships with the impacts of COVID-19 is ineffective. This study aims to model the causal relationships between COVID-19 impacts and response strategies in the construction industry, using Malaysia as a case study. To achieve this, a systematic literature review and semi-structured interviews with forty industry professionals were conducted, yielding 12 impacts and 22 response strategies. The impacts and strategies were inserted into a survey, and 107 valid responses were received. Exploratory factor analysis (EFA) was conducted to group the impacts and strategies. Then, partial least-squares structural equation modeling (PLS-SEM) was employed to identify the causal relationship between the impacts and strategies. The EFA results indicate that the underlying impacts are project- or material-related, and the underlying strategies are market stability and financial aid, supply chain and project support, and information and legislation. The PLS-SEM results indicate that supply chain and project support are required to address material-related impacts, and market stability and financial aid are required to address project-related impacts. This is the first paper that models the relationships between COVID-19 impacts and response strategies in the construction industry.