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This study aims to explore the “psychological contract of safety” (PCS), a key factor in the safety climate (SC), which relies on the behavioral safety actions of workers at construction sites. While numerous factors have been identified in various sectors across different countries, there is a consensus among researchers that there is a dearth of common assessment factors specifically for the Indian construction industry (ICI). Therefore, this study undertakes a systematic review of existing literature to identify the factors that determine PCS in construction and to ascertain the relative importance index (RII) of these variables and their interrelationships using structural equation modelling (SEM).

A structured survey was conducted among 420 professionals in the ICI to collect data. This data was then analyzed using descriptive and inferential statistical methods to derive results.

The findings of the study indicate that PCS factors have a significant impact on the construction industry (CI). The inferential analysis ranks “Safety System” as the top factor with the highest RII value. The chi-square results highlight two key SC factors that enhance and regulate an organization’s safety performance. The SEM results reveal that SC factors contribute to the improvement of PCS and influence worker safety behavior.

The outcomes of this study will be beneficial for stakeholders aiming to improve safety at construction sites and enhance safety performance by fulfilling the mutual safety obligations of employers and employees and by improving safety norms, procedures and policy-making. This paper also provides a theoretical framework for scholars to reassess the results in various contexts.

Set in the construction industry, this study aims to better understand managers’ work–family conflict (WFC) and their challenges regarding work–family (WF) issues, and to compare site workers’ and managers’ perceptions of work–family balance (WFB) practices in this male-dominated industry.

Using a mixed-method participatory design (qual-QUAN), this study was conducted in Quebec’s (Canada’s) construction industry. Semi-structured interviews with managers (n = 17) and workers (n = 20) were conducted, along with a survey of managers (n = 692) and workers (n = 789).

Triangulation of results shows that managers have significantly higher levels of WFC than workers and that the factors contributing to their WFC are similar (e.g. heavy workload, unsupportive organizational culture). The results suggest a discrepancy between workers’ and managers’ perceptions. While managers report offering a wide variety of WF measures, many of which stem from collective agreements, workers report little use of those measures.

Results highlight the contrast between availability and accessibility of WF measures in the construction industry and question both managers’ and workers’ possible lack of awareness of WFB measures and practices.

These results contribute to the literature by characterizing issues managers themselves face in the construction industry. The study also discusses managers’ support of workers in the context of their own organizational, interpersonal and individual constraints. Finally, this study contributes by paralleling data from managers and workers in the industry regarding WFB measures and policies.

This study aims to investigate the interrelationship between critical design criteria (CDC) that affect health, well-being and productivity (i.e. WELL) for residential buildings in developing countries, using Malaysia as a case study. To achieve the aim, the objectives are to identify CDC that affect WELL collectively; determine CDC that affect health, well-being, and productivity simultaneously; and analyze the interrelationship between the CDC.

Data from the semi-structured interviews and a systematic review of the existing literature were gathered for survey development. Next, survey data was collected from 114 professionals living in multistory buildings. Finally, normalized mean analysis, analytic hierarchy process (AHP), agreement analysis and Spearman correlation analysis were used to analyze the collected data.

Out of the 51 potential design criteria, 16 are critically affecting WELL collectively. Furthermore, six are critically affecting WELL collectively as well as health, well-being and productivity simultaneously: property price, water flow and supply, water treatment, pest management, management services and waste management. Finally, “water treatment” is highly correlated to “water management” and “water flow and supply.” In addition, “waste management” and “management services,” as well as “fire safety” and “emergency evacuation plans,” are highly correlated.

This study's originality includes investigating the CDC of residential buildings for the first time, to the best of the authors’ knowledge, in a developing country. As a result, this study uncovers holistic design criteria for policymakers to establish holistic building assessment tools for residential buildings.

The emergence of artificial intelligence (AI) which operates through technology and digital workspace has proven to transform organisations in recent times. However, there has been key concern over its efficiency among the workforce on how it may replace human intelligence in the contemporary work environment. This study aims to investigate the drawbacks otherwise known as the dark side of AI and its effect on employee quality of work−life and organisational performance through the lens of employee capacity development in reducing its shortcomings.

This study used a descriptive research design using a cross-sectional survey approach to administer the research instrument to 1,847 customer service officers of banks, customer agents of telecoms, customer care of retail organisations in Nigeria business environment across various units were respondents of this study, however, 862 participants were finally used. A simple random strategy was used to survey the study participants, and existing scales were adopted to form a new research instrument. A partial least square (PLS) based structural equation model (SEM) was adapted to analyse the collected data from the respondents.

The outcome of the study indicated that AI lacks creativity and has a negative impact on both employee quality of work−life and overall organisational performance. The outcome of the study demonstrated the drawbacks and the dark sides of AI as lack of emotional intelligence, lack of in-depth contextual knowledge, over-reliance on data quality and lack of ethical and moral decision analysis are the possible dark side of AI which adversely affect quality of work−life and overall performance of the organisations. The study concluded that it is difficult to replace human intelligence because of AI’s drawbacks and dark side. AI cannot function effectively beyond what is programmed in the system.

This study has offered a novel trajectory against the efficiency and possible benefits of AI that people are familiar with. It has changed the understanding of the researchers, policymakers and organisations that AI cannot replace human intelligence in the workplace without improvement on those established AI dark sides.