This study investigates the factors that lead to smartphone addiction in young adults as well as the negative health effects of this addiction. This study used confirmatory factor analysis (CFA) and structural equation modeling (SEM) to analyze the data from 430 online questionnaires of young adults aged between 15 and 55. The findings show that the association between smartphone addiction and health hazards is significantly mediated by bedtime procrastination, which links excessive usage of the device to negative mental and physical effects. The findings show that impulsivity, depression, gaming addiction, cyber-loafing, and other behavioral and psychological characteristics all play a major role in smartphone addiction, which has an adverse impact on both mental and physical health. Among the participants, 80% were single and 61.1% were female; these groups had greater rates of addiction and related health issues. The results have significant implications for psychiatrists, psychologists, parents, and anyone concerned about smartphone addiction and its associated health risks. The study highlights the crucial role of bedtime procrastination as a mediator in this context. This material will be particularly beneficial for therapists specializing in treating smartphone addiction in both children and adults.

This study aims to investigate the moderating effect of green competencies building (GCB) and green passion (GP) on the relationship between green human resource management (GHRM) and sustainable performance (SP). Moreover, it aims to find out the joint moderating effect of GCB and GP on the relationship between GHRM and SP. An online survey was used to gather 410 samples from various manufacturing organizations in Bangladesh, and the data was analyzed using structural equation modeling (SEM). The study found that GCB and GP separately and jointly moderate the relationship between GHRM and SP. This study uniquely explores how green competencies and green passion, both individually and jointly, moderate the relationship between GHRM and sustainable performance.

This study investigates how Artificial Intelligence Capability (AIC) might drive Sustainable Performance (SP) in businesses. It concentrates on the pivotal roles of Green Human Resource Management (GHRM), Green Supply Chain Management (GSCM), and Green Innovative Work Behavior (GIWB) as mediate that guides the impact of AIC to the results of sustainability. Moreover, the paper will examine the role of Agile Leadership (AL) in enhancing the effect of AIC on GHRM, GSCM, and GIWB by highlighting its role as a key mediator in the AI-sustainability relationship. The research is an empirical study and convenience survey study and has a sample size of 455 representatives of the various types of companies in developing country. The research was carried out through the online survey. The data were analyzed through structural equation modeling (SEM). This study determined that GHRM and GSCM mediate the association between AIC and GIWB to a significant degree. Moreover, we have found that the connection between AIC and SP is rather mediated by GHRM, GSCM, and GIWB. Also, the findings indicated that AL has a significant moderating effect on the association between AIC to GHRM, GSCM, and GIWB. This study gives new insights into the interaction of AI potentials, green HRM, green SCM and green innovative behavior on long-term performance, in which GHRM, GSCM, and GIWB have significant mediating roles. It also demonstrates the way agile leadership manages such interactions, which develops our understanding of AI-based workplace sustainability.