Search Results (1,984)

New nuclear power plant (NPP) designs, particularly advanced reactors and small modular reactors (SMRs), are expected to be highly automated, changing the job demands and shifting the roles and responsibilities of operators. The expanded capabilities of machines and their more prominent role in plant operation means that operators need new information to support effective human–automation teaming and the maintenance of situation awareness. To understand the impact of new automation and artificial intelligence (AI) technology in NPP control rooms, a literature review on function allocation (FA) methods was conducted. This review focused on four areas: (1) Identifying trends in the prevalence of quantitative, qualitative, and mixed methodologies. (2) Developments in levels of automation frameworks. (3) Revisions to the Fitts List. (4) Enabling factors for improved access to data-driven approaches. The review was limited to work occurring after 1983, when the U.S. Nuclear Regulatory Commission published research on FA. The results of the review demonstrate that many of the post-1983 methods are qualitative and descriptive. The review also identified several themes for managing human-out-of-the-loop issues. The discussion closes with proposed future work leveraging large language models and simulator-based approaches to enhance the existing FA methods. Full article

The current study assessed organizational and psychosocial factors related to intentions to quit in American working college undergraduates (N = 382; mean age = 19 years; ~80% female). Students were surveyed on organizational scales (e.g., organizational identification, perceived support, work–life conflict, and intentions to quit) and psychosocial scales (e.g., perceived stress, social support, burnout, and mental health conditions). Variables significantly correlated with intent to quit at the bivariate level were included in an exploratory multiple regression model. The results indicated that burnout, engagement, organizational identification, perceived social support, and life–work conflict were uniquely predictive of intention to quit. A subsequent path analysis based on the Job Demands–Resources model revealed a good fit to the student data: demands (i.e., work–life conflict, perceived stress) and resources (organizational support and identification) predicted burnout and engagement, which in turn predicted intent to quit (along with a direct path from organizational support). This model can therefore explain behavior in both traditional and college undergraduate employees. In order to retain these employees, organizations should invest in practices that increase organizational identification and perceived support, as well as initiatives that help students mitigate the increased risks of stress and burnout associated with working while in college. Full article

The COVID-19 pandemic introduced significant shifts in educational delivery, leading to widespread adoption of hybrid and remote instructional modalities. This study investigates the relationship between these modalities and teacher job satisfaction during the 2020–2021 academic year in the U.S., while also examining how teacher, classroom, and school characteristics predict satisfaction within each modality. Using data from the 2020–2021 National Teacher and Principal Survey (NTPS) on 31,160 full-time public school teachers, linear regression analyses were employed to assess the relationship between instructional modalities and a composite measure of teacher satisfaction, controlling for various teacher, classroom, and school characteristics. The analysis revealed that hybrid teaching was significantly associated with lower teacher satisfaction compared to in-person teaching; however, remote teaching’s initial association with lower satisfaction became non-significant after accounting for school-level factors. Specific teacher characteristics (e.g., female, experienced, younger, holding an advanced degree) and school characteristics (e.g., school level, size, student characteristics) exhibited varying associations with satisfaction across modalities. These findings suggest that hybrid teaching posed unique challenges during the pandemic and highlight the importance of understanding modality-specific risk factors to inform targeted support for teachers in future crises. Full article

Grounded in the Conservation of Resources (COR) theory, this study investigates the impact of workplace bullying on the psychological and physical well-being of Information Technology (IT) professionals in five major metropolitan cities in India (Chennai, Bengaluru, Hyderabad, Pune, and Mumbai). Specifically, it examines how workplace bullying increases psychological distress and how this distress subsequently impairs sleep quality, along with the moderating role of resilience in this relationship. Data were collected from 380 Information Technology employees using a structured online questionnaire through a Stratified simple random sampling technique. The sample consisted of full-time IT professionals across various age groups, job levels, and work arrangements. The hypothesized relationships were tested using Partial Least Squares Structural Equation Modeling (PLS-SEM). Results show that workplace bullying significantly elevates psychological distress and reduces sleep quality. Psychological distress partially mediates the effect of bullying on sleep, while resilience weakens the negative impact of distress on sleep, confirming a conditional mediation model. Theoretically, this study advances COR theory by demonstrating how personal resources such as resilience buffer the loss spirals associated with workplace stressors. Practically, the findings highlight the need for IT organizations to strengthen resilience-building initiatives and implement targeted interventions to reduce bullying and protect employee well-being. Full article

Sick leave is a key indicator of labour market performance and public health, reflecting employee well-being and working conditions while creating a socioeconomic burden. Rates have increased in Europe due to ageing and shrinking workforces, yet research has focused mainly on medical risks, with limited attention to psychosocial factors and subjective well-being. This study analysed the relationship between sick leave, employees’ subjective well-being, self-rated health, and psychosocial work factors. A cross-sectional survey was conducted in Latvia (July–September 2024) among employees in four sectors, public administration, healthcare, pharmaceuticals, and energy, yielding 1628 valid responses (81.6%). Data from online questionnaires (WHO-5, OECD frameworks) were linked to organisational sick leave records. Analyses used descriptive statistics, generalised linear models, bootstrapping, and structural equation modelling. Employees reported an average of 12 sick leave days in 2023, with higher levels among women and healthcare workers. Health problems and work environment risks were positively associated with the likelihood of sick leave, whereas greater job autonomy showed a negative association. Subjective well-being was indirectly related to sick leave through its association with health problems. These findings highlight the multifactorial nature of sick leave and underscore the importance of fostering healthy and supportive psychosocial work environments to promote employee well-being. Full article

With the deep development and iterative upgrading of algorithmic technology, the management practice of platform enterprises using intelligent algorithmic technology has become a hot issue. However, there is little research on the impact of perceived algorithmic control on work engagement from the perspective of platform workers. Drawing upon the regulatory focus theory, this study constructs a “double-edged sword” model to test the impact of perceived algorithmic control on platform workers’ work engagement by focusing on the positive mediating role of promotion-focused job crafting, the negative mediating role of prevention-focused job crafting, and the moderating role of algorithmic literacy. The data collected from 302 platform workers in China were used for an empirical study, and corresponding analyses were carried out to verify the theoretical model constructed by using SPSS and Mplus. The findings indicate the following: (a) perceived algorithmic control positively affects work engagement through promotion-focused job crafting; (b) perceived algorithmic control negatively affects work engagement indirectly through prevention-focused job crafting; (c) the indirect effect of perceived algorithmic control on work engagement via promotion-focused job crafting is stronger when there is a high level of algorithmic literacy and weaker in the case of low algorithmic literacy; and (d) the indirect effect of perceived algorithmic control on work engagement via prevention-focused job crafting is weaker in situations of high algorithmic literacy and stronger in those of low algorithmic literacy. The findings not only enrich theoretical studies on algorithmic control and work engagement but also offer guidance to platform-based enterprises on how to leverage the positive aspects of algorithmic control to better support individuals with different traits. Full article

Ageism remains a pervasive yet under-addressed form of workplace discrimination, affecting employees across age groups. This study, conducted within the framework of the EU-funded project SNAW–Say No to Ageism in the Workplace, presents findings from a cross-national survey in Germany, Romania, Ireland, Portugal, and Greece, with 511 participants including employees and employers. The survey examined five dimensions of workplace ageism (cognitive, emotional, behavioural, institutional, and outcome-related) through questions on stereotypes, experiences, organisational practices, and perceived impacts. Results indicate that age-based stereotypes are widely recognised, especially in Germany, Ireland, and Greece. Older workers were often portrayed as resistant to change or technologically outdated, while younger workers were described as inexperienced or unreliable. Despite some positive perceptions, these ambivalent views contribute to exclusionary dynamics. Employees consistently reported higher levels of ageism than employers, revealing a “perception gap”. Institutional responses were uneven: awareness of policies or initiatives promoting age diversity was low, and their effectiveness remained uncertain. Across countries, respondents linked ageism to reduced job satisfaction and productivity, though the perceived severity varied. The findings highlight ageism as a multifaceted challenge that undermines well-being and organisational performance. Counteracting it requires raising awareness, transparent communication, inclusive policies, and leadership engagement across Europe. Full article

The matter of aligning universities’ curricula with the actual demands of a constantly changing labor market has become an important issue nowadays, due to the prevailing mismatches between acquired skills and competences during education years and the necessities of current jobs. Disequilibria and inequalities in the labor market often generate general disappointment with education degrees. With the pressure of technological advancements and AI integration in many areas of work, future employees’ career paths are challenged even more, and the adaptability of higher education institutions to the real needs of the labor market is questioned. Artificial intelligence (AI) is the technology that allows computer systems and machines to simulate human learning, problem-solving, and decision-making. This paper aims to explore if universities in Romania foster sustainable human capital development through enhancing their educational programs to fit the changes produced by artificial intelligence and how the reskilling of graduates will play a hugely significant role in staying resilient during such disruptions. A quantitative survey was conducted among recent Romanian university graduates to outline their perceptions of curriculum relevance and their level of preparedness for the AI-driven job market. The results highlight gaps between formal education and labor market demands in terms of limited exposure to AI-related skills and a growing need for reskilling to secure suitable jobs for graduates in the long term, while also emphasizing the importance of aligning educational policies with sustainable labor market integration. Full article

Background: Metabolic dysfunction-associated steatotic liver disease (MASLD) is the leading cause of chronic liver disease worldwide. It greatly increases hepatic cirrhosis and cancer, cardiovascular disease, and chronic kidney disease. Despite the rising frequency of MASLD in Saudi Arabia, public understanding of its management is lacking. Objective: This study seeks to evaluate public knowledge, attitudes, and management barriers related to MASLD, thereby informing future educational and preventive strategies. Methods: A cross-sectional study was conducted from November 2023 to October 2024, involving 502 participants across Saudi Arabia, employing a modified self-administered online questionnaire. Data was analyzed using SPSS 25. Descriptive statistics and Chi-square tests were used to investigate correlations between knowledge or attitude levels and demographics, with a significance threshold of p < 0.05. Results: Less than half of the respondents who took part (47.2%) had heard of MASLD. Of them, 24.9% had good knowledge, 38.2% had fair knowledge, and 36.9% had low understanding. There were strong links between knowledge and age, education, and job status, but not between knowledge and gender (p = 0.514). People were somewhat aware that being overweight (48.4%) and having high cholesterol (51.8%) were risk factors, but they often had wrong ideas regarding diabetes and high blood pressure. Only 7.8% of those surveyed said they had been formally diagnosed, and 74.4% of those who had been were given advice on how to change their lifestyle. Barriers to management included the idea that lifestyle change alone suffices (46.7%), the absence of medical advice (46.7%), and insufficient disease awareness (33.3%). Conclusions: The research shows that many Saudis are unaware of MASLD and have misconceptions about it. Targeted health education programs, greater provider–patient communication, and primary care MASLD knowledge are needed to close these gaps and promote disease prevention and management. Full article

Employee retention remains a critical challenge in human resource management (HRM). Embeddedness theory offers a vital framework to understand retention dynamics, yet its development within HRM lacks systematic mapping. This study systematically examines the intellectual evolution, thematic clusters, and emerging trends of embeddedness theory in HRM from 1995 to 2025, addressing three research questions: (1) How has the theory developed over time? (2) What are the key research themes and conceptual structures? (3) Which emerging trends can inform future HRM practice? A bibliometric and science mapping analysis was conducted on 562 peer-reviewed articles from Web of Science using co-citation, co-word clustering, and keyword evolution techniques. Three distinct phases were identified: formative (1995–2005), expansion (2006–2015), and maturation (2016–2025). Findings reveal a dual focus on micro-level constructs, including job satisfaction and turnover intention, and macro-level themes, such as organizational commitment and performance. Recent trends highlight organizational and institutional contexts, cross-cultural perspectives, and post-pandemic dynamics. The study provides the first comprehensive longitudinal mapping of embeddedness theory in HRM, clarifying its intellectual structure, key contributors, and evolving research frontiers. These insights offer actionable guidance for scholars and practitioners, emphasizing the integration of multi-level and contextual factors to enhance employee retention in increasingly complex and globalized work environments. Full article

Despite significant advances in the medical sciences, out-of-pocket (OOP) healthcare costs have remained a concern, especially for lower-middle-class and poor people. The current study aims to investigate the critical factors that notably contribute to catastrophic healthcare expenses (CHCEs). To this end, the ongoing research is conducted through two phases. The first phase aims to identify the key determinants of CHCEs through expert and household evaluations. A multi-criteria decision analysis (MCDA) framework using the FullEX method is developed to analyze expert and household opinions. In the second phase, the experts investigate the hierarchical relationships among key determinants. Interpretive structural modeling (ISM) and MICMAC analysis are carried out to examine the structural relationships among the determinants. The findings of the FullEX analysis reveal that experts and households are in consensus. It is found that low-income level, number of dependable members, frequent birth rate, high child mortality, and lack of job security and risk pooling mechanisms notably contribute to the higher CHCEs. The ISM analysis indicates the strong driving power of income, education, and job security, leading to disparities in rural economic conditions, reflecting the need for holistic development. The MICMAC analysis confirms the hierarchical relationships among the key determinants of CHCEs. The findings necessitate formulating an inclusive strategy to reduce financial distress and improve the healthcare outlook for rural households, leading to sustainable development. Full article

This study examines whether an integrated human-talent system—incorporating recruitment/selection, development, appraisal/feedback, recognition, supportive leadership, and role utilization—is associated with job performance in a public technical organization. Using a quantitative, non-experimental, cross-sectional design, we surveyed 101 employees and constructed composite Likert indices for talent management and job performance. Reliability was acceptable (α = 0.850; α = 0.814). Kolmogorov–Smirnov tests indicated non-normal distributions (p < 0.001); thus, non-parametric procedures were used. Spearman’s correlation showed a moderate, positive association between overall talent management and job performance (ρ = 0.523, p < 0.001), with the “incorporate” process (competency-aligned recruitment/selection) displaying the strongest process-level link (ρ = 0.569, p < 0.001). Segment profiles (contract type, tenure, functional area, and gender) suggest unequal exposure to talent-supportive conditions within the workforce, which may help explain distributional differences in perceived performance. We discuss managerial implications for reducing intra-organizational disparities by ensuring fair access to development, feedback, and recognition systems. While the study does not directly measure well-being, the findings align with theoretical accounts that connect equitable access to talent resources with healthier work environments and better performance. Full article

Background: The COVID-19 pandemic has imposed unprecedented stress on healthcare workers (HCWs), potentially affecting their job satisfaction and life satisfaction. This study aimed to examine the role of perceived stress, self-efficacy, and coping strategies as predictors and mediators of well-being among HCWs during the pandemic. Methods: A total of 326 HCWs participated in the study. Perceived stress was assessed using the Perceived Stress Scale (PSS-10), self-efficacy was assessed with the Generalized Self-Efficacy Scale (GSES), life satisfaction was assessed with the Satisfaction with Life Scale (SWLS), job satisfaction was assessed with the Brief Job Satisfaction Scale (BJSS), and coping strategies were assessed with the Mini-COPE. Correlation, regression, and mediation analyses were conducted. Results: HCWs reported elevated stress levels (M ≈ 24), higher than general population norms. Stress was negatively associated with life satisfaction and job satisfaction. Self-efficacy and adaptive coping strategies (acceptance, social support) were positively associated with life and job satisfaction and mediated the relationship between stress and life satisfaction. Helplessness mediated the effect of stress on life satisfaction but not job satisfaction. Conclusions: High self-efficacy and adaptive coping strategies serve as protective factors for HCWs’ well-being during the COVID-19 pandemic. Interventions enhancing self-efficacy and promoting acceptance and social support may mitigate stress and improve life and job satisfaction. Full article

In the last few decades, Italy has emerged as an important destination for South Asian migrants, particularly from Pakistan, India, Bangladesh, Sri Lanka, and Nepal. While these groups contribute heavily to essential sectors such as agriculture, logistics, care work, and construction, they are often found in insecure, informal, and low-protection jobs. But at the same time, many migrants indicated moderate to high levels of job satisfaction even under such adverse circumstances. This study examines multidimensional job satisfaction among South Asian migrants in Italy and examines the effects of structural and demographic characteristics (region, nationality, sex, household size, and year of arrival) on the outcomes of satisfaction of job dimensions. A three-phase quantitative approach was applied: descriptive analysis to identify satisfaction distributions across five aspects of work; Multiple Correspondence Analysis (MCA) and cluster analysis to identify typologies of satisfaction profiles; and multinomial logistic regression to estimate the likelihood of belonging to low, medium, or high satisfaction categories. The results demonstrate the presence of three different latent clusters of satisfaction; namely, high, moderate, and low, and indicate that regional location and nationality are the best predictors of satisfaction in most areas of the job. Such factors as sex and year of arrival had little impact. Comparing the self-evaluation of migrants with their structural positions, the study provides new empirical data on the problem of the migrant satisfaction paradox and draws more attention to the necessity of policies that can mitigate regional labor market inequalities and improve the general quality of job of migrant workers. Full article

This paper addresses the flexible job-shop scheduling problem with multiple time factors—namely, transportation time and setup time—as well as job priorities (referred to as FJSP-JPC-TST). An optimization model is established with the objective of minimizing the completion time. Considering the characteristics of the FJSP-JPC-TST, we propose an improved whale optimization algorithm that incorporates multiple strategies. First, a two-layer encoding mechanism based on operations and machines is introduced. To prevent illegal solutions, a priority-based encoding repair mechanism is designed, along with an active scheduling decoding method that fully considers multiple time factors and job priorities. Subsequently, a multi-level sub-population optimization strategy, an adaptive inertia weight, and a cross-population differential evolution strategy are implemented to enhance the optimization efficiency of the algorithm. Finally, extensive simulation experiments demonstrate that the proposed algorithm offers significant advantages and exhibits high reliability in effectively solving such scheduling problems. Full article