Search Results (1,259)

Background/Objectives: Pharmacists play an essential role in healthcare delivery across Europe, yet growing professional demands, organisational constraints, and evolving practice models may negatively affect job satisfaction and professional fulfilment. This study aimed to evaluate job satisfaction and professional perception among pharmacists across multiple European countries and to identify sociodemographic and workplace-related factors associated with these outcomes. Methods: A cross-sectional, web-based survey was conducted between October 2023 and January 2024 among licensed pharmacists from 17 European countries. Eligible participants were pharmacists employed in community pharmacies, hospitals, clinical pharmacy services, or the pharmaceutical industry. The questionnaire, developed and administered in English, collected sociodemographic and professional data and included two composite measures: the Job Satisfaction Scale (12 items) and the Pharmacist Professional Perception Scale (6 items). Responses were recorded using 5-point Likert scales. Descriptive statistics and inferential analyses were performed using SPSS version 27.0. Results: A total of 789 pharmacists participated (median age 40 years; 80.1% female). The mean job satisfaction score was 3.26 (SD 0.88), with the lowest scores related to staffing adequacy and salary, and the highest to collegial relationships. The mean professional perception score was 3.08 (SD 0.81), indicating moderate perceived professional recognition. Significant associations were identified between both scales and workplace setting, income level, employment status, geographical region, education, and professional experience (p < 0.05). Conclusions: In this multi-country convenience sample, pharmacists reported moderate levels of job satisfaction and professional perception, with variation across workplace and sociodemographic factors. These findings should be interpreted cautiously, as the sample is not representative of all European pharmacists; however, they suggest that staffing conditions, remuneration, professional recognition, and career development opportunities may be relevant areas for further investigation and policy attention. Full article

How artificial intelligence (AI) reshapes the internal structure of firm-level skill demand remains largely uncharted. Using approximately 67 million online job postings from two major Chinese recruitment platforms (2019–2024), we construct firm-by-year potential AI exposure via semantic matching between AI patent texts and detailed occupation task descriptions, decompose exposure into displacement and augmentation components based on task routineness, and measure four skill-category demand shares and their within-category importance from job-description text, with identification from within-firm variation under firm and city-by-year fixed effects. Displacement and augmentation exposure exhibit opposing relationships with skill demand: displacement is negatively associated with the routine cognitive share, while augmentation is positively associated with the nonroutine analytical share. Both forms of exposure are associated with a de-coring pattern, a shallower and more dispersed skill portfolio with within-category importance diverging from share movements, concentrated among low entry-threshold, small firms. Reskilling policy should therefore emphasize portfolio breadth and portable competency frameworks rather than deeper single-track specialization, particularly for workers in small, lower-threshold firms. Full article

Background: Sustainability in education requires creating a supportive working environment that promotes the well-being, motivation, and professional development of employees in the education and science sector. From the perspective of sustainable human resource development in the education and science sector, it is essential to identify job resources that are positively associated with work engagement, as emphasized in the Job Demands-Resources (JD-R) model. The aim of this paper is to examine whether three key work organization and job content resources (influence at work, possibilities for development, and meaning of work) predict work engagement among employees in the Lithuanian education and science sector from a sustainability perspective. Methods: Based on the JD-R model, this study applied a quantitative research design. Data were collected through a structured written questionnaire completed by 446 employees in the Lithuanian education and science sector. The relationships between key work organization and job content resources and work engagement were examined using hierarchical multiple regression analysis, with gender, age, and position included as control variables. Results: The hierarchical regression analysis showed that meaning of work and influence at work remained statistically significant positive predictors of work engagement after controlling for gender, age, and position, whereas possibilities for development showed a positive but non-significant tendency in the controlled model. These findings are consistent with the Job Demands-Resources theory and can be interpreted from the perspective of the UNESCO Education for Sustainable Development framework, which emphasizes the importance of empowering teachers, scientists and other employees in the education and science sector, fostering continuous improvement, and connecting their work to a broader educational and societal purpose. Conclusions: The hierarchical regression analysis indicates that meaning of work and influence at work are the most stable predictors of work engagement in the education and science sector from a sustainability perspective. This study contributes to the literature by applying the JD-R model through a sustainability lens in the education and science sector. The results provide new insights into how influence at work, possibilities for development, and meaning of work can be interpreted as sustainability-oriented job resources associated with work engagement in the education and science sector. Full article

Based on the Job Demands–Resources theory, this research investigates how organisational resources shape employee resilience and, in turn, influence work engagement among nurses in the Lithuanian healthcare sector. The paper explores three organisational resources: co-worker support, staffing and recruitment adequacy, and dignified treatment for healthcare employees. Data were collected through a survey (n = 443) from nurses employed in public and private healthcare institutions and analysed using Partial Least Squares Structural Equation Modelling. The results indicate that co-worker support (β = 0.328, p < 0.001) and dignified treatment (β = 0.270, p < 0.001) are significant positive aspects of developing employee resilience, while staffing and recruitment adequacy did not have an impact on employee resilience. Employee resilience demonstrated a strong positive effect on work engagement (β = 0.488, p < 0.001). These findings help to understand the relations and structural antecedents of nurse resilience, demonstrating that social and interpersonal resources have a strong influence on employee engagement. The study has practical implications for healthcare human resource management in contexts of systemic workforce shortage and high occupational demand. Full article

While parenthood is gratifying, it is also a significant life transition, filled with challenges and stressors that require ongoing psychological and behavioral adjustments. This study aims to: (1) verify the psychometric characteristics of the Perceived Corporate Welfare Scale (PCWS), and (2), in line with the Job Demands-Resources (JD-R) theory, investigate how corporate welfare and parenting self-regulation act as resources against perceived stress and quiet quitting. We further explored the mediating role of stress and the moderating effect of parenthood. A group of 788 Italian workers (43.5% non-parents; 29.6% moms; 26.9% dads) participated. The psychometric properties of the PCWS were tested using CFA. A moderated mediation model was estimated using Bootstrap methods (95% CI). The PCWS showed a robust one-factor structure with significant item loadings (>0.60) and satisfactory reliability (CR and AVE). Findings suggest that perceived corporate welfare and parenting self-regulation function as resources and are negatively associated with perceived stress. Perceived stress fully mediates the relationship between perceived corporate welfare and quiet quitting and partially mediates the relationship between parenting self-regulation and quiet quitting. Crucially, parenthood moderates this relationship: fathers’ perceived stress has a stronger association with quiet quitting than mothers’ does. Consequently, the indirect effects are also stronger for fathers. This study provides a validated tool for monitoring perceptions of corporate welfare. The results suggest that personalized interventions and an organizational culture that values parenthood are key to sustaining well-being and long-term employee engagement. Full article

In this study, a special version of the Flexible Job Shop Scheduling Problem with equally and consistently batching constraints (hereafter called ECBFJSP) is considered, which involves multiple aspects of coordination, such as machine selection, process sorting, and batch splitting, which is highly complex and places strict demands on the optimization strategy. To effectively meet this challenge, this study constructs a dual-action deep reinforcement learning algorithm framework based on the Enhanced Heterogeneous Graph Neural Network (EHGNN). First, an enhanced heterogeneous graph and EHGNN model for the ECBFJSP is innovatively proposed. By integrating multi-dimensional node features such as work order priority, machine tool processing capability, and process constraints, dynamic feature aggregation of various types of information is achieved with the help of GATs and GRUs. The model can output context-aware representations containing global resource constraints, greatly improving the joint optimization efficiency of job scheduling and batch partitioning and significantly enhancing the adaptability of the dual-action decision framework to the complexity of the ECBFJSP. At the decision-making mechanism level, this study designed a dual-action decision space of process sequencing–machine selection action and batch partitioning action and used the DAPPO algorithm to collaboratively optimize the dual-action strategy to ensure the stability and efficiency of the decision-making process. The experimental data results show that compared with traditional algorithms, the proposed intelligent decision framework performs better in scheduling quality when solving the ECBFJSP, which fully verifies the significant effectiveness and practicality of the framework in solving the ECBFJSP. Full article

The article reports on the development and validation of an instrument to measure the well-being of public-school principals in Gauteng, South Africa, based on a specific theoretical framework. Adopting a quantitative, post-positivist paradigm, data were gathered from 207 principals selected by means of a census sample from various school types and socioeconomic backgrounds. The instrument included structured questions that evaluated job demands, job resources, and aspects of personal well-being. Exploratory factor analysis confirmed strong construct validity, revealing four contextual factors: support from the school community, support from the department, resource availability, and support from students and parents. Additionally, four dimensions of personal well-being were identified, namely professional, emotional, physical, and work-related well-being. Reliability analysis showed internal consistency across all scales. The findings indicated that principals’ well-being is influenced by the interplay between workplace demands and available resources, aligning with the theoretical principles of the JD–R theory. This study thus offers a reliable, contextually relevant measurement instrument that can be employed for further research, policy development, and leadership support initiatives. By providing an empirically validated instrument tailored to the South African context, it lays a practical foundation for monitoring principal well-being and guiding targeted interventions aimed at enhancing leadership sustainability, organizational effectiveness, and educational improvement. Full article

This paper investigates an energy-efficient single-machine scheduling problem under time-of-use (TOU) electricity tariffs with machine switching decisions. With the increasing importance of demand response programs in industrial systems, electricity cost can be reduced not only by shifting production to low-price periods but also by avoiding unnecessary energy consumption during idle times. To jointly exploit these two mechanisms, a mixed-integer linear programming (MILP) model is developed to integrate job scheduling and machine switching decisions within a unified framework. The model explicitly captures processing energy consumption, idle energy consumption, and switching-related costs under time-varying electricity prices. Computational experiments based on randomly generated instances demonstrate that the proposed model can effectively reduce total energy cost. Comparative results with a two-stage strategy show that the integrated optimization framework consistently achieves lower energy consumption. Sensitivity analysis under different TOU tariff settings further confirms that the performance advantage is influenced by electricity price variations but remains robust across different scenarios. Moreover, the benefit of machine shutdown becomes more pronounced as the scheduling horizon increases. These findings highlight the importance of jointly considering load shifting and machine switching in energy-aware production scheduling and provide practical insights for improving electricity utilization efficiency in industrial systems. Full article

Whether urban park supply effectively responds to residents’ actual use remains a critical issue for public service provision, residents’ health and well-being, and spatial equity in high-density cities. Conventional assessments based on static population data may fail to capture dynamic patterns of human activity, potentially obscuring mismatches between service provision and real demand. This study integrates mobile phone signaling data into a supply–demand assessment framework to evaluate urban park systems from a dynamic population perspective. The framework is applied to Shenzhen as a representative high-density megacity. Park supply is measured by service capacity, coverage, and accessibility, while demand is derived from observed visitation behavior. A Supply–Demand Ratio (SDR) index, combined with Getis-Ord Gi* analysis, is employed to identify spatial patterns of mismatch. The results reveal substantial supply–demand imbalances that are not captured by traditional static indicators, with approximately 30.9% of communities identified as significant cold spots. High-density central areas exhibit a persistent deficit in park services despite relatively high coverage levels, whereas peripheral areas with abundant ecological resources show relative surpluses. These patterns are closely associated with urban functional structure, population mobility, and jobs–housing separation. By uncovering the divergence between nominal accessibility and actual use, this study highlights the limitations of place-based planning approaches and underscores the need for a people-centered perspective. The findings point to the importance of shifting from “opportunity equity” to “outcome equity” in evaluating and improving urban public service provision to foster sustainable urban development. Full article

Background/Objective: This study examines how after-hours service demands (AHSD) are associated with dentists’ overall work experience (OWE) through the mediating role of compassion satisfaction (CS) and the moderating role of perceived organizational support (POS). Grounded in the Job Demands–Resources (JD-R) and Conservation of Resources (COR) theories, the study investigates how job demands, emotional resources, and organizational support jointly relate to dentists’ psychological well-being. Methods: Data were collected from 450 dentists across seven major Libyan cities—Tripoli, Benghazi, Misrata, Sabha, Al Bayda, Zawiya, and Derna—using a structured online questionnaire administered between May and August 2025. Results: Partial least squares structural equation modeling (PLS-SEM) results indicated that AHSD were positively associated with both CS and OWE, suggesting that demanding work conditions may, under certain conditions, coincide with more positive professional experiences when perceived as meaningful and supported. CS partially mediated the AHSD–OWE relationship, highlighting its role as a key emotional resource linked to more favorable work experiences. In addition, POS moderated the relationships between AHSD and CS, and between AHSD and OWE, although the effects were relatively modest, indicating that organizational support may provide incremental support in how dentists experience demanding work conditions rather than fundamentally altering these relationships. The moderated mediation analysis further suggested that the indirect association between AHSD and OWE via CS was stronger at higher levels of POS. Conclusions: Overall, the findings refine JD-R and COR perspectives by indicating that job demands, emotional resources, and organizational support are jointly associated with dentists’ work-related well-being in a high-demand healthcare context. Full article

Although organisational climate is increasingly examined, explicit modelling of demographic interaction effects remains comparatively underrepresented. A search strategy was conducted (25 September 2025), and 358 records were identified and filtered in the Scopus and Covidence databases; subsequently, 60 peer-reviewed articles met the inclusion criteria following PRISMA-guided screening. R-project, reference to VOSviewer, and Biblioshiny were used to perform the bibliometric mapping to demonstrate three (3) large thematic clusters: (1) conceptual models with a focus on the Job Demands–Resources (JD–R) framework; (2) growing cross-sector and post-COVID literature; and (3) small but growing incorporation of interactive demographic variables (age, gender, tenure) other than control-variable treatment. The results show that organisational climate is always placed at the forefront as an important predictor of satisfaction, but intersectional demographic modelling is underdeveloped and geographically biased to Western and Asian factors. Yet improvements have been made in theoretical integration; however, a lack of constructs, methodological conservatism, and geographic skewness limit theoretical cumulation and practical translation. The proposed multi-factor model is conceptually derived from bibliometric patterns and requires empirical validation using CFA, SEM, and multilevel modelling. However, organisations should integrate satisfaction policies that reflect diverse demographic and contextual realities, rather than adopting a general approach. The study advances the model of employee satisfaction research by offering practical evidence and a theoretical framework to support the sustainability of industrial and organisational psychology. Full article

Background: Job satisfaction remains a persistent concern in care facilities, where frontline caregivers work in highly relational and emotionally demanding environments. Although both personality traits and psychological safety have been associated with job satisfaction, their relative contributions and potential interrelationships in routine care settings remain unclear. Methods: Drawing on organizational and psychological theory, we hypothesized a priori that personality traits, psychological safety, and job satisfaction would be statistically associated, with psychological safety mediating the relationship between personality traits and job satisfaction. A cross-sectional questionnaire survey was conducted in care facilities, and the final analytical sample consisted of 183 frontline caregivers selected according to predefined inclusion criteria. Structural equation modeling (SEM) was used to test the hypothesized mediation model. Group comparison analyses examined differences in psychological safety across levels of job satisfaction. In addition, machine learning models were applied to explore predictive patterns among personality traits, psychological safety, and job satisfaction. Results: In the SEM analyses, psychological safety was significantly associated with job satisfaction ($\beta$ = 0.207, p < 0.05), although the effect size was modest. Personality traits did not show direct associations with job satisfaction. Instead, agreeableness ($\beta$ = 0.232, p < 0.01) and neuroticism ($\beta$ = −0.235, p < 0.01) were associated with psychological safety, which, in turn, was related to job satisfaction. Bootstrap resampling supported the presence of significant indirect associations. At the item level, communication-related aspects of psychological safety were particularly salient. Caregivers with different levels of job satisfaction differed most clearly in communication-related items. Consistent with this pattern, exploratory machine learning analyses (XGBoost) also identified psychological safety as a more important predictor of job satisfaction than personality traits. Conclusions: These findings suggest that, among frontline caregivers working in healthcare facilities, psychological safety was more closely associated with job satisfaction than individual personality traits. In particular, the ability to speak openly and raise concerns was more strongly associated with higher levels of job satisfaction within this care context. Personality traits were associated with job satisfaction primarily through their relationship with psychological safety rather than through direct associations. Full article

Organizations today face growing pressure from both digital transformation and sustainability. This creates challenges in aligning human resource practices with the skills and engagement of employees. While these two areas are often studied separately, less attention has been given to how sustainability-oriented HR practices function in digitally transforming organizations. This study examines the relationships among Sustainable Human Resource Management (SHRM) practices, green training, green skills, digital readiness, and employee engagement across organizations in North Macedonia. Drawing on the Job Demands—Resources framework, the study focuses on how organizational practices and employee competencies are associated within contexts shaped by both technological and environmental change. Using survey data from 152 employees representing 152 organizations, the findings indicate that SHRM practices are positively associated with green training and green skills. More importantly, green training emerges as a key mechanism linking SHRM practices with employee competencies, suggesting that sustainability-oriented HR systems are most closely associated with employee capabilities when supported by structured development processes. Green skills are positively associated with employee engagement, and this relationship appears stronger in organizations characterized by higher levels of digital readiness. These findings highlight the importance of training and digital context in shaping employee outcomes. The study contributes to the literature by integrating sustainability, HRM, and digital transformation perspectives, and by emphasizing the role of developmental mechanisms in linking organizational practices with employee outcomes. Full article

The Spanish tourism sector is experiencing an unprecedented boom. However, this macroeconomic success coexists with a growing crisis of burnout and job insecurity. While the macroeconomic effects of minimum wage policies are widely debated, the micro-level psychosocial reality of employees operating within these cost-pressured environments remains largely unexplored. This research uses the Job Demands–Resources (JD-R) framework to descriptively explore the current state of employee well-being in the Spanish hotel sector, operating within the macroeconomic context of recent minimum wage increases. Specifically, the study evaluates how environments characterized by high cost-containment pressures are associated with exacerbated labour demands and depleted resources, a pattern consistent with burnout, thus analysing the implications for social sustainability. Our data come from a survey of 384 hotel employees in Spain and were analysed using the Labour Demands–Resources (JD-R) framework and bootstrap methods. The results reveal that employees report very low agreement that their workloads are reasonable and manageable (mean = 1.8/5) and perceive limited development opportunities (mean = 1.9/5), despite acknowledging the importance of well-being for sustainability (mean = 4.8/5). Work intensification is particularly acute in regions with high seasonality and among cleaning staff. Furthermore, sustainability awareness moderates the negative impact of workload on employee engagement. The study concludes that within high-pressure hospitality environments, macroeconomic wage improvements can be offset by a decline in job quality, threatening the long-term social sustainability of the sector. We advocate for more nuanced policies and a shift in human resource management strategy toward genuine investment in human capital. Full article

Work–life balance (WLB) has become a critical component of social sustainability, yet empirical evidence remains uneven across economic sectors. While existing research predominantly focuses on service-oriented and public-sector occupations, comparatively little is known about the determinants of WLB in manufacturing, where high job demands, limited flexibility, and structural constraints on autonomy often characterize work. Addressing this gap, the present study examines how job characteristics, support mechanisms, and individual resources shape the likelihood of achieving WLB among manufacturing employees in a rapidly developing European economy. Drawing on the Job Demands–Resources (JD–R) framework, the study employs survey data from 361 manufacturing employees and estimates a series of Probit regression models. To facilitate a meaningful analysis, composite indices were constructed to capture job demands, job flexibility, organizational and social support, psychological boundaries, and overall well-being. Predicted probabilities were used to evaluate both direct effects and interaction patterns in the Probit models. The findings indicate that manageable job demands and individual resources, particularly well-being and effective self-management, are the strongest predictors of WLB. Job flexibility demonstrates a slight positive effect; however, when accounting for individual and structural factors, formal organizational and social support mechanisms do not show statistically significant direct effects. Furthermore, our analysis provides no empirical support for moderating effects, as the interaction terms between job characteristics and support variables are not statistically significant. This suggests that support mechanisms do not consistently modify the relationship between job demands, flexibility, and WLB within the analyzed sample. Overall, the findings underscore the importance of combining supportive organizational contexts with manageable work demands and individual resources to promote sustainable work–life balance in manufacturing. The study contributes sector-specific empirical evidence to sustainability research and offers practical insights for designing socially sustainable work environments in industrial settings. Full article