Search Results (38)

Generative AI (GenAI) adoption in higher education (HE) raises significant ethical concerns. The focus is shifting from rules- or outcomes-based learning environments towards the development of moral character, personality traits, integrity, and practical wisdom (phronesis). However, most existing AI ethics validation instruments are predominantly shaped by Global North paradigms. In Global South HE contexts, in particular, open distance e-learning (ODEL) HE institutions (HEIs) characterised by limited direct supervision and a digital divide, validation remains scant. Ethical risks are intensified by the adoption and integration of GenAI tools, such as large language models (LLMs), to enhance teaching, learning, research, and student support, thus recognising the need to develop and validate virtue ethics scales. The current paper attempts to address this gap by validating the Virtue Ethics Measurement Scale (VEMS) within South Africa’s largest comprehensive ODEL institution. Guided by the positivist paradigm, a 36-item cross-sectional survey of 503 undergraduate and postgraduate students measured six virtue dimensions (justice, honesty, responsibility, care, prudence, and fortitude). Confirmatory factor analysis (CFA) compared four competing models. The single-factor model showed poor fit, rejecting unidimensionality. A second-order hierarchical model demonstrated an acceptable fit (χ²/df = 2.992, CFI = 0.933, RMSEA (Root Mean Square Error of Approximation) = 0.063, SRMR (Standardized Root Mean Squared Residual) = 0.043) with subscale reliabilities ranging from Cronbach’s α = 0.84 to 0.90, supporting a multidimensional yet hierarchical virtue structure. The VEMS offers a psychometrically sound instrument for evaluating ethical AI use in ODEL institutions. This aligns with virtue ethics theory, which emphasises that moral character is a constellation of dispositions (e.g., honesty, care, prudence) rather than a single trait. The VEMS thus enables HEIs to assess students’ virtues, design targeted ethics capacity-development programmes, and inform policy reform for responsible GenAI adoption in under-researched Global South HE settings. Full article

The complex nature of the healthcare work environment, resource strains, and cultural diversity threaten human sustainability and exacerbate healthcare workers’ psychological disconnection from work. From the perspective of sustainable HRM and organizational sustainability, and in response to calls raised by the United Nations 2030 Agenda, our study examines how institutions can support human sustainability and healthy performance through sustainable HRM practices. Therefore, building upon the conservation of resources theory and person–environment fit theory, our study investigates the impact of grit and person–environment fit on work alienation, examining the mediating role of thriving at work, postulating that cultural intelligence moderates the effect of grit and person–environment fit on thriving at work. Data were collected from 335 healthcare workers working in private hospitals in Lebanon and analyzed via structural equation modeling with bootstrapping. The results indicated that grit, person–environment fit, and thriving at work have a significant negative effect on work alienation; meanwhile, grit and person–environment fit have a significant positive effect on thriving at work. Moreover, the results highlighted the mediating role of thriving at work between grit, person–environment fit, and work alienation. Additionally, the findings revealed that cultural intelligence moderates the effect of grit on thriving. However, the interaction between person–environment fit and cultural intelligence was significant in the opposite direction to the hypothesized effect. Theoretically, our research is one of the pioneering studies showing that thriving at work functions as a resource-gain mechanism linking personal resources, such as grit, and contextual resources, such as person–environment fit, to lower alienation. Practically, the findings suggest that management should strengthen person–environment fit, promote thriving, and develop cultural intelligence to enhance healthy performance and human-centered organizational sustainability. Full article

Background: Psychosocial well-being at work is a multidimensional construct associated with employee health, organizational functioning, sustainable workforce development, and population mental health. However, few theoretically integrated instruments simultaneously assess work-related resources, job demands, psychosocial risks, and employee subjective well-being. This study aimed to develop and conduct the initial validation of the Multidimensional Psychosocial Work Environment Scale for Employed Persons (MPWES), grounded in the OECD well-being framework, the WHO-5 conceptual approach, and the Job Demands–Resources model. Methods: Scale development involved theory-driven identification of psychosocial dimensions, item generation, content and face validity assessment, and stepwise psychometric evaluation. Content validity was assessed using the Content Validity Index, and face validity using the Face Validity Index. The hypothesized structure was examined using confirmatory factor analysis. Internal consistency was evaluated using Cronbach’s alpha and McDonald’s omega, while convergent and discriminant validity were assessed using Average Variance Extracted, Composite Reliability, and inter-factor correlations. Results: The proposed measurement model comprised ten dimensions: Subjective Well-Being, Inclusion, Social Support, Workplace Harassment, Work Intensity, Work-related Psychosomatic Strain, Professional Development, Health Risks, Financial Safety, and Autonomy. CFA results provided preliminary and partial support for the proposed ten-factor structure, with borderline-to-acceptable absolute fit indices but limited-to-moderate incremental fit indices. Most dimensions demonstrated acceptable internal consistency; however, convergent and discriminant validity findings should be interpreted cautiously, particularly for dimensions with few items, Financial Safety, and the high correlation between Inclusion and Social Support. Conclusions: The findings provide preliminary empirical support for the MPWES as an initial integrated assessment framework. Further longitudinal, cross-cultural, and independent validation is required. Full article

Person–Environment Fit Theory explains organizational match in beliefs and values influences employee satisfaction and motivation in the workplace. Automated systems [e.g., artificial intelligence (AI)] and advanced technology have been integrated into business operations to compete in the digital era. However, how employee technology orientation and individual differences influence workplace preferences is underexplored. This study advances how organizations can strategically attract talent aligned with their technological infrastructure and work design. Parallel mediation path analysis was conducted on a surveyed U.S. convenience sample (SPSS PROCESS Model 4; N = 912). Technology adaptability was positively associated with preference for a job role highlighting working with automated systems relative to emphasizing supportive coworkers. Technology adaptability related to a greater need to belong and job satisfaction (as parallel mediators) and thereby less preference for a role working with automated systems (i.e., preference for a supportive coworkers job ad). The findings reveal that job ads promoting automated systems do not unilaterally attract tech-adaptive employees. Belonging needs and job satisfaction can function as psychological factors that redirect tech-savvy workers towards socially enriched roles. Proactively advertising social belonging and job satisfaction cues alongside advanced technology use could more comprehensively appeal to tech-adaptive job seekers. This can signal a better value congruence between an organization and these job seekers. Full article

Background/Objectives: Nursing organizational well-being has important implications for nurses, patients, and healthcare organizations. From a nursing-specific perspective, it arises from the balance between nursing demands and nursing resources in the work environment. However, most available instruments are not grounded in explicit nursing theory and do not allow the identification of well-being profiles through person-centered approaches. This study aimed to develop and evaluate the psychometric properties of the Nursing Organizational Well-being Questionnaire (NOW_Q). Methods: Following COSMIN guidelines, a two-phase design was adopted. Phase 1 involved item generation and expert evaluation, resulting in a 28-item instrument rated on a 5-point frequency scale. Phase 2 consisted of a multicenter cross-sectional study. Construct validity was examined through exploratory and confirmatory factor analyses using cross-validation. Reliability was assessed using ordinal omega coefficients, concurrent validity through associations with a global organizational well-being item, and cluster analysis to explore practical utility. Results: Findings (n = 461 nurses; 7 hospitals) supported an eight-dimension structure: workload, emotional demands, work–family conflict, autonomy, available resources, nurse–nurse relationship, nurse–head nurse relationship, and nurse–physician relationship. The confirmatory model showed good fit (RMSEA = 0.051; CFI = 0.938; TLI = 0.927; SRMR = 0.067), and all dimensions demonstrated satisfactory internal consistency (ordinal omega = 0.75–0.87). Significant associations with global organizational well-being were observed. Three distinct profiles emerged (Nurturing, Observed-Detached, and Withstanding), reflecting different configurations of nursing demands and resources. Conclusions: The NOW_Q is a theory-based, nursing-specific instrument with satisfactory psychometric properties and practical utility for identifying organizational well-being profiles and supporting targeted interventions in clinical settings. Full article

Constructing age-friendly residential environments is essential for supporting aging in place among the growing population of urban empty-nest older adults in China. Grounded in person–environment fit theory, this study developed and validated a multidimensional Aging-Suitability Index (ASI) to examine how residential environmental factors shape housing suitability and perceived independence. In this study, “aging suitability” refers to the degree of fit between residential environments and older adults’ needs for safety, functionality, accessibility, social support, and technological support, with the central aim of enabling aging in place and independent living. Questionnaire data were collected from 753 urban empty-nest older adults across 19 provinces in China and analyzed using partial least squares structural equation modeling (PLS-SEM). The structural model showed strong explanatory power (R² = 0.754). The results revealed a clear hierarchy of environmental influences. Safety facilities and physical design were the strongest direct predictors of residential aging suitability, indicating that risk reduction and ergonomically appropriate spatial design constitute the foundation of age-friendly housing. Although accessibility showed a smaller direct effect, it exerted a significant indirect effect through perceived independence, with 67.35% of its total effect mediated through this pathway, highlighting the importance of barrier-free design in maintaining autonomy. Social support and smart technology also contributed positively as complementary resources that strengthened person–environment fit. These findings suggest that age-friendly housing interventions should move beyond fragmented modifications toward integrated residential renewal strategies that prioritize safety and physical design, improve accessibility to support independent living, and combine community support with age-friendly technologies. This study provides empirical evidence to inform built-environment decision-making in the design and renewal of housing for older adults in rapidly aging urban contexts. Full article

The transformation of university libraries into learning commons has highlighted the importance of informal learning spaces (ILSs). However, the mechanisms through which spatial elements influence learning experiences remain underexplored, particularly in western China. Drawing on person-environment fit theory and a multi-coupling framework, this study develops a four-dimensional analytical model comprising spatial layout, facility configuration, environmental quality, and cultural perception. A mixed-methods approach was employed, including 532 valid questionnaires, behavioral observations, and comprehensive environmental measurements (illuminance, noise, CO₂, PM2.5, TVOC, thermal conditions) across three university libraries in Lanzhou, China. Structural equation modeling (SEM) and coupling coordination degree modeling were used for analysis. Spatial layout (β = 0.324, p < 0.001), facility configuration (β = 0.287, p < 0.001), environmental quality (β = 0.196, p < 0.01), and cultural perception (β = 0.158, p < 0.05) all significantly predicted learning satisfaction, jointly explaining 67.3% of the variance. Learning satisfaction partially mediated the relationship between spatial elements and learning outcomes (indirect effect 31.2%). Coupling coordination degrees ranged from 0.578 to 0.634, revealing a “high coupling, low coordination” pattern, with cultural perception as the common shortfall. Environmental measurements showed CO₂ concentrations ranging from 823 to 946 ppm in quiet zones and up to 1085 ppm in lounge areas, correlating negatively with satisfaction (r = –0.41, p < 0.05). Spatial elements influence learning outcomes primarily through satisfaction enhancement. An integrated optimization framework is proposed, offering actionable strategies for ILS design in similar contexts. Full article

Background: Employee voice, as a bottom-up proactive behavior, is crucial for organizational development. However, sustaining employee voice over time remains a shared challenge for both practice and research. Among various influencing factors, supervisor feedback, due to its central role in organizational interactions, serves as a key source of decision-making information affecting employees’ subsequent voice intention. Nevertheless, existing research predominantly focuses on the unidirectional effects of supervisor feedback, often overlooking the bidirectional nature of leader–subordinate interactions. In reality, the effectiveness of supervisor feedback ultimately depends on its congruence with the subordinate’s psychological expectations. Methods: This study integrates person–environment fit theory and role identity theory to investigate how the congruence between subordinates’ expected feedback and supervisors’ actual feedback influences subsequent voice behavior. Through two studies—a scenario-based experiment with 201 participants and a retrospective questionnaire survey with 212 participants—we employed polynomial regression and response surface analysis to examine four feedback congruence patterns. Results: In congruent situations, the “expected positive–actual positive” combination promotes subsequent voice behavior more effectively than the “expected negative–actual negative” combination. In incongruent situations, the “expected negative–actual positive” combination is more effective in promoting subsequent voice than the “expected positive–actual negative” combination. Furthermore, voice role identity mediates the relationship between feedback congruence and subsequent voice behavior, revealing a key psychological mechanism. Implications: This study moves beyond a direct antecedent framework by focusing on the congruence between feedback expectations and reality, thereby deepening the theoretical understanding of the dynamics of voice. By empirically demonstrating how congruent and positive feedback strengthens employees’ internal identity as contributors, it provides practical insights for organizations aiming to foster a sustainable voice climate. Full article

In today’s volatile business environment, securing a sustainable competitive advantage hinges on retaining and effectively managing talent. While talent turnover is inevitable, strategic internal human resource (HR) transfers offer a solution to prevent talent outflow and supplement skill gaps. However, previous models for identifying internal substitutes often focus solely on individual work capabilities, neglecting the critical role of group interactions and collaborative structure. Drawing on social network theory, transactive memory systems, and person–group fit, this study proposes a graph-based analytical approach that models the organization as a complex system. Our methodology provides a holistic framework that integrates both (1) individual capabilities and (2) group-level characteristics (e.g., work-relationship networks and cluster-level similarity) to identify the most suitable substitutes. At the macroscopic level, we use an inductive graph neural network (GraphSAGE) to learn node embeddings from a work relationship network constructed from process event logs and to quantify group-level similarity. At the microscopic level, we compute dynamic collaboration intensity, frequency, and task similarity between employees over time. To validate the approach, we develop four simulation scenarios using an enriched incident management process event log and implement them in a SimPy-based simulator, benchmarking against an existing method that considers only individual factors. Across all scenarios, the proposed dual-factor model significantly outperforms the baseline in terms of efficiency, accuracy, and suitability. This research provides a practical, validated algorithm that supports evidence-based workforce management and more effective internal talent allocation. Full article

Generation Z is becoming a dominant market segment and an essential source of talent in the hospitality industry. Their digital fluency, sustainability expectations, and preference for meaningful and personalized experiences are increasingly reshaping service delivery, marketing strategies, and workforce management in the hotel industry. Following the PRISMA 2020 guideline, this review systematically analyzed 131 peer-reviewed studies published between 2011 and 2025. Performance analysis, science mapping through co-word and Leiden clustering, and trend analysis were conducted using VOSviewer (v1.6.20) and Biblioshiny in RStudio (v2025.09.2). The findings reveal a rapidly expanding but relatively young field, with key themes clustered around technology acceptance (AI, service robots), experiential and sustainable consumption, digital engagement (word-of-mouth, social media), workforce dynamics (person–environment fit, leadership, quiet quitting), and emerging topics such as experiential education, ethics, and self-efficacy. The study highlights the centrality of the Theory of Planned Behavior and technology acceptance models in explaining Gen Z’s decision-making, while also identifying substantial gaps in cross-cultural, ethical, and experiential research. Practical implications call hoteliers to integrate seamless digital services, robust sustainability initiatives, and adaptive talent management system to meet Gen Z’s evolving expectations. Full article

Urban ecosystem services (ESs) are increasingly recognized as critical determinants of residents’ quality of life and well-being. This study develops a data-driven demand–supply matching framework to integrate ES concepts into community-level planning and service performance evaluation. Based on 312 resident surveys across 10 communities in Wuhan, China, we identify the key environmental attributes shaping perceived service quality. A random forest (RF) algorithm is employed to assess the relative importance of environmental features, while a multinomial logit (Mlogit) model quantifies their specific effects. The results highlight that community autonomy, neighborhood relations, environmental awareness, and infrastructure—such as broadband networks and security systems—play pivotal roles in improving service quality. Although provisioning and regulating ESs, such as safety and infrastructure, are relatively well established, cultural services that promote social cohesion and civic participation remain under-supported. These findings uncover the heterogeneity of residents’ environmental expectations and provide actionable insights for incorporating ES-oriented thinking into community planning and fiscal decision-making. By bridging ecological theory with operational urban governance, this study contributes a replicable approach for advancing more inclusive and sustainable community development. Full article

This study investigates the role of career calling in shaping Chinese graduates’ professional match, with a focus on the mediating role of career loyalty and the moderating effect of industry income. Drawing on Conservation of Resources (COR) theory and person–environment (P–E) fit theory, we developed a three-wave, multi-source design with 2025 graduates across diverse industries. The results reveal that career calling significantly enhances professional match, and this relationship is fully mediated by career loyalty. Moreover, industry income strengthens the positive effect of calling, suggesting that external rewards amplify internal motivation in achieving sustainable career outcomes. Theoretically, the study extends calling research into the graduate labor market and integrates contextual economic factors into the COR and P–E fit frameworks. Practically, the findings highlight the importance of cultivating career calling through higher education, organizational practices, and policy initiatives to improve workforce alignment and long-term career sustainability. Full article

Grounded in the person–environment fit theory and an identity-based perspective, this study investigated the relationship between perceived overqualification and knowledge hiding, focusing on the mediating role of future work self-salience and the moderating role of the growth mindset. We suggest that perceived overqualification as a person–job misfit would negatively impact employees’ salient hoped-for work identities, representing a low level of future work self-salience. The diminished salience of a future work self leads employees to hide their knowledge. Furthermore, the growth mindset exacerbates the negative impact of perceived overqualification. We conducted a three-wave survey with 482 employees from knowledge-intensive industries. The results revealed that perceived overqualification boosted knowledge hiding by decreasing employees’ future work self-salience. The growth mindset enhanced the negative relationship between perceived overqualification and future work self-salience. Thus, the indirect effect of perceived overqualification on knowledge hiding via future work self-salience was more significant for those with a stronger growth mindset. Our findings contribute to the literature on person–job fit and knowledge behavior while providing practical insights for managing and guiding talented employees in knowledge management. Full article

Amid the nationwide promotion of fitness and the rapid expansion of China’s sports industry, enhancing spectator satisfaction in sports consumption has become a crucial driver for the industry’s sustainable development. Based on the theory of mind-flow perception, this paper explores the influence of stadium intelligent design on race consumption satisfaction, focusing on the four dimensions of stadium intelligent application perception, personality design perception, digital development perception, and technology integration perception, introduces the mind-flow experience as a mediating variable to construct a theoretical model, and analyzes the questionnaire data of 641 spectators with structural equation modeling. The results show that each perception dimension of intelligent design of stadiums has a significant positive effect on consumer satisfaction. Among them, intelligent applications enhance convenience and interactivity, individual design stimulates emotional resonance and immersion, and digital development and technological convergence optimize the audience’s interactive experience through augmented reality, the Internet of Things, and other technologies. flow experience serves as a key mediator to transform functional attributes into emotional value and immersion experience, significantly enhancing satisfaction. This study contributes theoretical insights and managerial guidance for the integration of AI-driven design, human–technology interaction, and smart construction strategies in modern sports venues. The results have broader implications for enhancing digital user environments and optimizing the infrastructure for next-generation event-based urban development. Full article

Smart classrooms leverage intelligent and mobile technologies to create highly interactive, student-centered environments conducive to personalized learning. However, measuring students’ personalized learning experiences in these technologically advanced spaces remains a challenge. This study addresses the gap by developing and validating a Smart Classroom Environment–Personalized Learning Scale (SCE-PL). Drawing on a comprehensive literature review, content-expert feedback, and iterative item refinement, an initial pool of 48 items was reduced to 39 and subsequently to 34 following item-level analyses. Two datasets were collected from Chinese middle-school students across three provinces, capturing diverse socio-economic contexts and grade levels (7th, 8th, and 9th). EFA on the first dataset (n = 424) revealed a nine-factor structure collectively explaining 78.12% of the total variance. Confirmatory factor analysis (CFA) on the second dataset (n = 584) verified an excellent model fit. Internal consistency indices (Cronbach’s α > 0.87, composite reliability > 0.75) and strong convergent and discriminant validity evidence (based on AVE and inter-factor correlations) further support the scale’s psychometric soundness. The SCE-PL thus offers researchers, policymakers, and practitioners a robust, theory-driven instrument for assessing personalized learning experiences in smart classroom environments, paving the way for data-informed pedagogy, optimized learning spaces, and enhanced technological integration. Full article