Abstract: This study is intended to examine how Human-AI collaboration-based identity threat appraisals in the form of loss of autonomy and loss of skill, triggers professional identity that fosters cyberloafing. Based on social identity theory, this study applied a three-wave survey design with 507 employees. The proposed research model was tested using partial least squares structural equation modeling (PLS-SEM) with SmartPLS 4, which enabled the assessment of both measurement and structural models Perceived loss of skill and loss of autonomy are positively associated with professional identity threat, which mediates their relationships with cyberloafing. AI-inclusive identity strengthens these associations for loss of autonomy suggesting employees high in AI-inclusive identity exhibit stronger professional identity threat and higher cyberloafing under autonomy loss. This study used self-reported data from a single cultural context, which may limit generalizability. The counterintuitive effect of AI-inclusive identity highlights the need for future research to examine when it serves as a protective versus a risk-enhancing factor. When integrating AI, organizations should mitigate autonomy and skill-erosion appraisals through participatory design, role redesign, and communication that emphasizes unique human contributions. Supporting healthy AI–human identity integration may reduce counterproductive behaviors such as cyberloafing. By positioning identity threat appraisals as Human-AI collaboration–driven antecedents of professional identity threat and cyberloafing, this study extends social identity theory to human–AI contexts. It further demonstrates that over-identification with AI may heighten professional identity threats by diminishing the value of uniquely human contributions.

Abstract: Theoretical background: Occupational burnout remains a key organizational challenge, while the phenomenon of quiet quitting (QQ - conscious limitation of effort to formal requirements) gains significance in contemporary workplaces. However, existing literature lacks frameworks for distinguishing deliberate disengagement from unintentional, apathetic withdrawal. To address this gap, the concept of passive quitting (PQ - apathetic withdrawal from exhaustion and loss of meaning) is introduced and both mechanisms' unique contributions to explaining burnout are examined.Purpose of the article: To determine the impact of quiet quitting and passive quitting phenomena on occupational burnout and empirically assess their unique contributions within a single coherent latent model.Research methods: Cross-sectional CAWI study on a nationwide sample of Polish employees (N = 1040). QQ and PQ were measured using validated scales, burnout was assessed with the OLBI questionnaire. Covariance-based structural equation modeling (CB-SEM) was employed to test hypotheses assuming both phenomena as significant predictors of occupational burnout.Main findings: Passive quitting is a strong and significant predictor of occupational burnout (β = 0.475, p < 0.001), while quiet quitting shows virtually no relationship (β = 0.0012, p > 0.001). The most influential factors were items related to loss of job satisfaction and meaning (PQS6, PQS7), distinguishing apathetic withdrawal from conscious boundary-setting. PQ may serve as a practical early warning indicator, while QQ behaviors alone do not increase burnout risk when PQ is controlled for.

Abstract: This study focuses on the factors influencing the performance of agribusiness MSME clusters in Central Java Province, an area that has not been previously studied. The novelty of this study lies in the use of cluster performance variables and indicators that differ from those in previous studies. This study uses a descriptive analytical method. The research locations were determined purposively, specifically in Pati Regency, Rembang, Demak, Purbalingga, Pekalongan, Sukoharjo, and Magelang City, which have a larger number of agribusiness MSME clusters compared to other regions. The research sample consisted of 251 agribusiness MSMEs, selected proportionally across seven areas. Data analysis used the SEM method with PLS tools. The results of the study indicate that social capital is the factor influencing the performance of agribusiness MSME clusters. Social capital drives the performance of agribusiness MSME clusters. While collective efficiency, social and economic benefits, and MSME performance do not affect the performance of agribusiness MSME clusters. Collective efficiency influences social capital, meaning that collective efficiency drives the development of social capital. Additionally, collective efficiency also influences socioeconomic benefits, indicating that collective efficiency drives socioeconomic benefits. However, collective efficiency does not affect MSME performance. Social capital influences socioeconomic benefits, meaning that it drives these benefits; however, social capital does not directly affect MSME performance. Socioeconomic benefits influence the performance of MSMEs, which means that socioeconomic benefits drive their performance.

Abstract: This study investigates the impact of transactional leadership on organizational commitment through the mediating roles of organizational culture and employee motivation, and moderating effect of role ambiguity and work-life balance on the public universities in Somaliland. The methodology was cross-sectional research design from 278 employees from four public universities located in Somaliland. Data were analyzed using partial least squares structural equation modeling with Smart PLS 4 software. Transactional leadership has a positive effect on organizational commitment, supporting with existing literature and indicating operational efficiency, clear goals and accountability using reward contingencies in high education. Both organizational culture and employee motivation were found to be complementary partial mediation roles on the transactional leadership and organizational commitment relationship, reflecting key mechanisms of the relationship. In contract, role ambiguity and work life balance did not demonstrate a significant moderation effect on the transactional leadership and organizational commitment relationship. This study affirms that transactional leadership is key driver of organizational commitment through mechanisms of organizational culture and employee centered motivation practices. The findings of the study offer practical insights for leveraging leadership perspectives that can foster a committed and engaged workforce in academic settings.

Abstract: This paper discusses motivations in the productive space. Since motivation is an integral part of both organisational and individual productivity, constraints to productivity must be overcome with incentive that inspire and drive people to action. Cognitive fatigue has become a norm in today’s high-paced productivity-driven economy, and so it must be dealt with, in order to overcome constraints to productivity. In this paper, we discuss the role of productive space, and how motivation creates an ambience of productivity that help deal with cognitive constraints which leads to mental fatigue. A philosophical—rather than a pure cognitive or psychological approach has been undertaken to understand the intricate link between productivity, motivation, and cognitive (mental) fatigue.

Abstract: In the global pharmaceutical industry, human resource strategy not only fulfills compliance and risk control functions but also directly impacts talent retention, organizational efficiency, and innovation capabilities. Drawing on the U.S. practices of a multinational biopharmaceutical enterprise, this study examines the key mechanisms of human resource strategy implementation across borders by integrating HR analytics with Hofstede's cross-cultural model. Research methods included a modular HR analytics pipeline built with Python, integrating structural equation modeling (SEM), machine learning classifiers, a Transformer-based cultural encoder, and a job-person matching engine powered by a neural network and Hungarian algorithm. Workflow orchestration was achieved using Apache Airflow, and deployment was managed via Docker with GPU acceleration. Results indicate that leadership models and career development maps significantly enhance employee engagement (β=0.62, p<0.01), reducing overall turnover by 8% within one year. Differentiated compensation structures and flexible benefit policies significantly enhanced employee satisfaction (β=0.55, p<0.01) while strengthening employer brand competitiveness. This study not only validates the effectiveness of localizing multinational corporations' HR strategies but also provides empirical evidence and a methodological framework for cross-cultural HR governance.

Abstract: High-growth enterprises face challenges such as organizational complexity, insufficient talent pipelines, and opaque promotion processes during expansion. This study examines a leading biotechnology company, applying competency model design, 360-degree assessments, and talent inventory tools to explore a data-driven organizational development model. Based on 1,200 employee assessment records and three years of performance evaluation data, the study employed multiple regression and cluster analysis to validate the impact of competency model alignment with promotion pathways on leadership pipeline retention rates. Results demonstrated a 22% increase in high-potential talent retention over three years, with promotion velocity showing a significant positive correlation (R²=0.47, p<0.01) to competency model alignment. Furthermore, by integrating engagement surveys with competitive incentives, the project achieved over 90% employee participation while saving more than 1 million yuan in budget. This research demonstrates that data-driven OD models can significantly enhance organizational efficiency and provide quantitative references for talent strategies in the biotechnology industry.

Abstract: Quiet quitting—meeting formal role requirements while withholding discretionary effort—has sparked a central debate: is it primarily a manifestation of organizational shortcomings or an individual coping strategy? We test these competing accounts using a dual-path structural equation model on cross-sectional data from 600 employees across multiple sectors in Lebanon. The model exhibited acceptable fit (χ²/df = 2.48; CFI = 0.943; RMSEA = 0.059). Results indicate that intrinsic motivation is the strongest negative predictor of quiet quitting, whereas HRM system gaps are associated with quiet quitting primarily through burnout (partial mediation). Direct effects of HRM gaps are weaker but non-trivial, suggesting that quiet quitting reflects both an individual coping response and a reaction to organizational shortcomings. This study provides the first integrated, head-to-head test of HRM system gaps versus intrinsic motivation, extends evidence beyond over-represented contexts through a multi-sector Lebanese sample, and delineates where managerial interventions—bolstering intrinsic motivation and mitigating burnout through support and voice—are likely to yield the greatest marginal returns.

Abstract: This study examines the evolving dynamics of occupational mobility among professionals in Computer Occupations as automation, large language models (LLMs), and autonomous agents transform the labor market. Drawing on data from ONET, the U.S. Bureau of Labor Statistics, and Indeed job postings, the analysis seeks to identify viable transition pathways toward Management Occupations. The assessment of 274 SOC 15 roles and their related occupations within ONET reveals strong associations with managerial positions, which frequently emerge as adjacent and compatible career alternatives. Building upon these findings, the study introduces a novel methodological framework combining Weighted Frequency with Semantic Clustering and a Graph Neural Network (GNN) model, applied to 1,000 job postings per sector to validate and extend the observed relationships. The results demonstrate substantive alignment between senior technical and managerial roles, underpinned by shared competencies such as communication, analytical reasoning, and problem-solving. These findings underscore management as a plausible and strategically advantageous upskilling pathway for experienced technical professionals navigating the AI-driven occupational landscape.

Abstract: Purpose:This conceptual study examines the relationship between Hofstede's cultural dimensions framework and International Human Resource Management (IHRM) practice effectiveness in multinational enterprises (MNEs), addressing the critical implementation gap between cultural theory and IHRM practice.Design/methodology/approach:A systematic literature synthesis analysed peer-reviewed research across cultural dimensions and IHRM domains, integrating findings from Hofstede's cultural research, IHRM integration models, and cross-cultural organisational behaviour studies to develop theoretical propositions and implementation frameworks.Findings:Power distance and individualism/collectivism dimensions most significantly influence HR practice effectiveness, with performance management emerging as the most culturally sensitive function. Cultural dimensions create systematic expectations for organisational practices, requiring adaptive approaches across recruitment, compensation, training, and employee relations. Knowledge-intensive sectors demonstrate higher cultural adaptation requirements than manufacturing or operational industries.Research limitations/implications:The conceptual nature limits empirical validation. Focus on Hofstede’s framework may not capture all cultural variation aspects, and the analysis reflects potential Westernorganisational bias by treating cultural dimensions as relatively static constructs.Practical implications:A five-phase implementation model spanning cultural assessment, strategic design, pilot implementation, full deployment, and continuous evaluation enables systematic cultural adaptation while maintaining organisational coherence across global operations.Originality/value:This study contributes an integrated framework positioning cultural dimensions as moderating variables between HR practices and organisational outcomes, offering novel implementation guidelines for culturally responsive HR practices and identifying specific adaptation requirements across industries and functional areas.

Abstract: This study examines workforce composition trends across artificial intelligence companies, focusing on the balance between technical and non-technical roles. Using a comprehensive dataset of 19 AI companies across six industry segments, we analyze employment patterns, job function distributions, and growth trends from 2023-2025. Our findings reveal a significant shift toward non-technical roles, particularly in sales, operations, and strategic functions, as AI companies mature. Foundation model leaders are increasingly investing in go-to-market capabilities, while enterprise platforms are reinforcing their sales functions. These patterns suggest that as AI technology matures, complementary organizational capabilities become crucial for commercial success. This research contributes to our understanding of industry life cycles in technology sectors and has implications for workforce development, educational institutions, and management strategy.

Abstract: This paper proposes Organizational Emotional Materiality (OEM) framework that specifies how emotions influence organizational value through three distinct pathways: Emotion-Decision pathway, Emotion-Social capital pathway and Emotion-Market signaling pathway. It integrates Affective Events Theory, Social Exchange Theory, Emotion Regulation Theory and organizational capability perspectives to develop five testable propositions that advance understanding of when, how and why emotions become strategically material for organizations. The OEM framework addresses gaps in organizational behavior literature by providing a systematic theoretical model linking micro-level emotional processes to macro-level organizational outcomes, while specifying boundary conditions and measurement considerations for empirical validation. The theoretical contribution lies in reconceptualizing emotions from peripheral organizational factors to measurable strategic resources that systematically influence competitive advantage through identifiable causal mechanisms. The paper offers evidence-based recommendations for embedding emotional awareness into strategic management while acknowledging the risks of dysfunctional emotional manipulation.

Abstract: A lack of effective strategies to improve work-life balance for remote millennial employees is a concern for healthcare leaders. Without such strategies, organizations may struggle to remain competitive and ensure sustainability. Grounded in Homans’s social exchange theory, this qualitative pragmatic inquiry identified and explored the effective strategies healthcare leaders use to improve work-life balance for remote millennial employees to increase productivity. Participants were six leaders of healthcare organizations located in the southeastern United States with at least 2 years of leadership experience managing remote employees. Data were collected through semistructured interviews and analyzed using Braun and Clarke’s six-step thematic analysis. Four key themes were revealed: (a) empowering flexibility through remote and hybrid work models, (b) building a culture of psychological safety and support, (c) investing in employee wellness and digital health tools, and (d) measuring strategy effectiveness through feedback and performance metrics. Key recommendations include adopting hybrid work policies with structured expectations, embedding psychological safety training into leadership development, expanding access to digital wellness resources, and implementing transparent feedback loops to monitor strategy effectiveness. The implications for positive social change include the potential for healthcare leaders to create healthier remote work environments, promote well-being, and enhance the quality of services delivered to the community through a more productive workforce.

Abstract: This study examines the strategic recalibration of human resources leadership across major industry sectors, revealing distinctive patterns of expansion and contraction in senior HR roles. Using data collected from 200 U.S.-based organizations through the GrauntX talent analytics platform, we identify a pronounced divergence in HR leadership investment strategies. Traditional sectors undergoing complex business transformations (banking, healthcare, manufacturing, and professional services) are substantially increasing their HR leadership capabilities, while technology, consumer goods, government, and entertainment sectors are systematically reducing HR leadership positions. Our analysis indicates that these patterns reflect fundamental strategic decisions rather than simple headcount adjustments. Organizations expanding HR leadership typically face complex transformation challenges requiring sophisticated people strategies, while those reducing HR leadership often prioritize operational efficiency, leverage technology, or consolidate administrative functions. These findings contribute to the strategic human resource management literature by demonstrating how organizations calibrate HR leadership capabilities based on their specific business context, transformation needs, and organizational maturity, rather than treating HR as a fixed administrative function. The study offers implications for both theory and practice in understanding the evolving strategic role of HR leadership in organizational effectiveness.

Abstract: As a newly established instrument of EU Cohesion Policy, the Just Transition Fund (JTF) aims to support regions most affected by the transition to climate neutrality. This study examines Baranya County in Hungary, where eligibility was primarily driven by the cement industry. The research investigates the economic and labor market impacts of recent regulatory changes—specifically supplementary mining royalties and CO₂ tax—on stakeholders in the cement and lime sectors. Using survey data from affected production units and industry trend analysis, the findings reveal substantial financial losses among local enterprises, prompting operational restructuring and reduced output. This decline in domestic cement and lime production is expected to cause job losses and the emigration of skilled labor, especially engineers. The anticipated reduction in national production capacity may lead to increased reliance on imports, driving up construction costs. Additionally, financial pressures on domestic producers threaten their competitiveness, potentially resulting in temporary plant closures. These closures are likely to affect the wider regional supply chain, forcing SMEs to downsize or suspend operations. In conclusion, the study highlights a convergence of economic risks, including brain drain and industrial contraction, that undermine the goals of the Just Transition and require targeted policy responses.

Abstract: This paper presents a review and propose framework for training older financial services employees (age 45+) in Generative AI applications. As banks rapidly adopt AI tools, our research identifies specific barriers facing older workers including technological anxiety, interface complexity, and knowledge retention challenges. We conclude that older workers require approximately 30-40% more training time than younger colleagues but achieve comparable proficiency with appropriate support. Key success factors include: (1) peer mentoring systems pairing tech-savvy junior employees with senior staff, (2) simplified interfaces removing unnecessary technical options, and (3) job-specific practice scenarios rather than abstract exercises. This paper further explores the critical need for training older adults in Generative AI (GenAI). While GenAI offers transformative potential across various sectors, ensuring equitable access and its adoption requires addressing the specific challenges faced by older populations. These challenges include digital literacy gaps, concerns about data privacy and security, and the need for user-friendly interfaces especially for older population who might be largely non-technical. The paper examines recent literature and key considerations for developing effective GenAI training programs for older adults, emphasizing the importance of foundational digital skills, accessible language, personalized learning, and ongoing support. Additionally, this study highlights the digital divide faced by older adults, emphasizing the need for structured AI training programs. Furthermore, it analyzes future projections of GenAI's impact, highlighting the necessity of upskilling and reskilling the workforce, including older individuals, to bridge the emerging GenAI skills gap. The paper categorizes and quantifies the types of sources used to support its claims, providing a comprehensive overview of the current state of research and expert opinion on this topic with tables, graphics and charts. By addressing the unique needs of older learners and preparing for the future of GenAI, we can foster digital inclusion and empower all members of society to benefit from this transformative technology. This paper also examines the impact of Generative AI (GenAI) and Agentic AI on the financial services sector, with a specific focus on workforce training and upskilling. Key findings from litreature indicate that by 2027, 80\% of the engineering workforce will require AI-related upskilling (Gartner) and AI-driven automation can reduce manual data tasks by up to 80% (West Monroe). For example, in banking, AI adoption has led to tangible productivity gains, such as Capitec Bank employees saving over one hour per week using AI tools (as suggested by recent reports). The paper categorizes and quantifies recent AI adoption trends, workforce transformation data, and financial efficiency metrics to provide a comprehensive condensed overview of the evolving AI landscape in financial services based on recent reports.

Abstract: In this paper, we have examined the role of motivation, ambition, and inspiration in shaping human productivity. Some people have a passion for action and want to become productive, but fail to do so because they feel demotivated. Motivation is a surge characterised by subjective emotional states that arouse positive feelings and productive instincts. Humanity has repeatedly observed the effects of motivation on human beings, and how motivation coupled with ambitions have shaped the nature of human productivity. These two factors are among the prime determinants of productivity enhancements—the endogenous factors, to say so. Productivity has economic significances and is the foundational basis of the theory of firm. In this paper, we discuss about how motivational states can augment and enhance human efficiency, and shape productivity.

Abstract: This mixed-methods study examines how organizations develop AI-first HR functions by fundamentally reimagining people operations rather than merely adopting new technologies. Drawing on survey data from 152 HR leaders, 24 in-depth interviews, and longitudinal case studies of 8 organizations during 2022-2024, the research identifies three foundational pillars of successful AI-HR integration: augmented capabilities, data-driven culture, and ethical governance. Organizations implementing AI-first approaches demonstrate significant improvements in talent acquisition efficiency (38%), performance management effectiveness (27%), and learning personalization (41%). However, implementation success is hindered by data quality issues (74% of organizations), capability gaps (68%), and employee resistance (61%). Statistical analysis reveals that organizations emphasizing augmentation over automation achieve significantly higher implementation success rates (p < .01), with change management effectiveness emerging as the strongest predictor of successful adoption (β = .42, R² = .53). The resulting evidence-based implementation framework provides practical guidance for organizations navigating this complex transformation, highlighting the critical importance of strategic alignment, process redesign, data architecture, capability development, change management, and ethical governance in realizing the potential of AI-HR integration.

Abstract: To understand the foundations of productive potential, it would be necessary to examine the utilisation of human noetic (intellectual) power to help unleash the latent productive potential inherent within. This intellectual power is the driving force which need be triggered as it is the characteristic ability of the mind—the potentialities within us that can make a difference. The noetic power potential can be whetted by various means which act as triggers. The effect being that, human beings become more productive, and which is a necessity in today’s context to match the productive power of artificial intelligent agents—that are continuously redefining productivity. These AI-based tools can, however, be used to augment our productivity levels, to make us become more efficient, intelligent, and smarter. But we cannot ignore the power of our own innate natural intelligence, which has many things to offer beyond boosting productivity. This paper is the result of such an inquiry.

Abstract: Two fundamentally new approach is presented to the ongoing and heated debate around the predatory division of the open access science publishing. 1. The somewhat relaxed peer-review practices of some Open-Access / Predatory [OA/P] journals have an important, not widely recognized function: it makes possible to disclose novel scientific insights which are automatically censored by the paradigm-oriented or politically manipulated Scholarly / Academic (S/A) publishers. They can be the contemporary “Samizdat” [1] alternative for some original and daring scientists. 2. Much of the critic against OA/P journals is failing even if they are well founded. It can be changed by publicly recognizing each Editorial Board member of every predatory journal as Predatory Editors, i.e. accomplices [2] in the fraudulent, deceptive publishing practices.