Abstract: Employee well-being has become a central concern in organizational research due to its strong implications for performance, job satisfaction, and organizational sustainability (Bakker & Demerouti, 2007; Schaufeli & Taris, 2014). In high-pressure sectors such as banking and microfinance, managers operate under strict regulatory requirements, demanding performance targets, and continuous monitoring, which may significantly affect their psychological well-being (Giorgi et al., 2017; Lee & Kim, 2023). Managerial well-being is particularly important because managers are responsible not only for achieving organizational objectives but also for supervising employees and maintaining operational stability. These challenges are especially relevant in emerging financial systems such as Albania’s, where the financial sector is largely lending-oriented and dominated by commercial banks, with microfinance institutions playing a complementary role in expanding access to finance (Bank of Albania, 2025; World Bank, 2020). Managers in these institutions face pressures related to regulatory compliance, performance expectations, and the responsibility of supporting credit access for households and SMEs. This study investigates the determinants of managers’ well-being in Albanian lending institutions using the Job Demands–Resources (JD-R) model (Bakker & Demerouti, 2007). It examines how job demands (e.g., workload, performance pressure), job resources (e.g., organizational support, autonomy), and work–family conflict influence managerial well-being. The study also explores whether significant differences in well-being exist across demographic characteristics such as gender, age, type of institution, position, years of service, and number of supervised employees.

Abstract: Application Tracking Systems (ATS) have evolved significantly since their inception in 1996, transitioning from simple resumé repositories to AI-driven tools with advanced capabilities. Although these innovations have improved recruitment efficiency, they have also introduced significant ethical and Human Rights challenges. Bias in machine learning (ML) training data and over reliance on algorithmic decision making have led to violations of Human dignity, equality, privacy, and other fundamental rights. This study examines these challenges and proposes a Human-centered approach to recruitment processes that integrates ATS with ethical safeguards. The proposed methodology involves the development of a Humanization application service to mitigate bias and enhance Human oversight. Key features include validating job vacancy requirements, identifying and addressing bias triggers in recruitment algorithms, and requiring digital signatures from qualified professionals to approve job postings, ensuring that there are humans that assume responsibility. By incorporating generative AI and blockchain, this system facilitates compliance, transparency, and fairness in recruitment, thereby addressing the ethical concerns of algorithmic hiring. Crucially, this study demonstrates that organizations can achieve meaningful Humanization of their recruitment processes, including the mitigation of bias and provision of personalized feedback (among many other potential steps) through targeted interventions that require surprisingly modest financial investment, time commitment, and computational resources. This study underscores the importance of combining technological advancements with ethical considerations to create equitable recruitment processes in an accessible and resource-efficient manner.

Abstract: The shift to remote and hybrid work has exposed the limitations of traditional performance management systems, which often rely on physical presence or intrusive surveillance rather than outcome-based evaluation. This paper asks how AI-driven performance management can be designed to address the documented challenges of teleworking while safeguarding employee autonomy, fairness, and well-being. The study integrates a comprehensive literature review on AI capabilities with empirical evidence from a sequential mixed-methods study of Canadian public servants, comprising machine learning analysis of over 205,000 tweets, document analysis of federal and provincial teleworking policies, a survey of 176 public servants analyzed using logistic regression, and semi-structured interviews with Government of Canada employees. Grounded in socio-technical theory and the Theory of Planned Behavior, the findings reveal that organizational support, workplace socialization, and attitudes are stronger predictors of teleworking success than digital skills or monitoring, while isolation functions as a measurable risk factor. These empirical patterns are mapped to specific AI capabilities to produce a socio-technical framework organized around three interdependent layers: technological, organizational, and human-centered. The paper contributes an empirically grounded alternative to purely speculative treatments of AI in performance management, offering design requirements derived from what remote workers actually experience rather than from technological possibilities alone.

Abstract: The study aimed to identify employee profiles reflecting combinations of quiet quitting, passive quitting, and work engagement. Using a person-centred approach and unsupervised learning, survey data from 1,040 employees were analysed. Clustering relied on composite indices derived from abbreviated quiet and passive quitting scales and the Utrecht Work Engagement Scale-9 (UWES-9). Multiple algorithms (k-means, hierarchical clustering, spectral clustering, Gaussian mixture models) were compared, and the optimal solution was selected using separation metrics (Silhouette coefficient, Davies–Bouldin index, Calinski–Harabasz index), information criteria (Bayesian Information Criterion [BIC], Akaike Information Criterion [AIC]), and bootstrap stability (Adjusted Rand Index [ARI]). Four distinct employee profiles emerged, differing in boundaries, exhaustion, and energy. Findings suggest quiet quitting and passive quitting are related but distinct withdrawal mechanisms. The study advances profile-based research on employee withdrawal and highlights implications for targeted human resources (HR) interventions.

Abstract: The article explains the narcissism leadership paradox in the existing organizations in relation to the rhetoric of ethics used strategically to legitimize the use of control. The loss of trust in leaders and in employees are both practiced in the sense that leaders manifest the disjunction between organizational discourses and reality by instantiating values in superficial ways in what they say and in real ways in what they do. The study relies on three guiding questions: (1) How do narcissistic leaders legitimize themselves by thinking that they are right in the moral sense? (2) What are a few of the stressors related to employees where ethics and practice collide? (3) Does dissonance cause organizational cynicism? Semi-structured interviews with 24 employees working in Higher Education Institutes were used to collect qualitative data to answer the following questions: The similar patterns and their comparison across cases were determined by coding and performing thematic analysis in computer through excel. The outcomes show 3 broad themes. First, the Virtue Costume demonstrates that both virtues signaling and moral language are being offered to fulfill personal interest and acquire power. Second, Branding the Self as the Company causes us to concentrate on how egoistic leaders project their own image as the identity and values of the company. Third, the Contagion of Cynicism explains how employees who become disillusioned, cynical and detached respond when they feel hypocrisy in the words and actions of their leaders. The paper associate’s impression management and moral justification of narcissist leaders with falling trust and calls on authentic leadership and open cultural supervision to restrain cynicism and provide theoretical and practical organizational knowledge. This study’s implications build on the dark triad perspective advanced by Alowais and Suliman, which demonstrated that Leader Dark Triad (LDT) traits can cascade into Employee Dark Triad (EDT) behaviors within organizational settings. Extending this logic, the present study shows that narcissistic leaders’ ethical rhetoric can similarly shape organizational climates in ways that reinforce manipulative dynamics, highlighting how seemingly ethical leadership signals may mask deeper patterns of influence and behavioral contagion.

Abstract: This study examines predictors of workplace adoption of artificial intelligence (AI) in a Norwegian employee sample (N = 196). Hierarchical logistic regression tested whether education, sector, sex, age, leadership, strengths-based leadership (SBL), training, and engagement predicted AI use. Education was the strongest predictor. Employees with a bachelor’s degree were 3.64 times, and those with a master’s degree more than 11.15 times, more likely to use AI than those with secondary education. Knowledge-intensive sector employees were 2.52 times more likely to adopt AI than those in skills-focused sectors. Men were 2.94 times more likely than women to use AI. Neither age nor leadership role showed significant effects. SBL independently predicted adoption (OR = 1.89). Training and engagement were unrelated to adoption. Overall, findings show that structural, sociodemographic, and organizational factors shape AI adoption, underscoring the need for targeted strategies to ensure equitable, effective uptake across the workforce.

Abstract: Organizations increasingly confront persistent tensions that require leaders to pursue competing demands simultaneously. Although prior research highlights paradox mindset as an orientation toward embracing tensions, less is known about the capability-based microfoundations that enable leaders to enact paradoxical leadership behaviors in practice. Addressing this gap, this study develops a cognitive–emotional capability framework that focuses on two developable resources: integrative complexity (IC)—a cognitive capacity for differentiating and integrating competing demands—and emotion regulation (ER)—an affective capacity for sustaining engagement under tension. Using survey data from 264 Japanese managers, we examine the independent and joint effects of IC and ER strategies on paradoxical leader behaviors (PLB). Results show that IC and cognitive reappraisal are positively associated with PLB. Polynomial regression and response surface analyses further reveal that PLB increases as IC and cognitive reappraisal rise together. However, when the two capabilities are imbalanced, PLB tends to be higher in profiles where IC exceeds reappraisal than in the opposite configuration.These findings suggest an asymmetric form of complementarity in which integrative complexity functions as a foundational capability while reappraisal provides supportive leverage. Overall, the study shifts attention from trait-like mindsets to trainable leadership capabilities and clarifies how cognitive–emotional capability configurations enable the enactment of paradoxical leadership.

Abstract: In volatile environments, work teams operate as complex adaptive systems that reconfigure internal processes in response to internal and external tensions. Team adaptability—a systemic outcome—is influenced by paradoxical leadership (PL), but the motivational pathways translating PL into adaptive behavior remain underexplored. Grounded in Conservation of Resources theory, this multi‑wave, supervisor–subordinate dyadic study of 114 high‑tech teams adopts a systems perspective and treats goal orientations as collective resource‑allocation rules. PL most strongly fosters systemic adaptability by cultivating a team performance‑approach orientation—an agentic, short‑term resource‑mobilization strategy that drives visible competence demonstration. Although team learning orientation predicts adaptability when tested alone, its mediating effect is suppressed once performance‑approach orientation is included, consistent with competitive resource‑allocation dynamics in specialist teams. PL also reduces performance‑avoidance orientation, but this reduction does not yield a significant indirect effect on adaptability, indicating that removing dysfunction is not equivalent to activating adaptive capacity. By comparing three competing motivational pathways, the study identifies a dominant leadership leverage point for configuring resource flows to produce emergent adaptation and offers implications for designing systemic interventions and models to enhance team resilience.

Abstract: Artificial intelligence (AI) is transforming organizational processes and workforce capabilities across multiple sectors, generating important implications for sustainable organizational performance. In educational institutions—an underexplored organizational context—administrative staff represent a critical workforce segment whose competencies, adaptability, productivity, and decision-making capacity directly shape institutional sustainability. Yet empirical evidence on how AI adoption affects these outcomes in emerging economy educational settings remains limited. Addressing this gap, the present study examines the predictive relationships between AI adoption and four organizational sustainability indicators: job competencies (CL), resistance to change (RC), administrative productivity (PA), and decision-making autonomy (ATD) among administrative personnel in educational institutions in Chimbote, Peru. A quantitative, cross-sectional, non-experimental design was employed, using Partial Least Squares Structural Equation Modeling (PLS-SEM) with SmartPLS 4.0. Data were collected from 98 administrative staff members across 54 educational institutions. The measurement model confirmed adequate reliability, convergent validity, and discriminant validity across three constructs; however, the Resistance to Change construct exhibited insufficient internal consistency reliability (Cronbach’s alpha below .70) and weak indicator loadings, failing to meet recommended PLS-SEM thresholds [77,81] and precluding its inclusion in the structural model. The structural results indicate that AI adoption exerts a positive and statistically significant predictive association with job competencies (β = 0.627, t = 11.55, p < 0.001), administrative productivity (β = 0.589, t = 9.885, p < 0.001), and decision-making autonomy (β = 0.398, t = 5.267, p < 0.001). The three empirically testable hypotheses (H1, H2, H3) are supported; H4 (Resistance to Change) could not be tested due to measurement reliability constraints. These findings position AI as a substantive driver of sustainable organizational performance in resource-constrained educational contexts, offering empirical evidence from a Latin American emerging economy perspective in alignment with Sustainable Development Goals 4, 8, and 9.

Abstract: The rapid and accelerating depletion of natural resources has spurred governments and pressure groups to call for effective environmental management initiatives. One such initiative is the creation of a green organisational culture to combat environmental degradation. As a result, there has been a burgeoning of literature on the concept of green organisational culture; however, the research is still in its nascent stage. For this reason, this study investigated the mediating role of green employee behaviours on the relationship between green organisational culture and environmental performance in the mining industry. Data was systematically collected from 277 participants and analysed using SMARTPLS 4. The results revealed that, while green organisational culture significantly impacted environmental performance, green employee behaviours partially mediated this relationship. These results offer important insights for mine managers.

Abstract: The full-scale invasion of Ukraine in February 2022 has subjected the national health system to unprecedented structural, financial, and operational stress. This article examines how Ukraine’s health system has functioned under sustained armed conflict, focusing on service delivery, workforce dynamics, health financing, governance, mental health integration, and long-term recovery planning. Drawing on reports from the World Health Organization (WHO), the World Bank, United Nations monitoring mechanisms, and emerging peer-reviewed literature, the analysis explores both system vulnerabilities and adaptive responses. Despite widespread destruction of infrastructure, repeated attacks on health facilities, population displacement, and economic contraction, primary health care services have remained operational in most regions. Pre-war financing reforms—particularly the centralized purchasing model implemented through the National Health Service of Ukraine—contributed to continuity of provider payments and financial protection for patients. At the same time, the conflict has intensified workforce shortages, disrupted supply chains, and generated a substantial burden of mental health conditions and unmanaged noncommunicable diseases. The Ukrainian case illustrates that health system resilience is rooted in pre-existing institutional capacity, protected pooled financing, digital health integration, and coordinated governance under national leadership. Beyond immediate survival, the conflict presents opportunities for transformative reconstruction aligned with equity, community engagement, and universal health coverage goals. The findings offer critical policy lessons for health systems operating in conflict and protracted crisis settings, emphasizing that preparedness, primary health care strengthening, and governance integrity are central determinants of systemic endurance during war.

Abstract: The aim of the present study is to investigate the relationship between job plateauing and organizational indifference in Iranian sports organizations (Case Study: Ilam Province Sports and Youth Departments). The research method is descriptive and correlational. The statistical population consisted of all employees of Ilam Province Sports and Youth Departments, 146 people. Due to the limited statistical population, the statistical sample of this study was considered equal to the entire population. To collect information, Milliman's (1992) job plateauing questionnaire and Danai Fard et al.'s (2010) organizational indifference questionnaire were used. Descriptive statistics (mean, standard deviation, graphs and tables) and inferential statistics (Kolmogrov-Smirnov test and Pearson correlation and stepwise regression) were used to analyze the data. The results showed that there is a positive and significant relationship between all dimensions of job plateauing and organizational indifference in Ilam Province Sports and Youth Departments. This means that with the increase in job plateau, organizational indifference increases. According to the results, it can be admitted that the lack of attention to the phenomenon of job plateau will increase various dimensions of organizational indifference in sports organizations. Therefore, it is suggested that managers of organizations should take action towards job enrichment, establishing a system for evaluating employee performance, and increasing their support and training.

Abstract: Recruitment is among the HRM processes in which information and communication technologies and artificial intelligence can be applied extensively and fruitfully. It’s acceptance is studied but mostly from candidates perspective and some studies have showed that the acceptance of artificial intelligence applications is not universal among recruiters. The aim of this study was to examine whether recruiters’ attitudes toward the use of AI in the recruitment process vary depending on the stage of the process and the form of AI intervention. Based on data collected through an online questionnaire from 120 Polish recruiters, the findings indicate that acceptance of AI is higher in the earlier stages of the recruitment process than in the later stages. The results further show, in line with self-determination theory, that AI is more readily accepted when it serves an advisory rather than a decision-making function, regardless of the phase of the selection process. It was also found that the factor that increases acceptance for AI applications is the willingness to sacrifice decision-making autonomy, while employment in a large (above 500 employees) company significantly affects this acceptance only in the earlier stages. Practical recommendations were formulated and directions for further research were proposed.

Abstract: Digital knowledge governance is critical for innovation, inter-institutional coordina-tion and evidence-informed decision-making in complex regional networks. This study analyses the determinants of prospective adoption of two knowledge-management mechanisms promoted within the Amazon cooperation context—the Observatorio Re-gional Amazónico (ORA) and the Red de Centros de Investigaciones Amazónicas (REDCIA)—by adapting the Unified Theory of Acceptance and Use of Technology (UTAUT) to a pre-implementation phase and operationalizing constructs through a Knowledge–Attitudes–Practices (KAP) survey. Using secondary survey data from a purposive, non-probability sample of 162 respondents across Amazon Cooperation Treaty Organization (OTCA) member countries and institution types, we estimate penalized ordinal logistic regression models for behavioral intention (complete cases: 144 for Observatorio Regional Amazónico (ORA); 143 for Red de Centros de Investigaciones Amazónicas (REDCIA)) and examine robustness when controlling for country and organization type. Results indicate generally high stated intention to use both mechanisms; however, social influence is the only consistently statistically significant predictor in both models, while performance expectancy and perceived facilitating conditions (modelled as barriers) show limited discriminatory power, consistent with ceiling effects in perceived usefulness. These findings suggest that implementation should prioritize institutional legitimacy, visibility, and peer-based mobilization (e.g., mandates and champions), while future longitudinal research should reassess whether technical and organizational constraints become more salient post-deployment.

Abstract: Strategic decision-making (SDM) has traditionally been viewed as a human activity based on judgment, experience, and negotiation among senior managers. These decisions are limited by attention constraints, incomplete information, and bounded rationality. Today, many firms embed artificial intelligence (AI) and algorithmic decision-making systems into strategic processes. In some cases, algorithms do more than support managers. They filter options, rank priorities, and strongly shape final decisions. This article asks when SDM remains meaningfully human and when it becomes effectively algorithmic in algorithmically mediated enterprises. The study uses a theory-building integrative review of 62 contributions from strategy, information systems, behavioural research, and governance. It compares human and algorithmic decision-making across five dimensions: interpretive authority, search structure, time orientation, accountability, and scalability. Based on this analysis, it develops a framework of human–AI decision structures. The framework identifies three main forms: human-dominant, sequential hybrid (AI-to-human or human-to-AI), and aggregated human–AI governance structures. Each form affects not only decision accuracy but also power, learning, agency, and accountability. The key challenge is not to defend purely human strategy. It is to design governance systems where decision rights, oversight, and contestability remain strong when algorithms act as active decision participants.

Abstract: Purpose The aim of the study was to evaluate and shorten a psychometric scale measuring quiet quitting and passive quitting, while maintaining the quality of measurement and the predictive utility of the instrument. Design / Methodology / Approach A hybrid approach was applied, integrating structural equation modeling (SEM) and supervised machine learning (ML). A two-factor measurement model with regression on organizational engagement (UWES-9) was estimated using a sample of 1,040 working respondents. Simultaneously, the predictive validity of the scale items was assessed using regression algorithms within a cross-validation procedure. The scale was shortened iteratively by eliminating only those items whose removal did not significantly worsen SEM model fit or ML predictive performance. Findings The scale was reduced from 14 to 9 items. The reduction led to improved SEM fit indices (increased CFI and TLI with stable RMSEA) and only a slight decrease in the predictive validity of the ML models. The results confirm that integrating SEM and ML enables effective shortening of psychometric tools while maintaining their reliability and diagnostic functionality. Research Limitations / Implications The study was based on a single external criterion (organizational engagement) and one research sample, which limits the generalizability of the results. Future studies should include other criteria (e.g., burnout, turnover) and independent validation samples. Practical Implications The shortened scale reduces respondent burden, shortens survey time, and lowers measurement costs while retaining predictive utility relevant for HR practice and organizational diagnostics. Social Implications Improved and more efficient measurement of quiet and passive quitting can support early identification of declining employee engagement, contributing to enhanced quality of work life and human resource management policies. Originality / Value The originality of the study lies in proposing an integrated procedure for shortening psychometric scales by combining measurement and predictive criteria, which constitutes a methodological contribution to research on the development and optimization of measurement tools in management and quality sciences.

Abstract: Introduction: Ethical mentorship is commonly portrayed as a mechanism for guidance, care, and professional development. However, within hierarchical settings, ethical language may also be strategically deployed by Machiavellian leaders to mask self-serving motives. This study examines the paradox of ethical mentorship when care-based rhetoric is used to legitimize control, obligation, and dependency. Building on Alowais and Suliman (2025), the study extends existing work on dark leadership traits by focusing specifically on mentorship dynamics within Higher Education Institutions (HEIs), contexts known for bureaucratic complexity and symbolic moral discourse. Methods: A qualitative research design was adopted using semi-structured interviews with employees working in HEIs. This approach enabled an in-depth exploration of lived experiences, emotional ambivalence, and relational power dynamics that are not readily captured through quantitative methods. Data were analysed thematically to identify recurring patterns related to ethical rhetoric, manipulation, and trust. Results: The findings revealed three interrelated themes. First, Machiavellian mentors strategically employed professional and ethical language to enhance legitimacy, making manipulative practices difficult to detect. Second, mentees experienced persistent emotional ambivalence, characterized by simultaneous feelings of gratitude and exploitation driven by norms of moral duty and reciprocity. Third, once manipulation became apparent, fractures in trust emerged and spread across teams, undermining morale and organizational culture. Discussion: The study contributes to leadership and ethics scholarship by demonstrating how mentorship can be weaponized under the guise of care, transforming ethical guidance into a subtle mechanism of control. The findings underscore the importance of distinguishing genuine support from performative ethics within mentoring relationships. Practically, the study highlights the need for institutional vigilance, targeted training, transparent feedback mechanisms, and safeguards that protect mentees from coercive dependency. Without such measures, ethical mentorship risks becoming an instrument of domination rather than development.

Abstract: Corporate social responsibility (CSR) training plays a crucial role in deepening employees’ understanding of the ethical, social, and environmental expectations associated with their work. Such training helps build the attitudes and competencies that strengthen organisational CSR performance and contribute to long-term trust and value creation for stakeholders. Drawing on the Resource-based view (RBV), this study examines how employees’ CSR training influences CSR performance and further explores how firm size and CSR expenditures shape this relationship. The study employed purposive sampling, guided by clear inclusion and exclusion criteria, to identify 488 non-financial firms listed on the Tokyo Stock Exchange (TSE) between 2010 and 2024. Data were sourced from the Bloomberg database. To ensure robust and reliable estimates, the analysis utilised Feasible Generalized Least Squares (FGLS), the Augmented Mean Group (AMG) estimator, and the two-step System Generalized Method of Moments (GMM). The findings indicate that employees’ CSR training, captured by the number of training sessions provided annually, has a significant and positive effect on CSR performance. Moreover, both firm size and CSR expenditures were found to strengthen the influence of CSR training on CSR outcomes. These results suggest that managers and policymakers should give sustained attention to CSR-related capacity-building efforts. Regular, well-designed CSR training can enhance employees’ awareness and ethical conduct, foster stronger engagement, and ultimately support more effective and sustainable corporate practices.

Abstract: The study aims to empirically analyze employees' perceptions of sustainable business model practices in Polish enterprises operating in the manufacturing, trade, and service sectors. The study is based on a three-dimensional model of sustainable development practices, encompassing the green economy, the social dimension, and employee development, whose structure was previously confirmed through factor analysis. The study involved 231 employees representing enterprises of various sizes, and the data were collected using a validated measurement instrument. Statistical analyses, including Kruskal–Wallis tests and linear regression models, revealed that employees rate initiatives related to employee development the highest, followed by social practices, while green economy initiatives receive the lowest evaluations. The perception of practices varies by industry and enterprise size, while seniority and position are of limited importance. The results highlight the differentiated perception of sustainability initiatives within organizations and indicate areas requiring strengthening, particularly regarding environmental actions. The article provides practical guidance for designing sustainability strategies and HR policies and also serves as a foundation for further research on employees’ perceptions of sustainable development practices.

Abstract: During the COVID-19 pandemic, working from home became widespread due to contact restrictions, substantially altering work arrangements. As organizations reassess long-term work policies, this study examines whether working from home is associated with higher job satisfaction than traditional office work and which factors influence job satisfaction in a home-office context. Data were collected via an online survey of 201 em-ployees in Germany. Job satisfaction was measured using the Job Description Form (ABB), and personality traits were assessed with the Big Five Inventory (BFI-10), which was included as a control variable. Results indicate that employees working predominantly from home report significantly higher overall job satisfaction than those working mainly in traditional office settings. This effect remained stable after controlling for personality traits and age and was evident across all job satisfaction subdimensions. Furthermore, effective communication tools, adequate technical equipment, a quiet workspace, and prior expe-rience with working from home were positively associated with job satisfaction. In contrast, the presence of children or other household co-workers did not significantly reduce job satisfaction, whereas sufficient childcare arrangements showed a strong positive association. Overall, the findings highlight the importance of supportive home office conditions for sustaining job satisfaction beyond the pandemic.