This research examines workplace pandemic xenophobia and resistance to change. Second, the study examines how resistance to change affects eco-xenophobia under the influence of pandemic xenophobia. Third, the study examines how eco-xenophobia affects employee vaccine acceptability. Finally, the study examined how acceptance of vaccination affects cross-cultural workplace performance. The study found five variables: contextual performance, change resistance, pandemic xenophobia, eco-xenophobia, and vaccination acceptance. The researchers obtained 219 responses after merging the 156 Pakistani and 63 Chinese responses. This research presents thermographic data for citizens of both nations separately. This study employed SEM-PLS using Smart-PLS version 4.0 to assess the reliability, validity, and relevance of the structural model. The study's findings revealed that all hypotheses were approved. The findings demonstrate that resistance to change can lead to xenophobic attitudes in the workplace, which can hurt employee performance. The research also emphasizes the importance of addressing workplace xenophobia, which can significantly impact workplace dynamics and employee outcomes. The study advances the understanding of the relationship between resistance to change and xenophobic attitudes. This study posits that resistance to change is a precursor to xenophobic attitudes. The findings have implications for managers and organizations operating in multicultural settings, underscoring the need for proactive measures to combat xenophobia and promote diversity and inclusion in the workplace.

Workplace stress has emerged as a critical challenge for organizations in the contemporary business environment, driven by factors such as increased workload, technological advancements, role ambiguity, and heightened performance expectations. This empirical study investigates the relationship between workplace stress and job satisfaction among employees across various organizations. The study was conducted using convenience sampling with a sample of 100 employees from selected public and private sector organizations. Primary data were collected through a structured questionnaire and analyzed using statistical tools including percentage analysis, correlation, regression, and chi-square tests. The findings reveal a significant negative relationship between workplace stress and job satisfaction, indicating that employees experiencing higher levels of stress tend to report lower satisfaction with their jobs. The study further highlights that excessive stress adversely affects employee performance, morale, and organizational commitment, whereas supportive leadership, effective communication, and a positive work environment contribute to reduced stress levels and enhanced job satisfaction. The study concludes that organizations should implement comprehensive stress management initiatives, employee well-being programs, and supportive workplace practices to enhance job satisfaction, improve employee performance, and foster long-term organizational effectiveness. Keywords: Workplace Stress, Job Satisfaction, Employee Well-being, Organizational Commitment, Work Environment

The rapid adoption of Artificial Intelligence (AI) in Human Resource Management (HRM) has transformed traditional workforce management by enabling intelligent recruitment, employee performance evaluation, talent analytics, workforce planning, and organizational decision-making. Simultaneously, the growing volume of research publications in AI-driven HRM has created complex collaboration networks among researchers, institutions, and countries. Social Network Analysis (SNA) provides an effective methodology for exploring these collaborative relationships by identifying influential authors, research communities, institutional partnerships, and knowledge diffusion patterns. This paper presents a comprehensive Social Network Analysis framework for examining research collaboration in AI-driven Human Resource Management. The proposed framework integrates bibliometric analysis, network construction, graph analytics, and visualization techniques to investigate co-authorship, institutional collaboration, countrylevel partnerships, keyword co-occurrence, and citation relationships. Graph-based metrics including degree centrality, betweenness centrality, closeness centrality, eigenvector centrality, network density, and modularity are utilized to evaluate collaboration strength and identify influential research communities. Comparative analysis demonstrates that AI-driven HRM research has experienced significant global collaboration growth, interdisciplinary knowledge sharing, and increased institutional connectivity over recent years. The findings provide valuable insights into emerging research trends, collaborative structures, influential contributors, and future research opportunities within AI-enabled Human Resource Management. The proposed framework contributes to strategic research planning, policy formulation, and international scientific collaboration by providing a data-driven understanding of the evolving research ecosystem.

This study investigates the interplay between remote work, digital surveillance, and employee autonomy, with a focus on the moderating role of trust in leadership within service organizations in Osun State, Nigeria. Drawing upon Social Exchange Theory and Self-Determination Theory, the research explores how digital surveillance practices influence employees’ perceived autonomy and how trust in leadership mitigates potential negative effects. The study employed a quantitative research design, with data collected through a structured questionnaire administered to 120 employees from selected Financial Technology (FinTech) organizations in Southwest Nigeria. Findings indicate that digital surveillance negatively affects employee autonomy, while trust in leadership significantly moderates this relationship. The study contributes to leadership and human resource management literature by highlighting the importance of trust in fostering employee well-being and performance in digitally monitored remote environments.

Purpose This study aims to examine how individual technology readiness shapes employees’ perceptions of generative artificial intelligence (GenAI) as a job resource and/or a job demand, and how these appraisals influence engagement, exhaustion and performance in small and medium enterprises (SMEs). Design/methodology/approach Survey data were collected from 465 UK SME employees who regularly use GenAI. The study integrates the technology readiness index (TRI) with the job demands–resources (JD–R) framework and tests the model using covariance-based structural equation modeling and multigroup analysis. Findings Optimism increases artificial intelligence (AI)-related job resources, while innovativeness, insecurity and discomfort primarily increase job demands. Resources enhance engagement, whereas demands increase exhaustion, which in turn reduces engagement. Engagement is the main predictor of employee performance. Effects are stronger in smaller firms. Research limitations/implications The cross-sectional design and self-reported data limit causal inference and generalizability. The study advances theory by showing that GenAI operates simultaneously as a job resource and a demand, with asymmetric effects shaped by technology readiness. Practical implications SMEs should actively reduce AI-related demands (e.g. cognitive load, validation effort) while strengthening resources such as training and workflow integration, prioritizing engagement to improve performance. Social implications The impact of GenAI depends on employee experience: it can enhance well-being when perceived as a resource but increase strain when experienced as a demand. Originality/value The study integrates TRI and JD–R to explain how individual technological predispositions shape AI-related work experiences and performance in SMEs.

In carrying out government and development activities, the position and role of civil servants are crucial. Civil servants are elements of the state apparatus that carry out elements of government and development in an effort to achieve organization goals. This research aims to analyze impact on islamic leadership and organization culture to organizational commitment and employee performance with spiritual intelligence as moderating variable. Research population were all employees at Ministry of Religion Regional Office of Riau Province with total sample as 150 respondents with cencus method. Data analysis used Structural Equation Modeling (SEM) with SMARTPLS 4.0.0. Research result show that organization culture has impact on organizational commitment and employee performance, islamic leadership has impact on employee performance but has not impact on organizational commitment. Organizational commitment has not impact on employee performance. Spiritual intelligence strengthen impact on organization culture to organizational commitment and employee performance. Spiritual intelligence weaken impact on islamic leadership to organizational commitment and employee performance. To maximize individual potential and enhance overall organizational results, spiritual intelligence development should be incorporated into training and culture.

Abstract. This study aims to examine the effects of medical managers' leadership behaviors on organizational outcomes and business growth indicators. The study analyzes transformational, transactional, and laissez-faire leadership. The study quantitatively analyzed the effects of behaviors on individual organizational outcomes such as extra effort, efficiency, and satisfaction, as well as growth indicators such as staff increase, revenue increase, and asset increase. Relationships between variables were tested using multiple regression analysis. The findings indicate that transformational leadership behaviors have strong and significant effects, particularly on individual outcomes related to employees. In this context, inspirational motivation and individual care dimensions were found to be the most decisive factors for extra effort, effectiveness, and satisfaction. In contrast, transactional leadership behaviors were found to be more effective, especially on organizational growth indicators such as personnel and revenue growth. However, laissez-faire leadership behaviors were found to have no significant effect on the variables examined. The findings reveal that leadership behaviors in healthcare organizations have varying degrees of impact on both employee performance and organizational growth; however, transformational leadership is more decisive in terms of sustainable organizational success. These findings indicate that leadership development should be considered a strategic priority in healthcare management practices. This study offers a unique contribution to the literature by examining leadership behaviors in conjunction with indicators of organizational growth.

Background: Notwithstanding the substantial volume of scholarly work addressing leadership and organizational change separately, empirical studies examining their concurrent influence on employee performance in Indonesian regional public agencies remain remarkably scarce, underscoring a critical knowledge gap that motivates the present inquiry. Objective: This study investigates how leadership and organizational structure change affect employee performance at BRIDA Kutai Kartanegara Regency, determines which variable exerts the stronger influence, and measures the extent of their collective explanatory power. Methods: The study adopted a quantitative explanatory design, gathering primary data through structured questionnaires administered to 75 BRIDA employees selected through simple random sampling. Data were analyzed using multiple linear regression, t tests, F tests, and the coefficient of determination (R²) through IBM SPSS Statistics version 24. Results: Organizational structure change demonstrated a significant and positive relationship with employee performance (β = 0.370, p < 0.001), whereas leadership did not produce a statistically significant partial effect (p = 0.675). When assessed jointly, both variables significantly predicted performance (F = 30.516, p < 0.001), accounting for 45.9% of the variance (R² = 0.459), with organizational structure change identified as the principal predictor. Conclusion: This study contributes to the public sector human resource management literature by confirming organizational structure change as a more proximate driver of performance than leadership in regional government agencies undergoing bureaucratic reform, with implications for BRIDA’s institutional policy.

Managing boss, a proactive behavior in which employees align their actions with supervisors' priorities, has been widely recognized for its positive effects on employee performance and supervisor-subordinate relationships. However, little is known about its potential negative interpersonal consequences from the supervisor's perspective. Drawing on social information processing theory and status-based perspectives on hierarchical threat, this study examines the conditional process through which managing boss (MB) relates to supervisor ostracism (SO). Using a three-wave, time-lagged survey of 452 supervisor-subordinate dyads in Chinese organizational contexts, the results indicated that MB was positively associated with supervisors' perceived threat to hierarchy (PTH). However, the simple mediating effect of PTH was not supported. Instead, a second-stage moderated mediation effect emerged, such that the indirect effect of MB on SO via PTH was significant only when supervisors exhibited high power distance (PD). Specifically, PD moderated the relationship between PTH and SO, such that the positive association was stronger under high PD conditions. These findings contribute to a more nuanced understanding of the potential interpersonal costs of proactive employee behaviors by showing that managing boss is not uniformly interpreted as threatening, but may evoke defensive supervisory responses under hierarchy-sensitive conditions. The study also extends research on hierarchical dynamics, status threat, and supervisor-subordinate interactions, while offering practical implications for managing proactive employee behaviors in culturally and hierarchically sensitive organizational contexts.

The growing integration of artificial intelligence (AI) into corporate managerial functions has transformed the methods used to monitor and evaluate employee performance. However, it has also increased concerns regarding privacy infringements and algorithmic bias, which may result in disciplinary measures or even employment termination. This study aims to examine the limits of employers’ authority in the use of AI-based performance monitoring systems and to analyze the legal protections available to employees subjected to automated performance evaluations. The research employs a normative legal methodology using statutory and conceptual approaches. The findings reveal that the implementation of AI in employment management must adhere to the principles of legality, transparency, purpose limitation, and human oversight. Furthermore, employee protection can be strengthened through effective complaint mechanisms, procedural fairness, and algorithmic accountability. The study concludes that, although an initial legal framework exists, further regulatory development is necessary to ensure comprehensive protection of employees’ privacy rights and human dignity in the context of AI-driven workplace management.

This study aims to analyze the effect of Perceived Organizational Support (POS) and Work Engagement on employee performance with organizational commitment as a mediating variable at SMEs in Kasongan, Bantul, Yogyakarta. This research was motivated by the importance of improving employee performance in the SME sector, which still faces various challenges, such as low employee engagement, suboptimal organizational support, and weak organizational commitment. This study employed a quantitative approach using a survey method. The population of this research consisted of employees working in SMEs in Kasongan, Bantul, Yogyakarta. The sampling technique used was purposive sampling with a total of 150 respondents. Data were collected through questionnaires using a Likert scale. The data analysis method used was Structural Equation Modeling based on Partial Least Square (SEM-PLS). The results showed that Perceived Organizational Support had a positive and significant effect on employee performance. However, Work Engagement did not have a significant direct effect on employee performance. In addition, Perceived Organizational Support and Work Engagement were found to have a positive and significant effect on organizational commitment. Organizational commitment also had a positive and significant effect on employee performance. The mediation test results indicated that organizational commitment partially mediated the effect of Perceived Organizational Support on employee performance and fully mediated (full mediation) the effect of Work Engagement on employee performance. This study implies that improving organizational support and strengthening organizational commitment are important strategies for enhancing employee performance in the SME sector, particularly in SMEs in Kasongan.

Purpose: This study aims to evaluate customer satisfaction with employee performance at PT WIKA based on service quality dimensions using Service Quality (SERVQUAL) and Multi-Objective Optimization on the Basis of Ratio Analysis (MOORA) based decision support system approaches. Research Methodology: This study employed a quantitative descriptive method by integrating SERVQUAL with the MOORA decision-support system. Data were collected through questionnaire-based surveys distributed to 100 PT WIKA customers using 20 service quality indicators representing the tangibility, reliability, responsiveness, assurance, and empathy dimensions. The analysis compared customer perception and expectation scores to identify satisfaction gaps and determine the priority service dimensions. Results: The findings revealed that the average SERVQUAL satisfaction ratio was 1.01, indicating that overall service performance generally met customer expectations. A total of 14 out of 20 indicators (67%) were categorized as satisfactory, while six indicators (33%) remained unsatisfactory. Furthermore, the MOORA analysis identified reliability as the most dominant service quality dimension contributing to customer satisfaction and employee performance evaluations. Conclusions: Overall, customers were satisfied with the employee performance at PT WIKA. However, several indicators related to responsiveness and service consistency require improvement to enhance customer satisfaction. Limitations: This study was limited to a single company and a specific customer sample, which may reduce the generalizability of its findings. In addition, the weighting process in the MOORA method is determined subjectively. Contributions: This study contributes to service quality and human resource management literature by integrating SERVQUAL and MOORA in evaluating employee performance and supporting service improvement decision-making

BackgroundHealthcare workers face challenges such as intense work tempo, irregular working hours and high patient expectations. This situation may affect the happiness and performance of employees, as well as the quality of health services.ObjectiveThe aim of this study is to reveal the relationship between organizational health perceptions, happiness and job performance of health personnel working in a university hospital.MethodThe data were collected from 350 healthcare workers between December 2023 and January 2024 by face-to-face survey method. Organizational Health Scale, Oxford Happiness Scale and Employee Performance Scale were used as measurement tools. Data were analyzed with SPSS 22.0 and AMOS 26.0 programs; descriptive statistics, correlation analysis and Structural Equation Modeling (SEM) were applied.ResultsAccording to the correlation analysis, there was a positive and low level relationship between organizational health and happiness (r = .359) and a very weak but significant relationship with performance (r = .136). A moderately significant relationship was found between happiness and performance (r = .252). According to SEM findings, organizational health significantly predicted happiness (β = 0.98, p < .001), while happiness predicted performance (β = 0.14, p = .002). The direct effect of organizational health on performance was not significant (β = 0.23, p = .077). In subgroup analyses, differences were observed according to occupational groups and length of experience.ConclusionsOrganizational health is a determinant of employee happiness, and happiness increases job performance. Therefore, it is recommended that healthcare organizations develop strategies that focus on employee well-being.

Purpose: This study aims to examine the determinants of civil servant performance by evaluating the impact of the digital attendance system, employee competencies, and work discipline—both individually and collectively—at the Dompu Regency Finance and Asset Management Agency (BPKAD). Research Method: Using a quantitative causal design, primary data were collected through a questionnaire distributed to the entire population of 77 employees (saturation sampling). The data were then analyzed using the Structural Equation Modeling-Partial Least Squares (SEM-PLS) approach. Results and Discussion: Digital attendance systems and work discipline have been shown to have a positive and significant impact on performance. Conversely, employee competence has been shown to have no significant impact. Collectively, this model explains 52.2% of the variation in performance. These findings confirm that the power of technological oversight and rule compliance can compensate for weaknesses in individual technical capacity. Implications: In practical terms, agency leaders are advised to prioritize E-HRM investments to ensure reliable infrastructure for monitoring and enforcing disciplinary regulations. Future research is recommended to expand the sample scope to include other Regional Government Work Units (SKPDs). Originality: This study integrates the Information System Success Model and the 21st-century digital competency framework into a single holistic Socio-Technical System analytical model for the public financial management sector.

BackgroundEffective leadership is crucial for delivering high-quality healthcare, optimizing employee performance, and improving patient outcomes.ObjectiveThis study conducts a bibliometric analysis to examine leadership styles in the healthcare sector, identifying key research trends, influential works, and their impact on work outcomes.MethodsUsing Scopus-indexed publications (2010-2024), this study analyzes eighty-three relevant documents with VOSviewer.ResultsThe findings reveal that various leadership styles, such as transformational, transactional, authentic, collaborative, inclusive, servant, and paternalistic leadership, have a significant impact on both individual and organizational outcomes. Furthermore, transformational leadership is the most studied and influential style, promoting employee engagement, innovation, and better patient care. Transactional leadership ensures structure and efficiency but offers limited long-term benefits. Servant leadership fosters trust, collaboration, and ethical decision-making, while authentic leadership enhances transparency and psychological safety. Additionally, the study highlights a growing focus on healthcare leadership, with Medicine and Business, Management & Accounting as the dominant disciplines.ConclusionThis bibliometric study highlights the critical role of leadership styles in shaping work outcomes in the healthcare sector. Transformational leadership emerges as the most influential, fostering innovation, engagement, and improved patient care.

In the construction industry, project performance is often closely tied to the individuals comprising the project team. This study examines the impact of emotional intelligence (EI) on project performance in the construction sector, particularly in contexts of trust and stress. Drawing on Affective Events Theory (AET) and EI-based performance theory, this study proposes a model to investigate the link between EI and project performance while exploring how trust and stress mediate this relationship. The model was tested with structural equation modelling (SEM) on data from 574 respondents in the construction industry of Pakistan. The results indicate that all dimensions of EI significantly impact project performance, except for the dimension related to understanding others’ emotions. Trust strongly mediates the relationship between EI dimensions and project performance. Conversely, stress negatively influences this relationship, contrasting with the positive mediation effect of trust. This research enriches existing literature by proposing a model that integrates AET and EI performance theory to enhance employee performance in the construction industry. The findings strongly suggest incorporating validated EI assessments into recruitment and supervisor development in construction firms. Management should institutionalize a participative climate that builds trust and deploy periodic stress checks to sustain performance in projects.

Purpose Digitalization has introduced new momentum into human resource management (HRM) practice and research. However, managers and scholars face the challenge of integrating digital technology with employees to maximize its positive impact. This study aims to explore how employees’ perceptions, emotions, adaptation and resistance toward digital technology influence job performance within the context of digital HRM. Design/methodology/approach Drawing on structuration theory and employee value proposition, this study develops a theoretical model linking employees’ responses to digital technology with job performance. A questionnaire survey was administered to 412 Didi drivers in China. Data were analyzed using structural equation modeling with LISREL 8.70 software to test the proposed hypotheses. Findings The study found that (1) the cognitive, emotional experience and adaptation stages of employees have a significant positive effect on their work performance. (2) The resistance mentality of employees has a significant negative effect on their work performance. (3) Work motivation and satisfaction play a significant mediating role between cognition and work outcomes. Research limitations/implications The study is limited in its focus on a specific sample of Didi drivers, a factor that may limit the general applicability of the study conclusions. Practical implications The research findings have effectively expanded the scope of discussion on the anthems of employee performance, provided the academic community with in-depth insights into multiple influencing factors and enriched the theoretical system of performance management. In addition, these findings have significant guiding implications for the field of practice, especially in addressing the challenges of digital HRM. Originality/value This study reveals the impact of digital technology on Didi drivers’ cognition, emotions, behavior and performance, providing corresponding social responsibility for managers and promoting closer integration and collaborative progress between technology, employees and organizations.

Although digital literacy has been widely examined in organizational and educational contexts, research specifically analyzing its effect on employee performance within the LLDIKTI environment remains relatively limited. This study aims to analyze the effect of digital literacy on employee performance at LLDIKTI Region X. A quantitative approach with a survey method was employed, involving 73 respondents selected through saturation sampling. Data were collected using a questionnaire and analyzed through simple linear regression with the assistance of SPSS software. The findings indicate that digital literacy has a positive and significant effect on employee performance at LLDIKTI Region X, as shown by a t-value of 5.911 and a significance level of p &lt; .05. The coefficient of determination, R² = .330, indicates that digital literacy contributes 33% to employee performance, while the remaining variance is explained by other factors outside the model. These findings demonstrate that employees with stronger digital literacy tend to show better performance in carrying out work tasks within higher education service institutions. This study contributes to the literature on digital literacy and human resource performance by emphasizing the importance of digital competence in improving workplace effectiveness. The practical implication is that LLDIKTI Region X should continue strengthening employees’ digital competencies through systematic training, mentoring, and professional development programmes. Further research is recommended to examine additional organizational, technological, and individual factors that may influence employee performance.

The growing demand for intelligent decision support in Strategic Human Resource Management (SHRM) drives the need for advanced predictive models for employee attrition and performance. This paper presents a hybrid deep learning framework combining TabNet and Long Short-Term Memory (LSTM) networks within a cloud-based architecture. TabNet’s attention-based feature selection and LSTM’s ability to model temporal relationships enable the model to effectively process both structured tabular data and time-series behavioural patterns. The model is trained and validated using the IBM HR Analytics Employee Attrition & Performance dataset, consisting of 1,470 employee records with 35 demographic and organizational features. Performance evaluation is conducted using metrics such as accuracy, precision, recall, F1-score, ROC-AUC, and regression metrics (R 2, RMSE, MAE). Results show that the proposed TabNet–LSTM framework significantly outperforms traditional models, including Artificial Neural Networks, Reinforcement Learning, and Gradient Boosting, in terms of predictive accuracy and reliability. These findings highlight the potential of hybrid cloud-enabled deep learning systems to support proactive employee retention and performance optimization strategies. The original contribution of the study lies in the integration of interpretable tabular learning and sequential modelling within a scalable cloud-based HR analytics framework for enhanced strategic workforce decision-making.

This study explored the Dimensions of Work Motivation of Construction Workers in the City of Mati, Davao Oriental. With construction being a vital driver of economic development, understanding the factors affecting work motivation of construction workers is essential to improve employee performance. Using a descriptive-comparative quantitative research design, the study surveyed 500 construction workers. Frequency Count and Percentage, Exploratory Factor Analysis(EFA) and Analysis of Variance(ANOVA) were employed to identify the motivational constructs of construction workers, determine their profile, assess the level of work motivation of construction workers across the factors, and ascertain the significant difference on the level of work motivation of construction workers across their demographic profiles. Results revealed that the respondents represent a young, predominantly male, relatively educated, and project-based workforce engaged mainly in skilled and general labor construction activities. Results indicate that the five dimensions of work motivation are performance reward, workplace support, occupational well-being, job security, and employee welfare. All these dimensions obtained mean scores interpreted as very high, reflecting a general strong level of motivation. The study also suggests that work motivation varies significantly across most demographic characteristics, except sex, highlighting the influence of educational, occupational, and economic factors on workers’ motivational experiences. Based on these findings, the study developed a guide to enhance work motivation of construction workers.