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The purpose of this paper is to propose a moderated mediation model to explain how corporate social responsibility (CSR) and ethical leadership influence knowledge sharing and job dedication through the mediating mechanism of positive affective tone and cognitive meaningfulness.

The research hypotheses were empirically tested using a survey of employees from the high-tech industry in Taiwan. The research constructs in this study were measured using five-point Likert scales modified from existing literature. The survey data were empirically analyzed with two-step structural equation modeling (SEM) and regression analysis.

The empirical results of this study reveal that CSR and ethical leadership positively relate to positive affective tone and cognitive meaningfulness. Knowledge sharing is positively affected by positive affective tone whereas job dedication is positively affected by positive affective tone and cognitive meaningfulness. While the relationship between positive affective tone and job dedication is positively moderated by job demand, the relationship between cognitive meaningfulness and job dedication is negatively moderated by job demand.

This study elucidates the ethical influences from organizations (i.e. CSR) and leaders (i.e. ethical leadership) respectively to explain affective and cognitive processes involved in work situations. At the same time, by clarifying the moderating role of job demand, this study provides valuable implications for managers to effectively leverage job demand for increasing employees’ job dedication.

To complement previous research on team performance, the purpose of this paper is to analyze the development of team performance and top management approval at the team level. In the proposed model, team performance and top management approval are influenced by the team leader’s charisma, teamwork exhaustion, and goal clarity via the full mediation of team planning. The effects of the leader’s charisma and goal clarity on team planning are moderated by teamwork exhaustion.

Empirical testing of this model based on hierarchical regression modeling, by investigating team personnel in high-tech firms, confirms the applicability of team planning among these firms’ work teams.

A team leader’s charisma and goal clarity positively relate to team planning, while teamwork exhaustion is not associated with team planning. Team planning further positively relates to team performance and top management approval, respectively. A team leader’s charisma negatively moderates the relationship between teamwork exhaustion and team planning, while goal clarity positively moderates the relationship between teamwork exhaustion and team planning.

While previous literature has focused in depth on team planning and its antecedents and outcomes, there still exists an important gap regarding potential moderation in the formation of team planning. This study provides some important findings that complement previous literature by examining three fresh exogenous determinants for explaining team planning, their interaction effects, and how they indirectly relate to team performance and top management approval via the full mediation of team planning.

The purpose of this paper is to apply the self-concept theory and conservation of resources theory to develop a model that explains how both corporate social responsibility (CSR) and ethical leadership influence turnover intention through work engagement and burnout.

A survey of employees from banking industry in Taiwan and the research hypotheses were empirically tested by two-step structural equation modeling (SEM) and regression analysis.

The empirical findings indicate that CSR and ethical leadership are both related to work engagement positively and burnout negatively. Turnover intention is affected by work engagement negatively and burnout positively. While the relationship between CSR and work engagement is positively moderated by ethical leadership, the relationship between burnout and turnover intention is negatively moderated by self-efficacy.

This study confirms that both CSR and ethical leadership play critical roles for influencing turnover intention through the mediation of work engagement and burnout. The moderating effects of ethical leadership and self-efficacy are also presented in this study.

The authors’ findings bring some suggestions for managers who want to prevent high turnover intention from spreading all over their organization. Specifically, CSR and ethical leadership should be taken into account when managers develop their strategies to reduce turnover intention.

This study analyzes how turnover intention takes shape from ethical perspectives and through which work-related state of mind (such as burnout, work engagement) can turnover intention be eventually affected.

To deepen our understanding about the development of team performance, the purpose of this paper is to develop a model that explains how ambidexterity and ethical leadership affect knowledge sharing and team performance through within-team competition.

This study demonstrates the applicability of ambidexterity and within-team competition by surveying 78 teams from the high-tech and banking industries. This study further presents a three-way interaction among ambidexterity, politics and job complexity.

This study finds that both ambidexterity and ethical leadership are positively related to knowledge sharing and team performance through the mediation of team development competition.

This study confirms that ambidexterity and ethical leadership play critical factors for improving knowledge sharing and team performance through the mediation of team development competition. Furthermore, the moderating effects of politics and job complexity are also confirmed in the research.

This study examines the impact of perceived human resource management practices on talent turnover intention, with work engagement mediating and self-efficacy moderating the relationship. It examines how employees' perceptions of pay satisfaction, empowerment, participation and communication are related to their turnover intentions.

A total of 283 valid questionnaires from UAE government employees were used for data analysis. Partial least squares structural equation modeling (PLS-SEM) was used to examine the proposed hypothesis.

The results reveal that employees' perceptions of pay satisfaction, empowerment, participation and communication are significant contributors to work engagement. The findings further demonstrate that work engagement significantly negatively affects talent turnover intention and acts as a mediator between employees' perceptions of individual human resource management practices and talent turnover intention. However, the results contradict the hypothesis that self-efficacy moderates the association between work engagement and talent turnover intention.

This study focuses on the impact of perceived human resource management practices on talent turnover intention, an area that has received limited attention in literature. By focusing on perceived human resource management practices, this study illuminates employees' subjective experiences and how they perceive human resource management practices intended to reduce talent turnover intention. The inclusion of the mediating effect of work engagement offers a more profound understanding of how employees' perceptions of human resource management practices influence their turnover intentions. This comprehensive approach to understanding the interplay between these variables provides valuable insights for organizations seeking to improve their human resource management practices and talent turnover intention.

This paper presents the Edge Load Management and Optimization through Pseudoflow Prediction (ELMOPP) algorithm, which aims to solve problems detailed in previous algorithms; through machine learning with nested long short-term memory (NLSTM) modules and graph theory, the algorithm attempts to predict the near future using past data and traffic patterns to inform its real-time decisions and better mitigate traffic by predicting future traffic flow based on past flow and using those predictions to both maximize present traffic flow and decrease future traffic congestion.

ELMOPP was tested against the ITLC and OAF traffic management algorithms using a simulation modeled after the one presented in the ITLC paper, a single-intersection simulation.

The collected data supports the conclusion that ELMOPP statistically significantly outperforms both algorithms in throughput rate, a measure of how many vehicles are able to exit inroads every second.

Furthermore, while ITLC and OAF require the use of GPS transponders and GPS, speed sensors and radio, respectively, ELMOPP only uses traffic light camera footage, something that is almost always readily available in contrast to GPS and speed sensors.