Leadership is one of the important factors that ensured organizational achievement. Servant leadership offers a unique point of view on leadership which developed around the idea of service to subordinates. The implementation of servant leadership can lead to various positive outcomes, including increased engagement, organizational citizenship behavior, and improved performance. However, engagement and organizational citizenship behavior can serve as mediators to enhance organizational performance even further. The present study aimed to explore a prediction model of servant leadership using mediating variables such as employee engagement and organizational citizenship behavior, with employee performance as the outcome. The sampling method used was purposive sampling. This study used a structural equation model analysis approach to determine the predicted model of servant leadership. The research showed that the role of mediating variables indicated that employee engagement and organizational citizenship behavior had a positive effect in mediating the relationship between servant leadership and employee performance. The study indicated that applying servant leadership, with employee engagement, and organizational citizenship behavior as mediating variables would have an impact on better results of employee performance.

In today’s fast-paced digital world, generative AI, especially OpenAI’s ChatGPT, has become a game-changing technology with significant effects on education. This study examines public sentiment and discourse surrounding ChatGPT’s role in higher education, as reflected on social media platform X (formerly Twitter). Employing a mixed-methods approach, we conducted a thematic analysis using Leximancer and Voyant Tools and sentiment analysis with SentiStrength on a dataset of 18,763 tweets, subsequently narrowed to 5655 through cleaning and preprocessing. Our findings identified five primary themes: Authenticity, Integrity, Creativity, Productivity, and Research. The sentiment analysis revealed that 46.6% of the tweets expressed positive sentiment, 38.5% were neutral, and 14.8% were negative. The results highlight a general openness to integrating AI in educational contexts, tempered by concerns about academic integrity and ethical considerations. This study underscores the need for ongoing dialogue and ethical frameworks to responsibly navigate AI’s incorporation into education. The insights gained provide a foundation for future research and policy-making, aiming to enhance learning outcomes while safeguarding academic values. Limitations include the focus on English-language tweets, suggesting future research should encompass a broader linguistic and platform scope to capture diverse global perspectives.

The Malaysian dilemma presents a complex challenge in the wake of the COVID-19 pandemic, requiring a comprehensive statistical analysis for the formulation of a sustainable economic framework. This study delves into the multifaceted aspects of reconstructing Malaysia’s economy post-COVID-19, employing a data-driven approach to navigate the intricacies of the nation’s economic landscape. The research focuses on key statistical indicators, including GDP growth, unemployment rates, and inflation, to assess the immediate and long-term impacts of the pandemic. Additionally, it examines the effectiveness of government interventions and stimulus packages in mitigating economic downturns and fostering recovery. A comparative analysis with pre-pandemic data provides valuable insights into the extent of economic resilience and identifies sectors that require targeted support for sustained growth. Furthermore, the study explores the role of technology and digital transformation in building a resilient economy, considering the accelerated shift towards remote work and digital transactions during the pandemic. The analysis incorporates data on technological adoption rates, digital infrastructure development, and innovation ecosystems to gauge their contributions to economic sustainability. Addressing the Malaysian Dilemma also involves an examination of social and environmental dimensions. The study investigates the impact of economic policies on income distribution, social equity, and environmental sustainability, aiming to achieve sustainable economic growth. The study contributes a nuanced analysis to guide policymakers and stakeholders in constructing a sustainable post-COVID-19 economy in Malaysia.

This study aims to examine the pathways through which the user experience (UX) of ChatGPT, a representative of generative artificial intelligence, affects user loyalty. Additionally, it seeks to verify whether ChatGPT’s UX varies according to a user’s need for cognition (NFC). This research proposed and examined how ChatGPT’ UX affect user engagement and loyalty and used mediation analysis using PROCESS Macro Model 6 to test the impact of UX on web-based ChatGPT loyalty. Data were collected by an online marketing research company. 200 respondents were selected from a panel of individuals who had used ChatGPT within the previous month. Prior to the survey, the study objective was explained to the respondents, who were instructed to answer questions based on their experiences with ChatGPT during the previous month. The usefulness of ChatGPT was found to have a significant impact on interactivity, engagement, and intention to reuse. Second, it was revealed that evaluations of ChatGPT may vary according to users’ cognitive needs. Users with a high NFC, who seek to solve complex problems and pursue new experiences, perceived ChatGPT’s usefulness, interactivity, engagement, and reuse intentions more positively than those with a lower NFC. These results have several academic implications. First, this study validated the role of the UX in ChatGPT. Second, it validated the role of users’ need for cognition levels in their experience with ChatGPT.

The human factor of production is a significant player in increased organizational productivity. Due to the contemporary competitive work environment, the millennial in front-line jobs is faced with demanding work activities, resulting in challenges to their psychological well-being. Therefore, exploring the connectedness between work-life balance, employee engagement and psychological well-being of the millennial becomes imperative. Research was conducted, using an ex-post facto research design, among 320 purposively selected front-line millennial employees, with a mean age of 32 years. The instrument administered in a Google Form survey contained a 44-item self-report questionnaire, comprising work-life balance, employee engagement with components as vigor, dedication and absorption, and employee well-being. Data analyzed revealed that work-life balance significantly predicted employee well-being, accounting for 25% variance. The dimensions of employee engagement (vigor, dedication and absorption) collectively accounted for 7% variance in employee well-being. The study establishes the fact that to enhance the psychological well-being of Millennials in front-line jobs, organizational management should design the work structures to allow for work-life balance, which will as well increase their work engagement. They can encourage employees to find meaning and purpose in their work (dedication), provide opportunities for skill development and autonomy (vigor), and create an environment that allows employees to fully immerse themselves in their tasks (absorption). These could be implemented through organizational development strategies and work design. However, future research should target additional variables, replicate the study in different contexts and among another population of employees, employ longitudinal data collection methods, and increase sample sizes. Furthermore, measures should be taken to minimize the impact of social desirability and enhance the generalizability of the research.