Digital and sustainable leadership, person-organization fit, and job involvement: Evidence from Vietnamese higher education

In the digitalization era, banks strive to implement digital transformations; digital culture, competence, and leadership become essential factors to advance the company’s digitalization. Digital transformation is indispensable in improving employee performance amidst rapid digital advancements, helping companies stay competitive and avoid falling behind fintech and banking rivals. The study aims to examine the influence of digital transformations on banking employee performance in Indonesia, targeting state-owned banks. Primary data were gathered through questionnaires involving 100 participants. Data analysis employed partial least squares structural equation modeling (PLS-SEM) to assess the influence of independent on dependent and mediating variables. The results demonstrate that digital culture (p < 0.05), digital competency (p < 0.05), and digital leadership (p < 0.05) positively and significantly influence employee performance. Self-efficacy does not function as a substantial mediating variable between digital culture (p > 0.05) or digital competence (p > 0.05) and employee performance. However, self-efficacy is a crucial mediating variable connecting digital leadership to employee success (p < 0.05). The study demonstrates that digital transformation in terms of culture, competence, and leadership can improve performance. Self-efficacy is able to mediate the effect of digital leadership on employee performance but fails to affect the influence of digital culture and digital capabilities on the performance of banking employees.

Acknowledgment
The authors thank Universitas Sumatera Utara, especially the Research Institute, for their support. Acknowledgments are also expressed to the Kementerian Pendidikan dan Riset through the DRTPM program (number: 92/UN5.4.10.S/PPM/KP-DRTPM/2024), which has provided intellectual and financial assistance. The authors would also like to thank the Management Science Study Program, Universitas Sumatera Utara.

The study aimed to identify the level of practicing the human resources staffing process and the level of the employees’ job involvement in the Irbid District Electricity Company in Jordan; it also aimed to examine the impact of human resources staffing process on the employees’ job involvement. The study adopted the descriptive, analytical method, since it determines the characteristics of the phenomenon, describes its nature accurately and then determines the quality of the relationship between its variables. The study population included all the individuals in the senior and middle administrative levels by 100 individuals. To achieve the objectives of the study, the researchers prepared a questionnaire to examine the study variables. One hundred questionnaires were distributed to each manager, deputy manager, and department head in the Irbid District Electricity Company out of which the researchers retrieved 97 questionnaires valid for analysis. In order to analyze the data collected, the study relies on the Statistical Package for Social Sciences (SPSS) where the descriptive statistics for all the fields of the study were estimated. The correlation matrix was also used to determine the relationship between variables. Furthermore, multiple regressions were used to determine the impact of the independent variable on the dependent variable. The findings showed that the level of practicing the human resources staffing process and the employees’ job involvement at Irbid District Electricity Company (IDECO) was moderate. The findings of the study showed that the process of human resources staffing was positively associated with the job involvement where the Pearson coefficient was r= .851 and at level of significance of 0.00. The research data have also indicated that the human resources staffing process had a positive impact on the employees’ job involvement. The study recommended that the procedures of staffing in all organizations should focus on achieving the fit between the employee and his job through focusing on choosing employees whose knowledge, skills and abilities correspond to the requirements of vacant jobs and also through implementing different tests and selection interviews, which help choose the person whose traits fit the job requirements. The study has also indicated that the recommended organizations should also pay attention to the job design process where the focus is on designing jobs in a way that creates a challenge, and enables employees feel independence and joy during the job; in this method, the employee can be more involved and can work in an effective way.

The increasing integration of Artificial Intelligence (AI) into education requires studying the motives for its use among students. This study aims to identify the key motivations for economics students to use AI and compare these motivations by grade level and gender. The study examines satisfaction with the use of AI and analyzes the number of AI tools used.

An anonymous empirical study was conducted among 264 students from the Faculty of Economics at Taras Shevchenko National University of Kyiv, Ukraine. Data analysis included descriptive statistical methods, non-parametric statistical methods, and exploratory factor analysis.

The study found that students’ main motivations for using AI are the automation of routine tasks (34.2%) and the need to save time (21.5%), while 18.7% use AI to compensate for lack of experience. Among Bachelor’s students, motivations such as automating routine tasks and saving time increased from 53% to 58% over the course of their studies, while lack of experience decreased from 22% to 15%. In contrast, Master’s students showed a decrease in routine automation (from 36% to 28%) but an increase in the need to compensate for lack of experience (from 15% to 28%) and to save time (from 18% to 25%). In terms of gender, men are more likely to use AI for learning and personal development, while women are slightly more likely to use AI for work. More than 38% of respondents say they need to use at least 2 AIs to achieve their goals.

Acknowledgment
This publication is based upon work from 24-PKVV-UM-002, ‘Strengthening the Resilience of Universities: Czech-Ukrainian Partnership for Digital Education, Research Cooperation, and Diversity Management,’ supported by the Czech Development Agency and the Ministry of Foreign Affairs under the initiative ‘Capacity Building of Public Universities in Ukraine 2024.’