Although various actors have examined the user acceptance of e-government developments, less attention has so far devoted to the relationship between attitudes of certain commuter groups against digital technologies and their intention to engage in productive time-use by mobile devices. This paper aims to fill this gap by establishing an overall framework which focuses on Hungarian commuters’ attitudes toward e-government applications as well as their possible demands of developing them. Relying on a representative questionnaire survey conducted in Hungary in March and April 2020, the data were examined by a machine learning and correlations to identify the factors, attitudes and demands that influence the use of mobile devices during frequent commuting. The paper argues that the regularity of commuting in rural areas, as well as the higher levels of qualification and employment status in cities show a more positive, technophile attitude to new ICT and mobile technologies that strengthen the demands for digital development, with special regard to optimising e-government applications for certain types of commuting groups. One of the main limitations of this study is that results suggest a picture of the commuters in a narrow timeframe. The findings suggest that developing e-government applications is necessary and desirable from both of the supply and demand sides. Based on prior scholarly knowledge, no research has ever analysed these correlations in Hungary where commuters are among the European citizens who spend extensive time with commuting.

The rapid advancement of financial technology (Fintech) has revolutionized the way financial transactions are conducted, with E-payment services becoming increasingly integral to daily commerce. This paper examines consumer perceptions and attitudes towards E-payment services offered by Fintech companies, identifying key factors that influence their acceptance and usage. Employing a quantitative approach, the research integrates quantitative data from surveys and applied SEM (Structural Equation Modelling) through AMOS. Out of 450, 420 respondents have given their views on perceptual preferences and attitudes with the help of SPSS. KMO and Bartlett’s Test are executed to understand and to check the factors for implementing factor analysis further through extractions. Anticipated findings are expected to reveal a spectrum of consumer attitudes shaped by factors such as trust, security, convenience, and technological familiarity. It contributes to the existing literature by providing updated insights into consumer behaviour in the Fintech sector and suggesting actionable strategies for service providers to enhance user engagement and satisfaction. It holds the potential to inform both theoretical frameworks in technology acceptance and practical marketing strategies for Fintech companies aiming to optimize E-payment services for diverse consumer bases.

The advent of the COVID-19 pandemic has precipitated a paradigm shift in education, marked by an increasing reliance on technology and virtual platforms. This study delves into the post-pandemic landscape of Islamic higher education at the State Islamic Institute of Palangka Raya, Central Kalimantan, Indonesia, focusing on students’ readiness, attitudes, and interests toward sustained engagement with e-learning. A cohort of 300 students across all semesters of Islamic Education partook in the investigation. Utilising Structural Equation Modelling, the study gauged students’ preparedness, perceptions, and inclinations toward online learning. Results indicate a general readiness among students for online learning, with a pivotal role attributed to technological devices and internet connectivity. Positive attitudes toward online learning were prevalent, with flexibility and accessibility emerging as significant advantages. Moreover, students showed keen interest in online learning, valuing its technological advancements, affordability, and intellectually challenging nature. These findings highlight the digital transformation of traditional teaching methods among Islamic higher education students, who are typically known for their emphasis on direct interaction in teaching and learning. Their receptivity to innovative learning modalities and adaptability to the digital era’s difficulties highlight the need for educational institutions to leverage this enthusiasm. Comprehensive online learning platforms, robust technological support, and a conducive learning environment are advocated to empower Islamic higher education students in navigating the digital landscape and perpetuating their pursuit of knowledge and enlightenment.

Currently, there is little study on managing organizational silence in Malaysia post COVID-19 pandemic. This study aims to examine the determinants of organizational silence and the impacts of silence on private sectors and employees. The target respondents are two hundred individuals above 21 years old working in private sectors across Malaysia. Purposive sampling is selected for this study because the target respondents must be individuals working in private sectors across Malaysia. The strongest predictor of organizational silence is the attitudes of immediate superior, followed by attitudes of top management and communication opportunities. This study provides valuable information to the employees and management in the private sector to recognize the behaviors that will create silence within the organization.

This study seeks to examine the factors affecting the intention of Indonesian MSMEs to adopt QRIS. It leverages variables from the Technology Acceptance Model (TAM), customizing the TAM framework to address the unique perceptions of risk and cost among MSMEs in Indonesia. Data were gathered from 212 MSME participants in Brebes Regency through convenience sampling, a non-probability sampling technique, using Google Forms for survey distribution. The findings indicate that perceived ease of use positively and significantly influences attitudes, which, in turn, positively and significantly impact the intention to continue using QRIS. However, perceived benefits, perceived risks, and perceived costs did not significantly affect the intention to continue use.

Background: According to the 2023 World Economic Forum report, the impact of Artificial Intelligence (AI) and automation on the job market was more significant than originally projected. Although 2018 research forecasted significant job losses balanced by job creation, current data indicates otherwise. Between 2023 and 2027, it is anticipated that 69 million new jobs will be created due to advancements in AI, however, this will be offset by the loss of 83 million jobs, leading to a net decrease of 14 million jobs worldwide. Roles related to AI, digitalization, and sustainability, such as AI specialists and renewable energy engineers are expected to grow, while those in clerical and administrative sectors are most at risk of decline. This shift underscores the need for reskilling and adapting to evolving fields, as nearly 44% of workers skills will face disruption by 2027. The demand for analytical thinking, technological literacy, and adaptability will grow as companies increasingly adopt frontier technologies. Objectives: (1) identify key variables influencing adaptability of college graduates in Indonesia, (2) quantify the strength of relationships between these variables to understand the combined effect on graduate adaptability. The research also aims to (3) develop theoretical and practical recommendations to strengthen ICIL policy and equip students with the relevant skills needed to thrive in an ever-changing job market. Methodology: The research focuses on predicting future employment trends, adaptability, and learning agility (LA), along with the implications for improving the Independent Campus Independent Learning (ICIL) policy. It focused on the significant unemployment rate among college graduates, along with the lack of research on the relationship between job change predictions, graduates’ adaptability, and the impact on graduates’ general well-being. The mixed-method strategy with quantitative analysis was used to conduct this research with data collected from 284 ICIL participants through online survey. The gathered data was evaluated using Structural Equation Modeling (SEM) with Lisrel version 10. Results: The result showed that job trend projections significantly influence responsiveness, which demonstrated a robust association between employment trend predictions and LA. Responsiveness significantly influenced learning agility which indicated no significant direct association between job trend projections and graduate adaptability. Conclusion: The research emphasized the need to consider adaptability as a concept with multiple dimensions. It proposed incorporating these factors into strategies for education and human resources development in order to better equip graduates for the demands of a constantly changing work market. Unique contribution: This research focused on adaptability as a multifaceted concept that consist of the ability to forecast job trends, be sensitive, and possess LA. It offered a deeper understanding of the relationships between these variables as discussed in the human resources literature. Technology, corporate culture, and training played a critical role in connecting employment trend prediction with the ability to respond effectively. Key recommendation: Institutions should implement a comprehensive approach to the development of human resources, with emphasis on fostering critical thinking, analytical abilities, and the practical application of information. By employing these tactics, higher education institutions may effectively equip graduates with both academic proficiency and the ability to adapt and thrive in quickly changing organizational environments, leading to the production of robust and versatile workers.