This study aims to examine the evolution of the system of support sources in Hungary, focusing on the specific goals supporting higher education in the development programs Széchenyi 2020 (2014–2020) and Széchenyi Plan Plus (2021–2027). The study provides insights into development program evolution and changes, aiming to inform EU funding opportunities for Hungarian higher education institutions over a nearly 10-year period. By focusing on the operational programs that are the basis for the upcoming tenders, the study will display the target system of EU funds that can be utilized to bolster higher education institutions in Hungary. The study is based on document analysis, examining the Hungarian policy tools of the development programs and the operational program strategies of the ten-year time period from 2014 to 2024. By analyzing the support landscape for higher education institutions in Hungary, this study contributes to a better understanding of how the key objectives and criteria of strategic programs have evolved. It also examines the aspects and elements defined in two different development programs over the last ten years. The result of the study can contribute to anticipate the types of funding opportunities that may be available in the future and inform future decision-making processes.

The COVID-19 pandemic provided a unique opportunity for educators and policymakers to reconsider education systems and rethink what is essential, necessary, and desirable for future generations. A sequential generic qualitative approach was used in this study. Based on the systematic literature review, a content analysis was conducted to identify dimensions that contribute toward higher education institutions sustainability. Subsequently, the Expert Opinion method that involved five professors holding key positions in respective universities from Malaysia, the Netherlands, India, and Bangladesh was applied to propose a post-COVID-19 sustainable framework. Four themes: 1) educational reform; 2) digital transformation; 3) resilience and change management; and 4) sustainability coupled with agility and flexibility formed the framework for HEIs’ sustainability during the post-COVID-19 pandemic. We propose that the themes be examined from an integrated perspective to ensure HEIs can be sustainable in the long run. Finally, other scholars are recommended to conduct a tracer study as well as develop qualitative instruments based on the themes and dimensions identified from the systematic literature review and the Expert Opinion Method to better understand the phenomenon of HEI sustainability.

The evolution of the internet has led to the emergence of social media (SM) platforms, offering dynamic environments for user interaction and content creation. Social media, characterized by user-generated content, has become integral to electronic communication, fostering higher engagement and interaction. This study aims to explore the utilization of SM marketing, particularly in Higher Education Institutions (HEIs), focusing on Széchenyi István University’s academic social network sites (SNS) as a case study to enhance student engagement and satisfaction. The primary objective of this study is to review recent academic literature on SM marketing, especially for HEI marketing, and investigate the potential of the University’s SNS platforms as a case study in increasing student engagement. First a systematic literature review was conducted using Scopus and Science Direct databases to analyze recent research in academic SM. Then the article examined the University’s website and SNS platforms using the Facepager program to collect and analyze posts’ content. The findings from the literature review and observation indicate the growing importance of SM in higher education marketing. The university’s use of various SM strategies, such as visual storytelling, multimedia content, blogs, and user-generated content, contributes to increased student engagement of the university’s values.

With the rapid development of artificial intelligence (AI) technology, its application in the field of auditing has gained increasing attention. This paper explores the application of AI technology in audit risk assessment and control (ARAC), aiming to improve audit efficiency and effectiveness. First, the paper introduces the basic concepts of AI technology and its application background in the auditing field. Then, it provides a detailed analysis of the specific applications of AI technology in audit risk assessment and control, including data analysis, risk prediction, automated auditing, continuous monitoring, intelligent decision support, and compliance checks. Finally, the paper discusses the challenges and opportunities of AI technology in audit risk assessment and control, as well as future research directions.

The purpose of this study is to determine the relationship between the exogenous variables (administrative support, career placement & employability, academic staff support, institutional factors, and information systems) as service delivery quality dimensions with satisfaction and moderating variable (academic and social integration) between endogenous variables (satisfaction and retention) among undergraduate students from Malaysian private higher education institutions. In order to accomplish the objectives proposed with hypotheses, a model reflecting the relationship between service delivery quality dimensions and satisfaction moderated by academic and social integration towards retention is applied. This empirical study focused on probability-stratified random sampling with a final sample size of 309 students. This study achieved statistically significant positive results by emphasizing academic and social integration as a moderating variable to achieve student retention by linking Perceived Performance Theory and Tinto’s Interactionist Theory from satisfaction to retention. Evaluation of the structural model on the coefficient of determination for the model’s predictive accuracy in this study produced an R² = 0.85 for satisfaction, suggesting nearly 85% of the variance in endogenous latent construct satisfaction is explained by all the service delivery quality dimensions linked to it. As for retention produced R² = 0.74, suggesting nearly 74% of the variance in endogenous latent construct retention is explained by all the service delivery quality dimensions linked together with satisfaction and academic and social integration as moderator. The model has a substantial effect with 0.76 in the Goodness-of-Fit index, indicating that the model has better explaining power.