This study explores the impact of digital economy engagement and digital adoption on the entrepreneurship performance of Small and Medium Enterprises (SMEs) in Malaysia, with a specific focus on the PG Mall platform. Through an analysis of SMEs’ involvement in digital activities such as e-commerce, digital marketing, and data analytics, the research identifies key factors that enhance business performance. The main objective of this paper is to examines the mediating role of government policies in supporting digital adoption and fostering a conducive environment for digital entrepreneurship. This paper employed a quantitative method to examine the impact of digital economy engagement and digital adoption on the entrepreneurship performance of Small and Medium Enterprises (SMEs) in Malaysia, with a focus on the PG Mall platform. Through data analysis, this research assessed several hypotheses related to the relationship between digital engagement, adoption, and business performance. The findings revealed that the majority of the hypotheses were supported, confirming the positive influence of digital economy engagement and digital adoption on various aspects of entrepreneurship performance. Based on these findings, this paper also proposes a conceptual framework that highlights the elements of digital economy engagement and digital adoption that contribute to SME performance. This framework serves as a valuable guideline for government policymakers, practitioners, and scholars in shaping strategies to foster digital entrepreneurship. It underscores the importance of supportive government policies, such as financial incentives and training, in facilitating the digital transformation of SMEs. By providing a structured approach to understanding the role of digital tools in enhancing business outcomes, the framework offers a foundation for future research and policy development aimed at promoting digital entrepreneurship in an evolving economic landscape.

In agriculture, crop yield and quality are critical for global food supply and human survival. Challenges such as plant leaf diseases necessitate a fast, automatic, economical, and accurate method. This paper utilizes deep learning, transfer learning, and specific feature learning modules (CBAM, Inception-ResNet) for their outstanding performance in image processing and classification. The ResNet model, pretrained on ImageNet, serves as the cornerstone, with introduced feature learning modules in our IRCResNet model. Experimental results show our model achieves an average prediction accuracy of 96.8574% on public datasets, thoroughly validating our approach and significantly enhancing plant leaf disease identification.

Sustainable hybrid education is an educational approach that combines multiple kinds of instruction. Online education and traditional face-to-face education will be implemented in tandem to propel the educational process towards contemporary approaches, with the aim of achieving high-quality outcomes and staying abreast of scientific and technical advancements. The objective of this study is to determine the correlation between hybrid education, which is a sustainable model, and the academic performance of graduate students in select Egyptian universities, based on international quality criteria. The study employed a descriptive analytical methodology, and data was collected using a meticulously designed computerized questionnaire, whose validity and reliability were verified using proper statistical techniques. The study sample comprised 2235 postgraduate students enrolled in Egyptian universities, specifically Cairo, Helwan, and Ain Shams. The study’s findings determined that the extent of hybrid education and the efficacy of the procedure. The sample members possess a high level of education, and hybrid education has a significant positive influence on the quality of the educational process. Hybrid education mostly impacts the academic components, and there are variations among universities in implementing hybrid education, with Ain Shams University being particularly favorable towards it. The study proposed enhancing the university’s human resources for students, faculty, and staff, as well as assuring the availability of diverse gadgets and resources utilized in the hybrid education setting.

In the context of big data, the era of educational informatization has fully arrived, making the influence of information technology on language disciplines not to be underestimated. This has promoted vocational English teaching from the original slide multimodal demonstration teaching to the multimodal teaching stage relying on micro courses, playing a good synergistic role in improving English teaching classrooms, innovating teaching reforms, and improving students' English listening, speaking, reading, and writing abilities.

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.

The study examines the factors shaping inflation in 2022–2023 and explores why inflation in the Hungarian economy has increased more sharply than in neighboring countries with similar structures. The research hypothesis suggests that the inflationary surge, which is notable both globally and within the European Union, is not solely due to market economy mechanisms, but also to specific circumstances in Hungary, including the state’s radical interventions aimed at curbing inflation. The study seeks to highlight these effects and provide recommendations for economic policymakers to develop a more resilient inflation policy. Additionally, it focuses on analyzing inflation in the agricultural sector. The results indicate that, alongside global inflationary pressures, several country-specific factors have driven up the inflation rate in Hungary. Energy prices have risen sharply, and some supply chains from the East have been disrupted. The country under study is less productive, and the impact of the energy price shock on the energy-intensive food industry is higher than in surrounding countries. Consequently, the exchange rate volatility in 2022–2023, combined with short- and medium-term factors, has had a significant impact on food inflation, causing substantial deviations from long-term equilibrium. The research concludes that, in addition to increasing food self-sufficiency, special attention should be given to the domestic development of the agricultural supply chain.