Social entrepreneurship (SE) had been introduced in the university as one of the efforts to nurture future social entrepreneurs. SE courses established at the university level with a combination of cooperation from the local community and industry give a more effective impact on the local community. The knowledge and skills taught from universities regardless of the academic or cultural background can be used to balance the social problems in the community with the development of social innovation to solve the issues. However, several challenges delayed further development of a successful SE programme in higher education. This research employs the systematic literature review (SLR) which utilizes in-depth and absolute evaluation of related literature on the research topic. Four challenges have been encountered include; the design of SE curricula, financial and funding problems, lack of professionals to teach SE courses, and prohibitive social and university environment issues. This research has also suggested some best practices include; more SE awareness programmes, university management in solving funding problems, preparing SE coaching professionals, and setting up more university-industry collaborations. This paper proposes suggestions to counter the challenges and leverage the social network as an innovative technological alternative and giving more opportunities for improved social benefits.

In its effort to modernize its public service delivery, Malaysia is actively leveraging on big data analytics. To support this ambitious initiative, a new framework addressing the needs of Big Data Quality for Malaysia is imperative, as big data analytics requires high quality data in order for it to be useful. Unfortunately, a proper big data quality framework, particularly one which focuses on the specific context and needs of Malaysia’s Public Sector Open Data initiative is missing. This paper thus focuses on the proposed development of the Big Data Quality Framework for Malaysia’s Public Sector Open Data Initiative (MyPS-ODI). Using Systematic Literature Review (SLR) approach, we conceptualize and propose a framework for big data quality that can contribute in enabling the sharing of quality data widely, so as to increase the transparency of the Malaysian government's services, and provide people and the business community the opportunity to increase creativity and innovation in developing new products and services through high quality data. The proposed framework will benefit IS managers in government sectors and help them better understand and meet their consumers’ data quality needs, as well as help them to facilitate big data analytics readiness of the public sector in the country. It will also assist in providing a high-quality platform to the citizens to get quality information from official government sources. Finally, the framework will help in saving the time and effort needed in correcting the results of data analysis due to poor data quality, by providing quality data from the data preparation stage.

Widely distributed misinformation shared across social media channels is a pressing issue that poses a significant threat to many aspects of society’s well-being. Inaccurate shared information causes confusion, can adversely affect mental health, and can lead to mis-informed decision-making. Therefore, it is important to implement proactive measures to intervene and curb the spread of misinformation where possible. This has prompted scholars to investigate a variety of intervention strategies for misinformation sharing on social media. This study explores the typology of intervention strategies for addressing misinformation sharing on social media, identifying 4 important clusters – cognition-based, automated-based, information-based, and hybrid-based. The study conducts a bibliometric analysis of 139 articles published from 2013-2023 using PRISMA method. A theme clustering method was used to develop the typology, and comparative analysis revealed patterns and evolution in the field. This provides valuable insights for both theory and practical applications. Overall, the study concludes that scholarly contributions to scientific research and publication help to address research gaps and expand knowledge in this field. Understanding the evolution of intervention strategies for misinformation sharing on social media can support future research that contributes to the development of more effective and sustainable solutions to this persistent problem.

Disaster Information Media in ASEAN Countries: A Paired Comparison Method

The rapid dissemination of information on social media has many positives but has also raised significant concerns regarding misinformation, making it crucial to understand the factors driving information-sharing behavior. This study employs the Elaboration Likelihood Model (ELM) with its dual processing pathways (central and peripheral route processing) to identify key information characteristics influencing information-sharing behavior on social media. Through Reflexive Thematic Analysis (RTA) of 92 viral tweets from three Malaysian news channels between January and October 2024, five key themes emerged: Social Interest, Political Interest, Visual Appeal, Credible Sources, and Emotional Appeal. Illustrative case studies of viral Malaysian tweets were analyzed, revealing how different information characteristics trigger varying cognitive processing routes. Our findings indicate that Social Interest and Political Interest align with central route processing, require deeper cognitive engagement. Conversely, Visual Appeal, Credible Sources, and Emotional Appeal follow the peripheral route processing, relying on heuristic cues. Importantly, many viral tweets engage mixed processing, highlighting the need for hybrid interventions. Building on these insights, the study offers practical guidance for stakeholders: policymakers can enforce regulations and promote awareness, platforms can add credibility markers and prioritize trusted sources, educators can teach media literacy, and users can adopt a “pause-and-verify” approach. Collectively, these efforts can help create a digital ecosystem that balances user engagement with accuracy in online information sharing.