Entrepreneurship education plays a crucial role in improving college students' entrepreneurial skills. With the significant momentum gained by digital entrepreneurship, there is an urgent need for digital transformation in entrepreneurship education. However, entrepreneurship education digital transformation (EEDT) is developing in a rapid but fragmented manner, which requires more systematic guidance. This study aims to assess the current research themes and formulate a framework for entrepreneurship education digital transformation. The research employs a systematic literature review and a theory triangulation method. According to the review’s outcome, which focused on 56 articles published between 2018 and 2023, the researcher constructed a conceptual framework for entrepreneurship education digital transformation. To test the construct validity of the framework, the researcher modified it twice through theory triangulation, following the guidelines of the entrepreneurship education ecosystem theory and the education digital transformation framework. This study offers recommendations for research and practice in digital transformation of entrepreneurship education, encompassing a holistic strategy, new educational approaches, novel curriculum designs, and the enhancement of digital literacy among entrepreneurship teachers.
Countering cyber extremism is a crucial challenge in the digital age. Social media algorithms, if designed and used properly, have the potential to be a powerful tool in this fight, development of technological solutions that can make social networks a safer and healthier space for all users. this study mainly aims to provide a comprehensive view of the role played by the algorithms of social networking sites in countering electronic extremism, and clarifying the expected ease of use by programmers in limiting the dissemination of extremist data. Additionally, to analyzing the intended benefit in controlling and organizing digital content for users from all societal groups. Through the systematic review tool, a variety of previous literature related to the applications of algorithms in the field of online radicalization reduction was evaluated. Algorithms use machine learning and analysis of text and images to detect content that may be harmful, hateful, or call for violence. Posts, comments, photos and videos are analyzed to detect any signs of extremism. Algorithms also contribute to enhancing content that promotes positive values, tolerance and understanding between individuals, which reduces the impact of extremist content. Algorithms are also constantly updated to be able to discover new methods used by extremists to spread their ideas and avoid detection. The results indicate that it is possible to make the most of these algorithms and use them to enhance electronic security and reduce digital threats.
The study is focusing on cyberspace—a new type of space mastered by humans with the help of digital technologies. This systematic review uses SPAR-4-SLR protocol to analyze over 30 years of scholarly research indexed in Scopus database, highlighting five time periods: before 1995, 1996–2008, 2009–2012, 2013–2019, and after 2020. A final sample of 6645 publications in social sciences, Business, management and accounting (BMA), and Economics, econometrics and finance (EEF) was analyzed across multiple parameters, including: chronology, types of documents, sources, countries, institutions, authors, topics, and most cited publications. The review has systematized information about the most influential organizations and individuals involved in cyberspace research. First of all, these are researchers from the United States, the United Kingdom, and China. Key journals that publish research on the topic have been identified, and a ranked list of funding organizations supporting research on the social and economic aspects of cyberspace are identified. The study provides insights into the achievements of the social and economic sciences in cyberspace over the past 30 years. The results will be useful to scholars who seek for a general overview on the topic of cyberspace, as well as experts and policymakers developing mechanisms and tools for regulating cyberspace as a mixture of the virtual and real worlds.
The presence of a crisis has consistently been an inherent aspect of the Supply Chain, mostly as a result of the substantial number of stakeholders involved and the intricate dynamics of their relationships. The objective of this study is to assess the potential of Big Data as a tool for planning risk management in Supply Chain crises. Specifically, it focuses on using computational analysis and modeling to quantitatively analyze financial risks. The “Web of Science—Elsevier” database was employed to fulfill the aims of this work by identifying relevant papers for the investigation. The data were inputted into VOS viewer, a software application used to construct and visualize bibliometric networks for subsequent research. Data processing indicates a significant rise in the quantity of publications and citations related to the topic over the past five years. Moreover, the study encompasses a wide variety of crisis types, with the COVID-19 pandemic being the most significant. Nevertheless, the cooperation among institutions is evidently limited. This has limited the theoretical progress of the field and may have contributed to the ambiguity in understanding the research issue.
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