The emergence of digital multi-sided platforms has disrupted day-to-day business in many industries. Nowadays, many small businesses participate in digital platform (DP) ecosystems and act as value creators or complementors. Investigating the small business perspective does not have a rich tradition in platform research yet. In response, this paper presents a systematic literature review (SLR) analyzing the thematic points of focus and highlighting new avenues for information systems and small business research. We find that objectives related to digital transformation, digital strategy- and business model-development, and DP adoption are fundamental topics in the conjunction of small business and DP ecosystems. Based on the findings, an agenda for future research is developed, including propositions for practice-oriented and human-centered approaches fostering sustilience, innovation capabilities and digital leadership competencies in small businesses facing DP ecosystem participation.
In European competition law, consumer protection agencies and competition authorities play a crucial role in ensuring fair competition. When a violation is identified by these institutions, they typically obtain a cease-and-desist declaration to ensure compliance with applicable laws. However, the manual verification of compliance is a time-consuming task, which poses a risk of companies continuing to engage in unlawful practices to the detriment of consumers. We propose a technology-enhanced solution to address this issue. Artificial Intelligence emerges as a transformative solution and Large Language Models now provide the potential for automation, replacing the need for manual completion of such tedious compliance checks. In our project KIVEDU, we aim to design an AI-based system that automates the enforcement of consumer rights. In this article, we present an overview of the current state of research, the planned project, the challenges we expect to encounter, and our initial results as well as planned next steps. With this work, our goal is to contribute to the enforcement of European consumer protection law, foster fair competition, and strengthen consumer rights.
The rapid advancements in Web 2.0 applications and artificial intelligence (AI) have significantly influenced the educational domain, introducing novel challenges for both educators and learners in online learning contexts. By continually learning and adopting innovative teaching methods, educators can cultivate enhanced learning experiences and collaboration between teachers and students. Effective strategies for delivering course content in online environments can further contribute to students’ satisfaction and in-depth understanding of the subject matter. This article aims to present a framework for educators to improve interaction with students, grounded in pertinent e-learning literature and supported by institutional research as it discusses the results of a pilot project designed to stimulate learning by tailoring it to students’ individual needs and maximizing the advantages of visual technologies in the learning process through gamification. Six courses on various subjects were developed, but this article focuses solely on a computer science course. The outcomes indicate visible improvements in student academic performance and satisfaction and that is to be seen over a comparison on two groups of students – with the second group beneficiating by a new way of delivering course materials.
News can distribute in many forms across social networks in a fragmented media landscape. Misinformation, such as conspiracy theories, can reach people on social media, leading them into polarized spaces. The consequences of this polarization can be a loss of trust in the media and the perception of news that only reflects one’s true or false beliefs. In the context of the COVID-19 pandemic, these beliefs could be that wearing masks is unnecessary. Scientific questions are often politicized and subjected to polarized discussions on social media. Yet, it needs to be clarified to what extent these public health questions are used for political purposes by partisan news channels. This study analyzed 13 ideologically diverse news channels, 11,293 news headlines, and 413,583 user-generated comments on the media coverage concerning COVID-19 on the YouTube platform. For method, wordfish is used to find identity ideology and polarisation and sentiment analysis is used for finding polarization. Results show that textual video information throughout most news channels on YouTube was hardly marked by ideological polarization, except on the Fox News channel. Furthermore, ideological polarization was more pronounced within the comment sections of those news channels and was characterized strongly by negative emotions.
Mob lynching is violent human behaviour where people punish someone without a legal trial. Lynching ends with a significant injury or death of a person. In the digital era, almost every piece of news, including the incident of mob lynching, is shared on social media. Once a case of mob lynching is shared on social media, it propagates to a wide range of audiences. This study uses quantitative and qualitative approaches to investigate mob lynching in India and discuss possible prevention measures through social media using two datasets, one collected from Twitter and another from a fact-checking website. The fact-checked data provides an overview of the cause and effect of mob lynching, while the tweets provide the current discussion and user response. The proposed analysis highlights frequent topics discussed on Twitter, user reactions to those posts, and their relation with historic mob lynching incidents. In the end, a prevention measure is proposed using a user study. The result shows that most tweets are of negative sentiment; tweets are more retweeted than likes. The topic modelling shows the tweets are asking for mob lynching and help. There is partial support for prevention measures, and there is a need for literacy, awareness, and strict law to control mob lynching in future.
