This study investigates the impact of digital payment infrastructure accessibility on the social influence of microenterprises in Barranquilla, Colombia, while examining the mediating roles of financial inclusion, digital literacy, social support networks, and collaboration with social innovation initiatives. Employing a mixed-methods approach, the study analyzes data from a sample of 25 microenterprises operating in various sectors. The findings, based on statistical techniques such as multiple regression, path analysis, and structural equation modeling (SEM), provide strong evidence for the positive influence of digital payment infrastructure accessibility on the social relationship of microenterprises. The results also highlight the crucial roles played by financial inclusion and social support networks in mediating this relationship. The study contributes to the growing body of literature on the factors driving the social effect of microenterprises and offers valuable insights for policymakers and practitioners aiming to foster inclusive economic development in the region. The findings suggest that investing in the development and expansion of digital payment systems, alongside efforts to promote financial inclusion and strengthen social support networks, can have far-reaching benefits for microenterprises and their communities.

Considering the role of tourism in promoting sustainable practices in destinations, this study aims to map the scientific literature on footprint calculators in the last three years (2020–2023) with a focus on the tourism context. The method adopted is a scoping review with a qualitative and exploratory approach, using the Scopus database. The originality of this research lies in the study of publications related to footprint calculators with a focus on the tourism sector. Based on the analysis carried out, the main results show that the study of footprint calculators applied to the tourism sector has had little prominence in the indexed research in the Scopus database during the specific period considered for this study. Consequently, the conclusion of the study highlights the marginality of the tourism sector in the discussion of footprint calculators in the last 3 years of scientific publications.

Indonesia’s stock market has seen an increase in investment due to the ease of investing and the availability of information about stocks on different social media platforms. This research uses a social network approach to analyze overconfidence behavior in millennial stock investors. This research uses a descriptive quantitative method. The population used in this study are capital market investors in the Greater Solo area who are millennials (<30 years). The number of stock investors in the Greater Solo area is 60,542 investors. The sampling technique in this study was non-probability sampling using purposive sampling. This research uses the AMOS SEM (Structural Equation Model) analysis tool. The conclusion of this study is that millennial investors’ overconfidence behavior increases influenced by financial literacy. investor skills. family ties and friendship ties. The contribution of this research can be applied to understand and educate millennial investors in order to overcome overconfidence behavior so that they can anticipate the losses received. This research may have implications for improving Behavioral Finance Integration Incorporating insights from behavioral finance into investment strategies can help mitigate the negative effects of overconfidence. The limitation in this study is that the scope used in the study is only in the greater solo area.

Social media influencer marketing has emerged as an essential marketing strategy in the online interactive environment. This study investigates the impact of influencer-consumer fit (ICF) on behavioral intentions; intention to co-create brand value (ICC) and purchase intention (PI), with the serial mediation of influencer authenticity (IA) and attitude toward brand (ATB). A self-administered questionnaire was distributed to followers of social media influencers in Pakistan. The data were collected from 421 female followers of social media influencers through survey and partial least squares—structural equation modeling was used for data analysis. The findings reveal that ICF impacts IA, while the latter impacts ATB. ATB in turn impacts behavioral intentions. The direct effects suggest that ICF impacts consumers’ PI but not the ICC. However, with the serial mediation of IA and ATB, the relationship becomes significant. The findings of this study may assist managers in building brand strategies to achieve excellence in a highly dynamic and competitive market by leveraging the power of influencer marketing.

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.