This research aims to understand how farmers, especially those with limited technological knowledge, utilize social media in their agricultural activities. The study also aims to identify the impact and responses of farmers to the use of social media in their agricultural practices. Additionally, the research discusses a conceptual framework that integrates internal and external factors in understanding social media user behavior. The research methodology employed is a systematic literature review using scientometric analysis. Bibliometric approaches, machine learning, and social network analysis are utilized to achieve research objectives. Data were obtained from the Scopus database, consisting of high-quality articles published between 2011 and 2023.The findings indicate that social media plays a significant role in influencing farmers' responses to the information they receive and their levels of trust, subsequently affecting their willingness to adopt smart agricultural technologies. Furthermore, the research highlights internal and external factors influencing social media user behavior in the agricultural context. The novelty of this research lies in its holistic approach that integrates cognitive and behavioral factors in understanding social media user behavior. Additionally, the study complements previous literature by addressing antecedents, mechanisms, and consequences of social media use by farmers, as well as identifying barriers they face in leveraging social media.

The outbreak of the Covid-19 pandemic and the introduction of Society 5.0 by the Japanese government in 2019 have resulted in significant changes to consumer behavior. The aim of this research is to examine the impacts of consumption value on customers' behavioral shifts. Furthermore, quantitative methods were used with a sample of 344 respondents, and data analysis using the structural equation model with the Lisrel 8.72 application. The stages in the structural equation analysis of this model are: development of theoretical models, development of path diagrams, conversion of path diagrams to structural equations, selecting input matrices and types of estimates, identifying models, assessing goodness of fit criteria, and interpreting results. The results obtained showed that consumers' attitudes and habits toward utilizing meal delivery applications can be influenced by factors such as their social, conditional, emotional, epistemic, and functional values. In the use of food delivery applications, consumers are not only interested in tangible benefits, but also in less tangible benefits, such as information provided by businesses.