ABSTRACT
Purpose>The COVID-19 pandemic has badly affected the global economy. The use of social capital as a resource to diversify agribusiness to get more customers and improve the agricultural supply chain is a considerable issue to explore. This study aims to develop a comprehensive measurement of social capital and examine its effect on the intention to diversify agribusiness. From a supply chain perspective, it uses theory of planned behavior (TPB) and resource-based view (RBV).Design/methodology/approach>The study uses a mixed-methods approach. In-depth interviews, focus group discussions and surveys are used. Structural equation modeling on a sample of 465 respondents in Vietnam was employed to examine the hypothesized relationships.Findings>An integrative measurement scale of social capital from an agricultural supply chain perspective is suggested. The study also shows significant causal relationships amongst social capital, motives, TPB's determinants and the intention to diversify agribusinesses in light of supply chain perspectives.Originality/value>The study offers a significant contribution to the existing body of knowledge in the literature on social capital, motives, TPB, RBV and supply chain perspectives. The study was executed in Vietnam, where most farmers are smallholders, family business owners or micro-scale entrepreneurs in agriculture.
ABSTRACT
Hydroxychloroquine (HCQ) is used to prevent or treat malaria caused by mosquito bites. Recently, the drug has been suggested to treat COVID-19, but that has not been supported by scientific evidence. The information regarding the drug efficacy has flooded social networks, posting potential threats to the community by perverting their perceptions of the drug efficacy. This paper studies the reactions of social network users on the recommendation of using HCQ for COVID-19 treatment by analyzing the reaction patterns and sentiment of the tweets. We collected 164,016 tweets from February to December 2020 and used a text mining approach to identify social reaction patterns and opinion change over time. Our descriptive analysis identified an irregularity of the users' reaction patterns associated tightly with the social and news feeds on the development of HCQ and COVID-19 treatment. The study linked the tweets and Google search frequencies to reveal the viewpoints of local communities on the use of HCQ for COVID-19 treatment across different states. Further, our tweet sentiment analysis reveals that public opinion changed significantly over time regarding the recommendation of using HCQ for COVID-19 treatment. The data showed that high support in the early dates but it significantly declined in October. Finally, using the manual classification of 4,850 tweets by humans as our benchmark, our sentiment analysis showed that the Google Cloud Natural Language algorithm outperformed the Valence Aware Dictionary and sEntiment Reasoner in classifying tweets, especially in the sarcastic tweet group.
Subject(s)
COVID-19ABSTRACT
In this study, we present a general formulation for the optimal control problem to a class of fuzzy fractional differential systems relating to SIR and SEIR epidemic models. In particular, we investigate these epidemic models in the uncertain environment of fuzzy numbers with the rate of change expressed by granular Caputo fuzzy fractional derivatives of order ß ∈ (0, 1]. Firstly, the existence and uniqueness of solution to the abstract fractional differential systems with fuzzy parameters and initial data are proved. Next, the optimal control problem for this fractional system is proposed and a necessary condition for the optimality is obtained. Finally, some examples of the fractional SIR and SEIR models are presented and tested with real data extracted from COVID-19 pandemic in Italy and South Korea.