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This document provides a summary of a special issue that focuses on the effects of fake news and misinformation on information management practices during times of crisis, with a particular emphasis on the COVID-19 pandemic. The authors highlight the importance of reliable information and the negative impacts of fake news on decision-making and crisis management. They propose that digital resilience and mindfulness can be used to mitigate the effects of misinformation and improve recovery from crises. The document outlines three main challenges related to fake news and suggests that advanced technologies, such as AI and data analytics, can be used to combat fake news and support decision-making. The special issue includes ten papers that explore various topics related to digital resilience and mindfulness, clustered around three thematic areas: data management, diffusion of fake news, and the implications of fake news and misinformation. The papers discuss concepts such as mindful data, biases in data analysis, social media's role in spreading fake news, and the use of mindfulness and digital resilience to mitigate the effects of fake news. The document concludes by suggesting areas for further research, including the impact of fake news on businesses and supply chains and the potential role of emerging technologies in combating misinformation. [Extracted from the article]

Fake news (FN) on social media (SM) rose to prominence in 2016 during the United States of America presidential election, leading people to question science, true news (TN), and societal norms. FN is increasingly affecting societal values, changing opinions on critical issues and topics as well as redefining facts, truths, and beliefs. To understand the degree to which FN has changed society and the meaning of FN, this study proposes a novel conceptual framework derived from the literature on FN, SM, and societal acceptance theory. The conceptual framework is developed into a meta-framework that analyzes survey data from 356 respondents. This study explored fuzzy set-theoretic comparative analysis; the outcomes of this research suggest that societies are split on differentiating TN from FN. The results also show splits in societal values. Overall, this study provides a new perspective on how FN on SM is disintegrating societies and replacing TN with FN. [ABSTRACT FROM AUTHOR]

Supply chain risk management (SCRM) literature is heterogeneous. While much attention has been given to the economic and environmental dimensions, the social dimension has so far received less focus. Thus, this study analyzes the social risks involved in the agri-food supply chains (AFSCs) of Argentina and China by employing an integrated approach. Semi-structured interviews were used to collect data, followed by using a combination of three complementary data analysis methods: thematic analysis to identify social risks, total interpretive structural modeling (TISM) to build interrelationships among the identified social risks, and fuzzy MICMAC (cross-impact matrix multiplication applied to classification analysis) to cluster social risks into four categories. Next, we conducted a comparative analysis between the two countries. Theoretical contributions are mainly threefold. First, we identified various social risks involved in the AFSCs of Argentina and China, including those just touched on by scholars, such as cultural issues, government’s weak monitoring system, the power differential between managers and subordinates, inappropriate disposal of agrichemical containers, and the lack of basic literacy skills. Second, we believe that our study is the first to establish connections among the identified AFSC social risks, which represents the originality of this work. Third, we discover that cultural issues is the key risk that has the highest capability to elicit other social risks involved in the AFSCs. Our work extends scholarship’s knowledge to understand AFSC social risks from the cultural perspective. This study also generates contributions to policymakers, migrant associations, and the government tax departments of Argentina and China. [ABSTRACT FROM AUTHOR]