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PurposeDuring the past few years, the rise in social media use for information purposes in the absence of adequate control mechanisms has led to growing concerns about the reliability of the information in circulation and increased the presence of fake news. While this topic has recently gained researchers' attention, very little is known about users' fake news identification behavior. Hence, the purpose of this study is to understand the factors that contribute to individuals' identification of fake news on social media.Design/methodology/approachThis study employs a quantitative approach and proposes a behavioral model that explores the factors influencing users' identification of fake news on social media. It relies on data collected from a sample of 211 social media users which is tested using SEM.FindingsThe findings show that expertise in social media use and verification behavior have a positive impact on fake news identification, while trust in social media as an information channel decreases this identification behavior. Furthermore, results establish the mediating role of social media information trust and verification behavior.Originality/valueThe present study enhances our understanding of social media users' fake news identification by presenting a behavioral model. It is one of the few that focuses on the individual and argues that by identifying the factors that reinforce users' fake news identification behavior on social media, this type of misinformation can be reduced. It offers several theoretical and practical contributions.

PurposeCryptocurrencies such as bitcoins represent a novel method of conducting financial transactions and exchanging money. However, their adoption by the general public remains low. Within countries facing financial distress and characterized by a high level of risk, cryptocurrency adoption might offer opportunities for countering crises. The purpose of this study is to explore the factors that influence individuals' adoption of cryptocurrencies for financial transactions within a high-risk context.Design/methodology/approachTo do so, it presents a behavioral model, which is tested using data collected from a survey of 255 respondents residing in Lebanon. The causal relationships between the different factors and individuals' willingness to use cryptocurrencies were then analyzed through Structural Equation Modeling.FindingsFindings show that financial technology awareness and social influence contribute to reducing perceived risk and increasing individuals' willingness to use cryptocurrencies, while individuals' risk aversion and the presence of regulatory support increase the perceived risk of cryptocurrencies.Originality/valueThe study is among the first to use a human-centered approach to understanding cryptocurrency adoption and takes place within a country that is facing a deep financial crisis. Its outcomes contribute to existing theories of cryptocurrency adoption and provide policymakers with insight into how adoption is unfolding namely in developing countries.

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