Amal Dabbous, Karine Aoun Barakat and May Merhej Sayegh
As artificial intelligence (AI) has become increasingly popular and accessible, most companies have recognized its far-reaching potential. However, despite numerous research…
Abstract
Purpose
As artificial intelligence (AI) has become increasingly popular and accessible, most companies have recognized its far-reaching potential. However, despite numerous research papers on organizational adoption of new technologies including AI, little is known about individual employees’ intentions to use them. Given that organizational innovations are of limited value if they are not adopted by employees, the purpose of this study is to understand the underlying factors that push employees to make use of these new technologies in the workplace.
Design/methodology/approach
This study builds on previously developed technology acceptance models to provide a new theoretical model. The model is then tested using data collected from a survey of 203 employees and analyzed through structural equation modeling.
Findings
Findings show that five factors affect employees’ intention to use AI either directly or as mediators. Organizational culture and habit exert a positive impact on employees’ intention to use AI, whereas job insecurity has a negative impact. Perceived self-image and perceived usefulness fully mediate the relation between job insecurity and intention to use. Moreover, perceived self-image and perceived usefulness partially mediate the relationship between habit and intention to use.
Originality/value
To the best of the authors’ knowledge, this study is among the first to determine the factors that influence employees’ intention to use AI in general and more particularly chatbots within the workplace.
Details
Keywords
Karine Aoun Barakat, Amal Dabbous and Abbas Tarhini
During 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…
Abstract
Purpose
During 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/approach
This 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.
Findings
The 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/value
The 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.
Details
Keywords
Amal Dabbous, May Merhej Sayegh and Karine Aoun Barakat
Cryptocurrencies such as bitcoins represent a novel method of conducting financial transactions and exchanging money. However, their adoption by the general public remains low…
Abstract
Purpose
Cryptocurrencies 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/approach
To 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.
Findings
Findings 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/value
The 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.
Details
Keywords
Amal Dabbous and Karine Aoun Barakat
The spread of fake news represents a serious threat to consumers, companies and society. Previous studies have linked emotional arousal to an increased propensity to spread…
Abstract
Purpose
The spread of fake news represents a serious threat to consumers, companies and society. Previous studies have linked emotional arousal to an increased propensity to spread information and a decrease in people’s ability to recognize fake news. However, the effect of an individual’s emotional state on fake news sharing remains unclear, particularly during periods of severe disruptions such as pandemics. This study aims to fill the gap in the literature by elucidating how heightened emotions affect fake news sharing behavior.
Design/methodology/approach
To validate the conceptual model, this study uses a quantitative approach. Data were collected from 212 online questionnaires and then analyzed using the structural equation modeling technique.
Findings
Results of this study show that positive emotions have indirect effects on fake news sharing behavior by allowing users to view the quality of information circulating on social media in a more positive light, and increasing their socialization behavior leading them to share fake news. Negative emotions indirectly impact fake news sharing by affecting users’ information overload and reinforcing prior beliefs, which in turn increases fake news sharing.
Research limitations/implications
This study identifies several novel associations between emotions and fake news sharing behavior and offers a theoretical lens that can be used in future studies. It also provides several practical implications on the prevention mechanism that can counteract the dissemination of fake news.
Originality/value
This study investigates the impact of individuals’ emotional states on fake news sharing behavior, and establishes four user-centric antecedents to this sharing behavior. By focusing on individuals’ emotional state, cognitive reaction and behavioral response, it is among the first, to the best of the authors’ knowledge, to offer a multidimensional understanding of individuals’ interaction with news that circulates on social media.
Details
Keywords
Xinyue Zhou, Zhilin Yang, Michael R. Hyman, Gang Li and Ziaul Haque Munim