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.

In the last decade, food and drink supply chain management has become an important part of global operations strategy. The global food and drink industries (FDIs) is establishing supply chain operations across countries as a result of increasing demand, this expansion has created challenges in coordinating operations that connect multi-suppliers, one as such is the financial enabler for the multi-layered supply chain network. However, literature on artificial intelligence (AI) in FDIs is limited, this study explores AI theory in supply chain networks and alternative supply chain financing for the FDIs. This study proposes a new conceptual framework based on theoretical contributions identified through literature, a conceptual framework is established and further developed to a meta-framework. This study explored the set-theoretic comparative approach for data analysis, the outcomes of this research suggest that the probable contributions of supply chain networks driven by AI technologies provide a sustainable financing stream for the food and drink supply chain.

Supply chain finance (SCF) is receiving increasing awareness in research as a result of uncertainties in the global financing for supply chain (SC). There are limited and fragmented studies in the implementations of financial services in SC management. This article builds on recovery from the financial crisis of 2008 and posts COVID-19 pandemic, where uncertainties crippled SCF providers and brokers services. At the same time, cutting-edge technological advancements such as Artificial Intelligence (AI) are revolutionizing the processes of business ecosystem in which SCF is entrenched. This article thus adopts a fuzzy set theoretical approach to unpack the entities relationship validity for sustainable SCF mate-framework, and the originality of AI concepts to sustainable SCF to identify the issues and inefficiencies. The results indicate that AI contributes significant economic opportunities and deliver the most effective utilization of the supply networks. In addition, the article provides a theoretical contribution to financing in SC and broadens the managerial implications in improving performance.

The increasing use of digital technologies has significantly reshaped marketing and consumer behavior (CB) as online communities and cutting-edge innovations such as artificial intelligence (AI) disrupt and advance consumer attitudes on specific products and services. As such, online communities that are supported by AI technologies creating new knowledge from consumer interactions through platforms like social media as consumers share experiences on specific products or services. Since AI is designed to “learn” and improve with data generated from digital technologies linked to consumer interactions, AI relies on consumer knowledge-sharing (KS) activities to replicate new knowledge for product and service improvement. However, given the knowledge gap in this area, this article applies the fsQCA technique to data generated from 291 participants to develop CB metaframework predicted on the concepts of AI, CB, and KS. Our results suggest that AI advances consumer attitudes and behaviors when knowledge is acquired while online communities promote curiosity and engage consumers to learn by sharing experiences about specific products or services. Furthermore, understanding the causality between AI, CB, and KS concepts offers critical decision-making insights to marketing experts across the industry.

This study explores the factors that influence the dissemination process of and public susceptibility to fake news amidst COVID-19. By adopting a qualitative approach that draws on 21 interviews with social media users from the standpoint of source credibility and construal level theories, our findings highlight motives of news sharers, platform features, and source credibility/relatedness as major factors influencing the dissemination of and public susceptibility to fake news. The paper further argues that public susceptibility to fake news can be mitigated by building an integrated approach that combines a tripartite strategy from an individual, institutional and platform level. For example, educating the public on digital resilience and enhancing awareness around source credibility can help individuals and institutions reflect on news authenticity and report fake news where possible. This study contributes to fake news literature by integrating concepts from information management, consumer behaviour, influencer marketing and mindfulness to propose a model to help authorities identify and understand the key factors that influence susceptibility to fake news during a public crisis such as COVID-19.