Impact of fake news on firm performance during COVID-19: an assessment of moderated serial mediation using PLS-SEM

Purpose: Fake news on social media about COVID-19 pandemic and its associated issues (e.g. lockdown) caused public panic that lead to supply chain (SC) disruptions, which eventually affect firm performance. The purpose of this study is to understand how social media fake news effects firm performance, and how to mitigate such effects. Design/methodology/approach: Grounded on dynamic capability view (DCV), this study suggests that social media fake news effects firm performance via SC disruption (SCD) and SC resilience (SCR). Moreover, the relation between SCD and SCR is contingent upon SC learning (SCL) – a moderated mediation effect. To validate this complex model, the authors suggest effectiveness of using partial least squares structural equation modeling (PLS-SEM). Using an online survey, the results support the authors’ hypotheses. Findings: The results suggest that social media fake news does not affect firm performance directly. However, the authors’ serial mediation test confirms that SCD and SCR sequentially mediate the relationship between social media fake news and firm performance. In addition, a moderated serial mediation test confirms that a higher level of SCL strengthens the SCD–SCR relationship. Research limitations/implications: This work offers a new theoretical and managerial perspective to understand the effect of fake news on firm performance, in the context of crises, e.g. COVID-19. In addition, this study offers the advancement of PLS as more robust for real-world applications and more advantageous when models are complex. Originality/value: Prior studies in the SC and marketing domain suggest different effects of social media fake news on consumer behavior (e.g. panic buying) and SCD, respectively. This current study is a unique effort that investigates the ultimate effect of fake news on firm performance with complex causal relationships via SCD, SCR and SCL.