Lessons learnt from COVID-19 vaccine operations and distribution performance: challenges and resilience strategies

Purpose: Grounded in dynamic capability view, this research develops a decision support model, which enables determining consistent and sufficient configurations of resilience strategies to mitigate vaccine operations and distributions (O&D) challenges and thus improve O&D performance (i.e. O&DP). Design/methodology/approach: Through qualitative in-depth interviews, the authors first identified challenges and resilience strategies related to vaccine O&D. Next, using the quality function deployment technique, three quantitative case studies were performed to determine the most important challenges and resilience strategies. Finally, utilising fuzzy set qualitative comparative analysis, the authors determine sufficient conditions of challenges and strategies leading to improve vaccine O&DP. Findings: The findings reveal that strategies alone are not effective instead a combination of strategies and nullification of challenges is needed to enhance vaccine O&DP. Further, the findings revealed that not only the presence of challenges, but also the lack of strategies reduces the vaccine O&DP. Practical implications: The authors' findings will assist the health service decision-makers for strategizing an effective and efficient vaccination program by selecting the right combination of challenges and resilience strategies. Originality/value: The authors' study develops a novel decision support model and offers significant learning for the future vaccine O&DP. © 2023, Emerald Publishing Limited.

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

PurposeFake 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/approachGrounded 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.FindingsThe 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/implicationsThis 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/valuePrior 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.