Can information sharing predict fresh produce supply chain performance amid the COVID-19 pandemic? A social learning perspective

Abstract

PurposeThis research aims to provide a predictive model assessment on the effect of information sharing on fresh produce supply chain (FPSC) performance during the COVID-19 pandemic by incorporating information quality as an important part of information sharing, as well as cognitive and affective appraisals as part of a social learning process (mediators) into the model.Design/methodology/approachAn online survey was conducted on 197 small fresh produce (fruits and vegetables) retailers in Indonesia during the COVID-19 pandemic. The data were analysed using Partial Least Squares Structural Equation Modeling (PLS-SEM) particularly PLSpredict supported by SmartPLS 4 software.FindingsThis research reveals that information sharing is positively and significantly associated with information quality and that the two constructs are not directly associated with FPSC performance. The path analysis suggests that the effect of information sharing on FPSC performance is fully mediated by cognitive and affective appraisals to the information-sharing activity. It also suggests that the effect of information quality on FPSC performance is fully mediated by affective rather than cognitive appraisal. This model shows a high predictive power and highlights the pivotal role of the learning process during the COVID-19 pandemic.Originality/valueThis research is the first to employ a predictive model assessment in PLS-SEM to empirically predict the effect of information sharing on FPSC performance using a social learning perspective, particularly in the context of the COVID-19 pandemic.