Intellectual capital and supply chain resilience

2021 
Purpose: The main objective of this study is to test whether firms with a higher level of intellectual capital (IC) perform better in terms of their supply chain resilience compared to those with lower levels of IC Likewise, the study also examines the impact of IC (characterized by human capital, relational capital and structural capital) on supply chain resilience directly and through supply chain learning Design/methodology/approach: Data were collected from the 159 processed-food sector firms using a close-ended questionnaire during the corona virus 2019 (COVID-19) pandemic Partial least squares structural equation modelling (PLS-SEM), partial least squares multigroup analysis (PLS-MGA) and one-way analysis of variance (ANOVA) were used to test a set of hypotheses emanating from a conceptual model of IC and supply chain resilience Findings: Empirical results revealed a significant influence of all dimension of IC on a firm's supply chain learning and supply chain resilience Likewise, findings also exhibit a momentous role of supply chain learning in reinforcing the impact of IC on supply chain resilience Cross-firm size comparison reveals that supply chain resilience of firms with a higher level of IC performed significantly better than those with lower levels of IC Firms with a higher level of structural capital had a highly resilient supply chain Practical implications: Findings of the study imply that IC and supply chain learning should be considered as a strategic tool and should be strategically developed for uplifting a supply chain performance of a firm The development of IC and supply chain learning (SCL) not only improves the supply chain resilience of a firm but also can help to integrate the internal and external knowledge for harnessing supply chain resilience Originality/value: This research study was conducted during the COVID-19 pandemic which provides a unique setting to examine resiliency and learning © 2021, Emerald Publishing Limited
    • Correction
    • Source
    • Cite
    • Save
    • Machine Reading By IdeaReader
    85
    References
    12
    Citations
    NaN
    KQI
    []