The Resonant Effect of Risks on Supply Chain Performance: A Covid-19 Perspective

Purpose – This paper investigates the resonant effect of risks on supply chain performance under COVID-19.

Design/methodology/approach – Eleven managers attended and applied the Q-sort method to evaluate the unidimensionality, reliability and validity of research Afterwards, a comparative model containing the single effects of risks on supply chain performance was developed as a basis for comparison with the theoretical. The impacts of each risk on supply chain performance were demonstrated in both models when the parameters of the theoretical model are greater than those in the competitive model, the resonant effect mechanism is proven and vice versa.

Findings – 63% variance of supply chain performance was explained by our risk model, which includes positive and negative resonant effects between It is a remarkable rate compared with the comparative model and previous studies. Whilst a positive relationship (α ≥ 0) increases the effect of the impacted risk on the output, a negative relationship (α ≤ 0) decreases this effect, bringing benefits for companies which “see” these. Thus, practitioners should treat risk as an opportunity rather than a threat.

Research limitations/implications – A positive optimal resonant model is necessary to maximize the impact of risks on supply chain Hence, companies can predict the worst-case scenario when six risks occur. However, companies can devise mitigating techniques if a negative optimal resonant model is. Although risks can not be eliminated, their impact is likely to be abated by using a new paradigm.

Originality/value – The data used in this research is from a large-scale survey supported by Japanese Government to promote ASEAN sustainable socio-economic This dataset collected during the Covid-19 pandemic to validate our models is an interesting and topical point of this study.

Paper type: Research paper

Risk management, supply chain management, supply chain risk management, supply chain