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Uncertainties and risks play a central role in creating vulnerabilities for logistics service operations. Over the years, Logistic Service Providers (LSPs) have learned how to ensure resilience to confront uncertainties and risks triggered by adverse events. However, quite unlike any seen in recent times, the COVID-19 pandemic brings about unavoidable uncertainties and risks for the logistics industry. Yet, there is no common approach to contextualize how they interact together. We incorporate an empirical research design and make a threefold contribution: first, we identify uncertainties and risks that LSPs encounter during the COVID-19 pandemic and investigate their prominence. Second, we unveil intertwined schemes of afore-identified uncertainties and risks and augment the understanding of their cause-effect structure. Third, we provide an uncertainty and risk assessment guideline for LSPs affected by threats emerging from unforeseeable crises. In this study, we combine qualitative work and the fuzzy DEMATEL method. Qualitative thematic analysis of in-depth interviews reveals the most important uncertainties (COVID-19 measures, employee welfare, forecast horizon, demand change, and government regulations) and risks (COVID-19 risk, delivery delays, supply chain disruptions, financial failure, and product returns) for LSPs. The fuzzy DEMATEL method shows that COVID-19 measures and COVID-19 risk are highly prominent and influence other factors. The results indicate that demand change, government regulations, and supply chain disruptions are net causers, and employee welfare, financial failure, forecast horizon, delivery delays, and product returns are net receivers. Distinctly, employee welfare is the most affected factor, empirically confirming that major risks for LSPs are related to the human factor. More investigation in our results suggests that supply chain disruptions and demand change, two factors triggered by the COVID-19 pandemic, influence financial failure and forecast horizon, two factors associated with operational performance. |
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