Recovering Supply Chain Disruptions in Post-COVID-19 Pandemic Through Transport Intelligence and Logistics Systems: India's Experiences and Policy Options

Abstract

Before the COVID-19 pandemic, Indian firms have focused on interconnected and lean supply chains to ameliorate the gaps through increased efficiency of supply chains. However, the pandemic has exposed most Indian firms to severe supply chain disruptions (SCDs) due to undiscovered supply chain vulnerabilities. Against this background, we reviewed the existing relevant literature on SCDs and transportation disruption in general context and pandemic specific context and identified that there exists very little research on this issue especially in the context of Indian firms, and offered policy options by developing a new model of robust transport and advanced logistics system (ALS) for speedier supply chains recovery (SCR). We have utilized and analyzed the rich available literature on SCDs, transport intelligence (TI), and ALS using gray literature. The study revealed that many Indian firms have experienced major disruptions in transportation and logistics services, including impact on transportation and logistics data, time delays, and cargo cancellations due to cramped freight capacity, restricted circulation, closure of ports, and slow customs clearances. This has also impacted adversely the production and transport consignments including logistics services and led to delays and rerouting to final consumers. With the gradual removal of restrictions, firms are making concerted efforts to recover from SCDs; however, with weak applications of robust TI and ALS, the SCR is relatively very slow. This called for a review of current transport and ALS used by priority firms. Therefore, we offered a new model for addressing the SCDs using robust intelligence transportation systems and ALS.