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

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 of Indian firms to severe supply chains 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 grey literature. The study reveals 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 gradual removal of restrictions, firms are making concerted efforts to recover from SCDs, however, weak applications of robust TI and advanced ALS, the SCR is relatively very slow. This calls for reviewing current transport and ALS used by firms on priority. Therefore, we offered a new model for addressing the SCDs using robust intelligence transportation systems and ALS.