The onset of the COVID-19 pandemic generated an unusually rapid and multidisciplinary research response to global supply chain disruption. Individual studies addressed emerging challenges across healthcare, logistics, economics, manufacturing, information systems, public policy, sustainability, and related fields, yet the higher-order conceptual relationships connecting these independently developed research streams were difficult to identify through conventional literature review. This study examines 148 peer-reviewed publications from the first 18 months of the pandemic using bibliometric and linguistic Semantic Link Analysis to identify prevalent concepts, semantic relationships, conceptual clusters, contextual absences, and emerging research fronts. The resulting networks reveal substantial convergence across disciplinary boundaries around supply chain disruption, resilience, digitalization, technological adaptation, governance, global supply relationships, and organizational response. Technologies including artificial intelligence, the Internet of Things, and dynamic data-driven systems emerge not as isolated innovations but as complementary elements within an increasingly integrated supply chain orientation. The analysis also identifies persistent gaps involving equitable resource distribution, worker protections, trust, and digital transparency. Empirically, the findings demonstrate how independently developed pandemic research converged toward a common conceptual architecture for understanding supply chain adaptation. Methodologically, the study demonstrates the value of Semantic Link Analysis for identifying latent relationships within rapidly expanding multidisciplinary research corpora and establishes a replicable foundation for longitudinal analysis of how research networks evolve following large-scale disruption.