Restructuring Global Supply Chains: Navigating Challenges of the COVID-19 Pandemic and Beyond
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Problem definition: The COVID-19 pandemic imposed unprecedented stresses on global supply chains (GSCs), compelling companies to reassess their supply chain structures and strategies. This crisis has also heightened awareness among businesses, consumers, and policymakers about the critical importance and far-reaching implications of GSC design and management. This unique moment presents a generational opportunity for Operations Management (OM) researchers to document and understand the ongoing restructuring of GSCs. Methodology/results: By analyzing microlevel data on U.S. customs import shipments (2019–2021), we uncover shifts in GSC strategies during the COVID-19 pandemic. Firms diversified suppliers within existing sourcing locations and reallocated volumes among them. Whereas dependence on China decreased, imports from other Asian nations like India and Vietnam, as well as North American countries like Canada and Mexico, increased. Industry-specific differences were pronounced, and a notable shift toward lower-frequency, higher-quantity shipments was also observed. Managerial implications: Beyond the challenges of COVID-19, recent years have witnessed other major supply chain disruptions, due to causes such as geopolitical tensions, natural disasters, and port worker strikes. We offer actionable insights for executives designing supply chain strategies to prepare for similar disruptions as they increase in frequency and severity. We identify future research avenues aimed at enhancing the resilience and adaptability of GSCs in a continuously evolving environment. Supplemental Material: The online appendix is available at https://doi.org/10.1287/msom.2024.0879 .
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it