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Because prior knowledge may not generalize to the COVID-19 setting, scholars are racing to test the efficacy of existing theoretical frameworks during COVID-19. Most business studies are conceptual or surveys of damage. The main purpose of the paper is to extend the forthcoming stream that tests firm performance by examining it during COVID-19. We examine the sales growth of 1298 US manufacturers during COVID-19 compared to their pre-COVID-19 baselines. Riskier firms with higher R&D intensities performed better during COVID-19, especially when cash-to-inventory levels were low. This study is among the first to empirically identify actionable predictors of firm performance during COVID-19 via a quantitative analysis of strategies and performance outcomes. Understanding what type of firms perform at higher levels during COVID-19 will help decision makers make more informed decisions moving forward. Employing ordinary least squares (OLS) regression to test our hypotheses, our findings suggest that R&D intensive firms should pivot tactically regarding current asset management, if needed, but not strategically, while prioritizing inventory versus cash retention. The positive effect of inventory versus cash extends theory by suggesting a new boundary condition related to pandemics that reverses the positive link between cash and performance found during crises with more conventional levels of turbulence. Our most important contribution, however, is practical, via the testing of predictors that can help firms during COVID-19. For example, we found that firms with higher levels of operating risk experienced 60 percent more sales growth than risk-averse firms. This knowledge that risk-taking predicted performance during COVID-19 (especially when coupled with a focus on R&D intensity and inventory level) may encourage those that can adopt less risk-averse strategies, while others focus on tactical adjustments or mitigative measures during COVID-19 and future black swan events.
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Papers that cite the same references — the relational fallback while embeddings are still backfilling.
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