Beschreibung:
The COVID-19 pandemic has highlighted the importance of corporate resilience in the face of sudden and severe shocks to the global economy. In response, there has been renewed interest in studying the capabilities that enable firms to weather such crises. Previous studies have identified a range of capabilities that contribute to resilience, but these have typically been studied in isolation, using traditional regression techniques, and without clear tie with external environment. In this paper, we extend the literature by demonstrating a portfolio effect through major capability bundles, using an ensemble of machine learning techniques that predict resilience more accurately than traditional regression techniques. We also perform a systematic analysis at the industry level, recognizing that the best mix of capabilities to boost resilience should be shaped by the external environment. Our machine learning results suggest that while all major capabilities contribute to firm resilience, the mix is industry-specific and driven by bundling. This paper contributes to the literature on corporate resilience by providing new insights into the best mix of capabilities to build resilience in the face of external shocks