Revisiting industry effects: The assignment of firms to industries

Research Summary Strategy research examines the drivers of firm performance. Variance decomposition studies have analyzed industry's impact, with little attention paid to the industry to which a firm is assigned. This study investigates how industry assignment affects the findings about industry's impact. We analyze existing industry classification schemes and introduce a machine learning‐based scheme that leverages an embedding model to process text from annual reports. We find that industry assignment differs substantially across schemes, and that certain firms are more consistently grouped together. Schemes that group more similar firms together exhibit stronger industry effects. Given the literature's frequent reliance on the criticized Standard Industrial Classification scheme, industry's role in firm performance has likely been systematically underestimated. Managerial Summary Understanding what drives a company's success is crucial. Prior research has surprisingly found that a firm's industry plays little role in explaining a firm's performance. However, this study suggests that industry's importance is likely understated due to how firms are grouped into industries. Comparing several existing industry classification schemes alongside a new one we built using machine learning, we find that grouping similar firms in the same industry increases reported industry importance and decreases firm importance. Being more precise about industry membership reveals that industry matters more than previously thought. The implication is that understanding the industry is more important for a firm's performance and could be key to understanding sustained success.