Profitability of New Entrants in Capacity-constrained Oligopolies: A Data-driven Analysis - Savanam Chandra Sekhar (Journal of Management and Informatics, 2026)
This study examines the profitability of new entrants in capacity-constrained oligopolistic markets using a data-driven empirical approach. Drawing on firm-level panel data across multiple industries over a 10–15-year period, the analysis integrates industrial organization theory with econometric modeling to assess how capacity conditions influence entry outcomes. The study focuses on key determinants, including incumbent capacity utilization, incumbent excess capacity, entrant capacity constraints, and market demand growth, while accounting for firm-specific and market-level controls. A fixed effects panel regression model, supplemented by robustness checks and alternative specifications, employed to examine the relationships between capacity conditions and entrant profitability while controlling for firm-specific and time-specific heterogeneity. The empirical results indicate that incumbent capacity utilization positively affects entrant profitability, while excess capacity serves as a strategic deterrent, reducing entrant performance. Entrant capacity constraints significantly hinder profitability, and interaction effects indicate that entrants must possess sufficient capacity to benefit from incumbent limitations. Market demand growth further enhances profitability, highlighting the role of external conditions. The study contributes to the literature by establishing capacity as a dynamic and strategic variable in entry analysis, offering implications for theory, managerial decision-making, and competition policy.