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	Market Entry Timing Hazard Analysis	Agent-Based Model of Competitive Strategy
Dziedzina	Zarządzanie strategiczne	Zarządzanie strategiczne
Rodzina	Survival analysis	Process / pipeline
Rok powstania	1989	2007
Twórca	Will Mitchell; Timothy S. Schoenecker & Arnold C. Cooper	Jason P. Davis, Kathleen M. Eisenhardt & Christopher B. Bingham (simulation-methods roadmap)
Typ	Hazard / duration model of market entry timing	Agent-based computational simulation of competitive strategy
Źródło pierwotne	Mitchell, W. (1989). Whether and When? Probability and Timing of Incumbents' Entry into Emerging Industrial Subfields. Administrative Science Quarterly, 34(2), 208-230.	Davis, J. P., Eisenhardt, K. M., & Bingham, C. B. (2007). Developing Theory Through Simulation Methods. Academy of Management Review, 32(2), 480-499.
Inne nazwy	Entry Timing Hazard Modeling, Whether-and-When Entry Analysis, Incumbent Entry Hazard Analysis, Time-to-Entry Duration Analysis	Competitive Strategy Agent-Based Simulation, Firm-Interaction Simulation Modeling, Computational Model of Competitive Dynamics, Multi-Firm Agent-Based Strategy Model
Pokrewne	3	3
Podsumowanie	Market entry timing hazard analysis models both whether and when a firm enters a new market or emerging industrial subfield, treating time-to-entry as a survival outcome. Will Mitchell's 1989 study of incumbents facing emerging subfields framed the question precisely this way: rather than asking only if an established firm eventually enters, it asks how its probability and speed of entry depend on its capabilities and the competitive situation. Schoenecker and Cooper's 1998 cross-industry study extended the logic, showing that technological and marketing resources and organizational commitment to a threatened market accelerate entry. By modeling the hazard of entry, the method turns timing — a central variable in competitive strategy and first-mover debates — into something that can be estimated from data on firms at risk of entering.	An agent-based model of competitive strategy represents firms as autonomous, heterogeneous, adaptive agents whose decision rules and local interactions generate emergent industry-level dynamics that no single firm designs. Davis, Eisenhardt, and Bingham's 2007 roadmap for developing theory through simulation places this kind of computational modeling in the sweet spot between inductive case research and formal mathematics, well suited to longitudinal, nonlinear, and interactive strategy phenomena. Instead of solving for an equilibrium, the analyst builds firms with strategies, lets them compete over many simulated periods, and studies the market structures, survival patterns, and performance dispersions that emerge. The method gives strategy researchers a controlled laboratory for theory building about competitive dynamics that are too complex and path-dependent for closed-form analysis.