Dynamic Competitive Pricing Strategies

Pricing decisions have long been of interest to researchers in the competitive strategy area. Static game theory models of competitive pricing commonly assume that rivals act with full information and full rationality. Such models imply that rivals immediately reach a Nash equilibrium. This implication is consistent neither with experimental research results nor with casual observation of real markets. We therefore relax the assumption of full information to investigate how competitors learn and update their marketing strategies over time, as well as to identify the ultimate equilibrium they reach. This dual focus on the learning process as well as its outcome is important to understanding how rivals compete over time. We find that the ultimate equilibrium takes some time to reach, and is neither the standard Nash solution nor a collusive one. These differences from the usual static game solutions suggest the value of models that better capture the incomplete information facing a firm in a competitive marketplace.