Organization of innovation in a multi-unit firm: Coordinating adaptive search on multiple rugged landscapes

In Chang and Harrington (2000a) a computational model of a multi-unit firm is developed in which unit managers continually search for better practices Search takes place over a rugged landscape defined over the space of unit practices There it is shown that a more centralized organization is optimal when markets are not too different and the horizon is not too long The robustness of those results are explored here with respect to the shape of the landscape In particular we find that centralization does better when the search space is larger and there is a stronger correlation in a consumer's preferences across different dimensions A richer description of comparative dynamics is also provided.