Modeling innovative search processes with PR landscapes

Abstract

This paper develops and analyzes a stylized simulation model of the process of innovation, with emphasis on the differences in outcomes for innovation strategies having a high tolerance for ambiguity and those with a low tolerance. The model is implemented in the context of new product development (NPD). The market value of potential products is represented by the height of a PR landscape, where P is the number of peaks and R is the ruggedness or narrowness of the peaks on the landscape. Innovation teams search the landscape for the best product concepts, but can observe only noisy estimates of the value of a landscape position. At each point, teams consider possible interpretations of their observations in determining their next move. Teams also incur costs during the search process. Teams with a high tolerance for ambiguity, as opposed to those with a low tolerance, are likely to take larger steps across the landscape and to move to new locations more quickly. Since high and low tolerance for ambiguity can be associated with tendencies for exploration and exploitation, we then turn to the consideration of the decomposition of exploration and exploitation into search depth and search breadth or scope.