Novelty

Innovation requires sources of novelty, but the challenge is that not all sources lead to innovation, so its value needs to be determined. However, since ways of determining value stem from existing knowledge, this often creates barriers to innovation. To understand how people address the challenge of novelty, we develop a conceptual and an empirical framework to explain how this challenge is addressed in a software and scientific context. What is shown is that the process of innovation is a cycle where actors develop a novel course of action and, based on the consequences identified, confirm what knowledge is necessary to transform and develop the next course of action. The performance of the process of innovation is constrained by the capacities of the artifacts and the ability of the actors to create and use artifacts to drive this cycle. By focusing on the challenge of novelty, a problem that cuts across all contexts of innovation, our goal is to develop a more generalized account of what drives the process of innovation.

Selecting among alternative projects is a core management task in all innovating organizations. In this paper, we focus on the evaluation of frontier scientific research projects. We argue that the “intellectual distance” between the knowledge embodied in research proposals and an evaluator’s own expertise systematically relates to the evaluations given. To estimate relationships, we designed and executed a grant proposal process at a leading research university in which we randomized the assignment of evaluators and proposals to generate 2,130 evaluator–proposal pairs. We find that evaluators systematically give lower scores to research proposals that are closer to their own areas of expertise and to those that are highly novel. The patterns are consistent with biases associated with boundedly rational evaluation of new ideas. The patterns are inconsistent with intellectual distance simply contributing “noise” or being associated with private interests of evaluators. We discuss implications for policy, managerial intervention, and allocation of resources in the ongoing accumulation of scientific knowledge.