This paper provides a graph-theoretic framework for assessing the progress potential for a product or class of products based on the underlying knowledge structure. We characterize the knowledge structure based on singular value signatures and extend the characterization to multi-dimensional functional model representations of product knowledge. We show that the progress potential for a product is partially determined by graph properties of the knowledge structure, and whether the graph structure is modular, random, or hierarchically modular. The characterization is empirically tested on energy harvesting devices. Our model connects the knowledge underlying a product to its potential for progress, appropriately taking into account the nature of product knowledge and its ‘complexity’.

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