Invention to innovation: A framework and the roles of uncertainty and open innovation in an emerging personalized medicine ecosystem

In this dissertation, I explore the antecedents, processes and outcomes of the translation of scientific invention to innovation, which is of particular interest to scholars and policy makers who wish to understand how publicly funded university research can be harnessed to increase national productivity. While there has been an increasing amount of research on the roles that innovation intermediaries and mechanisms play in science innovation, there have been few attempts at characterizing the inputs, mediators and outputs of this process. Innovation management and policy research is far more developed around technology innovation than science innovation. Few empirical studies have been conducted at the ecosystem level in emerging science-based contexts. Firms in such contexts exhibit markedly different characteristics compared to large software incumbents, including higher technical and market uncertainty. In three essays I explore the following research questions: "what factors influence the translation of scientific invention to innovation?", "do uncertainty, partnerships and patenting have an influence on innovation performance outcomes?" and "why and under what conditions do the Open Innovation mechanisms of selective revealing, strategic timing and strategic partnering affect value capture by personalized medicine firms?". The investigation of these questions aims to inform scientist-entrepreneurs, scholars, policy makers and university leadership on how to more effectively translate breakthrough invention to improved economic, health and social outcomes. This dissertation contributes to the Technology and Innovation Management literature in three ways. In the first essay, the results of a bibliographic review are synthesized into a novel theoretical framework on science innovation. In the second essay, the relationship between uncertainty, patenting and innovation performance outcomes is explored, using a novel and custom-built dataset on British Columbia personalized medicine firms. The results show that uncertainty, partnerships and patenting play a role in innovation performance outcomes, which have implications for both practitioners and policy makers. In the third essay, I heed the call from the Open Innovation research community to more deeply explore the boundary conditions of Open Innovation. A new model on Open Innovation is presented, which is empirically supported by two key findings: the Open Innovation mechanisms of Strategic Partnerships, Selective Revealing and Strategic Timing appear to play important roles in value capture, but this relationship is moderated by technical uncertainty.