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Dissecting diffusion: Tracing the plurality of factors that shape knowledge diffusion
Institution:1. Georgia Institute of Technology, School of City and Regional Planning, 245 Fourth Street, Atlanta, GA 30313, United States;2. University of Oregon, Lundquist College of Business, 1208 University Street, Eugene, OR 97403, United States;1. Henley Business School, University of Reading, United Kingdom;2. Imperial College, University of London, United Kingdom;3. Department of Economics, Society and Politics, Carlo Bo University, Urbino, United Kingdom;1. Henley Business School, University of Reading, UK;2. Department of Economics, Society, Politics, University of Urbino, Italy;3. Gran Sasso Science Institute, Italy;4. Department of Economics, Society, Politics, University of Urbino, Italy;5. Department of Economics, University of Perugia, Italy;1. Durham University Business School, Ustinov College, Millhill Ln, Durham DH1 3LB, Durham, United Kingdom;2. College of Economics and Management, Nanjing University of Aeronautics and Astronautics, Nanjing, 211106, China;3. Durham University Business School, Millhill Ln, Durham DH1 3LB, Durham, United Kingdom;1. Department of Management and Marketing, The Hong Kong Polytechnic University, Hung Hom, Hong Kong;2. Department of Management, The Hong Kong University of Science and Technology, Clear Water Bay, Hong Kong
Abstract:Knowledge diffusion drives both technical progress and economic growth. In this study, we present a unique comparative case study that examines the diffusion of two comparable, foundational biotechnology inventions – recombinant DNA (rDNA) and polymerase chain reaction (PCR). Using a variety of metrics to trace knowledge diffusion, we find robust evidence that the diffusion of PCR significantly outperforms rDNA. Examining the historical record, we then consider how organizational origin, licensing strategy, complementary assets, industry stage, and early social networks play a role in shaping these processes. Ultimately, we show that reliance on a single diffusion metric or factor is insufficient in explaining knowledge diffusion. We argue for the exploration of multiple underlying factors in diffusion studies, and we highlight the utility of employing multiple complementary measures in diffusion research.
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