Do innovation measures actually measure innovation? Obliteration, symbolic adoption, and other finicky challenges in tracking innovation diffusion
Although innovation diffusion is a central topic in policy and strategy, its measurement remains difficult – particularly in cases where the innovation is a complex and possibly ambiguous practice. In this paper, we develop four theoretical mechanisms that may bias diffusion markers by leading to the understatement and/or overstatement of diffusion at different points in time. Employing the case of “green chemistry,” we then compare three different diffusion markers – keywords, database index terms, and domain expert assessments – and we demonstrate how they lead to differing conclusions about the magnitude and timing of diffusion, organizational demography, publication outlets, and collaboration. We also provide suggestive evidence of extensive “greenwashing” by particular organization types and in particular countries. Building on these findings, we point to potential challenges with existing diffusion studies, and we make a case for the incorporation of practitioners in construct measurement and for the integration of comparative metrics in diffusion studies.
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- Albert G.Z. Hu & Adam B. Jaffe, 2001.
"Patent Citations and International Knowledge Flow: The Cases of Korea and Taiwan,"
NBER Working Papers
8528, National Bureau of Economic Research, Inc.
- Hu, Albert G. Z. & Jaffe, Adam B., 2003. "Patent citations and international knowledge flow: the cases of Korea and Taiwan," International Journal of Industrial Organization, Elsevier, vol. 21(6), pages 849-880, June.
- Alfred Kleinknecht & Kees Van Montfort & Erik Brouwer, 2002. "The Non-Trivial Choice between Innovation Indicators," Economics of Innovation and New Technology, Taylor & Francis Journals, vol. 11(2), pages 109-121.
- Herman Aguinis & Jeffrey R. Edwards, 2014. "Methodological Wishes for the Next Decade and How to Make Wishes Come True," Journal of Management Studies, Wiley Blackwell, vol. 51(1), pages 143-174, 01.
- Jamasb, T. & Pollitt, M.G., 2009.
"Electricity Sector Liberalisation and Innovation: An Analysis of the UK Patenting Activities,"
Cambridge Working Papers in Economics
0902, Faculty of Economics, University of Cambridge.
- Jamasb, Tooraj & Pollitt, Michael G., 2011. "Electricity sector liberalisation and innovation: An analysis of the UK's patenting activities," Research Policy, Elsevier, vol. 40(2), pages 309-324, March.
- Freeman, Christopher & Soete, Luc, 2009.
"Developing science, technology and innovation indicators: What we can learn from the past,"
Elsevier, vol. 38(4), pages 583-589, May.
- Soete, Luc & Freeman, Chris, 2007. "Developing science, technology and innovation indicators: what we can learn from the past," MERIT Working Papers 001, United Nations University - Maastricht Economic and Social Research Institute on Innovation and Technology (MERIT).
- Wu, Ching-Yan & Mathews, John A., 2012. "Knowledge flows in the solar photovoltaic industry: Insights from patenting by Taiwan, Korea, and China," Research Policy, Elsevier, vol. 41(3), pages 524-540.
- Mogoutov, Andrei & Kahane, Bernard, 2007. "Data search strategy for science and technology emergence: A scalable and evolutionary query for nanotechnology tracking," Research Policy, Elsevier, vol. 36(6), pages 893-903, July.
- Garth Saloner & Andrea Shepard, 1995. "Adoption of Technologies with Network Effects: An Empirical Examination of the Adoption of Teller Machines," RAND Journal of Economics, The RAND Corporation, vol. 26(3), pages 479-501, Autumn.
- Lee, Jaegul & Veloso, Francisco M. & Hounshell, David A., 2011. "Linking induced technological change, and environmental regulation: Evidence from patenting in the U.S. auto industry," Research Policy, Elsevier, vol. 40(9), pages 1240-1252.
- Beaudry, Catherine & Allaoui, Sedki, 2012. "Impact of public and private research funding on scientific production: The case of nanotechnology," Research Policy, Elsevier, vol. 41(9), pages 1589-1606.
- Geroski, Paul A, 1999.
"Models of Technology Diffusion,"
CEPR Discussion Papers
2146, C.E.P.R. Discussion Papers.
- Hélène Giroux, 2006. "'It Was Such a Handy Term': Management Fashions and Pragmatic Ambiguity," Journal of Management Studies, Wiley Blackwell, vol. 43(6), pages 1227-1260, 09.
- Cockburn, Iain M & Henderson, Rebecca M, 1998. "Absorptive Capacity, Coauthoring Behavior, and the Organization of Research in Drug Discovery," Journal of Industrial Economics, Wiley Blackwell, vol. 46(2), pages 157-82, June.
- Gay, Brigitte & Dousset, Bernard, 2005. "Innovation and network structural dynamics: Study of the alliance network of a major sector of the biotechnology industry," Research Policy, Elsevier, vol. 34(10), pages 1457-1475, December.
- Mina, A. & Ramlogan, R. & Tampubolon, G. & Metcalfe, J.S., 2007. "Mapping evolutionary trajectories: Applications to the growth and transformation of medical knowledge," Research Policy, Elsevier, vol. 36(5), pages 789-806, June.
- Stoneman, Paul & Diederen, Paul, 1994. "Technology Diffusion and Public Policy," Economic Journal, Royal Economic Society, vol. 104(425), pages 918-30, July.
- Nelson, Andrew J., 2012. "Putting university research in context: Assessing alternative measures of production and diffusion at Stanford," Research Policy, Elsevier, vol. 41(4), pages 678-691.
- Aaron K. Chatterji & David I. Levine & Michael W. Toffel, 2009. "How Well Do Social Ratings Actually Measure Corporate Social Responsibility?," Journal of Economics & Management Strategy, Wiley Blackwell, vol. 18(1), pages 125-169, 03.
- Julia Lane, 2010. "Let’s make science metrics more scientific," Working Paper Series of the German Council for Social and Economic Data 137, German Council for Social and Economic Data (RatSWD).
- Nameroff, T. J. & Garant, R. J. & Albert, M. B., 2004. "Adoption of green chemistry: an analysis based on US patents," Research Policy, Elsevier, vol. 33(6-7), pages 959-974, September.
- Ryan Lampe, 2012. "Strategic Citation," The Review of Economics and Statistics, MIT Press, vol. 94(1), pages 320-333, February.
- Ashish Arora, 1996.
"Patents, Licensing, And Market Structure In The Chemical Industry,"
- Arora, Ashish, 1997. "Patents, licensing, and market structure in the chemical industry," Research Policy, Elsevier, vol. 26(4-5), pages 391-403, December.
- Achilladelis, Basil & Schwarzkopf, Albert & Cines, Martin, 1990. "The dynamics of technological innovation: The case of the chemical industry," Research Policy, Elsevier, vol. 19(1), pages 1-34, February.
- Hagedoorn, John & Cloodt, Myriam, 2003. "Measuring innovative performance: is there an advantage in using multiple indicators?," Research Policy, Elsevier, vol. 32(8), pages 1365-1379, September.
- Kevin B. Hendricks & Vinod R. Singhal, 1997. "Does Implementing an Effective TQM Program Actually Improve Operating Performance? Empirical Evidence from Firms That Have Won Quality Awards," Management Science, INFORMS, vol. 43(9), pages 1258-1274, September.
- Nelson, Andrew J., 2009. "Measuring knowledge spillovers: What patents, licenses and publications reveal about innovation diffusion," Research Policy, Elsevier, vol. 38(6), pages 994-1005, July.
- Jaffe, Adam B, 1989. "Real Effects of Academic Research," American Economic Review, American Economic Association, vol. 79(5), pages 957-70, December.
- Walsh, Vivien, 1984. "Invention and innovation in the chemical industry: Demand-pull or discovery-push?," Research Policy, Elsevier, vol. 13(4), pages 211-234, August.
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