Do innovation measures actually measure innovation? Obliteration, symbolic adoption, and other finicky challenges in tracking innovation diffusion. Nelson, A., Earle, A., Howard-Grenville, J., Haack, J., & Young, D. Research Policy.
Do innovation measures actually measure innovation? Obliteration, symbolic adoption, and other finicky challenges in tracking innovation diffusion [link]Paper  doi  abstract   bibtex   
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.
@article{nelson_innovation_????,
	title = {Do innovation measures actually measure innovation? {Obliteration}, symbolic adoption, and other finicky challenges in tracking innovation diffusion},
	issn = {0048-7333},
	shorttitle = {Do innovation measures actually measure innovation?},
	url = {http://www.sciencedirect.com/science/article/pii/S0048733314000201},
	doi = {10.1016/j.respol.2014.01.010},
	abstract = {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.},
	urldate = {2014-02-10},
	journal = {Research Policy},
	author = {Nelson, Andrew and Earle, Andrew and Howard-Grenville, Jennifer and Haack, Julie and Young, Doug},
	keywords = {Diffusion, Green chemistry, Innovation, Labeling, Measurement},
	file = {ScienceDirect Full Text PDF:files/48303/Nelson et al. - Do innovation measures actually measure innovation.pdf:application/pdf;ScienceDirect Snapshot:files/48304/S0048733314000201.html:text/html}
}
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