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Serial and comparative analysis of innovation policy change

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  • Niinikoski, Marja-Liisa
  • Moisander, Johanna

Abstract

Much of the existing literature on innovation policy analyzes policy change as an outcome of rational, cognitive processes, where the availability of new information prompts policy-makers to rethink and revise their policies. This paper aims to broaden this perspective by building a new methodological approach, Serial Comparative Analysis (SCA), to the analysis of policy change. SCA is proposed as an analytical perspective that sheds light on the social and political complexities of policy-making, and thus allows for a more nuanced understanding of the dynamics of policy change. SCA builds on the archaeological approach to discourse, and basic methodological principles of ethnographic inquiry. By conceptualizing a policy domain as a discursive formation, SCA provides insights into the socio-historical conditions under which a specific policy emerges, forms and transforms. While other methodological approaches may adopt the presumption that policy change is a causal outcome of new information used in policy-making, SCA views policy change as something that is discursively constructed and negotiated in specific institutional and historical settings. In doing so, SCA brings to light the rules that organize the truth-values of policy discourses in particular contexts, and elucidates how changes in these rules bring about changes in policy.

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  • Niinikoski, Marja-Liisa & Moisander, Johanna, 2014. "Serial and comparative analysis of innovation policy change," Technological Forecasting and Social Change, Elsevier, vol. 85(C), pages 69-80.
    • Handle: RePEc:eee:tefoso:v:85:y:2014:i:c:p:69-80
    DOI: 10.1016/j.techfore.2013.07.011
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    References listed on IDEAS

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    1. Charles Edquist & Terttu Luukkonen & Markku Sotarauta, 2009. "Broad-Based Innovation Policy," Chapters, in: Reinhilde Veugelers (ed.), The Evaluation of the Finnish National Innovation System, pages 11-70, The Research Institute of the Finnish Economy.
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    5. Metcalfe, J S, 1994. "Evolutionary Economics and Technology Policy," Economic Journal, Royal Economic Society, vol. 104(425), pages 931-944, July.
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    7. Mytelka, Lynn K. & Smith, Keith, 2002. "Policy learning and innovation theory: an interactive and co-evolving process," Research Policy, Elsevier, vol. 31(8-9), pages 1467-1479, December.
    8. Flanagan, Kieron & Uyarra, Elvira & Laranja, Manuel, 2011. "Reconceptualising the 'policy mix' for innovation," Research Policy, Elsevier, vol. 40(5), pages 702-713, June.
    9. Elvira Uyarra, 2010. "What is evolutionary about ‘regional systems of innovation’? Implications for regional policy," Journal of Evolutionary Economics, Springer, vol. 20(1), pages 115-137, January.
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    Cited by:

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    3. Yang, Chao & Huang, Cui & Su, Jun, 2020. "A bibliometrics-based research framework for exploring policy evolution: A case study of China's information technology policies," Technological Forecasting and Social Change, Elsevier, vol. 157(C).
    4. Dufva, Mikko & Ahlqvist, Toni, 2015. "Knowledge creation dynamics in foresight: A knowledge typology and exploratory method to analyse foresight workshops," Technological Forecasting and Social Change, Elsevier, vol. 94(C), pages 251-268.
    5. Diercks, Gijs, 2019. "Lost in translation: How legacy limits the OECD in promoting new policy mixes for sustainability transitions," Research Policy, Elsevier, vol. 48(10).

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