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Evolutionary learning methodology: A case study of R&D strategy development

Author

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  • Hooshangi, Soheil
  • Arasti, Mohammad R.
  • Hounshell, David A.
  • Sahebzamani, Sarah

Abstract

This article concerns the notion of methodology in strategic management of R&D/technology. Though development of new tools and methods has received much attention during the recent decades, attention to understanding methodologies has remained disproportionally low. In this study we distinguish two methodologies that are used in strategic management of R&D/technology: planning methodology and evolutionary learning methodology. We mainly focus on defining and describing the origins, nature, and characteristics of the latter. We propose a framework for methodology selection by investigating context, content, and process factors. Using this framework, we provide supportive evidence for appropriateness of evolutionary learning methodology to develop a robust R&D strategy for Iran's power industry. We then describe the details of operationalizing the methodology for the Iranian power industry. This study is particularly focused on delineating how evolutionary learning methodology can be applied as an effective framework to improve the formation method and content of R&D strategy. We conclude that methodological knowledge can provide a powerful lens with which to understand performance of methods, and we suggest that evolutionary learning methodology is particularly appropriate for the following situations: when the environment is uncertain or fast changing, when there exist many stakeholders with conflicting interests, and when a method needs to be applied in a context other than the one for which it was initially developed.

Suggested Citation

  • Hooshangi, Soheil & Arasti, Mohammad R. & Hounshell, David A. & Sahebzamani, Sarah, 2013. "Evolutionary learning methodology: A case study of R&D strategy development," Technological Forecasting and Social Change, Elsevier, vol. 80(5), pages 956-976.
  • Handle: RePEc:eee:tefoso:v:80:y:2013:i:5:p:956-976
    DOI: 10.1016/j.techfore.2012.08.017
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    Citations

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    Cited by:

    1. Cheng, M.N. & Wong, Jane W.K. & Cheung, C.F. & Leung, K.H., 2016. "A scenario-based roadmapping method for strategic planning and forecasting: A case study in a testing, inspection and certification company," Technological Forecasting and Social Change, Elsevier, vol. 111(C), pages 44-62.
    2. Chakraborty, Swagata & Nijssen, Edwin J. & Valkenburg, Rianne, 2022. "A systematic review of industry-level applications of technology roadmapping: Evaluation and design propositions for roadmapping practitioners," Technological Forecasting and Social Change, Elsevier, vol. 179(C).
    3. Harms, Rainer, 2015. "Self-regulated learning, team learning and project performance in entrepreneurship education: Learning in a lean startup environment," Technological Forecasting and Social Change, Elsevier, vol. 100(C), pages 21-28.
    4. Yu, Xiang & Zhang, Ben, 2019. "Obtaining advantages from technology revolution: A patent roadmap for competition analysis and strategy planning," Technological Forecasting and Social Change, Elsevier, vol. 145(C), pages 273-283.

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