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

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

Technological Forecasting and Social Change, 2013, vol. 80, issue 5, 956-976

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.

Keywords: Methodology; Evolutionary epistemology; Learning; R&D strategy; Roadmapping; Expert judgment (search for similar items in EconPapers)
Date: 2013
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Citations: View citations in EconPapers (4)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:tefoso:v:80:y:2013:i:5:p:956-976

DOI: 10.1016/j.techfore.2012.08.017

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