Twenty years of technology and strategic roadmapping research: A school of thought perspective
•Roadmapping studies have diverged into seven schools of thought.•This review draws on the mixed-methods approach: topic modelling, genealogical analysis, content analysis and interviews.•The schools differ in terms of research orientation; research methods; and research contributions.•Six schools f...
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Veröffentlicht in: | Technological forecasting & social change 2020-05, Vol.154, p.119965, Article 119965 |
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Sprache: | eng |
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Zusammenfassung: | •Roadmapping studies have diverged into seven schools of thought.•This review draws on the mixed-methods approach: topic modelling, genealogical analysis, content analysis and interviews.•The schools differ in terms of research orientation; research methods; and research contributions.•Six schools focus on solution-oriented research, with an emerging school of thought on theory-oriented research.
Two decades ago the thirtieth-anniversary special issue of Technological Forecasting and Social Change correctly anticipated the widespread adoption of technology and strategic roadmapping at firm, sectoral and national levels. In this article, we explore the evolution of roadmapping studies since that time. Drawing on a mixed-methods approach (i.e. topic modelling, genealogical analysis, content analysis and interviews), we reveal the development of seven distinctive ‘schools of thought’: the Cambridge practical school, the Seoul school, the Portland and Bangkok schools, the Cambridge phenomenological school, the Beijing school and the Moscow school. We show that the schools differ in terms of (a) the research orientation, whether it be solution- or theory-oriented; (b) the research methods and data sources being used; and (c) the nature of contributions that each school seeks to achieve. The different areas of emphasis associated with each school are not competing but complementary, and together they develop the eclectic body of knowledge on roadmapping. |
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ISSN: | 0040-1625 1873-5509 |
DOI: | 10.1016/j.techfore.2020.119965 |