5 research outputs found

    The Past and Future of Evolutionary Economics : Some Reflections Based on New Bibliometric Evidence

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    This document is the Accepted Manuscript version of the following article: Geoffrey M. Hodgson, and Juha-Antti Lamberg, ‘The past and future of evolutionary economics: some reflections based on new bibliometric evidence’, Evolutionary and Institutional Economics Review, first online 20 June 2016. The final publication is available at Springer via doi: http://dx.doi.org/10.1007/s40844-016-0044-3 © Japan Association for Evolutionary Economics 2016The modern wave of ‘evolutionary economics’ was launched with the classic study by Richard Nelson and Sidney Winter (1982). This paper reports a broad bibliometric analysis of ‘evolutionary’ research in the disciplines of management, business, economics, and sociology over 25 years from 1986 to 2010. It confirms that Nelson and Winter (1982) is an enduring nodal reference point for this broad field. The bibliometric evidence suggests that ‘evolutionary economics’ has benefitted from the rise of business schools and other interdisciplinary institutions, which have provided a home for evolutionary terminology, but it has failed to nurture a strong unifying core narrative or theory, which in turn could provide superior answers to important questions. This bibliometric evidence also shows that no strong cluster of general theoretical research immediately around Nelson and Winter (1982) has subsequently emerged. It identifies developmental problems in a partly successful but fragmented field. Future research in ‘evolutionary economics’ needs a more integrated research community with shared conceptual narratives and common research questions, to promote conversation and synergy between diverse clusters of research.Peer reviewedFinal Accepted Versio

    Self-citations, co-authorships and keywords: A new approach to scientists' field mobility?

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    This paper introduces a new approach to detecting scientists' field mobility by focusing on an author's self-citation network, and the co-authorships and keywords in self-citing articles. Contrary to much previous literature on self-citations, we will show that author's self-citation patterns reveal important information on the development and emergence of new research topics over time. More specifically, we will discuss self-citations as a means to detect scientists' field mobility. We introduce a network based definition of field mobility, using the Optimal Percolation Method (Lambiotte & Ausloos, 2005; 2006). The results of the study can be extended to selfcitation networks of groups of authors and, generally also for other types of networks
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