Knowledge context, learning and innovation: an integrating framework
James Love () and
Ying Zhou ()
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James Love: Warwick Business School
Ying Zhou: Aston University Business School
No 20, Research Papers from Enterprise Research Centre
In this paper we develop a framework to identify those elements of firms’ knowledge context which are important for innovation, and the mechanisms through which that knowledge impacts on firms’ innovation performance. We make four main contributions to the existing literature. First, our characterisation of knowledge context provides the basis for a more specific identification of which elements of firms’ knowledge environment are important for innovation, discriminating between spatial, industrial and network influences. Second, we reflect the role of innovation ambition in shaping firms’ knowledge search strategies. Third, we differentiate between firms’ interactive and non-interactive knowledge search activities and recognise that these may be complemented by unanticipated and serendipitous knowledge spillovers. Finally, we introduce the notion of encoding capacity to reflect firms’ internal ability to assimilate and apply external knowledge. Our framework provides an integrating mechanism for existing empirical studies, suggests a number of new research directions related to the determinants of innovation performance and the heterogeneity of innovation outcomes.
Keywords: Knowledge; innovation; spatial; industry; learning (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-cse, nep-ent, nep-ino, nep-knm, nep-sbm and nep-ure
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Journal Article: Knowledge context, learning and innovation: an integrating framework (2018)
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Persistent link: https://EconPapers.repec.org/RePEc:enr:rpaper:0020
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