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The knowledge-innovation nexus in the welfare service ecosystem

The knowledge-innovation nexus in the welfare service ecosystem This paper makes two contributions on knowledge-intensive innovation research. Firstly, it identifies and elaborates on the knowledge problems present in the welfare service’s innovation ecosystem. Secondly, drawing on relevant theoretical approaches, this paper discusses the managerial implications these knowledge problems pose for stakeholders involved in innovating welfare services. The identified knowledge problems are uncertainty, complexity and ambiguity; uncertainty refers to a lack of information or factual knowledge about something, complexity arises from the intricacy and connectivity of the various elements, and ambiguity stems from multiple interpretations. The paper also presents the managerial implications for each type of knowledge problem; uncertainty can be reduced by the acquisition of more information and knowledge increased by creating connections within the ecosystem, complexity can be minimised by increasing knowledge capacity and decomposing problems, and ambiguity can be addressed by structuring the unknown into a frame of reference. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png International Journal of Knowledge-Based Development Inderscience Publishers

The knowledge-innovation nexus in the welfare service ecosystem

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Publisher
Inderscience Publishers
Copyright
Copyright © Inderscience Enterprises Ltd. All rights reserved
ISSN
2040-4468
eISSN
2040-4476
DOI
10.1504/IJKBD.2013.052492
Publisher site
See Article on Publisher Site

Abstract

This paper makes two contributions on knowledge-intensive innovation research. Firstly, it identifies and elaborates on the knowledge problems present in the welfare service’s innovation ecosystem. Secondly, drawing on relevant theoretical approaches, this paper discusses the managerial implications these knowledge problems pose for stakeholders involved in innovating welfare services. The identified knowledge problems are uncertainty, complexity and ambiguity; uncertainty refers to a lack of information or factual knowledge about something, complexity arises from the intricacy and connectivity of the various elements, and ambiguity stems from multiple interpretations. The paper also presents the managerial implications for each type of knowledge problem; uncertainty can be reduced by the acquisition of more information and knowledge increased by creating connections within the ecosystem, complexity can be minimised by increasing knowledge capacity and decomposing problems, and ambiguity can be addressed by structuring the unknown into a frame of reference.

Journal

International Journal of Knowledge-Based DevelopmentInderscience Publishers

Published: Jan 1, 2013

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