Tassabehiji, R, Mishra, J and Dominguez-Péry, C (2019) Knowledge sharing for innovation performance improvement in micro/SMEs: an insight from the creative sector. Production Planning and Control, 30 (10-12). pp. 935-950. ISSN 0953-7287
Abstract
As economies become more reliant on innovative, knowledge-intensive firms, understanding the interaction between knowledge and improving innovation performance is increasingly important. Although most UK businesses are micro, small or medium-sized enterprises (micro/SMEs), knowledge management research has tended to focus on large companies Knowledge sharing can be critical for innovation performance, especially for smaller players with limited resources. Our study presents an insight from micro/SMEs operating in the highly knowledge-intensive and innovative games/entertainment software development sector. Using a mixed method approach, we investigate knowledge sharing and its contribution to firm innovation performance improvements. Our findings suggest that micro/SMEs are at the forefront of the creative sector precisely because of their smaller size. Our study reveals evidence of knowledge donation but limited evidence of knowledge collection in the knowledge sharing process. We develop a model highlighting the importance of industry context, individual knowledge and organizational size in knowledge sharing for innovation performance.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | (c) 2019 Informa UK Limited, trading as Taylor & Francis Group. This is an Accepted Manuscript of an article published by Taylor & Francis in Production Planning and Control on 30th June 2019, available online: https://doi.org/10.1080/09537287.2019.1582101 |
Keywords: | Knowledge sharing; knowledge donation; innovation; micro/SMEs; innovation performance; creative industries |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Business (Leeds) > Management Division (LUBS) (Leeds) > Logistics, Info, Ops and Networks (LION) (LUBS) |
Depositing User: | Symplectic Publications |
Date Deposited: | 27 Mar 2019 14:37 |
Last Modified: | 30 Jun 2020 00:38 |
Status: | Published |
Publisher: | Taylor & Francis |
Identification Number: | 10.1080/09537287.2019.1582101 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:144109 |