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Knowledge for Translating Management Innovation into Firm Performance

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Knowledge Management in Organizations (KMO 2017)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 731))

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Abstract

This paper examines the role of tacit and explicit knowledge in translating innovation measures into firm performance in Japanese companies. While innovation has been found to be a source of higher firm performance, this research is considering whether innovation measures adopted by the firm translate directly into higher firm performance or whether these innovation measures generate tacit and/or explicit knowledge which themselves produce higher corporate performance.

Using a questionnaire survey and conditional process analysis, this paper found that there was no direct effect of innovation measures onto firm performance, and that instead, both tacit and explicit knowledge fully mediated the relationship between innovation measures and firm performance. Previous research did not consider the role of knowledge as interface to translate management innovation into firm performance. This paper uncovers the mediating role of knowledge, potentially elucidating past inconclusive results.

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Author information

Authors and Affiliations

  1. Graduate School of Business Sciences, University of Tsukuba, 3-29-1 Otsuka, Bunkyo-ku, Tokyo, 112-0012, Japan

    Remy Magnier-Watanabe & Caroline Benton

Authors
  1. Remy Magnier-Watanabe
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  2. Caroline Benton
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Corresponding author

Correspondence to Remy Magnier-Watanabe .

Editor information

Editors and Affiliations

  1. University of Staffordshire, Stoke-on-Trent, Staffordshire, United Kingdom

    Lorna Uden

  2. Beijing Jiaotong University, Beijing, China

    Wei Lu

  3. Department of Information Management, University of Kaohsiung, Kaohsiung, Taiwan

    I-Hsien Ting

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Magnier-Watanabe, R., Benton, C. (2017). Knowledge for Translating Management Innovation into Firm Performance. In: Uden, L., Lu, W., Ting, IH. (eds) Knowledge Management in Organizations. KMO 2017. Communications in Computer and Information Science, vol 731. Springer, Cham. https://doi.org/10.1007/978-3-319-62698-7_14

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  • DOI: https://doi.org/10.1007/978-3-319-62698-7_14

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-62697-0

  • Online ISBN: 978-3-319-62698-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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