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Effective Innovation Implementation: A Mixed Method Study

Author

Listed:
  • MALTE HANS GEORG SCHNEIDER

    (Porsche AG, Chair of Strategic Management and Digital Entrepreneurship, HHL Leipzig, Graduate School of Management, Leipzig, Germany)

  • JOHANNES HOFMEISTER

    (Porsche AG, Chair of Strategic Management and Digital Entrepreneurship, HHL Leipzig, Graduate School of Management, Leipzig, Germany)

  • DOMINIK K KANBACH

    (Porsche AG, Chair of Strategic Management and Digital Entrepreneurship, HHL Leipzig, Graduate School of Management, Leipzig, Germany)

Abstract

Ensuring that innovations are implemented organisation-wide remains a critical business challenge for organisations. This study identifies how organisations can improve the effectiveness of innovations and specifies the effects of innovation implementation antecedents and capabilities. By applying a mixed method approach, using data from 42 semi-structured interviews and 125 questionnaire participants, we develop a new framework for understanding the mechanisms that underlie and enhance effective innovation implementation. The results emphasise that achieving high and consistent use of innovations requires organisations to focus on organisational members and their individual characteristics, rather than on organisational design. Additionally, implementation leadership serves as a central mediator to explain the framework’s relationships. Furthermore, a middle management-driven approach that combines implementation leadership and dialogue facilitates the effective implementation of innovation. In conclusion, our study contributes to innovation implementation research by presenting a framework to guide future research, whilst helping practitioners to implement innovations more effectively.

Suggested Citation

  • Malte Hans Georg Schneider & Johannes Hofmeister & Dominik K Kanbach, 2022. "Effective Innovation Implementation: A Mixed Method Study," International Journal of Innovation Management (ijim), World Scientific Publishing Co. Pte. Ltd., vol. 26(06), pages 1-36, August.
    • Handle: RePEc:wsi:ijimxx:v:26:y:2022:i:06:n:s1363919622500426
    DOI: 10.1142/S1363919622500426
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    Citations

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    Cited by:

    1. Johannes Hofmeister & Dominik K. Kanbach & Jens Hogreve, 2024. "Service productivity: a systematic review of a dispersed research area," Management Review Quarterly, Springer, vol. 74(3), pages 1249-1281, September.
    2. Roppelt, Julia Stefanie & Kanbach, Dominik K. & Kraus, Sascha, 2024. "Artificial intelligence in healthcare institutions: A systematic literature review on influencing factors," Technology in Society, Elsevier, vol. 76(C).

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