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The Dynamic Driving Path of Organizational Resilience to Digital Transformation—An Empirical Study Based on TJ-QCA

Author

Listed:
  • Wen Li

    (Inner Mongolia University of Science and Technology
    Research Center of Industrial Informationization and Innovation in Inner Mongolia University of Science and Technology)

  • Keyang Yun

    (Tianjin University of Finance and Economics)

  • Fengshu Li

    (Anhui University)

Abstract

In the current complex and rapidly evolving business environment, organizational resilience (OR) significantly influences the acceleration of the digital transformation (DT) process within enterprises, yet few studies have elucidated the mechanisms through which OR drives DT. The purpose of this paper is to investigate the theoretical underpinnings and general principles of the dynamic influence of OR on the DT of manufacturing enterprises. Utilizing the dynamic capabilities theory, this paper examines 15 Chinese manufacturing enterprises as the subjects of study and employs a trajectory-based qualitative comparative analysis to investigate the dynamic pathways of OR across various stages of DT. The findings are as follows: (1) OR diverges into aspects such as crisis awareness, resilience recovery, opportunity exploration, anticipatory planning, and feedback learning. (2) A singular dimension of OR is not a prerequisite for DT. (3) There are four organizational resilience-driven pathways in the process of accelerated DT, namely, strategic planning and response, feedback integration, crisis-led resilience, and innovation-led resilience types. The conclusions contribute to the fields of DT and OR research. They not only offer theoretical support and guidance for manufacturing enterprises to undertake DT in complex and dynamic environments, but also offer direction for policymakers to develop incentive policies that support the digital infrastructure of enterprises.

Suggested Citation

  • Wen Li & Keyang Yun & Fengshu Li, 2025. "The Dynamic Driving Path of Organizational Resilience to Digital Transformation—An Empirical Study Based on TJ-QCA," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 16(3), pages 13753-13775, September.
    • Handle: RePEc:spr:jknowl:v:16:y:2025:i:3:d:10.1007_s13132-024-02361-6
    DOI: 10.1007/s13132-024-02361-6
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