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Influencing factors and improvement paths of manufacturing innovation performance: Configuration analysis based on TOE framework

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  • Youcai Ma
  • Zhaobing Cui

Abstract

Innovation is the first driving force to lead development, how to improve manufacturing innovation performance has become a hot topic. Based on 47 listed companies in the computer, communication and other electronic equipment manufacturing industry in the A-share market, this paper adopted the Fuzzy set qualitative comparative analysis (fsQCA) to explore the influencing factors of technology, organization and environment on the innovation performance of manufacturing industry and the improvement path. The findings are as follows: (1) A single condition is not a necessary condition for high innovation performance in manufacturing industry, but government support plays a key role in improving innovation performance in manufacturing industry. (2) There are two improvement paths for high innovation performance in manufacturing industry, which are specifically explained as “technology-environment dual improvement path” and “technology-organization-environment collaborative improvement path”. (3) The improvement of innovation performance in the manufacturing industry is the result of multiple factors, showing the characteristics of “all paths lead to the same destination”. Different manufacturing enterprises have different paths to improve innovation performance based on their actual conditions. Based on these findings, this study may provide some implications for the effective improvement of manufacturing innovation performance.

Suggested Citation

  • Youcai Ma & Zhaobing Cui, 2023. "Influencing factors and improvement paths of manufacturing innovation performance: Configuration analysis based on TOE framework," PLOS ONE, Public Library of Science, vol. 18(11), pages 1-18, November.
    • Handle: RePEc:plo:pone00:0294630
    DOI: 10.1371/journal.pone.0294630
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    Cited by:

    1. Md Zohurul Islam & Munshi Muhammad Abdul Kader Jilani & Mohammad Rezaul Karim, 2024. "Enhancing post-training evaluation of annual performance agreement training: A fusion of fsQCA and artificial neural network approach," PLOS ONE, Public Library of Science, vol. 19(6), pages 1-29, June.

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