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Research on the Improvement Path of Total Factor Productivity in the Industrial Software Industry: Evidence from Chinese Typical Firms

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  • Xiaoxiang Wang

    (College of Economics and Management, Beijing University of Technology, Beijing 100124, China
    School of Economics and Management, Wenzhou University of Technology, Wenzhou 325035, China)

  • Songling Wu

    (Business School, Henan University of Science and Technology, Luoyang 471023, China)

  • Lixiang Zhao

    (College of Economics and Management, Beijing University of Technology, Beijing 100124, China)

Abstract

The high-quality development of the industrial software industry is of strategic significance to enhancing the core competitiveness of the manufacturing industry and promoting the high-quality development of China’s industrial economy. By integrating the “capital-technology-environment-human” production factor theory and configuration perspective, this paper constructs a comprehensive analysis framework that drives the total factor productivity (TFP) of the industrial software industry. This paper uses 40 typical industrial software firms in 2018–2020 as case samples and uses fuzzy set Qualitative Comparative Analysis (fsQCA) to empirically explore the influencing factors and complex mechanisms that achieve high-quality development of the industrial software industry. It is found that: (1) a single industrial factor is hardly a necessary condition to drive the industrial software industry; (2) there are four paths to achieving high TFP, which are summarized as “technical-human-environmental” balanced driving type, “capital-human-environmental” balanced driving type, “technical-capital” dual driving type, and “capital” single driving type. There are four driving mechanisms. There are also four not-high TFP configurations with asymmetric characteristics; (3) under certain conditions, the combination of capital factors, technical factors, environmental factors, and human factors can drive TFP in an “all roads lead to Rome”. In this process, the government’s attention plays a more universal role. The study not only expands the application scenarios of fsQCA but also provides decision guidelines for the practice of strategic emerging industrialization represented by the industrial software industry.

Suggested Citation

  • Xiaoxiang Wang & Songling Wu & Lixiang Zhao, 2023. "Research on the Improvement Path of Total Factor Productivity in the Industrial Software Industry: Evidence from Chinese Typical Firms," Mathematics, MDPI, vol. 11(24), pages 1-26, December.
    • Handle: RePEc:gam:jmathe:v:11:y:2023:i:24:p:4944-:d:1299239
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    References listed on IDEAS

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