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Measuring Corporate Digital Transformation: Methodology, Indicators and Applications

Author

Listed:
  • Limin Zou

    (School of Economics and Management, University of Chinese Academy of Sciences, Beijing 100190, China
    Kezhu Property Company, Administration Bureau of the Chinese Academy of Sciences, Beijing 100086, China)

  • Wan Li

    (School of Economics and Management, University of Chinese Academy of Sciences, Beijing 100190, China)

  • Hongyi Wu

    (School of Economics and Management, University of Chinese Academy of Sciences, Beijing 100190, China
    Sino-Danish College, University of Chinese Academy of Sciences, Beijing 101408, China)

  • Jiawen Liu

    (Economics and Management School, Wuhan University, Wuhan 430072, China)

  • Peng Gao

    (School of Economics and Management, University of Chinese Academy of Sciences, Beijing 100190, China)

Abstract

With the rapid development of data science, digital technology is integrating deeply with enterprise management, driving companies towards digital transformation to achieve sustainable development. However, digital transformation is a systematic and comprehensive process, posing challenges in accurately depicting firm-level digitalization. Hence, this study systematically reviews measurement methods for digital transformation across various themes related to enterprise digitalization. Existing literature predominantly employs questionnaire analysis, quantitative statistics, and text analysis to gauge the extent of digital transformation. In terms of indicator construction, existing literature mainly relies on input, process, and outcome variables to construct measurement indicators. Nevertheless, due to the subjectivity of questionnaires, the uniqueness of industry data, and the limitations of textual information, these methods and the indicators derived from them possess distinct applicability scopes. Refining the measurement of digital transformation should hinge on both the research objectives and the characteristics of the data. Furthermore, through the analysis of industry cases such as agriculture, manufacturing and service industries, this study also reveals the unique characteristics encountered by these industries in the process of digital transformation, provides a more detailed summary of measurement methods for these specific industries, and emphasizes the importance of selecting measurement methods according to industry characteristics.

Suggested Citation

  • Limin Zou & Wan Li & Hongyi Wu & Jiawen Liu & Peng Gao, 2024. "Measuring Corporate Digital Transformation: Methodology, Indicators and Applications," Sustainability, MDPI, vol. 16(10), pages 1-15, May.
    • Handle: RePEc:gam:jsusta:v:16:y:2024:i:10:p:4087-:d:1393879
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    References listed on IDEAS

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    Cited by:

    1. Xing Liu & Shaobo Hong & Zhi Su & Yuanren Zhou, 2025. "The Impact of Digital Transformation on High-Quality Development of Manufacturing Enterprises: An Integrated Perspective on Efficiency and Social Responsibility," Mathematics, MDPI, vol. 13(5), pages 1-36, February.
    2. Jingyang Yan & Chao Gao & Yinan Tan & Zhimin Du, 2025. "The Impact of Digital Supply Chain Management on Enterprise Total Factor Productivity: Evidence from a Quasi-Natural Experiment in China," Sustainability, MDPI, vol. 17(17), pages 1-16, August.
    3. Chao Gao & Jiayu Fang, 2025. "The Green Effect of Digital Intelligence in Chinese Cities: An Empirical Investigation Based on Big Data and Machine Learning Methods," Sustainability, MDPI, vol. 17(15), pages 1-20, July.

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