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Quantitative Measurement of Digital Maturity in Manufacturing Enterprises: An Application Scenario-Based Study

Author

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  • Qing Liu

    (College of Management Science and Engineering, China Jiliang University, Hangzhou 310018, China)

  • Xiaoyan Jiang

    (College of Management Science and Engineering, China Jiliang University, Hangzhou 310018, China)

Abstract

With the rapid advancement of intelligent manufacturing and digital transformation, assessing the digital transformation and maturity of manufacturing enterprises enables firms to evaluate their digital achievements and establish appropriate transformation pathways. Existing maturity assessment models for manufacturing enterprises predominantly emphasize strategic-level evaluation and rely heavily on survey-based data, while paying limited attention to the business-function level. However, in practice, enterprises often initiate digital transformation by addressing specific business challenges and then gradually advance through concrete application scenarios. To address this gap, this paper proposes a scenario-based approach for measuring the digital transformation and maturity of manufacturing enterprises. With this approach, a differentiated weighting system is constructed based on “core keywords–extended keywords–negative keywords”, and a semantic similarity model is used to identify and quantify digital application scenarios in corporate annual reports. Building on this, a three-dimensional evaluation framework, comprising scenario coverage, scenario depth, and scenario consistency, is developed to comprehensively assess the extent of digital transformation from the perspective of application scenarios. With the proposed method, different business units can be evaluated independently, thereby capturing transformation progress across heterogeneous levels. Since it relies on publicly available corporate annual reports, the evaluation process is transparent and traceable and generates quantitative results. By shifting from survey-based, strategy-oriented assessments to function-oriented, data-driven, and modular evaluations, the method not only enhances accuracy and interpretability but also provides practical guidance for resource allocation, cross-functional complexity management, and the progressive expansion of digital transformation.

Suggested Citation

  • Qing Liu & Xiaoyan Jiang, 2025. "Quantitative Measurement of Digital Maturity in Manufacturing Enterprises: An Application Scenario-Based Study," Sustainability, MDPI, vol. 18(1), pages 1-33, December.
  • Handle: RePEc:gam:jsusta:v:18:y:2025:i:1:p:274-:d:1827369
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