Development of a digital supply chain maturity assessment model for advanced manufacturing companies using OWA-EWM and cloud model evaluation

Purpose To support advanced manufacturing companies in precisely evaluating the maturity of their digital supply chains and identifying improvement opportunities, we developed the digital supply chain maturity model (DSCMM). This model is grounded in the supply chain operations reference digital standard framework and incorporates a multidimensional, multilevel set of assessment indicators. Design/methodology/approach The first step involves identifying the primary assessment dimensions and corresponding secondary indicators to construct a comprehensive supply chain maturity assessment index system. Next, the ordered weighted averaging operator and the entropy weight method are applied in a combined approach to determine indicator weights. Finally, the digital supply chain maturity level is defined, and the cloud model is applied to a selected case company to assess the maturity level of its digital supply chain. Findings A representative advanced manufacturing enterprise was selected for in-depth analysis. The empirical findings confirm that the DSCMM model provides an accurate and reliable method for assessing the digital supply chain maturity of advanced manufacturing companies. Research limitations/implications The model proposed in this paper is primarily founded on the SCOR DS model. However, as the understanding of digital supply chain concepts deepens and related terminologies are standardized, it becomes clear that continuous improvement of the assessment model is essential. Future empirical research will include additional case studies to verify the model's applicability. Social implications This study offers tools and methods enabling advanced manufacturing companies to assess their digital supply chain maturity level and identify areas for future improvement by analyzing current gaps. It can effectively support the continuous optimization of a company's supply chain management, which is essential to remain competitive in a fiercely competitive market environment. Originality/value A structured, standardized, and systematic digital supply chain maturity assessment model for advanced manufacturing enterprises is proposed. This model enables firms to accurately assess their digital supply chain capabilities, identify gaps and determine specific directions and pathways for further enhancement. It ensures the continuous improvement of a company's digital supply chain maturity.

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Publication Details

Journal
Kybernetes
Published
2026-02-27
DOI
https://doi.org/10.1108/k-10-2024-2917
Primary Topic
Digital Transformation in Industry
Type
article
Field-Weighted Citation Impact
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article

Development of a digital supply chain maturity assessment model for advanced manufacturing companies using OWA-EWM and cloud model evaluation

Huiling Zhang, Xiaonong Lu, Keyu Zhu, Zhanglin Peng et al.
Kybernetes
Digital Transformation in Industry
article

Development of a digital supply chain maturity assessment model for advanced manufacturing companies using OWA-EWM and cloud model evaluation

Huiling Zhang, Xiaonong Lu, Keyu Zhu, Zhanglin Peng, Qiang Zhang, Shanlin Yang
article en

Abstract

Purpose To support advanced manufacturing companies in precisely evaluating the maturity of their digital supply chains and identifying improvement opportunities, we developed the digital supply chain maturity model (DSCMM). This model is grounded in the supply chain operations reference digital standard framework and incorporates a multidimensional, multilevel set of assessment indicators. Design/methodology/approach The first step involves identifying the primary assessment dimensions and corresponding secondary indicators to construct a comprehensive supply chain maturity assessment index system. Next, the ordered weighted averaging operator and the entropy weight method are applied in a combined approach to determine indicator weights. Finally, the digital supply chain maturity level is defined, and the cloud model is applied to a selected case company to assess the maturity level of its digital supply chain. Findings A representative advanced manufacturing enterprise was selected for in-depth analysis. The empirical findings confirm that the DSCMM model provides an accurate and reliable method for assessing the digital supply chain maturity of advanced manufacturing companies. Research limitations/implications The model proposed in this paper is primarily founded on the SCOR DS model. However, as the understanding of digital supply chain concepts deepens and related terminologies are standardized, it becomes clear that continuous improvement of the assessment model is essential. Future empirical research will include additional case studies to verify the model's applicability. Social implications This study offers tools and methods enabling advanced manufacturing companies to assess their digital supply chain maturity level and identify areas for future improvement by analyzing current gaps. It can effectively support the continuous optimization of a company's supply chain management, which is essential to remain competitive in a fiercely competitive market environment. Originality/value A structured, standardized, and systematic digital supply chain maturity assessment model for advanced manufacturing enterprises is proposed. This model enables firms to accurately assess their digital supply chain capabilities, identify gaps and determine specific directions and pathways for further enhancement. It ensures the continuous improvement of a company's digital supply chain maturity.

Kybernetes
Hefei University of Technology (CN)
Industry, innovation and infrastructure
Openalex Percentile: Top 45%
Digital Transformation in Industry
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