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Development of Digital Transformation Maturity Assessment Model for Collaborative Factory Involving Multiple Companies

Author

Listed:
  • Keeeun Lee

    (Department of Industrial & Systems Engineering, School of Engineering, Dongguk University, Seoul 13557, Republic of Korea)

  • Youngchul Song

    (Department of Industrial & Systems Engineering, School of Engineering, Dongguk University, Seoul 13557, Republic of Korea)

  • Minyoung Park

    (Department of Industrial & Systems Engineering, School of Engineering, Dongguk University, Seoul 13557, Republic of Korea)

  • Byungun Yoon

    (Department of Industrial & Systems Engineering, School of Engineering, Dongguk University, Seoul 13557, Republic of Korea)

Abstract

Recent advancements in digital transformation (DX) in the industrial sector have spotlighted digital collaborative factories, which emphasize relationships with partners, particularly in the manufacturing sector. However, existing DX maturity assessment models primarily focus on evaluating individual companies, lacking consideration of partnerships and thereby failing to reflect the complexities of collaborative systems. To address this limitation, this study aims to develop a DX maturity assessment model tailored to digital collaborative factories while accounting for collaborative relationships. Initially, 25 existing DX maturity assessment models were reviewed, and the evaluation elements related to collaboration were extracted from each. Accordingly, the maturity assessment model was created with 15 evaluation factors, including organizational aspects, process management, quality control, and logistics operations. Finally, to verify the applicability of the model, the DX maturity levels of a lead company—a forklift-manufacturing company—and its partner—an automotive component manufacturer—within the same value chain were assessed, and the model’s suitability was evaluated. The results indicate that the lead company needed to improve on the intelligence, connectivity, and automation aspects, while its partner needs to streamline production process operations and technological connectivity. This approach enables manufacturers to obtain more reliable information in resolving issues arising from collaboration with partners, as well as in establishing future strategies. The findings suggest that strengthening collaboration systems among partners and advancing DX based on digital collaboration will raise competitiveness within the manufacturing sector.

Suggested Citation

  • Keeeun Lee & Youngchul Song & Minyoung Park & Byungun Yoon, 2024. "Development of Digital Transformation Maturity Assessment Model for Collaborative Factory Involving Multiple Companies," Sustainability, MDPI, vol. 16(18), pages 1-30, September.
  • Handle: RePEc:gam:jsusta:v:16:y:2024:i:18:p:8087-:d:1479099
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    References listed on IDEAS

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    1. Osterrieder, Philipp & Budde, Lukas & Friedli, Thomas, 2020. "The smart factory as a key construct of industry 4.0: A systematic literature review," International Journal of Production Economics, Elsevier, vol. 221(C).
    2. Li, Wei & Chen, Jing & Chen, Bintong, 2018. "Supply chain coordination with customer returns and retailer's store brand product," International Journal of Production Economics, Elsevier, vol. 203(C), pages 69-82.
    3. Fulgence Dominick WARYOBA, 2022. "The effect of information and communication technology on business performance," Romanian Journal of Economics, Institute of National Economy, vol. 55(2(64)), pages 84-102, December.
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    Cited by:

    1. Yanmei Xu & Yanan Zhang & Xiang Li & Ziqiang Wang & Qiwen Zhang, 2025. "Research on Digital Transformation and the Innovation Model of SMMEs: The Case Study of PAYA," Sustainability, MDPI, vol. 17(8), pages 1-32, April.

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