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Activating supply chain business models' value potentials through Systems Engineering.

  • Published In: Systems Engineering, 2023, v. 26, n. 5. P. 660 1 of 3

  • Database: Academic Search Ultimate 2 of 3

  • Authored By: Nuerk, Jochen; Dařena, František 3 of 3

Abstract

New business opportunities, driven by smart digitalization technology and initiatives such as Industry 4.0, significantly change business models and their innovation rate. The complexity of methodologies developed in recent decades for balancing exploration and exploitation activities of digital transformation has risen. Still, the desired integration levels across organizational levels were often not reached. Systems thinking promises to holistically consider interdisciplinary relationships and objectives of various stakeholders across supply chain ecosystems. Systems theory‐based concepts can simultaneously improve value identification and aligned transformation among supply networks' organizational and technical domains. Hence, the study proposes synthesizing management science concepts such as strategic alignment with enterprise architecture concepts and artificial intelligence (AI)‐driven business process optimization to increase innovation productivity and master the increasing rate of business dynamics at the same time. Based on a critical review, the study explores concepts for innovation, transformation, and alignment in the context of Industry 4.0. The essence has been compiled into a systems engineering‐driven framework for agile value generation on operational processes and high‐order capability levels. The approach improves visibility for orchestrating sustainable value flows and transformation activities by considering the ambidexterity of exploring and exploiting activities and the viability of supply chain systems and sub‐systems. Finally, the study demonstrates the need to harmonize these concepts into a concise methodology and taxonomy for digital supply chain engineering. [ABSTRACT FROM AUTHOR]

Additional Information

  • Source:Systems Engineering. 2023/09, Vol. 26, Issue 5, p660
  • Document Type:Article
  • Subject Area:Business and Management
  • Publication Date:2023
  • ISSN:1098-1241
  • DOI:10.1002/sys.21676
  • Accession Number:171349302
  • Copyright Statement:Copyright of Systems Engineering is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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