Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/249616 
Year of Publication: 
2021
Citation: 
[Editor:] Kersten, Wolfgang [Editor:] Ringle, Christian M. [Editor:] Blecker, Thorsten [Title:] Adapting to the Future: How Digitalization Shapes Sustainable Logistics and Resilient Supply Chain Management. Proceedings of the Hamburg International Conference of Logistics (HICL), Vol. 31 [ISBN:] 978-3-7549-2770-0 [Publisher:] epubli GmbH [Place:] Berlin [Year:] 2021 [Pages:] 185-218
Publisher: 
epubli GmbH, Berlin
Abstract: 
Purpose: Many Industry 4.0 projects fail because impending sociotechnical risks are managed insufficiently. An indicator-based, sociotechnical risk monitoring can help to overcome this challenge. However, its effectiveness depends significantly on selecting appropriate risk indicators. This paper outlines a framework that helps decision-makers with the necessary structuring, allowing for subsequent indicator definition. Methodology: Indicators must be embedded in specific contexts to be meaningful. The design of indicator-based monitoring systems, therefore, first requires an appropriate framework. For this purpose, specific requirements related to digitization projects are derived from both literature and practitioners' needs. Findings: Risks in the context of Industry 4.0 projects are systemic risks. For efficient monitoring, new approaches are needed that can manage this high complexity. Systems theory is found suitable to develop a new framework for indicator-based, sociotechnical project risk monitoring. The framework considers the characteristics of projects and enterprises as complex, open, and sociotechnical systems. Originality: Especially in complex projects like those of Industry 4.0, situational risk awareness can contribute crucially to project success. However, achieving this awareness always requires tailored approaches addressing the unique project characteristics. To help solve this challenge for digitization projects, the proposed framework sets both a science-based and practitioner-relevant foundation for subsequent derivation of sociotechnical risk indicators.
Subjects: 
Advanced Manufacturing
Industry 4.0
Persistent Identifier of the first edition: 
Creative Commons License: 
cc-by-sa Logo
Document Type: 
Conference Paper

Files in This Item:
File
Size





Items in EconStor are protected by copyright, with all rights reserved, unless otherwise indicated.