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Lăcrămioara Radomir, Raluca Ciornea, Huiwen Wang, Yide Liu, Christian M. Ringle & Marko Sarstedt (Editors), State of the Art in Partial Least Squares Structural Equation Modeling (PLS-SEM), Springer, 2023
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Karagiannis, D., Buchmann, R.A. & Utz, W. (2022) Computers in Industry [Info Economics, Q1]

Autor: Ovidiu Ioan Moisescu

Publicat: 20 Martie 2022


Karagiannis, D., Buchmann, R.A. & Utz, W. (2022) The OMiLAB Digital Innovation environment: Agile conceptual models to bridge business value with Digital and Physical Twins for Product-Service Systems development. Computers in Industry, 138, 103631.

DOI: https://doi.org/10.1016/j.compind.2022.103631

✓ Publisher: Elsevier
✓ Categories: Computer science, interdisciplinary
✓ Article Influence Score (AIS): 1.546 (2022) / Q1

Abstract: OMiLAB is a community of practice which offers a digital ecosystem bringing together open technologies to investigate and apply conceptual modeling methods for varying purposes and domains. One of the core value propositions is a dedicated Digital Innovation environment comprising several toolkits and workspaces, designed to support Product-Service Systems (PSS) prototyping – a key ingredient for PSS lifecycle management. At the core of this environment is a notion of Agile Digital Twin – a conceptual representation that can be tailored with knowledge engineering means to bridge the semantic and functional gap between a business perspective (focusing on value creation) and an engineering perspective (focusing on cyber-physical proofs-of-concept). To facilitate this bridging, the hereby proposed environment orchestrates, across three abstraction layers, methods such as Design Thinking, Agile Modeling Method Engineering and Model-driven Engineering to turn Ideation into smart Product-Service Systems experiments, in a laboratory setting. The proposed environment was built following Design Science principles. It addresses the problem of historically-disconnected skills required for Digital Innovation projects and it provides a testbed for feasibility experimentation. For design-oriented, artifact building research, a higher Technology Readiness Level can thus be achieved (compared to the level that idea development methods typically attain).



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