Stoiber, Christoph and Schoenig, Stefan (2024) Leveraging the industrial internet of things for business process improvement: a metamodel and patterns. INFORMATION SYSTEMS AND E-BUSINESS MANAGEMENT, 22 (2). pp. 285-313. ISSN 1617-9846, 1617-9854
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Industrial organizations of all kinds increasingly recognize the industrial internet of thing's (IIoT) capabilities to enable valuable business process improvement (BPI). However, both theoretically and practically, there is a lack of clarity regarding the systematic and successful identification, specification, and implementation of corresponding applications. This article aims to bridge this research gap by presenting a comprehensive metamodel encompassing all relevant aspects and elements of IIoT applications with BPI propositions. The metamodel is the foundation for deriving generic yet practical patterns that can assist organizations in effectively executing IIoT projects. To evaluate the usefulness of the approach, five initial patterns were designed and applied by a market-leading organization. The metamodel and patterns contribute to the descriptive knowledge of the IIoT and facilitate sense-making, theory-led design, and practical project execution. To ensure rigor, the research endeavor followed fundamental principles of the design science research (DSR) methodology.
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | DESIGN SCIENCE; IOT; MANAGEMENT; Industrial internet of things; Business process improvement; Business process management; Metamodel; Patterns |
| Divisions: | Business, Economics and Information Systems > Institut für Wirtschaftsinformatik Business, Economics and Information Systems > Institut für Wirtschaftsinformatik > Professur für Wirtschaftsinformatik insbesondere IoT-basierte Informationssysteme – Prof. Dr. Stefan Schönig Informatics and Data Science > Department Information Systems > Professur für Wirtschaftsinformatik insbesondere IoT-basierte Informationssysteme – Prof. Dr. Stefan Schönig |
| Depositing User: | Dr. Gernot Deinzer |
| Date Deposited: | 28 Jul 2025 11:37 |
| Last Modified: | 28 Jul 2025 11:37 |
| URI: | https://pred.uni-regensburg.de/id/eprint/63865 |
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