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The Industrial Internet of Things (IIoT) paradigm constitutes the connection of uniquely identifiable things to the internet in an industrial context. It provides disruptive capabilities and value propositions, especially for the management and improvement of business processes. To exploit these, many companies have already implemented manifold IIoT applications along their value chain activities aiming at beneficial Business Process Improvements (BPI). However, research on IIoT-based BPI is low on theoretical insights. To add to the descriptive knowledge of the IIoT, a structured synoptic view and classification scheme are required. The work at hand addresses this need by providing a taxonomy of IIoT-based BPI applications. Based on the combination of an inductive and deductive research methodology, the created taxonomy consists of six dimensions, seven subdimensions, and 40 characteristics. The taxonomy is evaluated on a sample of 30 IIoT applications from the literature and 10 real-life applications from a market-leading company.



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