The role of digital technologies in service business transformation is under-investigated. This paper contributes to filling\ud
this gap by addressing how the Internet of things (IoT), cloud computing (CC) and predictive analytics (PA) facilitate\ud
service transformation in industrial companies. Through the Data–Information–Knowledge–Wisdom (DIKW) model, we\ud
discuss how the abovementioned technologies transform low-level entities such as data into information and knowledge\ud
to support the service transformation of manufacturers. We propose a set of digital capabilities, based on the extant\ud
literature and the findings from four case studies. Then, we discuss how these capabilities support the service transformation\ud
trajectories of manufacturers. We find that IoT is foundational to any service transformation, although it is mostly\ud
needed to become an availability provider. PA is essential for moving to the performance provider profile. Besides\ud
providing scalability in all profiles, CC is specifically used to implement an industrialiser strategy, therefore leading to\ud
standardised, repeatable and productised offering
Organisations have been approaching servitisation in an unstructured fashion. This is partially because there is insufficient understanding of the different types of Product-Service offerings. Therefore, a more detailed understanding of Product-Service types might advance the collective knowledge and assist organisations that are considering a servitisation strategy. Current models discuss specific aspects on the basis of few (or sometimes single) dimensions. In this paper, we develop a comprehensive model for classifying traditional and green Product-Service offerings. Our work is not purely environmentally focused; instead, it combines business and green offerings in a single model. We describe the model building
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