The market for the Industrial Internet of Things (IIoT) platforms remains highly dynamic and is rapidly evolving regarding the growth of the platform-based ecosystems. However, digital platforms, used in the industrial business-to-business setting, differ significantly from the established platforms in the business-to-consumer domains and remain little researched. In this study, we apply a data-driven approach and conduct bottom-up and top-down content analysis, exploring social media data on the current state of IIoT platforms. For a top-down analysis, we draw on the theoretical concept of platform boundary resources. Specifically, we apply descriptive analytics and topic modeling on the Twitter data regarding the market-ready IIoT platforms Adamos, Cumulocity, Watson IoT, MindSphere, Leonardo, and ThingWorx, thus conducting an exploratory multiple case study. Our findings generate descriptive insights on the currently discussed topics in the area of IIoT platforms, contributing to the knowledge of the current state of digital platforms used in IIoT.
