The internet of things (IoT) is one of the pillars of Industry 4.0. Prior OM research has conceptualized IoT, and analyzed potential applications and risks and challenges associated with its adoption. However, little empirical evidence exists on the main types of IoT projects undertaken by organizations and on their impacts. The purpose of this paper is to close this gap by searching for a taxonomy of IoT projects that may be associated to different IoT readiness levels. The dynamic capability lens is used as the theoretical background for the analysis.
A database of secondary IoT case studies is used to identify an IoT project taxonomy through two-step cluster analysis. The taxonomy obtained allows classifying projects into homogenous groups by technological novelty, IoT capabilities and functional areas of application. ANOVA is then used to test for the association between cluster membership and alternative operational impacts. Finally, the analysis of selected case studies from the database allows throwing light on the nature of the projects typical of each cluster.
Five clusters of projects have been identified and positioned along varying degrees of capabilities, novelty and scope. The taxonomy is consistent with a three layer IoT technological readiness model. In turn, the three IoT readiness levels correspond to three managerial capabilities: monitoring, control and optimization. Combining cluster results with detailed case analysis suggests that IoT technological readiness can be interpreted as a dynamic capability enabling knowledge creation that can support competitive advantage.
This is a first attempt to describe projects firms undertake when adopting IoT. Building on cluster analysis, the study suggests that different IoT readiness levels are needed to reach different impacts.
