Studying the adoption and acceptance of Mobile Data Services (MDS) has been an intriguing endeavour for quite some time. Much of the related literature is inspired by the Technology Acceptance Model and its heirs. The study presented in this paper adopts an alternative perspective and proposes the study of MDS actual usage patterns under the lens of the Triandis theory of explaining human behaviour. To this end, we adjust the concepts included in the original Triandis model to the MDS context and construct a model predicting MDS use. The model is empirically validated through a survey (N=365) and tested for its predictive capacity against four different MDS categories (m-commerce, communication, information, and entertainment services). Results suggest that the uptake of each of the four service categories is contingent upon a limited set of factors. In addition, financial barriers emerge as a universal inhibitor over and above specific service groupings.