Industrial Data-Driven Business Models: Towards a Goods-Service-Data Continuum

Current developments and trends in the business environment, like digitalization or servitization, are transforming industrial value creation logic and especially business models. Therefore, this study analyzes the impact of data on industrial business models and how newly emerging industrial data-driven business models (IDDBMs) can be systematically clustered. Given the novelty of the research topic, we choose an exploratory study design that consists of two parts. Firstly, we analyze the body of literature on data-driven business models and discuss existing clustering approaches, including elemental classifications and archetype schemes. Using the insights from the analysis of our literature sample, we develop a preliminary conceptual-theoretical classification framework. In a second step, we match, adapt, and enrich this initial framework with empirical data from seven expert interviews, strengthening practical embeddedness and generalizability. The resulting IDDBM cluster framework consists of six clusters for IDDBMs that differ in the manner by which data is transferred to the customers. While business models in the first cluster extensively use data to improve their product portfolio, in the fifth cluster, data is only used to provide a service to the customers. Business models in the sixth cluster, in contrast, generate value with their data alone without any product or service in the process. Thereby, our model expands the well-established goods-to-service continuum towards a goods-service-data continuum. Against the backdrop of the currently proposed service-dominant logic, we propose a data-dominant logic to sensitize industrial companies for the disruption that is about to influence their business models. Therefore, several recommendations are given for corporate practice to adapt to this uprising new business environment. At the same time, our model is suited to function as a research agenda on IDDBMs by channeling and structuring future research efforts into a unified framework.