From hesitation to participation in industrial data ecosystems: Analysis of motives and incentives in the automotive industry - Marc Brechtel (Electronic Markets, 2025)
Industrial firms are increasingly dependent on data from business partners, raising the need for and value of inter-firm data sharing. Yet, many industrial firms are hesitant to join and share data within industrial data ecosystems. Existing research neglects the diversity of actor groups along industrial supply chains and lacks a detailed understanding of their motives and requirements for incentivizing data sharing. This study adopts a two-step qualitative research approach dedicated to investigating Catena-X—the data ecosystem for the automotive industry. Drawing on 28 expert interviews combined with secondary data, we have discovered a differentiating pattern in data-sharing motives along the automotive supply chain. We analyze the relationships of selected motives, appropriate incentives, and incentive-supporting components by applying the incentive theory of motivation. These findings result in propositions for each supply chain stage on how data ecosystem initiators can further incentivize the participation of actors. Our findings help in supporting the establishment of industrial data ecosystems.
Keywords: 620; Industrial data ecosystems; Inter-firm data sharing; Incentive theory of motivation; Catena-X