Towards An Understanding Of Coopetition In Data Ecosystems: A Systematic Literature Review Zerbin, Julian Koldewey, Christian Dumitrescu, Roman data sharing interfirm relations paradox theory strategic alliances network governance Data ecosystems offer new opportunities for value creation by enabling companies to combine and reuse data beyond their own boundaries. Coopetition, i.e., simultaneous cooperation and competition, is an important dynamic within data ecosystems that must be understood and managed well to leverage the non-rivalrous nature of data. A systematic literature review of 38 peer-reviewed studies on ecosystems and coopetition was conducted to clarify how coopetition affects data ecosystems. Using qualitative content analysis, the study summarizes how coopetition is calibrated, what results it produces, and what challenges are associated with it. The resulting Data Ecosystem Coopetition (DECo) model specifies four management levers, as well as the associated outcomes and common challenges. In addition, six cycles were identified that link levers, challenges, and outcomes. These cycles provide concise guidance on elements that tend to vary together and highlight areas that are prone to specific tensions. 2026 info:eu-repo/semantics/conferenceObject doc-type:conferenceObject text http://purl.org/coar/resource_type/c_5794 https://ris.uni-paderborn.de/record/66071 Zerbin J, Koldewey C, Dumitrescu R. Towards An Understanding Of Coopetition In Data Ecosystems: A Systematic Literature Review. In: <i>ECIS 2026 Proceedings</i>. ; 2026. eng info:eu-repo/semantics/closedAccess