@article{66070,
  abstract     = {{Der Beitrag stellt einen Online-Quick-Check vor, der KMU einen niedrigschwelligen Einstieg in industrielle Datenräume ermöglicht. Der Check kombiniert eine zweidimensionale Einschätzung der Readiness (strategisch/technologisch) mit einer Mehrwert-Priorisierung zur Ableitung passender Use Cases. In einer Pilotierung (n = 19) zeigen sich v. a. Defizite bei der Vernetzung, den datenbasierten Entscheidungen und Datenrollen; priorisiert werden Mehrwerte in Planung, Qualität und Effizienz.}},
  author       = {{Zerbin, Julian and Grünwoldt, Max and Koldewey, Christian and Dumitrescu, Roman}},
  issn         = {{2511-0896}},
  journal      = {{Zeitschrift für wirtschaftlichen Fabrikbetrieb}},
  keywords     = {{KMU, Data Space, Data Sharing, Industrie 4.0, Datensouveränität, Readiness}},
  number       = {{6}},
  pages        = {{458--462}},
  publisher    = {{Walter de Gruyter GmbH}},
  title        = {{{Ein Quick-Check für Industrielle Datenräume – Voraussetzungen und Mehrwerte}}},
  doi          = {{10.1515/zwf-2026-1077}},
  volume       = {{121}},
  year         = {{2026}},
}

@inproceedings{66071,
  abstract     = {{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.}},
  author       = {{Zerbin, Julian and Koldewey, Christian and Dumitrescu, Roman}},
  booktitle    = {{ECIS 2026 Proceedings}},
  keywords     = {{data sharing, interfirm relations, paradox theory, strategic alliances, network governance}},
  location     = {{Mailand}},
  title        = {{{Towards An Understanding Of Coopetition In Data Ecosystems: A Systematic Literature Review}}},
  year         = {{2026}},
}

@inproceedings{66073,
  abstract     = {{Data-driven business models are transforming industries, yet small and medium-sized enterprises (SMEs) often lack the resources to participate in emerging data sharing initiatives. Data spaces provide a federated infrastructure for sovereign data sharing, but SME participation remains limited due to complex onboarding processes involving technical, organizational, legal, and economic barriers. Data trustees have been proposed as intermediaries to facilitate data sharing, but their specific role in supporting SME onboarding has not been systematically explored. Here we present a reference process for SME data space onboarding and derive four design principles, structured along the TELO framework, describing how data trustees can address these barriers. Our findings reveal that SMEs require comprehensive support throughout the onboarding journey, with particular emphasis on business case development. The results offer actionable guidance for data space operators and policymakers seeking to broaden ecosystem participation as the European Union advances its data strategy.}},
  author       = {{Hupperz, Marius Johannes and Zerbin, Julian and Kunert, Julia}},
  booktitle    = {{AMCIS 2026 Proceedings}},
  keywords     = {{Data spaces, data trustees, SME Onboarding, data sharing}},
  location     = {{Reno - Nevada}},
  title        = {{{Toward Design Principles for Data Trustee-Supported SME Onboarding in Data Spaces}}},
  year         = {{2026}},
}

@inproceedings{66072,
  abstract     = {{Data Spaces are establishing themselves as a decentralized alternative for sovereign data sharing across organizations. However, their adoption faces significant challenges, particularly the lack of proven business models that encourage participation and value creation. A data space business model captures value differently than either traditional business models or platform business models. This paper addresses this challenge by developing the Data Space Canvas, a structured framework for designing and aligning business models in data spaces consisting of nine building blocks. The canvas was developed following the design science research methodology. The modular and role-specific structure of the Data Space Canvas facilitates shared understanding and supports business model development across participants. This research contributes a practical tool that enables organizations to conceptualize, communicate, and refine their role and business model in data spaces.}},
  author       = {{Zerbin, Julian and Koldewey, Christian and Dumitrescu, Roman}},
  booktitle    = {{ECIS 2026 Proceedings}},
  keywords     = {{data ecosystems, business model, design science, resource orchestration theory, data sharing}},
  location     = {{Mailand}},
  title        = {{{The Data Space Canvas: A Framework For Structuring Business Models In Data Spaces}}},
  year         = {{2026}},
}