Paper Number
1226
Paper Type
Complete Research Paper
Abstract
With the increasing abundance of data, organizations may not only leverage internal data sources to create value but also share data across organizations. However, successful real-world applications of data sharing are still scarce, and support for the systematic development of data sharing practices remains weak. Realizing the true potential of data sharing requires understanding and making informed choices among a wide range of design options, such as bilateral sharing or data ecosystems. In this study, we draw on a systematic literature review as well as 72 real-world data sharing practices to develop a comprehensive taxonomy consisting of 15 dimensions across three meta-dimensions. From a theoretical perspective, our work contributes to structuring and systematizing existing knowledge on data sharing to form the basis for future theorizing processes. In practical terms, it should enable organizations to systematically embrace and evaluate strategic data sharing opportunities.
Recommended Citation
Fassnacht, Marcel; Benz, Carina; Bode, Jan; Heinz, Daniel; and Satzger, Gerhard, "Systematizing Data Sharing Practices: A Taxonomy" (2024). ECIS 2024 Proceedings. 3.
https://aisel.aisnet.org/ecis2024/is_governance/track21_is_govern/3
Systematizing Data Sharing Practices: A Taxonomy
With the increasing abundance of data, organizations may not only leverage internal data sources to create value but also share data across organizations. However, successful real-world applications of data sharing are still scarce, and support for the systematic development of data sharing practices remains weak. Realizing the true potential of data sharing requires understanding and making informed choices among a wide range of design options, such as bilateral sharing or data ecosystems. In this study, we draw on a systematic literature review as well as 72 real-world data sharing practices to develop a comprehensive taxonomy consisting of 15 dimensions across three meta-dimensions. From a theoretical perspective, our work contributes to structuring and systematizing existing knowledge on data sharing to form the basis for future theorizing processes. In practical terms, it should enable organizations to systematically embrace and evaluate strategic data sharing opportunities.
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