DataEcoSys - Data EcoSystem in Information Systems
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Paper Type
Complete
Paper Number
1059
Description
Big data are collected along the entire food industry value chain, but remain mostly unused. Data sharing in data ecosystems could lead to efficiency gains and new revenue streams. We investigate data sharing within food industry and derive challenges and opportunities for data sharing in this context. We conducted interviews with ten qualified experts from the German food industry. The results reveal that mainly trust, usefulness and value influence users’ attitude towards data sharing. Our results confirm social exchange theory in conjunction with technology acceptance model as relevant underlying IS theories of data sharing.
Recommended Citation
Stein, Hannah; Rix, Calvin; Effertz, Anna; Bergau, Sven; and Maass, Wolfgang, "Data Sharing in the German Food Industry - Empirical Insights" (2022). AMCIS 2022 Proceedings. 1.
https://aisel.aisnet.org/amcis2022/DataEcoSys/DataEcoSys/1
Data Sharing in the German Food Industry - Empirical Insights
Big data are collected along the entire food industry value chain, but remain mostly unused. Data sharing in data ecosystems could lead to efficiency gains and new revenue streams. We investigate data sharing within food industry and derive challenges and opportunities for data sharing in this context. We conducted interviews with ten qualified experts from the German food industry. The results reveal that mainly trust, usefulness and value influence users’ attitude towards data sharing. Our results confirm social exchange theory in conjunction with technology acceptance model as relevant underlying IS theories of data sharing.
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DataEcoSys