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.
| Verfasserangaben: | Hannah Stein, Calvin Rix, Anna Effertz, Sven Bergau, Wolfgang Maass |
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| URL: | https://aisel.aisnet.org/amcis2022/DataEcoSys/DataEcoSys/1 |
| Titel des übergeordneten Werkes (Englisch): | AMCIS 2022 Proceedings |
| Dokumentart: | Konferenzveröffentlichung |
| Sprache: | Englisch |
| Datum der Veröffentlichung (online): | 30.10.2023 |
| Datum der Erstveröffentlichung: | 16.05.2023 |
| Datum der Freischaltung: | 30.10.2023 |
| Freies Schlagwort / Tag: | rev data ecosystems; data sharing; data value; food industry |
| Umfang: | 10 S. |
| FIR-Nummer: | SV7771 |
| Konferenzname: | Twenty-eighth Americas Conference on Information Systems (AMCIS) |
| Konferenzort: | Minneapolis (MS) |
| Konferenzzeitraum: | 10.08.2022-14.08.2022 |
| Institut / Bereiche des FIR: | FIR e. V. an der RWTH Aachen |
| Dienstleistungsmanagement | |
| DDC-Klassifikation: | 6 Technik, Medizin, angewandte Wissenschaften / 62 Ingenieurwissenschaften |
