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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Metadaten
Author:Hannah Stein, Calvin Rix, Anna Effertz, Sven Bergau, Wolfgang Maass
URL:https://aisel.aisnet.org/amcis2022/DataEcoSys/DataEcoSys/1
Parent Title (English):AMCIS 2022 Proceedings
Document Type:Conference Proceeding
Language:English
Date of Publication (online):2023/10/30
Date of first Publication:2023/05/16
Release Date:2023/10/30
Tag:03; rev
data ecosystems; data sharing; data value; food industry
Page Number:10 S.
FIR-Number:SV7771
Name of the conference:Twenty-eighth Americas Conference on Information Systems (AMCIS)
place of the conference:Minneapolis (MS)
Date of the conference:10.08.2022-14.08.2022
Institute / Department:FIR e. V. an der RWTH Aachen
Dienstleistungsmanagement
Dewey Decimal Classification:6 Technik, Medizin, angewandte Wissenschaften / 62 Ingenieurwissenschaften