Toward Cross-Company Value Generation from Data: Design Principles for Developing and Operating Data Sharing Communities

Détails

ID Serval
serval:BIB_FA4976B2B2E6
Type
Actes de conférence (partie): contribution originale à la littérature scientifique, publiée à l'occasion de conférences scientifiques, dans un ouvrage de compte-rendu (proceedings), ou dans l'édition spéciale d'un journal reconnu (conference proceedings).
Collection
Publications
Institution
Titre
Toward Cross-Company Value Generation from Data: Design Principles for Developing and Operating Data Sharing Communities
Titre de la conférence
Lecture Notes in Computer Science
Auteur⸱e⸱s
Lefebvre Hippolyte, Flourac Gabin, Krasikov Pavel, Legner Christine
Editeur
Springer Nature Switzerland
Organisation
International Conference on Design Science Research in Information Systems and Technology
ISBN
9783031328077
9783031328084
ISSN
0302-9743
1611-3349
Statut éditorial
Publié
Date de publication
2023
Peer-reviewed
Oui
Volume
13873
Série
Lecture Notes in Computer Science
Pages
33-49
Langue
anglais
Résumé
Unlike other assets, data’s value increases when it is shared and reused. Whereas organizations have traditionally exchanged data vertically with other actors along the value chain, we observe that they increasingly share complementary data assets with others, even at times with their competitors, to address business and societal challenges. Research on these new forms of horizontal data sharing and the emerging data ecosystems is still scarce. Building on the theory of communities of practice, we study a pioneer data sharing community comprising more than 20 multinational companies that developed an innovative approach to pool data management efforts. We derive eight design principles for horizontal data sharing, which we cluster according to the following dimensions: domain of interest, shared practice, and community. By offering prescriptive design knowledge, our findings make an important contribution to the emerging literature on cross-company data sharing. Our research also provides practitioners with actionable insights on how to establish and operate data sharing communities effectively.
Mots-clé
Data Sharing, Data Community, Data Ecosystem, Design Principle
Financement(s)
Autre / Competence Center Corporate Data Quality (CC CDQ)
Université de Lausanne
Création de la notice
23/06/2023 0:00
Dernière modification de la notice
23/06/2023 5:55
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