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dc.contributor.authorZavolokina, Liudmila-
dc.contributor.authorSpychiger, Florian-
dc.contributor.authorTessone, Claudio-
dc.contributor.authorSchwabe, Gerhard-
dc.date.accessioned2019-05-09T13:46:16Z-
dc.date.available2019-05-09T13:46:16Z-
dc.date.issued2018-
dc.identifier.isbn978-0-9966831-7-3de_CH
dc.identifier.urihttps://aisel.aisnet.org/icis2018/economics/Presentations/6/de_CH
dc.identifier.urihttps://digitalcollection.zhaw.ch/handle/11475/17045-
dc.description.abstractRecent research reports the need for consistent incentives in blockchain-based systems. In this study, we investigate how incentives for a blockchain-based inter-organizational network should be designed to ensure a high quality of data, exchanged and stored within the network. For this, we use two complementary methodological approaches: an Action Design Research approach in combination with agent-based modelling, and demonstrate, through the example of a real-world blockchain project, how such an incentive system may be modelled. The proposed incentive system features a rating mechanism influenced by measures of data correction. We evaluate the incentive system in a simulation to show how effective the system is in terms of sustaining a high quality of data. Thus, the paper contributes to our understanding of incentives in inter- organizational settings and, more broadly, to our understanding of incentive mechanisms in blockchain economy.de_CH
dc.language.isoende_CH
dc.publisherAssociation for Information Systemsde_CH
dc.rightsLicence according to publishing contractde_CH
dc.subjectAction design researchde_CH
dc.subjectBlockchainde_CH
dc.subjectData qualityde_CH
dc.subject.ddc658.4: Leitendes Managementde_CH
dc.titleIncentivizing data quality in blockchains for inter-organizational networks : learning from the digital car dossierde_CH
dc.typeKonferenz: Paperde_CH
dcterms.typeTextde_CH
zhaw.departementSchool of Management and Lawde_CH
zhaw.organisationalunitInstitute for Organizational Viability (IOV)de_CH
dc.identifier.doi10.5167/uzh-157909de_CH
zhaw.conference.details39th International Conference of Information Systems 2018, San Francisco, USA, 13-16 December 2018de_CH
zhaw.funding.euNode_CH
zhaw.originated.zhawYesde_CH
zhaw.publication.statuspublishedVersionde_CH
zhaw.publication.reviewPeer review (Abstract)de_CH
zhaw.title.proceedingsICIS 2018 Proceedingsde_CH
Appears in collections:Publikationen School of Management and Law

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Zavolokina, L., Spychiger, F., Tessone, C., & Schwabe, G. (2018). Incentivizing data quality in blockchains for inter-organizational networks : learning from the digital car dossier. ICIS 2018 Proceedings. https://doi.org/10.5167/uzh-157909
Zavolokina, L. et al. (2018) ‘Incentivizing data quality in blockchains for inter-organizational networks : learning from the digital car dossier’, in ICIS 2018 Proceedings. Association for Information Systems. Available at: https://doi.org/10.5167/uzh-157909.
L. Zavolokina, F. Spychiger, C. Tessone, and G. Schwabe, “Incentivizing data quality in blockchains for inter-organizational networks : learning from the digital car dossier,” in ICIS 2018 Proceedings, 2018. doi: 10.5167/uzh-157909.
ZAVOLOKINA, Liudmila, Florian SPYCHIGER, Claudio TESSONE und Gerhard SCHWABE, 2018. Incentivizing data quality in blockchains for inter-organizational networks : learning from the digital car dossier. In: ICIS 2018 Proceedings [online]. Conference paper. Association for Information Systems. 2018. ISBN 978-0-9966831-7-3. Verfügbar unter: https://aisel.aisnet.org/icis2018/economics/Presentations/6/
Zavolokina, Liudmila, Florian Spychiger, Claudio Tessone, and Gerhard Schwabe. 2018. “Incentivizing Data Quality in Blockchains for Inter-Organizational Networks : Learning from the Digital Car Dossier.” Conference paper. In ICIS 2018 Proceedings. Association for Information Systems. https://doi.org/10.5167/uzh-157909.
Zavolokina, Liudmila, et al. “Incentivizing Data Quality in Blockchains for Inter-Organizational Networks : Learning from the Digital Car Dossier.” ICIS 2018 Proceedings, Association for Information Systems, 2018, https://doi.org/10.5167/uzh-157909.


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