Please use this identifier to cite or link to this item: https://doi.org/10.21256/zhaw-28256
Publication type: Article in scientific journal
Type of review: Peer review (publication)
Title: Incentivizing data quality in blockchain-based systems : the case of the digital cardossier
Authors: Spychiger, Florian
Tessone, Claudio J.
Zavolokina, Liudmila
Schwabe, Gerhard
et. al: No
DOI: 10.1145/3538228
10.21256/zhaw-28256
Published in: Distributed Ledger Technologies
Volume(Issue): 1
Issue: 1
Issue Date: 2022
Publisher / Ed. Institution: Association for Computing Machinery
ISSN: 2769-6472
2769-6480
Language: English
Subjects: Action design research; Blockchain; Data quality; Incentive; Digitalisierung; Automotive industry; Digitalization
Subject (DDC): 005: Computer programming, programs and data
Abstract: Inspired by an industry initiative to address the celebrated market for lemons (poor-quality used cars), we investigate how incentives for a permissioned blockchain-based system in the automobile ecosystem can be designed to ensure high-quality data storage and use by different stakeholders. The peer-to-peer distributed ledger platform connects organizations and car owners with disparate interests and hidden intentions. While previous literature has chiefly examined incentives for permissionless platforms, we leverage studies about crowdsensing applications to stimulate research on incentives in permissioned blockchains. This article uses the action design research approach to create an incentive system featuring a rating mechanism influenced by data correction measures. Furthermore, we propose relying on certain institutions capable of assessing data generated within the system. This combined approach of a decentralized data correction and an institutionalized data assessment is distinct from similar incentive systems suggested by literature. By using an agent-based model with strategy evolution, we evaluate the proposed incentive system. Our findings indicate that a rating-based revenue distribution leads to markedly higher data quality in the system. Additionally, the incentive system reveals hidden information of the agents and alleviates agency problems, contributing to an understanding of incentive design in inter-organizational blockchain-based data platforms. Furthermore, we explore incentive design in permissioned blockchains and discuss its latest implications.
URI: https://digitalcollection.zhaw.ch/handle/11475/28256
Fulltext version: Published version
License (according to publishing contract): CC BY 4.0: Attribution 4.0 International
Departement: School of Management and Law
Organisational Unit: Institute for Organizational Viability (IOV)
Appears in collections:Publikationen School of Management and Law

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Spychiger, F., Tessone, C. J., Zavolokina, L., & Schwabe, G. (2022). Incentivizing data quality in blockchain-based systems : the case of the digital cardossier. Distributed Ledger Technologies, 1(1). https://doi.org/10.1145/3538228
Spychiger, F. et al. (2022) ‘Incentivizing data quality in blockchain-based systems : the case of the digital cardossier’, Distributed Ledger Technologies, 1(1). Available at: https://doi.org/10.1145/3538228.
F. Spychiger, C. J. Tessone, L. Zavolokina, and G. Schwabe, “Incentivizing data quality in blockchain-based systems : the case of the digital cardossier,” Distributed Ledger Technologies, vol. 1, no. 1, 2022, doi: 10.1145/3538228.
SPYCHIGER, Florian, Claudio J. TESSONE, Liudmila ZAVOLOKINA und Gerhard SCHWABE, 2022. Incentivizing data quality in blockchain-based systems : the case of the digital cardossier. Distributed Ledger Technologies. 2022. Bd. 1, Nr. 1. DOI 10.1145/3538228
Spychiger, Florian, Claudio J. Tessone, Liudmila Zavolokina, and Gerhard Schwabe. 2022. “Incentivizing Data Quality in Blockchain-Based Systems : The Case of the Digital Cardossier.” Distributed Ledger Technologies 1 (1). https://doi.org/10.1145/3538228.
Spychiger, Florian, et al. “Incentivizing Data Quality in Blockchain-Based Systems : The Case of the Digital Cardossier.” Distributed Ledger Technologies, vol. 1, no. 1, 2022, https://doi.org/10.1145/3538228.


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