TY - GEN
T1 - Application of Hyperledger Blockchain to Reduce Information Asymmetries in the Used Car Market
AU - Shen, Chien Wen
AU - Koziel, Agnieszka Maria
AU - Wen, Chieh
N1 - Publisher Copyright:
© 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.
PY - 2022
Y1 - 2022
N2 - The used car market has long been an example of a market rife with information asymmetry between sellers and buyers. Since most consumers have little experience and knowledge in buying cars, they rely on the historical vehicle documents provided only by car dealers, which might be insufficient to make pre-purchase judgments. To receive more information about events that occurred in the vehicle’s past, buyers need to spend time collecting other related documents from different sources. The whole process is time-consuming and leads to quality uncertainties causing market inefficiency. Such a problem can be alleviated by blockchain technology by using nodes of a computer network to record the historical information of a car, where the chain of data cannot be falsified, creating transparent, verified, and easy access to all documents. Accordingly, we propose a Hyperledger-based approach and simulate the acquisition time of historical vehicle data to illustrate the blockchain application to reduce information asymmetries in the used car market. In Hyperledger Fabric, all business network transactions are recorded on the smart contracts, allowing the records to coexist among the participants, including dealers, maintenance plants, motor vehicle offices, police offices, and buyers. This blockchain technology application mitigates information asymmetries between buyers and sellers, guarantees the integrity and transparency of data, and shortens the time obtaining historical car information.
AB - The used car market has long been an example of a market rife with information asymmetry between sellers and buyers. Since most consumers have little experience and knowledge in buying cars, they rely on the historical vehicle documents provided only by car dealers, which might be insufficient to make pre-purchase judgments. To receive more information about events that occurred in the vehicle’s past, buyers need to spend time collecting other related documents from different sources. The whole process is time-consuming and leads to quality uncertainties causing market inefficiency. Such a problem can be alleviated by blockchain technology by using nodes of a computer network to record the historical information of a car, where the chain of data cannot be falsified, creating transparent, verified, and easy access to all documents. Accordingly, we propose a Hyperledger-based approach and simulate the acquisition time of historical vehicle data to illustrate the blockchain application to reduce information asymmetries in the used car market. In Hyperledger Fabric, all business network transactions are recorded on the smart contracts, allowing the records to coexist among the participants, including dealers, maintenance plants, motor vehicle offices, police offices, and buyers. This blockchain technology application mitigates information asymmetries between buyers and sellers, guarantees the integrity and transparency of data, and shortens the time obtaining historical car information.
KW - Asymmetric information
KW - Blockchain
KW - Hyperledger
KW - Smart contract
KW - Used car
UR - http://www.scopus.com/inward/record.url?scp=85145250677&partnerID=8YFLogxK
U2 - 10.1007/978-3-031-21967-2_40
DO - 10.1007/978-3-031-21967-2_40
M3 - 會議論文篇章
AN - SCOPUS:85145250677
SN - 9783031219665
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 495
EP - 508
BT - Intelligent Information and Database Systems - 14th Asian Conference, ACIIDS 2022, Proceedings
A2 - Nguyen, Ngoc Thanh
A2 - Trawiński, Bogdan
A2 - Nguyen, Ngoc Thanh
A2 - Tran, Tien Khoa
A2 - Tukayev, Ualsher
A2 - Hong, Tzung-Pei
A2 - Szczerbicki, Edward
PB - Springer Science and Business Media Deutschland GmbH
T2 - 14th Asian Conference on Intelligent Information and Database Systems , ACIIDS 2022
Y2 - 28 November 2022 through 30 November 2022
ER -