The Whole-Course Logistics Enterprise Credit Reference System Based on Blockchain Technology

Yang Mao (), Minzhen Huang (), Shifeng Liu (), Yi Song (), Guohua Li () and Jingya Liu ()
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Yang Mao: Beijing Jiaotong University
Minzhen Huang: China Academy of Railway Sciences
Shifeng Liu: Beijing Jiaotong University
Yi Song: Beijing Jiaotong University
Guohua Li: China Academy of Railway Sciences
Jingya Liu: Beijing Jiaotong University

A chapter in LISS 2020, 2021, pp 279-290 from Springer

Abstract: Abstract In order to solve the problem of credit information asymmetry between whole-course logistics enterprises, this paper proposes a credit reference system structure based on the blockchain technology and expounds the application processes of data collection, credit modeling scoring and credit score sharing by blockchain technology. Based on the data of A-share listed logistic companies in China from 2011 to 2019, this paper empirically examines the scoring model and discusses the advantages of blockchain application in the logistics credit industry in the era of big data: dynamic update and traceability of credit data, promoting credit data sharing, ensuring the privacy of information subjects and unifying industry credit evaluation standards.

Keywords: Blockchain; Whole-course logistics; Scoring model; Credit reference system (search for similar items in EconPapers)
Date: 2021
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-981-33-4359-7_20

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DOI: 10.1007/978-981-33-4359-7_20

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