Application of Blockchain Hierarchical Model in the Realm of Rural Green Credit Investigation
Haoyang Tan and
Qiang Zhang
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Haoyang Tan: School of Finance and Statistics, Hunan University, Changsha 410000, China
Qiang Zhang: School of Finance and Statistics, Hunan University, Changsha 410000, China
Sustainability, 2021, vol. 13, issue 3, 1-9
Abstract:
In order to realize the application research of blockchain technology in the field of green credit investigation, the current paper adopts the method of a blockchain hierarchical model to study the rural green credit. With regard to the realm of rural green credit investigation, this paper sorts out the characteristics of credit data in China’s countryside by countryside credit investigation and determines the major problems and in rural green credit investigation of financial inclusion. Subsequently, the authors put forward a blockchain hierarchical model, which not only has reinforced the advantages in original blockchain dedicated to agriculture, rural areas and rural residents, such as traceability and immutability, but also has transformed the decentralization into disintermediation and changed the single-layered P2P network into a multilayered structure based on China’s rural financial environment. Finally, the authors collect and extract the proper credit investigation data on the rural internet to assess the application value of the model by investigating its practical applicability in reality and problems that may occur during the application of the model. Results show that private credit information has an important impact on the prediction accuracy, and the blockchain hierarchical model is helpful to ensure the reliability and security of rural green credit data.
Keywords: blockchain; hierarchical model; rural green credit investigation; probability of default (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)
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Persistent link: https://EconPapers.repec.org/RePEc:gam:jsusta:v:13:y:2021:i:3:p:1324-:d:488066
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