Factors affecting SMEs credit risk and credit risk assessment based on blockchain-driven supply chain finance

Factors affecting SMEs credit risk and credit risk assessment based on blockchain-driven supply chain finance

<p>The purpose of this research is to examine the factors affecting SMEscredit risk and</p><p>credit risk assessment based on blockchain-driven supply chain finance. This research</p><p>mainly includes three objectives: The first...

Full description

Saved in:
Bibliographic Details
Main Author: Xiao, Ping
Format: thesis
Language:eng
Published: 2023
Subjects:
HG Finance
Online Access:https://ir.upsi.edu.my/detailsg.php?det=11095
Tags: Add Tag
No Tags, Be the first to tag this record!
id oai:ir.upsi.edu.my:11095
record_format uketd_dc
spelling oai:ir.upsi.edu.my:110952024-07-16 Factors affecting SMEs credit risk and credit risk assessment based on blockchain-driven supply chain finance 2023 Xiao, Ping HG Finance <p>The purpose of this research is to examine the factors affecting SMEscredit risk and</p><p>credit risk assessment based on blockchain-driven supply chain finance. This research</p><p>mainly includes three objectives: The first objective is to examine whether the</p><p>financing enterprises, core enterprises, assets position under financing, blockchain</p><p>platform and supply chain operation have significant impacts on credit risk by using</p><p>logistic regression and entropy method. The panel data were collected from CSMAR</p><p>on fifty-six SMEs, eight core enterprises and twenty-six blockchain enterprises in the</p><p>period of 2016-2020. The second objective is to establish a credit risk evaluation</p><p>index system and used factor analysis to extract the principal factors, then 11 factors</p><p>are extracted as the variable sources for credit risk assessment modeling. The third</p><p>objective is to build a credit risk assessment model by using five methods:</p><p>Classification Tree, Bagging algorithm, AdaBoost algorithm, Random Forest and</p><p>Logistic Regression to construct the credit risk assessment model. Then, according to</p><p>the model evaluation criteria, this research found out the credit risk assessment model</p><p>with the best prediction classification performance. The findings show that the</p><p>financing enterprises, core enterprises, assets position under finance, blockchain</p><p>platform, and supply chain operation have significant impacts on SMEscredit risk</p><p>when the confidence level is 90%. In general, the performance of AdaBoost algorithm</p><p>model is the best. It has the strongest ability to distinguish between enterprises with</p><p>credit risk and without credit risk, and has strong stability. The research not only</p><p>enriches the theories and method of credit risk assessment of SMEs, but also provides</p><p>assistance in solving the problem of financing difficulties for SMEs due to its ability</p><p>to accurately assess credit risk.</p> 2023 thesis https://ir.upsi.edu.my/detailsg.php?det=11095 https://ir.upsi.edu.my/detailsg.php?det=11095 text eng closedAccess Doctoral Universiti Pendidikan Sultan Idris Fakulti Pengurusan dan Ekonomi N/A
institution Universiti Pendidikan Sultan Idris
collection UPSI Digital Repository
language eng
topic HG Finance
spellingShingle HG Finance
Xiao, Ping
Factors affecting SMEs credit risk and credit risk assessment based on blockchain-driven supply chain finance
description <p>The purpose of this research is to examine the factors affecting SMEscredit risk and</p><p>credit risk assessment based on blockchain-driven supply chain finance. This research</p><p>mainly includes three objectives: The first objective is to examine whether the</p><p>financing enterprises, core enterprises, assets position under financing, blockchain</p><p>platform and supply chain operation have significant impacts on credit risk by using</p><p>logistic regression and entropy method. The panel data were collected from CSMAR</p><p>on fifty-six SMEs, eight core enterprises and twenty-six blockchain enterprises in the</p><p>period of 2016-2020. The second objective is to establish a credit risk evaluation</p><p>index system and used factor analysis to extract the principal factors, then 11 factors</p><p>are extracted as the variable sources for credit risk assessment modeling. The third</p><p>objective is to build a credit risk assessment model by using five methods:</p><p>Classification Tree, Bagging algorithm, AdaBoost algorithm, Random Forest and</p><p>Logistic Regression to construct the credit risk assessment model. Then, according to</p><p>the model evaluation criteria, this research found out the credit risk assessment model</p><p>with the best prediction classification performance. The findings show that the</p><p>financing enterprises, core enterprises, assets position under finance, blockchain</p><p>platform, and supply chain operation have significant impacts on SMEscredit risk</p><p>when the confidence level is 90%. In general, the performance of AdaBoost algorithm</p><p>model is the best. It has the strongest ability to distinguish between enterprises with</p><p>credit risk and without credit risk, and has strong stability. The research not only</p><p>enriches the theories and method of credit risk assessment of SMEs, but also provides</p><p>assistance in solving the problem of financing difficulties for SMEs due to its ability</p><p>to accurately assess credit risk.</p>
format thesis
qualification_name
qualification_level Doctorate
author Xiao, Ping
author_facet Xiao, Ping
author_sort Xiao, Ping
title Factors affecting SMEs credit risk and credit risk assessment based on blockchain-driven supply chain finance
title_short Factors affecting SMEs credit risk and credit risk assessment based on blockchain-driven supply chain finance
title_full Factors affecting SMEs credit risk and credit risk assessment based on blockchain-driven supply chain finance
title_fullStr Factors affecting SMEs credit risk and credit risk assessment based on blockchain-driven supply chain finance
title_full_unstemmed Factors affecting SMEs credit risk and credit risk assessment based on blockchain-driven supply chain finance
title_sort factors affecting smes credit risk and credit risk assessment based on blockchain-driven supply chain finance
granting_institution Universiti Pendidikan Sultan Idris
granting_department Fakulti Pengurusan dan Ekonomi
publishDate 2023
url https://ir.upsi.edu.my/detailsg.php?det=11095
_version_ 1804890583578181632

Similar Items