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Cluster Computing
Published in: Cluster Computing 4/2019

29-10-2017

The clustering analysis on data and lending strategy of supply chain with information asymmetry method

Authors: Xiao-feng Xie, Yang Yang, Yi-mao Zhou, Zong-fang Zhou

Published in: Cluster Computing | Special Issue 4/2019

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Abstract

In this paper, a theoretical framework is proposed to analyze how trade credit effect bank credit in circumstance of supply chain. We constructed a model to describe information asymmetry among lender and borrower based on game theory and conducted numerical simulation to discuss risk contagion. The static comparison and numerical results illustrate that the loan interest in symmetric case is significantly lower than it in asymmetric case. Default risk of buyer increases the cost of borrower compared to the case when buyer pays for sure and massive trade credit associated with higher loan interest. However the impact on loan amount of credit risk and default risk is more complex. It turns out that information asymmetry can be seen as a moderating factor in the impact on loan amount of default risk and credit risk. Generally this study may not only bring some policy implications for banks to control credit risk along supply chain, but also shed lights in theoretical analysis of trade credit.
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Metadata
Title
The clustering analysis on data and lending strategy of supply chain with information asymmetry method
Authors
Xiao-feng Xie
Yang Yang
Yi-mao Zhou
Zong-fang Zhou
Publication date
29-10-2017
Publisher
Springer US
Published in
Cluster Computing / Issue Special Issue 4/2019
Print ISSN: 1386-7857
Electronic ISSN: 1573-7543
DOI
https://doi.org/10.1007/s10586-017-1281-x

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