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

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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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Acknowledgements

This research was partially supported by the Natural Science Foundation of China (Grant No.71271043) and National Natural Science Foundation of China Youth Fund (Grant No. 71701166) and the Specialized Research Fund for the Doctoral Program of Higher Education of China (Grant No. 20110185110021).

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Authors and Affiliations

  1. School of Management and Economics, University of Electronic Science and Technology of China, Chengdu, 611731, Sichuan, China

    Xiao-feng Xie & Zong-fang Zhou

  2. Genenal Education Department, Chengdu Neusoft University, Chengdu, 611844, Sichuan, China

    Xiao-feng Xie

  3. School of Economics Mathematics, Southwestern University of Finance and Economics, Chengdu, 611130, Sichuan, China

    Yang Yang

  4. Jiangsu Hui-Yu-Tong Data Technology Co., LTD, Suzhou, 215021, Jiangsu, China

    Yi-mao Zhou

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  1. Xiao-feng Xie
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Correspondence to Yang Yang.

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Xie, Xf., Yang, Y., Zhou, Ym. et al. The clustering analysis on data and lending strategy of supply chain with information asymmetry method. Cluster Comput 22 (Suppl 4), 10299–10307 (2019). https://doi.org/10.1007/s10586-017-1281-x

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  • DOI: https://doi.org/10.1007/s10586-017-1281-x

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