Research on Financial Risk Management of Automobile Supply Chain Based on Data Mining Technology

DOI

10.2991/mse-17.2017.24How to use a DOI?

Keywords

data mining; automobile supply chain; risk management

Abstract

With the rapid development of supply chain finance, the risk management problem ensues. In this paper, the data mining technology is used to study the large amount of data of the spare parts suppliers in the automobile supply chain, and to identify the characteristic attributes of the default suppliers, and try to help the core enterprises to evaluate and select the partners more efficiently. The results show that the six attributes such as "supplier locations" are highly correlated with the default risk of the supplier, and can help the core enterprises to identify the default suppliers. In addition, "registered capital" and "auto parts properties" are weakly related to default risk, we can delete them.

Copyright

© 2017, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Zi-Gui Chen
AU  - Shi-Ping Guan
PY  - 2017/10
DA  - 2017/10
TI  - Research on Financial Risk Management of Automobile Supply Chain Based on Data Mining Technology
BT  - Proceedings of the 3rd Annual 2017 International Conference on Management Science and Engineering (MSE 2017)
PB  - Atlantis Press
SP  - 94
EP  - 96
SN  - 2352-5428
UR  - https://doi.org/10.2991/mse-17.2017.24
DO  - 10.2991/mse-17.2017.24
ID  - Chen2017/10
ER  -