Proceedings of the 2016 International Conference on Politics, Economics and Law (ICPEL 2016)

Comprehensive Scores of Legal Risk by Using Clustering Analysis

Authors
Ying Zhang, Dongsheng Xu, Juanjuan Geng
Corresponding Author
Ying Zhang
Available Online May 2016.
DOI
https://doi.org/10.2991/icpel-16.2016.14How to use a DOI?
Keywords
Legal risk, Clustering analysis, Minimum variance unbiased estimation, Distance
Abstract
To evaluate the legal risk of big enterprise in China for the sake of avoiding unnecessary loss, multivariate statistical analysis method was adopted. In the evaluation process, a criterion which contains 967 observation points was raised. All the 967 observation points were carried out by priority setting and risk assessment. To complete the evaluation process hierarchical clustering analysis was applied. It can be concluded that there is no possibility of significant legal risk happening in the enterprise, but its potential legal risk should not be ignored. The result of this paper is a reminder for the enterprise to pay attention to its legal risk. The case showed in the paper indicates that the method used was feasible to evaluate the legal risk. Thus, the enterprise is able to reduce its legal risk in accordance with the provided result.
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This is an open access article distributed under the CC BY-NC license.

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Proceedings
2016 International Conference on Politics, Economics and Law (ICPEL 2016)
Part of series
Advances in Social Science, Education and Humanities Research
Publication Date
May 2016
ISBN
978-94-6252-190-2
ISSN
2352-5398
DOI
https://doi.org/10.2991/icpel-16.2016.14How to use a DOI?
Open Access
This is an open access article distributed under the CC BY-NC license.

Cite this article

TY  - CONF
AU  - Ying Zhang
AU  - Dongsheng Xu
AU  - Juanjuan Geng
PY  - 2016/05
DA  - 2016/05
TI  - Comprehensive Scores of Legal Risk by Using Clustering Analysis
BT  - 2016 International Conference on Politics, Economics and Law (ICPEL 2016)
PB  - Atlantis Press
SP  - 59
EP  - 62
SN  - 2352-5398
UR  - https://doi.org/10.2991/icpel-16.2016.14
DO  - https://doi.org/10.2991/icpel-16.2016.14
ID  - Zhang2016/05
ER  -