• ISSN: 2301-3567 (Print), 2972-3981 (Online)
    • Abbreviated Title: J. Econ. Bus. Manag.
    • Frequency: Quarterly
    • DOI: 10.18178/JOEBM
    • Editor-in-Chief: Prof. Eunjin Hwang
    • Executive Editor: Ms. Fiona Chu
    • Abstracting/ Indexing:  CNKI, Google Scholar, Electronic Journals Library, Crossref, Ulrich's Periodicals Directory, MESLibrary, etc.
    • E-mail: joebm.editor@gmail.com
JOEBM 2021 Vol.9(4): 93-100 ISSN: 2301-3567
DOI: 10.18178/joebm.2021.9.4.662

Logistic Regression-Based Enterprise Credit Evaluation Model

Ziyuan Li

Abstract—In recent years, enterprises in Beijing have developed rapidly. As one of the economic centers in China, the integrity system of enterprises has become a hot topic. An objective and effective evaluation model for enterprises in Beijing can not only help consumers avoid consumption risks and provide reference for the government to formulate relevant policies, but also provide a reference for enterprises in choosing partners. The research objective of this paper is to construct a logistic regression-based enterprise credit evaluation model in Beijing. In the empirical study, 4648 Beijing enterprises were taken as samples, and the K-S test and Mann-whitey U test were used to test the correlation between test indicators and their correlation with explanatory variable y, and the qualified 6 test indicators were selected from the 15 indicators. KMO and Bartlett tests were used to test the six indicators to see whether they were suitable for principal component analysis. After principal component analysis of 6 indicators, the principal component factors obtained were taken into the binary logistic regression model as input variables, and the stepwise forward method based on maximum likelihood estimation was adopted to estimate the model parameters, so as to determine the final variables entering the model. Finally, test samples are used to test the accuracy of the model. The test results show that the model can predict the integrity of enterprises in Beijing.

Index Terms—Logistic regression, Beijing enterprises, factor analysis, parameter significance test.

Ziyuan Li is with Columbia Business School, China (e-mail: ziyuanli2020@outlook.com).


Cite:Ziyuan Li, "Logistic Regression-Based Enterprise Credit Evaluation Model," Journal of Economics, Business and Management vol. 9, no. 4, pp. 93-100, 2021.

Copyright © 2021 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).

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