Research on Credit Decision-making for SMEs Based on the Entropy Weight TOPSIS Method

Yijia Liu; Chuheng Liu; Min Zhang; Xuedi Zhang

doi:10.2991/978-94-6463-710-6_17

<Previous Article In Volume

Next Article In Volume>

Research on Credit Decision-making for SMEs Based on the Entropy Weight TOPSIS Method

Authors

Yijia Liu¹, Chuheng Liu¹, Min Zhang²^{, *}, Xuedi Zhang¹

¹School of Business, Guilin University of Electronic Technology, Guilin, China

²Graduate school, Guilin University of Electronic Technology, Guilin, China

^*Corresponding author. Email: guidianzm@qq.com

Corresponding Author

Min Zhang

Available Online 14 May 2025.

DOI: 10.2991/978-94-6463-710-6_17 How to use a DOI?
Keywords: SMEs; Linear Programming; Entropy Weight Method; TOPSIS; Credit Decision-Making
Abstract: In the context of the rapid development of big data, small and medium-sized micro-enterprises (SMEs) hold an indispensable position in contributing to the national economy. To tackle the challenges encountered by banks in extending credit to SMEs, this research develops a credit decision-making model grounded in risk assessment. This model utilizes linear programming to ascertain the loan amounts for SMEs across various credit ratings and adopts the entropy weight method to define risk assessment metrics. Moreover, it takes into account the potential influence of sudden events on credit risks for both financial institutions and enterprises. Through the application of the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) for integrated evaluation and scoring, this study delineates credit risk management strategies specifically aimed at SMEs.
Copyright: © 2025 The Author(s)
Open Access: Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Download article (PDF)

<Previous Article In Volume

Next Article In Volume>

Volume Title: Proceedings of the 2025 4th International Conference on Big Data Economy and Digital Management (BDEDM 2025)
Series: Advances in Intelligent Systems Research
Publication Date: 14 May 2025
ISBN: 978-94-6463-710-6
ISSN: 1951-6851
DOI: 10.2991/978-94-6463-710-6_17 How to use a DOI?
Open Access: Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

ris enw bib

TY  - CONF
AU  - Yijia Liu
AU  - Chuheng Liu
AU  - Min Zhang
AU  - Xuedi Zhang
PY  - 2025
DA  - 2025/05/14
TI  - Research on Credit Decision-making for SMEs Based on the Entropy Weight TOPSIS Method
BT  - Proceedings of the 2025 4th International Conference on Big Data Economy and Digital Management (BDEDM 2025)
PB  - Atlantis Press
SP  - 149
EP  - 156
SN  - 1951-6851
UR  - https://doi.org/10.2991/978-94-6463-710-6_17
DO  - 10.2991/978-94-6463-710-6_17
ID  - Liu2025
ER  -

download .riscopy to clipboard