Business

Building a core rule-based decision tree to explain the causes of insolvency in small and medium-sized enterprises more easily

S. Lee, K. Choi, et al.

This study introduces a novel approach, the harmonic average of support and confidence method (HSC), to derive key rules from decision trees, ultimately creating a core rule-based decision tree (CorDT) that unravels the factors contributing to insolvency in SMEs. Conducted by Sanghoon Lee, Keunho Choi, and Donghee Yoo, this research not only predicts insolvency but also provides tailored prevention strategies.

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Abstract

This study proposes a harmonic average of support and confidence method (HSC) to select important rules from a decision tree, building a core rule-based decision tree (CorDT) that explains insolvency factors in SMEs. An insolvency prediction model was developed using a decision tree algorithm and technological feasibility assessment data, categorized into general, technology development, and toll processing types. Data balancing techniques were applied, with SMOTE showing the highest performance (77.6% hit ratio). Important rules were selected using HSC, and CorDTs were built for each SME type, explaining insolvency causes and suggesting customized prevention strategies.

Publisher

HUMANITIES AND SOCIAL SCIENCES COMMUNICATIONS

Published On

Dec 11, 2023

Authors

Sanghoon Lee, Keunho Choi, Donghee Yoo

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