Predicting Business Failure for Malaysia SMEs in the Hospitality Industry

DOI

10.2991/aebmr.k.210121.011How to use a DOI?

Keywords

Business Failure, Hospitality Industry, SMEs

Abstract

SMEs are an important segment of the Malaysian economy and contribute significantly to the country’s economic growth. Nonetheless, SMEs are riskier and associated with a high failure rate. Hence, the aim of this study is to develop a failure prediction model for SMEs in the hospitality industry by using the logit and artificial neural network (ANN) approach for 82 SMEs over the period 2000 to 2016. The findings show that the ANN model predicts better than the logit model in both the estimation and holdout sample with a predictive accuracy rate of 98.2% and 92%, respectively, while the logit model provides overall accuracy rates of 86% and 80%, respectively. This study also finds that both models identify return on assets and board size as an important signal of business failure. The models could be used to assist investors, creditors and lenders to screen out failing SMEs, and the authorities could decide on policies to improve SMEs in the hospitality industry.

Copyright

© 2021, 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  - Juraini Zainol Abidin
AU  - Nur Adiana Hiau Abdullah
AU  - Karren Lee-Hwei Khaw
PY  - 2021
DA  - 2021/01/22
TI  - Predicting Business Failure for Malaysia SMEs in the Hospitality Industry
BT  - Proceedings of the Conference on International Issues in Business and Economics Research (CIIBER 2019)
PB  - Atlantis Press
SP  - 67
EP  - 73
SN  - 2352-5428
UR  - https://doi.org/10.2991/aebmr.k.210121.011
DO  - 10.2991/aebmr.k.210121.011
ID  - Abidin2021
ER  -