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Ratio based failure prediction models for the Small-Medium Enterprises (SMEs) in the UK

Khanji, IMJ

Authors

IMJ Khanji



Contributors

J Liu
Supervisor

Abstract

Although SMEs represent over 99% of companies in the UK, there has been limited research
into SME failure prediction modelling. This study develops failure prediction models
specifically for liquidated SMEs using financial ratios. Despite the fact that there is a clear
distinction between small sized (SEs) and medium sized (MEs) companies (in terms of assets,
turnovers and employees size), the majority of studies developed models for SMEs as one
group, but not as two different groups.
In order to capture the predictive power of ratios in each group, there should be different
prediction models for both sizes. The main question this study aims to answer: are there any
differences between SEs and MEs predictive variables. To answer this question the study will
1) identify the financial variables for each group and examine their predictive power, 2)
compare the classification accuracy of three different statistical techniques namely, Multiple
Discriminant Analysis (MDA), Logistic Regression (LR), and Probabilistic Neural Network
(PNN). And finally 3) testing reliability level and validation of the different ratio based
prediction models.
In order to include all categories of ratios, the data sample consists of 560 SMEs that
disclosed full financial statements, and were liquidated in the period 2000-2007. The sample
was divided into three groups; SEs, MEs and a combined SME group for size-specific
predictions. A range of financial ratios were selected and examined, two sample procedures
were tested to validate the results.
Profitability is found to be the most important predictor for the SEs group, while liquidity is
for the MEs. The overall accuracy of the three methods (MDA, LR, PNN) for each model is:
SEs model (70%, 71%, 81%), MEs model (74%, 76%, 87%), and combined SME model
(72%, 74%, 84%). For the first time, we reported size-specific financial ratio predictors for
predicting SMEs failure. The results support our main question that there are differences
between SEs and MEs predictive variables. Further studies are needed to explore the nature
of these findings.

Citation

Khanji, I. Ratio based failure prediction models for the Small-Medium Enterprises (SMEs) in the UK. (Thesis). University of Salford

Thesis Type Thesis
Deposit Date Jul 29, 2021
Award Date Feb 1, 2013

This file is under embargo due to copyright reasons.

Contact Library-ThesesRequest@salford.ac.uk to request a copy for personal use.





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