Prediction of business failure among Malaysian construction companies using logistic regression analysis / Aina Syakirah Mohd Nong

UNSPECIFIED (2015) Prediction of business failure among Malaysian construction companies using logistic regression analysis / Aina Syakirah Mohd Nong. Masters thesis, Universiti Teknologi MARA.

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Abstract

This study attempts to investigate whether financial ratio analysis derived from financial statements information can be used to give sufficient signal prior to financial distress and/or business failure in the context of Malaysian construction industry. The paper also aims to develop business failure prediction model using logistic regression as a statistical model and financial ratios as independent variables. This study focused on construction industry and thus analyse 14 construction companies consist of seven distressed firms and its healthy counterpart. Data was collected up to five years before the distressed company being declared as PN17. This study employs descriptive and correlation analysis to compare the characteristics of both group and investigates the relationship between financial ratios and financial health of companies. Logistic regression was then utilised in an attempt to develop a model that can predict business failure and the outcome of this study shows that, the model has the ability to predict financial distress of Malaysian construction companies with 71.4% accuracy rate. The findings also reveal the significance of solvency in determining the financial health of a company which supports prior literature in this field'. In conclusion, the study provides overview of Malaysian construction industry and might benefit related stakeholder in economic decision making process while considering and analysing financial statements information.

Item Type: Thesis (Masters)
Divisions: Faculty of Accountancy
Item ID: 18285
Uncontrolled Keywords: Malaysian construction industry; Logistic regression analysis; Business failure
Last Modified: 10 Nov 2017 01:36
Depositing User: Staf Pendigitalan 5
URI: http://ir.uitm.edu.my/id/eprint/18285

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