English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

This study aimed to find a model consisting of a set of financial ratios in which each ratio has its own weight that indicate its importance in discriminating between distressed and non-distressed firms in both Algeria and Jordan. The early prediction of industrial firm's distress warns the concerned parties that they can intervene and take corrective actions before the collapses of institution. To achieve this, twenty seven ratios were calculated for 1 to up 3 years before actual distress for a sample of thirty eight Jordanian industrial firms, half of which had failed and twenty four Algerian enterprises (eight bankrupt enterprises and sixteen nonbankrupt enterprises). These ratios were analyzed using the partial least square logistic regression to reach the best form of financial ratios that can distinguish between distressed firms and non-distressed firms in one year at least before failure. It has already been reached that the best model in predicting corporate failure is the model which was built in the first year before distress and which included twelve financial ratios, has been able to this form of re-classification of industrial companies to distressed companies and non-distressed companies with accuracy amounted to 92.9% in this year for the Jordanian companies and the determining coefficient of this model which expresses its goodness of fit has reached 90.4%. To ensure the ability of this model to predict failed industrial companies and non-failed industrial companies, it was tested on another sample of industrial companies (out of sample) of ten firms half of which had failed enabling the model to distinguish between these companies accurately amounted to 90% in the first year before distress. The statistical results show that the logistic regression model is 95.7% accurate to predict Algerian enterprises financial distress and we can generally use three variables (net profit to sale, return on asset, net profit to total liabilities) in firm’s financial distress prediction.

iosr journal of business and management

A Proposed Model for Predicting the Financial Failure of Companies Using Partial Least Square Logistic Regression (Comparative study between Algeria and Jordan)