A retail failure prediction model

Abstract

Financial ratios have long been used for business analysis. Researchers have formulated business failure prediction models utilizing nancial ratios. This study focuses on the use of nancial ratios to discriminate between failed and non-failed rms in the retail industry.Using a matched sample of sixty-six failed and sixty-six non-failed retail rms obtained from the COMPUSTAT database, multiple discriminant analysis was utilized to develop a retail prediction model which accurately classi ed 78 per cent of the sample rms as failed or non-failed. Hotelling's T 2 test determined that the mean vector of the discriminant function for failed rms differed from that of non-failed rms. The model was further validated using a jackknife procedure and split sample analysis. Failed or non-failed classi cation accuracy was found to be signi cantly better than chance.

Deconstructing the notion of blame in corporate failure

“…The use of synonyms such as collapse, decline, breakdown and demise confuses this task. Researchers in the finance area suggest failure equates to bankruptcy or insolvency (Altman, 1968;Altman et al, 1977;Beaver, 1966;Bhargava et al, 1998;McGurr and DeVaney, 1998b;Sharma and Mahajan, 1980). By contrast, Morris (1997, p. 2) defines failure as embracing "various types of financial distress, ranging from bankruptcy at one extreme to decline in profitability at the other".…”

Predicting Profitability of Neighbourhood Stores in Colombia

“…From the results, it is possible to identify a profitability position of the neighbourhood stores and thus be able to define strategies for their future plans (Craig & Moores, 2010; Kaplan & Norton, 2004). Also, the results could be used to support the creation of new stores, as well as for the search of funding from investors (Gepp et al, 2010;Mcgurr & Devaney, 1998). Additionally, having an instrument to predict business failure has the potential to benefit not only small business such as neighbourhood stores, but the whole economy of any country (Khaled, 2019).…”