Prediction of Retail Chain Failure: Examples of Recent US Retail Failures

ABSTRACT Over the last several years, several prominent brick‐and‐mortar retail chains have ceased operations, raising concerns that some have referred to as the retail apocalypse. Scholars have attempted to model the likelihood of firm failure using various approaches. This study examines the failures of Bed Bath and Beyond, J.C. Penney, Rite Aid, and Sears Holdings in the United States between 2013 and 2022. Retail failure models that consider internal and external firm factors using both annual reports and macroeconomic data were analyzed and evaluated using logistic regression, PCA, and Random Forest approaches. The findings suggest that EBITDA/Revenue and annual average US inflation rates are strong predictors of retail failure across various modeling approaches. The modeling results provide an early warning signal at least 1–2 years before failure, with accuracies of 93.8%–96.9%.

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Publication Details

Journal
Managerial and Decision Economics
Published
2025-02-10
DOI
https://doi.org/10.1002/mde.4506
Citations
1
Primary Topic
Vehicle License Plate Recognition
Type
article
Field-Weighted Citation Impact
1.14
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article

Prediction of Retail Chain Failure: Examples of Recent US Retail Failures

Shawn Berry
1 citations
Managerial and Decision Economics
Vehicle License Plate Recognition
1.14
article

Prediction of Retail Chain Failure: Examples of Recent US Retail Failures

Shawn Berry
article en
1 citations

Abstract

ABSTRACT Over the last several years, several prominent brick‐and‐mortar retail chains have ceased operations, raising concerns that some have referred to as the retail apocalypse. Scholars have attempted to model the likelihood of firm failure using various approaches. This study examines the failures of Bed Bath and Beyond, J.C. Penney, Rite Aid, and Sears Holdings in the United States between 2013 and 2022. Retail failure models that consider internal and external firm factors using both annual reports and macroeconomic data were analyzed and evaluated using logistic regression, PCA, and Random Forest approaches. The findings suggest that EBITDA/Revenue and annual average US inflation rates are strong predictors of retail failure across various modeling approaches. The modeling results provide an early warning signal at least 1–2 years before failure, with accuracies of 93.8%–96.9%.

Managerial and Decision EconomicsVol. 46(5)
William Howard Taft University (US)
Openalex Percentile: Top 23%
Vehicle License Plate Recognition
1.14
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