Which Characteristics Predict the Survival of Insolvent Firms? An SME Reorganization Prediction Model

15 Pages Posted: 16 Mar 2015

See all articles by Maria‐del‐Mar Camacho‐Miñano

Maria‐del‐Mar Camacho‐Miñano

Universidad Complutense de Madrid (UCM) - Faculty of Economics and Business Administration

Maria‐Jesus Segovia‐Vargas

Universidad Complutense de Madrid (UCM)

David Pascual‐Ezama

Universidad Complutense de Madrid (UCM)

Date Written: April 2015

Abstract

The negative impact of insolvency, especially in small and medium enterprises, informs the objective of this paper: to study the characteristics of bankrupt firms to achieve a preventive diagnosis for reorganization by means of artificial intelligence (AI) methodologies such as rough set and PART methods. The AI models obtained show not only the key variables to predict insolvency, but also their relations and the critical values. Using only five firm characteristics (sector, size, number of shareholdings, return on assets, and cash ratio), our model could reduce delays and costs, since it is able to predict which firms will undergo reorganization or liquidation before the legal procedure.

Suggested Citation

Camacho-Miñano, María-del-Mar and Segovia‐Vargas, Maria‐Jesus and Pascual‐Ezama, David, Which Characteristics Predict the Survival of Insolvent Firms? An SME Reorganization Prediction Model (April 2015). Journal of Small Business Management, Vol. 53, Issue 2, pp. 340-354, 2015. Available at SSRN: https://ssrn.com/abstract=2578132 or http://dx.doi.org/10.1111/jsbm.12076

María-del-Mar Camacho-Miñano (Contact Author)

Universidad Complutense de Madrid (UCM) - Faculty of Economics and Business Administration ( email )

School of Business Administration
Somosaguas Campus
Madrid, Madrid 28223
Spain

Maria‐Jesus Segovia‐Vargas

Universidad Complutense de Madrid (UCM)

Carretera de Humera s/n
Madrid, Madrid 28223
Spain

David Pascual‐Ezama

Universidad Complutense de Madrid (UCM) ( email )

Carretera de Humera s/n
Madrid, Madrid 28223
Spain

Register to save articles to
your library

Register

Paper statistics

Downloads
0
Abstract Views
312
PlumX Metrics