Goodness of aggregation operators in a diagnostic fuzzy model of business failure

Abstract

The aim of the following paper is proposed a mechanism of analysis useful to verify the capacity of the Vigier and Terceño (2008) diagnostic fuzzy model to predict diseases. The model is enriched by the inclusion of aggregation operators because this allows reducing the detected map of causes or diseases in strategic areas of continuous monitoring. And at the same time this causes can be disaggregated once some alert indicator is identified. The capacity of explanation and prediction of estimated diseases are measured through this mechanism; and also are detected the monitoring key areas that warning insolvency situations. In this approach are introduced aggregation operators of causes of business failure, and a goodness measure using approximate solutions. This index of goodness allows testing the degree of fit of the predictions of the model. Also, as an example, the empirical estimation and the verification of the improvement proposal to a set of small and medium- sized enterprises (SMEs) of the construction sector are presented.