Paraconsistent and fuzzy logic applied to company profitability analysis

This study proposes an application of two models based on non-classical logic, the paraconsistent logic and the fuzzy logic, in company profitability analysis. We conduct interviews with market specialists in order to identify the main explanatory variables related to company profitability and apply the paraconsistent model in order to classify the data and to attribute a degree of favorable evidence and of contrary evidence to each profitability ratio. In the fuzzy model, the collected data is analyzed and classified using inference rules and membership functions, thus assigning a qualitative variable to each profitability index. The empirical implementation indicates that both models can be used as tools for assistance and validation of opinions of specialists in the analysis of a company's profitability.