A study on sfpm analysis using fuzzy soft set

Abstract

Evaluating the financial performance of a company is a turbulent work. There are lots of financial performance measures circling around the field of evaluation. It is very essential to find out a model or tool to select the best financial performance measure which should tolerate the elusiveness in the companies' decision making problem. Fuzzy Set Theory and Fuzzy Soft Theory have proved to be a successful in handling imprecise and vague knowledge that characterize this kind of problems, and it has been applied in a variety of fields in the last decades. Based on earlier literature, four important parameters, Earnings Per Share (EPS), Price Earning Ratio (P/E Ratio), Economic Value Added (EVA), Market Value Added (MVA), have been selected. The first two measures are from Traditional Accounting Measures (TAM) and the latter two measures are from Value Based Measures (VBM). Selecting a Superior Financial Performance Measure (SFPM) of a company using fuzzy soft set is the target of this paper.