Performance Evaluation of Software Companies using Dea Methods in Fuzzy Environment

Data envelopment analysis (DEA) calculates the relative efficiency of homogenous decision- making units (DMUs) with multiple inputs and outputs. Classic DEA models usually suffer from several issues such as: discrimination power, variable weights of inputs/outputs, inaccurate efficiency estimation for small number of DMUs and incapability in working with zero and negative data. In this chapter, a four-phase DEA framework with initial relative weights on financial ratios is proposed to evaluate the financial performance of set of software companies in fuzzy environment. Data on the nine financial ratios is collected during FY2013-14 to FY2017-18. The crisp data on financial ratios is converted into triangular fuzzy numbers by utilizing the data during five financial years. The best relative efficiency of the ideal DMU and the worst relative efficiency of the nadir DMU are determined in fuzzy environment and combined to rank the DMUs. Performance evaluation of these companies is also made through hybrid GRA-DEA in fuzzy environment. Initial weights of the financial ratios are considered during evaluation of these companies in the proposed hybrid GRA-DEA method. The comparability of proposed approaches is made and final ranking of the companies is arrived.