Applying an integrated data-driven weighting system – CoCoSo approach for financial performance evaluation of Fortune 500 companies

Abstract

Financial performance evaluation provides information about a firm’s liquidity position, profitability, capital structure and asset utilization. Financial performance evaluation is considered as a multi-criteria decision making (MCDM) problem, as it is a multidimensional concept that is realized by bringing together multiple indicators. This study is aimed to evaluate the financial performance of the Fortune 500 companies by using the integrated data-driven weighting system (IDDWS) – combined compromise solution (CoCoSo) approach. The criteria weights were calculated with the IDDWS and the companies were ranked by the CoCoSo method. In the last stage, a three-stage sensitivity analysis was performed to test the robustness of the model. In the first stage, 15 scenarios were defined by changing the criteria weights. In the second stage, the rankings of the CoCoSo method were compared with the other MCDM methods [range of value (ROV), proximity indexed value (PIV), complex proportional assessment (COPRAS), Biswas and Saha’s method]. In the third stage, a sensitivity analysis was conducted under five different scenarios based on different δ parameters. It was determined that the rankings obtained as a result of the sensitivity analysis show small deviations and except for a few companies, the ranking of most companies remained the same. The results show that the proposed model is suitable for measuring financial performance and Alphabet performs best. The suitability of the proposed model for measuring financial performance was tested for the first time. It is thought that the comparative use of many MCDM methods through a comprehensive sensitivity analysis will contribute to the literature.