A single-valued neutrosophic CIMAS-CRITIC-RBNAR decision support model for the financial performance analysis: A study of technology companies

Abstract

Financial performance stands as a fundamental performance indicator that reflects companies' current financial conditions, providing information to investors and stakeholders about companies' financial well-being. In this research, a decision support system is developed for identifying the financial performance of companies traded on stock exchanges. This decision support system is based on a multicriteria decision-making (MCDM) approach and neutrosophic logic. The research introduces a novel method for calculating and ranking financial performance, using financial ratio indicators as selection criteria. The importance levels of financial ratio indicators are weighted through two different approaches. In the first approach, expert opinions and criteria importance assessment (CIMAS)-based on single-valued neutrosophic (SVN) sets are utilized for calculation. In the second approach, criteria importance through intercriteria correlation (CRITIC)-based on reference-based normalization processes is employed for criteria weighting. Subsequently, the results of the two criterion weightings are combined to calculate the final criterion weights. The SVN reference-based normalization alternative ranking (RBNAR) method is presented for ranking companies based on their financial performance. Thus, SVN-CIMAS-CRITIC-RBNAR is developed and its algorithm is presented. The novel hybrid decision support model is applied to a case study of technology companies traded on the Borsa Istanbul. The research results support the applicability of the SVN-CIMAS-CRITIC-RBNAR hybrid method. The results of the case study and sensitivity analyses affirm the applicability and robustness of the SVN-CIMAS-CRITIC-RBNAR hybrid model. The research provides detailed implications and insights for financial managers.