Assessment of management accounting information using decision algorithm with prioritized weights in circular fermatean fuzzy CRITIC WASPAS model

In this manuscript, fuzzy sets are used to handle uncertainty in enhancing risk management and operational efficiency in management accounting based on a decision-making algorithm. For this purpose, a circular fermatean fuzzy (CFF) set (CFFS), which not only contains membership and non-membership grades but also provides circular behavior. Management accounting information is a process of collecting, analyzing, interpreting, and presenting financial and non-financial data that is specifically designed to aid internal management in planning, decision-making, performance evaluation, and control of business operations. For this constraint, extend criteria importance through intercriteria correlation (CRITIC) method and the weighted aggregated sum product assessment (WASPAS) method into the CFF framework. The proposed model can easily describe the importance of multiple attributes and the weight of decision-makers. Additionally, this paper explored an algorithm for the multi-attribute group decision-making problem based on the CRITIC-WASPAS technique under the presence of defined linguistic terms. The defined techniques are significantly applied in handling uncertainties in hypothetical data obtained by management accounting. Moreover, this paper validates the defined model through a case study. To evaluate the challenges of management accounting, considering five alternatives, each with five attributes, to select the best option. After the evaluation, the second alternative, i.e., internal accounting, is the best. A sensitivity analysis confirms effectiveness and reliability. A comparative analysis is conducted between the proposed approach and previous aggregation operators to validate its performance and reliability.