Assessment and prioritization of economic systems by using decision-making approach based on bipolar complex fuzzy generalized Maclaurin symmetric mean operators

The problem of assessing and prioritizing various economic systems and their types from the perspective of decision-making is a complex problem, which involves the evaluation of multiple conflicting criteria in the presence of uncertainty and incomplete information. The imprecisions of fuzzy set theory and the existing decision-making (DM) approaches could not fully take into account the complexities and subtleties that are embedded in this problem. Hence, the need to create a better DM model that can handle both the bipolar and complex nature of the economy and come up with a more comprehensive and robust solution. Thus, in this manuscript, we devise a DM technique in the setting of the bipolar complex fuzzy set (BCFS). For this, we firstly investigate various generalized Maclaurin symmetric mean operators in the setting of BCFS that are bipolar complex fuzzy generalized Maclaurin symmetric mean, bipolar complex fuzzy weighted generalized Maclaurin symmetric mean, bipolar complex fuzzy generalized geometric Maclaurin symmetric mean, and bipolar complex fuzzy weighted generalized geometric Maclaurin symmetric mean operators. After that, we use a newly developed decision-making technique in the context of economic systems and find that the traditional economic system is the finest economic system. In the last, we compare the developed work with a certain number of prevailing theories to reveal the supremacy and advantages. The proposed work.