The q-rung orthopair fuzzy sets and their hybrid models are capable of dealing with uncertain situations very effectively than the theories of intuitionistic and Pythagorean fuzzy sets and thus have numerous decision-making applications in daily life, while the fuzzy parameterized soft set theory has its impact on different decision-making scenarios. Motivated by these facts, in this research article, these theories are combined to form a new structure named fuzzy parameterized q-rung orthopair fuzzy soft expert sets (FPq ROFSESs) for dealing with more generalized information. The developed model is an efficient extension of fuzzy parameterized intuitionistic fuzzy soft expert sets. Some of its basic notions, including subset, complement, OR operation, AND operation, intersection, and union are studied and illustrated via examples. Moreover, to show the applicability and efficiency of the developed model, two real-life applications are solved under the FPq ROFSES approach, which is supported by an algorithm, the first application is about selecting an appropriate site for a cafe outlet, and the second application is about selecting the Best News Channel for an award. At last, a comparison of the initiated model with some existing approaches is presented to verify its advantages over them.
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