The difficulty of innovation risk assessment makes it necessary to use a multi-criteria analysis. Innovative projects are related to unstructured problems and the uncertainty, therefore, the use of fuzzy logic in the innovation risk assessment is analyzed. This paper proposes a method of determining the weights of criteria in order to innovation risk assessment. The weights are determined by 5 general criteria and 14 detailed criteria of innovation risk assessment. The proposed method is an extension of the fuzzy AHP method. The extension consists in taking into consideration the group decision-making approach with experts’ psychological conditions. The groups of experts have been chosen based on an elaborated form. The form makes it possible to characterize the persons within the scope of different psychological conditions. The proposed method provides objective and rational decision-making. The paper presents also a comparison of results with the fuzzy AHP method without the group decision making. The weights obtained by the proposed method are more diversified and bring out the most important criteria.
The recently proposed q-rung orthopair fuzzy set (q-ROFS) characterized by a membership degree and a non-membership degree is powerful tool for handling uncertainty and vagueness. This paper proposes the concept of q-rung orthopair linguistic set (q-ROLS) by combining the linguistic term sets with q-ROFSs. Thereafter, we investigate multi-attribute group decision making (MAGDM) with q-rung orthopair linguistic information. To aggregate q-rung orthopair linguistic numbers ( q-ROLNs), we extend the Heronian mean (HM) to q-ROLSs and propose a family of q-rung orthopair linguistic Heronian mean operators, such as the q-rung orthopair linguistic Heronian mean (q-ROLHM) operator, the q-rung orthopair linguistic weighted Heronian mean (q-ROLWHM) operator, the q-rung orthopair linguistic geometric Heronian mean (q-ROLGHM) operator and the q-rung orthopair linguistic weighted geometric Heronian mean (q-ROLWGHM) operator. Some desirable properties and special cases of the proposed operators are discussed. Further, we develop a novel approach to MAGDM within q-rung orthopair linguistic context based on the proposed operators. A numerical instance is provided to demonstrate the effectiveness and superiorities of the proposed method.
The purpose of this article is to develop a multicriteria group decision making (MCGDM) method in dual hesitant fuzzy (DHF) environment by evaluating the weights of the decision makers from the decision matrices using two newly defined prioritized aggregation operators based on score function to remove the inconsistencies in choosing the best alternative. Prioritized weighted averaging operator and prioritized weighted geometric operator based on Einstein operations are described first for aggregating DHF information. Some of their desirable properties are also investigated in details. A method for finding the rank of alternatives in MCGDM problems with DHF information based on priority levels of decision makers is developed. An illustrative example concerning MCGDM problem is considered to establish the application potentiality of the proposed approach. The method is efficient enough to solve different real life MCGDM problems having DHF information.