The Integral Assessment of Interorganizational Innovation Effectiveness Using Fuzzy Sets Method

In the current economic environment, the effective operation of higher education institutions is difficult to imagine without collaboration with organizations from the real sector of the economy, particularly in the context of innovation generation. Decision-makers responsible for the development of academic-industrial partnerships require modern methods to assess the potential effectiveness of such interactions. This study aims to develop a fuzzy-set-based integral aggregation model for evaluating the effectiveness of interorganizational innovations. The research contributes to scientific novelty through the following key solutions: the development of a hierarchical structure of integral indicators for assessing interorganizational innovation effectiveness; the selection of components and the evaluation of their significance using Fishburne’s weighting method; the creation of a fuzzification database to transform precise numerical values into fuzzy sets; the construction of an equation system to quantify non standardized components values to term sets membership degree and the formulation of a calculation method for intersection points of non-inversive indicators. The results of the conducted research has practical value and are possible to be used by both academic institutions and organizations in the real sector of economy for a preliminary assessment of interorganizational collaboration effectiveness in innovation generation. Future research by the author in this field will be aimed at testing the developed model refining it, and further systematizing and algorithmizing the results for efficient use in interorganizational innovation management.