Numerical Implementation of a Fuzzy Model for Evaluating the Effectiveness of Technological Innovations in the Formation of a Portfolio of Projects in an Industrial Enterprise

Abstract

A high uncertainty and fuzziness of information in the systems of development and organizations production of technological innovations are forming the need to use adequate management decision-making tools. A key condition for decisions in such systems is, as a rule, the criterion of efficiency. The paper presents the results of the numerical implementation of a methodological approach to evaluating the effectiveness of technological innovations from the standpoint of non-stochastic uncertainty. The approach is based on fuzzy calculations and fuzzy modeling. This approach is aimed at integrating deterministic, stochastic and expert knowledge of the system; it provides an expanded view of the content of the “effectiveness” category itself and the composition of relevant factors, allows you to take into account the restrictions and preferences of decision makers relevant to the system under study. The considered approach is adapted to the specifics of managing technological innovation in an industrial enterprise. The results of the development and numerical implementation of a fuzzy model for evaluating the effectiveness of technological innovations have led to the conclusion that the approach used expands (complements) the composition of the existing methods in this field of knowledge; the numerical value of the efficiency (W) obtained in the fuzzy model can be considered as an additional analytical indicator of information support of the management decision-making process; the significance of this indicator is due to the fact that the indicator W reveals strategically significant prerequisites and provides clarification (justification) of the values of the key technical and economic parameters. The fuzzy W evaluation model allows for combining deterministic and stochastic data with expert estimates and to formalize mental judgments of decision makers using language means of mathematics. Thus, the prerequisites for building an intelligent automated decision-making system in the management of innovative processes and projects in the enterprise are provided.