Пілотна оцінка ставлення експертів до значущості характерних рис інноваційної привабливості об’єктів інтелектуальної власності

Abstract

Modern technology transfer is associated, inter alia, with the selection and implementation into production of the objects of intellectual property. At the same time, proactive assessment of the investors’ or experts’ attitude to the characteristics and indicators of these objects determines the appropriate "order" and promotes more effective interaction between the producers and the users of intellectual property. The experts’ preference patterns as the ordered series of many characteristics of attractiveness for innovation of objects of intellectual property are one of the indicators of human influence on decision-making about the degree of acceptability of a particular object and should be used to implement the method of successive concessions based on the pattern recognition methodology, "glob pattern/masks" of this acceptability. The research involved m = 90 highly qualified specialists who are constantly involved in UkrISTEI to provide various expert examinations. A more up-to-date list of n=18 characteristics of attractiveness for innovation of objects of intellectual property has been formed, which allows to study these objects comprehensively and to the fullest extent. The pairwise comparison and normative method of establishing part of the total value (significance, acceptability) of these characteristics were used by the experts, who took part in the research. They built individual systems of preferences, which were then aggregated into a group preference pattern using a group decision-making strategy such as summarizing and grade averaging. Verification of consistency of the group preference pattern revealed that the obtained empirical value of the Kendall's coefficient of concordance is statistically valid at an unusually high level of significance of a= 1% as for human factor studies. However, it does not satisfy the criterion for the minimum acceptable value: Wemp.=0,4772<Wmin=0,7. The ways of further research related to the application of multi-step technology of detection and elimination of marginal thoughts while eliminating the statistical error of the "survivor", as well as improving the group preference pattern where the classical Savage’s criterion in decision-making and the Kemeni median are applied.