Experimental check of model of object innovation evaluation

TL;DR

This paper evaluates a model for assessing the innovation potential of products and technologies using fuzzy methods, with experimental validation confirming its consistency with expert assessments.

Contribution

It introduces a formal model for innovation evaluation based on novelty, relevance, and implementability, validated through experimental data.

Findings

The model's assessments align with expert estimates.

Dynamic indicator changes and interdependence were observed.

The additive utility function was validated for local criteria.

Abstract

The article discusses the approach for evaluating the innovation index of the products and technologies. The evaluation results can be used to create a warehouse of the object descriptions with significant innovation potential. The model of innovation index computation is based on the concepts of novelty, relevance, and implementability of the object. Formal definitions of these indicators are given and a methodology for their calculation are described. The fuzzy methods to coprocess (incomplete) data from numerous sources and to obtain probabilistic innovation assessments are used. The experimental data of the model check including the calculations of local criteria and global additive evaluation criterion are presented. The cyclical nature of dynamic changes in indicators, their interdependence was established, some general features of the products promotion were found. The obtained experimental data are consistent with expert estimates of the products under study. The analysis of the local criteria used in the research gives grounds to assert the correct use of the additive n-dimensional utility function. The adequacy of assumptions and formal expressions that are used in computational algorithms for selection information for data warehouse is confirmed.