A Fuzzy Logic Approach Towards Innovation Measurement

Abstract

Innovation is a convened critical factor for firm success in today’s economic environment. As academics and practitioners acquire knowledge on innovation, tendencies, points of view and practices arise. Yet measurement approaches meant to help decision makers to evaluate their current innovative position do not follow a main stream, moreover much of the information needed for an accurate evaluation tends to be qualitative or subjective. The objective of the present investigation is to review how Fuzzy Logic is currently dealing with subjective complex data in innovation management approaches, results will turn as implications for further applications in innovation measurement. An examination of new methodologies towards innovation measurement is presented and linked to a systematic review on Fuzzy Logic applications to innovation management. Results convey that there is no ultimate model to address innovation measurement in firms, yet a set of innovation measurement key issues are described in novel frameworks. Fuzzy Logic stands as a viable way to adopt decision-making due to its capacity of dealing with uncertain and subjective conditions. According to results, the use of Fuzzy Logic to evaluate qualitative and subjective factors in innovation measurement is encouraged.

Keywords: Innovation Measurement, Fuzzy Logic, Uncertainty, Decision Making

JEL Classification: O320, M100, M420