Measuring open innovation under uncertainty: A fuzzy logic approach

Abstract

Open innovation has received growing interest in recent years, both in academia and industry. Currently, assessing the degree of openness of a company’s innovation process can be highly challenging due to many qualitative and quantitative factors with different units of measurements involved in the evaluation process. Moreover, the open innovation assessment process is affected by vagueness and uncertainty. In this paper, starting from a thorough review of the open innovation literature and following a holistic approach to open innovation assessment, a novel modular fuzzy rule based system is developed in order to help managers to evaluate the openness of their company. The proposed system allows the decision maker to assess the open innovation level of the firm by providing 19 input variables. The information is then processed by the system through 231 rules in order to compute sub-dimensions, dimensions, building blocks and finally the total degree of open innovation. Furthermore, the proposed system was tested using numerical examples and two real-world case studies of two companies. The results showed the capability of the system to assess open innovation in different scenarios, allowing the decision maker to identify the areas with strengths and weaknesses.