Using fuzzy cognitive maps to evaluate the innovation in micro, small and medium-sized enterprises

Purpose This article presents a fuzzy cognitive map for the evaluation of innovation in organizations. Design/methodology/approach The purpose of this paper is to develop a model to evaluate the innovative capacity of organizations based on fuzzy cognitive maps (FCM), particularly for micro, small and medium-sized enterprises (MSMEs). The specification of the innovation evaluation model based on FCM was carried out with the “Intelligent Decision Support System” methodology. It is a six-step methodology: selection of experts, definition of concepts and relationships, model design, inference, interpretation and decision. Findings Our approach yielded good results in three case studies, effectively determining the level of innovation in an organization. The fuzzy cognitive maps demonstrated a high level of accuracy, with an accuracy of 82% in the Colombian case studies and 92% in the global case studies. These results highlight the effectiveness of the model for quantitatively assessing levels of innovation within organizations. Furthermore, the study revealed the most influential and essential innovative activities/variables within organizations, contributing significantly to the improvement of their operations and competitiveness. Research limitations/implications It is important to automate the definition of the relationships between the concepts of the context and of our FCM. It is also possible to improve the behavior of the FCM by analyzing the variables with a greater impact on the level of innovation and very dynamic in the context since they are the variables to be observed in real-time to follow the evolution of the innovative behavior of an organization. Practical implications The study found that innovative activities emerged as an influential factor in organizations, essential to improving their operations and competitiveness. Our model can help in identifying areas that require improvement to impact positively organizations. By improving innovation assessment through the FCM model, organizations can anticipate higher profitability because innovations are often closely tied to revenue generation and cost savings. The tool can determine the necessity of new products or services, improve operational processes or enter new markets. Originality/value The previous results in the literature show that although there are relevant advances on this topic, there is not enough knowledge to provide clear guidelines for evaluating innovation and improving performance in an organization using intelligent systems. Also, previous works have not defined a framework for evaluating innovation in MSMEs based on FCMs. They also do not use the data of an organization to assess the key characteristics related to innovation. This work applies FCM to automate the evaluation of the process and the capacity for innovation in an organization. These are the main differences between our approach and previous studies.