An assessment tool for the evaluation of circular economy implementation

Purpose: In this paper, the authors adopt the theory of the circular economy to study the transitions that take place in three case studies in Mexico and Ecuador. The work is aimed to systematize a circular economy assessment tool that fosters opportunities for improvement in business practices. Design/methodology/approach: The methodology is based on a descriptive quantitative analysis, where a checklist is made with 91 items and nine study variables. This is from the study of the bibliography and business practice. Furthermore, the neural network method is used in a case study to predict the level of circular economy and the importance of each variable according to the sensitivity by the Lek’s profile method. Findings: It is based on a descriptive quantitative analysis, where a checklist with 91 items and nine study variables is made, defined from a bibliographic study and business practice. Furthermore, the neural network method is used in a case study to predict the level of circular economy and the importance of each variable based on sensitivity. Research limitations/implications: The application of the tool requires prior knowledge of the circular economy approach, which is why specialized personnel are needed for its application. This makes research more expensive in time and human resources. Practical implications: The practical and methodological contribution of this work lies in the feasibility of the tool that favors the definition of improvement actions for the implementation contribution to the circular economy in business practices. Social implications: The social contribution is framed in the gradual transition to circular economy approaches in underdeveloped countries. Originality/value: The use of the neural network method to predict the level of circular economy in a case study allows making decisions in a predictive way. This encourages the development of the circular economy according to the context needs.