Objectives: This article aims to apply fuzzy logic, using Fuzzy Cognitive Maps (FCMs), to the evaluation of an environmental project. The aim is to identify strengths and opportunities for improvement, especially in data collection and qualitative analysis processes. Theoretical Framework: The theoretical framework is based on fuzzy logic (Zadeh, 1965) and its application through FCMs (Kosko, 1986), which allow representing uncertainties in human reasoning in complex systems. The literature highlights the potential of FCMs for modeling causal relationships in social, environmental, and organizational systems, with examples of their use in the fields of medicine, engineering, and sustainability. Method: The research is classified as qualitative and quantitative, based on a literature review and document analysis. The PICO method was used to structure the research question. The Mental Modeler tool was used to construct the cognitive maps, assigning fuzzy weights to the connections between the project indicators and their respective bibliographic sources. The final model had 33 components, 44 connections, and a density of 0.0417, indicating low connectivity but high analytical value. Results and Discussion: The analysis revealed that the "No data" component was the main negative influencer, highlighting informational fragility in the project. The "U" component stood out as a key institutional actor, and indicator 9 showed high centrality, suggesting a strategic role. The system revealed drivers (20), receptors (1), and ordinary components (9), allowing for the simulation and interpretation of causal impacts. Despite the inherent subjectivity of fuzzy logic, the results showed that the methodology contributes to visually structuring the data and aiding decision-making. Research Implications: The research demonstrates that FCMs can be effective tools in evaluating environmental projects, especially under data and resource constraints. Modeling allows for greater objectivity in qualitative analysis and makes the process more robust. Practical application of the method can support managers and decision-makers in real-world contexts. Originality/Value: This study innovates by integrating fuzzy logic, cognitive maps, and environmental project evaluation based on qualitative data. The use of Mental Modeler as a bibliometric and causal analysis tool represents a methodological advancement. The proposed model is replicable and adaptable, even in scenarios with limited information, adding value to evidence-based environmental management and assessment.
Silva et al. (Wed,) studied this question.