Fuzzy clustering of investment projects in Tabriz Municipality Waste Management Organization with ecological approach

Purpose: Clustering of investment projects is an essential step in the process of planning the investment projects of organizations. Choosing the right project portfolio has a direct impact on the profitability and other strategic goals of organizations. Factors affecting the clustering of investment projects are many and the use of traditional methods alone cannot be useful, so it is necessary to use a suitable model for clustering projects and investment plans. The purpose of this research is to analysis investment projects of the Tabriz Municipality Waste Management Organization. Methodology: This research is a descriptive - survey method in terms of its objectives. The method used is Fuzzy clustering (FCM), in which the first large investment projects in waste management using the background of participants in research and investment clusters(3 clusters) using the FCM clustering approach is determined, then the priority of the appropriate investment methods (from 6 methods) of each project was obtained using expert judgment and other aspects. Due to the need for planning and clustering of investment projects, using the opinion of experts (10 experts), the importance of projects with ecological perspective was examined. Findings: The result of the research has been that Recycled tire recycling, Glass recycling, Electronic waste recycling, Plastic recycling and Construction project of a specialized recycling town are important projects that located in the first cluster and under normal circumstances, three investment methods, civil partnership agreements, BOT, and partnership contracts (property from the municipality) can be used for them. Originality/Value: Tabriz Municipality Waste Management is an important and influential organization in the activities of the city, in which the investment methods in its projects are mostly based on common contracts and are performed in the same way for all projects. This research offers new methods for projects and their diversity according to clustering technique.