An interval-valued neutrosophic TOPSIS method with green approach criteria for patent evaluation

In this thesis, a decision support model has been developed to evaluate green patents through a systematic and multidimensional approach, aiming to assess technologies that prioritize environmental impact on sustainable development goals. It is emphasized that the patent evaluation process is not limited to technical criteria (innovation, inventive step, industrial applicability); environmental and social impacts should also be taken into account. However, it has been observed that traditional decision-making methods are inadequate in cases where the process in question is largely based on subjective judgments and uncertain expert opinions. Accordingly, TOPSIS method, which is one of the multi-criteria decision making (MCDM) approaches where the opinions of more than one decision maker are taken into account, was preferred in the study. In order to model the uncertainties and differences of opinion in the evaluation process more flexibly, Interval Valued Neutrosophic Sets (IVNS) were integrated into the method. It has been shown that the IVNS structure is capable of defining the degrees of accuracy, uncertainty and inaccuracy of each alternative interval by interval, which enables the decision process to be carried out in a more comprehensive and realistic manner. At the same time, the effects of decision makers with different levels of experience and education on the decision process could be modeled with the weights. In the last section, sensitivity analysis is performed on the relevant weights. The developed IVNS-based TOPSIS method has been shown to be applicable not only in the evaluation of green patents but also in various decision problems such as supplier selection, investment planning and candidate evaluation. In this context, this thesis aims to provide both a methodological contribution to the literature and an effective guiding tool for decision makers on sustainable technology investments.