Decomposed fuzzy cost-benefit analysis and an application on ophthalmologic robot selection

Abstract

Cost-benefit analysis is a benefit measurement method that compares the cost required to realize the product, service or result with the benefits to be obtained. It allows future earnings to be calculated with the present value of money and different projects can be compared. In this study, the uncertainties of decision maker inputs were reflected in a more realistic way by dealing with the cost-benefit analysis under decomposed fuzzy sets. The contribution of this study to the literature are the decomposed fuzzy linguistic term scale, which is proposed for the first time, and the new equations and formulations developed for cost-benefit analysis under fuzziness. This study also contributes to the successful applicability of engineering economics issues and financial analysis methods under fuzziness.