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The most important feature of decision problems is that they contain alternatives and criteria expressed both objectively and subjectively. Such problems are solved by multi-criteria decision-making (MCDM) methods. The difficulty, however, is that qualitative criteria cannot be modeled and measured quantitatively. There are many tools, fuzzy set, intuitionistic fuzzy set, neutrosophic set, and so on, to analyze the incompleteness and uncertainty in the data. The most important characteristic that distinguishes neutrosophic sets from these sets is that they use three membership values as truth, indeterminacy, and false. In this sense, it is superior to classical fuzzy sets. Therefore, in this study, a novel-integrated solution method based on Neutrosophic Criteria Importance Through Inter-Criteria Correlation (N-CRITIC) and Neutrosophic Additive Ratio ASsessment (N-ARAS) methods is developed for the MCDM problems by integrating Single-Valued Neutrosophic Numbers (SVNNs) into CRITIC and ARAS methods. A case study from the literature concerning the most appropriate technology forecasting method selection has been applied to present the computational details. First, N-CRITIC method is performed to find the weights of selection criteria. Then, N-ARAS method is used to determine the ranking order of technology forecasting methods and select the optimal one. The sensitivity and comparative analyses have also proved that the novel-integrated solution method gives a consistent ranking for the alternatives.

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