This study presents a novel multi-attribute decision-making (MADM) model on the basis of Pythagorean fuzzy linguistic information measures. To do so, we first present a new concept of Pythagorean fuzzy linguistic sets to describe fuzziness and inconsistent information, in which the Pythagorean fuzzy linguistic values (PFLVs) are represented by the linguistic membership degree and linguistic non-membership degree. Then, we introduce two axiomatic definitions of information measures for PFLVs, including Pythagorean fuzzy linguistic entropy and the Pythagorean fuzzy linguistic similarity measure, to measure the uncertainty degree of PFLVs and the similarity degree between among PFLVs. In addition, based on the logarithmic function, we construct two new information measure formulas and verify that they satisfy the axiomatic conditions of the Pythagorean fuzzy linguistic entropy and similarity measure, respectively. We further explore the relationship between the Pythagorean fuzzy linguistic entropy and similarity measure. Finally, we present a novel Pythagorean fuzzy linguistic MADM model with the Pythagorean fuzzy linguistic entropy and similarity measure. A numerical example of selecting the most desirable sustainable blockchain product is given, and a comparison with the existing approach was performed to validate the reliability of the developed decision-making model.
An Unsupervised Three-way Decisions Framework of Overload Preference Based on Adjusted Weight Multi-attribute Decision-making Model
