Pythagorean Z-linguistic VIKOR method based on modified value function under Pythagorean Z-linguistic environment and its application on smart healthcare

In response to the growing maturation of technological level in the modern medical industry, this paper proposes the PZLMVF-VIKOR method to tackle uncertain multi-attribute group decision-making in smart healthcare. First, a novel Pythagorean Z-linguistic modified value function based on regret theory is defined to consider the impact of DMs’ emotions on decision outcomes. Then, a combined weighting method is used to obtain the final attribute weight vector by the closeness degree, with the expert weight determination based on consensus measures. Subsequently, we propose an extended VIKOR method in Pythagorean Z-linguistic environment to solve the evaluation problem of the development in smart healthcare. Finally, a practical case and some comparative analysis is conducted to illustrate the justifiability and effectiveness of this method.