Evaluating Internet hospitals by a linguistic Z-number-based gained and lost dominance score method considering different risk preferences of experts

Abstract

Internet hospitals are platforms that provide medical information, prescription, and treatment by combining online and offline medical resources. Well-development Internet hospitals can reduce operational pressure of offline hospitals and unnecessary waste of medical resources. Evaluating the performance of Internet hospitals is helpful for their development. In this paper, we introduce a linguistic Z-number-based gained and lost dominance score (GLDS) method to evaluate Internet hospitals. Firstly, to ensure the reliability of evaluation information, we extend the GLDS method to the linguistic Z-number environment. To model the risk preference of an expert, we depict the negative performance of an alternative over other alternatives under each criterion by a lost dominance score function, and represent the individual regret of a expert to the worst alternative by a net lost dominance score function. A weighting method that combines the best worst method and correlation coefficient method is developed to determine the weights of criteria. To verify the validity and practicability of the proposed method, a case study of ranking Internet hospitals is provided. Comparative analysis shows that the solutions of the proposed method reflect the preferences of experts.