Search

Group decision-making is an effective method to deal with complex unstructured problem in uncertain environment, and it has been widely used in many fields such as medical decision-making. This is a novel study that considers the decision-makers as different groups in the group decision-making problems in uncertain environment. This paper aims to present a novel method combined with evolutionary game for decision-making problem of knowledge sharing in uncertain environment between the large and the small groups in Telemedicine service. For this purpose, the evolutionary game model is constructed to solve decision-making problem of large-small group. Through analyzing the evolutionary path and balance, the influencing factors of the selection strategies and objective and subjective factors restricting the establishment of knowledge sharing between the large and small groups cloud be determined. Finally, a numerical simulation experiment is conducted with Matlab to demonstrate the feasibility of the proposed method. In this study, the range of decision groups in the research of group decision-making problem has been expanded, and the complicated factors of knowledge sharing between hospitals in uncertain environment under the background of Telemedicine service have been discussed.

Purpose. This paper presents a new method and model based on stochastic MULTIMOORA method and discuss its application to the doctor evaluation in healthcare service. Design/Methodology/Approach. In the previous studies, the number of decision group is often assumed to be small, and the different dimensions of the evaluation indexes were also less. In this paper, the authors study how to evaluate the healthcare service quality of doctors by the large group. Based on the stochastic MULTIMOORA theory, the authors use the method that builds the function of the net probability, the distance between the ideal solutions, and the utility of each doctor. Findings. This paper presents a novel model to determine the optimal doctor that considers both two dimensions in the index system and balances the evaluation results of the two dimensions. The authors designed the questionnaire and conducted field survey to make the proposed method closer to the actual situation in China. Then, they determined the optimal evaluation result for the healthcare service quality of doctors. Research Limitations/Implications. In the process of practical decision-making, there are differences in intellectual literacy level, regional background, and language preference between different decision-makers. it is impossible for the method we proposed to consider the differentiation index system of decision-makers’ preference comprehensively. And this will be a further research direction. Practical Implications. The authors proposed two evaluation index dimensions and tryed to balance the evaluation results of the two dimensions as much as possible. Meanwhile, the information aggregation method based on stochastic MULTIMOORA is distinguished. Social Implications. The proposed method can be applied to the evaluation of doctors in actual healthcare service. It is helpful to improve the healthcare service quality and the hospital management level, further improve the core competition of hospitals Originality/Value. This paper makes up for the lack of existing studies of the large group evaluation decision in the healthcare service. A new method on the evaluation of doctors by the large group is established and applied to a healthcare management decision-making problem with Chinese characteristics in reality.