An improved multi-attribute group decision-making method for selecting the green supplier of community elderly healthcare service

Abstract

With rapid social and economic development, the process of population aging has increased the demand for community elderly healthcare service (CEHS) in China. However, the traditional government-oriented service supply cannot meet the various needs of CEHS, and it is critical to select a suitable supplier of CEHS to provide high-quality green services in the community. Therefore, this study focuses on the issue of green supplier selection of CEHS, explores an improved transformation method for processing multi-type data, and proposes an integrated method of multi-attribute group decision-making (MAGDM) which innovatively applies the degree of overall deviation measure (ODM) to determine expert weight. Finally, the effectiveness and accuracy of the new method are verified by experimental analysis. The results show that H2 is the top choice in the green supplier selection of CEHS, followed by H1, H4, H8, H5, H6, H3, H7, H12, H11, H9, and H10. In addition, the authors apply the traditional ED method to calculate expert weights and compare the results of ODM and ED. It is a fact that the improved ODM method should be more efficient and accurate than the traditional ED method.