Model-based evaluation for online food delivery platforms with the probabilistic double hierarchy linguistic EDAS method
针对在线外卖平台评估问题，提出基于概率双层次语言EDAS方法的多属性群决策模型，结合CRITIC和累积前景理论确定权重，并通过实例验证其有效性。
In recent years, with the rapid expansion of internet technology, the number of online food delivery services has grown. Despite the ease, a poor online food delivery platform (OFP) produces all kinds of problems for individuals. A comprehensive and reasonable evaluation of online food delivery is of great significance. Therefore, this study establishes an OFP evaluation model based on the probabilistic double hierarchy linguistic EDAS (PDHL-EDAS) method for multiple attribute group decision-making (MAGDM). Then the CRITIC model is introduced to derive the objective weight and the cumulative prospect theory is leaded to obtaining the cumulative weight of PDHLTS. In furthermore, the benefits and applicability of the PDHL-EDAS method are illustrated by solving practical MAGDM problems concerning the evaluation of OFPs. Lastly, the proposed method is verified by comparison with other MAGDM methods, in addition to discussing potential future research directions.