Service Quality Evaluation of New Retail Fresh E-commerce Based on AHP-Entropy TOPSIS Model

The outbreak of the COVID-19 and the rise of new retail models have promoted the vigorous development of the fresh e-commerce industry, but at the same time, some service quality problems have also been exposed. An accurate evaluation of the service quality of fresh e-commerce under the new retail background can provide theoretical support for the improvement of the service quality of fresh e-commerce, and has a certain practical significance. In this study, we propose a hybrid evaluation model based on fuzzy AHP-entropy TOPSIS (technique for order preference by similarity to ideal solution) model. Specifically, referring to SERVQUAL model and the service characteristics of fresh food industry, this paper firstly constructs the initial evaluation index; Then, the principal component analysis is further applied to adjust it, and an evaluation index system consisting of 6 dimensions and 25 indicators is finally constructed. By introducing AHP and entropy weight method, the problem of index weight distribution of TOPSIS evaluation model is solved. Finally, the above AHP-entropy TOPSIS model is applied to analyze the service quality of six fresh food e-commerce companies, the strategies that can promote service quality of fresh e-commerce are also put forward based on the results.