Analysis on Customer Satisfactory Rate of University Canteen Based on Fuzzy Comprehensive Evaluation and K-Means Arithmetic

Abstract

As the population of university students grows every year, more and more attention is paid on the dining problems at university canteen and therefore the service quality of a university canteen plays an important role in building a university's reputation. In this paper, the customer satisfactory rate of the canteens at South China Agricultural University (SCAU) is taken as an example. Firstly, Fuzzy Comprehensive Evaluation is used to analyze the comprehensive satisfactory degree of the canteen, then the K-means algorithm carried out by the SPSS Clementine data mining tools would be adopted to conduct cluster analysis on the customer satisfaction survey data, and explore the individual characteristics factors that affect the customer satisfaction of university canteens. The target is to provide canteen management strategies with some scientific evidence for decision making and improving the quality of their service.