The Analysis of Service Quality Through Stated Preference Models and Rule-Based Classification

Abstract

The analysis of quality of services is an important issue for the planning and the management of many businesses. The ability to address the demands and the relevant needs of the customers of a given service is crucial to determine its success in a competitive environment. Many quantitative tools in the areas of statistics and mathematical modeling have been designed and applied to serve this purpose. Here we consider an application of a well established statistical technique, the Stated Preference Models (SP), to identify from a sample of customers significant weights to attribute to different aspects of the service provided; such aspects may additively compose an overall satisfaction index. In addition such weighting system is applied to a larger set of customers and a comparison is made between the overall satisfaction identified by the SP index and the overall satisfaction directly declared by the customers. Such comparison is performed by two rule-based Classification systems, Decision Trees and the Logic Data Miner Lsquare. The results of these two tools help in identifying the differences between the two measurements from the structural point of view, and provide an improved interpretation of the results. The application considered is related to the customers of a large Italian Airport.