MULTIDIMENSIONAL STATISTICAL METHODS BASED ON CO-INERTIA FOR THE CUSTOMER SATISFACTION EVALUATION

A sure guide for business strategies is the knowledge of customers evaluation of the service. This knowledge represents a competitive advantage. In this way, the company may guide the renewal of its offer as well as the pricing itself. Moreover the enterprises of excellence tend necessarily to the maximum customers satisfaction. There have been several technical proposals for the quality assessment of the services, and others are being added, together with the theory improvement and brand new practical challenges. A generalized way to carry out a quality control implies the measure of some parameters on a given number of objects (or subjects). To measure those parameters of a service which consumers would expect as ideal or Expectations Score and then those elements of a service that they have recently experienced or Perceptions Score. Customers’ satisfaction is measured as the gap between Perceptions and Expectations. The aggregation of these measures in order to estimate the global "trend" of the investigated system and the introduction of some criteria of judgment create some problems on the subjective evaluations. The problem here is that we have to cope with subjective evaluations and consequently with ordinal scale of measures. The approach proposed in this paper consists of a first phase of data pre-coding, in order to obtain quantitative scales and of a second phase of data analysis.