Open Accessscaling problems in service quality evaluation
Author(s) -
Michele Gallo
Publication year - 2007
Publication title -
metodološki zvezki
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.127
H-Index - 7
eISSN - 1854-0031
pISSN - 1854-0023
DOI - 10.51936/ugho6081
Subject(s) - categorical variable , ordinal scale , ordinal data , ordinal regression , computer science , data mining , service (business) , scale (ratio) , service quality , multidimensional scaling , level of measurement , quality (philosophy) , measure (data warehouse) , statistics , mathematics , machine learning , philosophy , physics , economy , epistemology , quantum mechanics , economics
In service quality evaluation we have to treat data having different kinds of scales. In order to obtain a measure of the service quality level a conventional ordinal rating scale for each attribute of a service is used. Moreover additional information on the customers or on the objective characteristics of the service is available (interval, ordinal and or categorical scale). In the latter the importance or weight assigned to the different items must be also considered (compositional scale). To analyze these different kinds of data particular precaution should be used, a transformation of quality level perceived (expected) data in quantitative scale is carried out before a multidimensional data analysis. In literature more techniques are proposed for the quantification of ordinal data preserving the original characteristics. The aims of this paper are to analyze different ways to quantify ordinal data, and illustrate how the additional information on the customers or on the service could be used in the multidimensional analysis as external information.