Statistical techniques for continuous improvement: a citizen's satisfaction survey

Purpose - The purpose of this paper is to propose a path analysis of data coming from a citizen's satisfaction survey to support decision makers in quality service improvement. In detail, the survey aims to measure citizen's satisfaction of an Italian local Public Administration regarding...

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Bibliographic Details
Published in:TQM journal 2010-04, Vol.22 (3), p.267-284
Main Authors: Cappelli, Lucio, Guglielmetti, Roberta, Mattia, Giovanni, Merli, Roberto, Francesca Renzi, Maria
Format: Article
Language:English
Subjects:
Attitude surveys
Citizens
Customer satisfaction
Customer services
Customer services quality
Data analysis
Decision making
Economic models
Economic statistics
Economic theory
Enrollments
Information industry
Information services
Likert scale
Marketing
Multivariate analysis
Organizational learning
Public sector
Quality management
Quality of service
Questionnaires
Statistical methods
Studies
Total quality
Variables
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Summary:Purpose - The purpose of this paper is to propose a path analysis of data coming from a citizen's satisfaction survey to support decision makers in quality service improvement. In detail, the survey aims to measure citizen's satisfaction of an Italian local Public Administration regarding the "infant school (0-6 years) enrollment service".Design methodology approach - The survey represents an experimentation of an original model measuring customers' satisfaction toward on-line services. Some statistical methods to analyse a given dataset from different points of view are selected.Findings - Outcomes of descriptive statistics as well as of multivariate data analysis to summarize information variables are presented. A new multivariate statistical technique, Probabilistic Expert Systems (PES) (Cowell et al.), is proposed to simulate corrective actions (scenarios) and to suggest the best one for the service quality improvement.Originality value - The paper shows that statistical methods are able to support the decisional process because they allow the development of information (gathered from survey) into know-how. However, managers need to join together both statistical information and experience by means of a systematic method, in order to take effective decisions.
ISSN:1754-2731
1754-274X
DOI:10.1108/17542731011035514