Overview
- Presents statistical techniques used to analyze data from real situations where customer satisfaction surveys were performed
- Explains how to construct a nonparametric composite indicator to include different benchmarks of satisfaction
- Describes rank-based procedures for analyzing survey data using R
Part of the book series: SpringerBriefs in Statistics (BRIEFSSTATIST)
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Table of contents (5 chapters)
Keywords
About this book
This book deals with problems related to the evaluation of customer satisfaction in very different contexts and ways. Often satisfaction about a product or service is investigated through suitable surveys which try to capture the satisfaction about several partial aspects which characterize the perceived quality of that product or service. This book presents a series of statistical techniques adopted to analyze data from real situations where customer satisfaction surveys were performed.
The aim is to give a simple guide of the variety of analysis that can be performed when analyzing data from sample surveys: starting from latent variable models to heterogeneity in satisfaction and also introducing some testing methods for comparing different customers. The book also discusses the construction of composite indicators including different benchmarks of satisfaction. Finally, some rank-based procedures for analyzing survey data are also shown.
Authors and Affiliations
About the authors
Rosa Arboretti received her PhD in Statistical Methodology for Scientific Research at the University of Bologna. She is currently Associate Professor at the Department of Civil, Architectural and Environmental Engineering of the University of Padova. Her main research interests are related to Statistical Methods applied to Biomedicine and Engineering.
Arne Bathke is Full Professor of Statistics at the University of Salzburg. His main research interests are related to Nonparametric and Multivariate Statistics applied in different fields from Social Sciences to Biomedicine and Engineering.
Stefano Bonnini is Associate Professor of Statistics at the Department of Economics and Management of the University of Ferrara. His main research interests are related to Nonparametric Statistics and Statistics applied to Economic and Social Sciences, Health Sciences and Engineering.
Paolo Bordignon is a Psychologist graduated at the University of Padova. He received his PhD at the Department of Management and Engineering of the University of Padova. His main research interests are related to Choice and Latent Statistical Models for Marketing Research.
Eleonora Carrozzo is a Post-Doc Research Fellow at the Department of Management and Engineering of the University of Padova where she received her PhD. Her main interests are related to Non-parametric Sstatistical Methods for Multivariate Hypothesis Testing and Ranking with application in Engineering and Biostatistics.
Livio Corain is Assistant Professor at the Department of Management and Engineering of the University of Padova. His main research interests are related to Nonparametric Methods for Ranking and Multivariate Hypothesis Testing, Quality Control and Applied Statistics for Engineering and Biomedical studies.
Luigi Salmaso is Full Professor of Statistics at the Department of Management and Engineering of the University of Padova. His main research interests include Biostatistics, Statistical Methods for Marketing Research, Design of Experiments, Nonparametric Statistics and Industrial Statistics.
Bibliographic Information
Book Title: Parametric and Nonparametric Statistics for Sample Surveys and Customer Satisfaction Data
Authors: Rosa Arboretti, Arne Bathke, Stefano Bonnini, Paolo Bordignon, Eleonora Carrozzo, Livio Corain, Luigi Salmaso
Series Title: SpringerBriefs in Statistics
DOI: https://doi.org/10.1007/978-3-319-91740-5
Publisher: Springer Cham
eBook Packages: Mathematics and Statistics, Mathematics and Statistics (R0)
Copyright Information: The Author(s), under exclusive licence to Springer International Publishing AG, part of Springer Nature 2018
Softcover ISBN: 978-3-319-91739-9Published: 27 June 2018
eBook ISBN: 978-3-319-91740-5Published: 18 June 2018
Series ISSN: 2191-544X
Series E-ISSN: 2191-5458
Edition Number: 1
Number of Pages: X, 84
Number of Illustrations: 5 b/w illustrations, 12 illustrations in colour
Topics: Statistical Theory and Methods, Probability and Statistics in Computer Science, Computational Mathematics and Numerical Analysis