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  • © 2018

Parametric and Nonparametric Statistics for Sample Surveys and Customer Satisfaction Data

  • 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)

  1. Front Matter

    Pages i-x
  2. The CUB Models

    • Rosa Arboretti, Arne Bathke, Stefano Bonnini, Paolo Bordignon, Eleonora Carrozzo, Livio Corain et al.
    Pages 1-17
  3. Customer Satisfaction Heterogeneity

    • Rosa Arboretti, Arne Bathke, Stefano Bonnini, Paolo Bordignon, Eleonora Carrozzo, Livio Corain et al.
    Pages 19-35
  4. Ranking Multivariate Populations

    • Rosa Arboretti, Arne Bathke, Stefano Bonnini, Paolo Bordignon, Eleonora Carrozzo, Livio Corain et al.
    Pages 37-55
  5. Composite Indicators and Satisfaction Profiles

    • Rosa Arboretti, Arne Bathke, Stefano Bonnini, Paolo Bordignon, Eleonora Carrozzo, Livio Corain et al.
    Pages 57-69
  6. Analyzing Survey Data Using Multivariate Rank-Based Inference

    • Rosa Arboretti, Arne Bathke, Stefano Bonnini, Paolo Bordignon, Eleonora Carrozzo, Livio Corain et al.
    Pages 71-84

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

  • Department of Civil and Environmental Engineering, University of Padova, Padova, Italy

    Rosa Arboretti

  • Natural Science, University of Salzburg, Salzburg, Austria

    Arne Bathke

  • Department of Economics and Management, University of Ferrara, Ferrara, Italy

    Stefano Bonnini

  • Department of Management and Engineering, University of Padova, Padova, Italy

    Paolo Bordignon, Eleonora Carrozzo, Livio Corain, Luigi Salmaso

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

Buy it now

Buying options

eBook USD 39.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Other ways to access