Modern Analysis of Customer Surveys: With Applications Using R
Ron S. Kenett, Silvia SaliniKey features:
- Provides an integrated, case-studies based approach to analysing customer survey data.
- Presents a general introduction to customer surveys, within an organization’s business cycle.
- Contains classical techniques with modern and non standard tools.
- Focuses on probabilistic techniques from the area of statistics/data analysis and covers all major recent developments.
- Accompanied by a supporting website containing datasets and R scripts.
Customer survey specialists, quality managers and market researchers will benefit from this book as well as specialists in marketing, data mining and business intelligence fields.Content:
Chapter 1 Standards and Classical Techniques in Data Analysis of Customer Satisfaction Surveys (pages 1–18): Silvia Salini and Ron S. Kenett
Chapter 2 The ABC Annual Customer Satisfaction Survey (pages 19–36): Ron S. Kenett and Silvia Salini
Chapter 3 Census and Sample Surveys (pages 37–53): Giovanna Nicolini and Luciana Dalla Valle
Chapter 4 Measurement Scales (pages 55–70): Andrea Bonanomi and Gabriele Cantaluppi
Chapter 5 Integrated Analysis (pages 71–88): Silvia Biffignandi
Chapter 6 Web Surveys (pages 89–105): Roberto Furlan and Diego Martone
Chapter 7 The Concept and Assessment of Customer Satisfaction (pages 107–127): Irena Ograjensek and Iddo Gal
Chapter 8 Missing Data and Imputation Methods (pages 129–154): Alessandra Mattei, Fabrizia Mealli and Donald B. Rubin
Chapter 9 Outliers and Robustness for Ordinal Data (pages 155–169): Marco Riani, Francesca Torti and Sergio Zani
Chapter 10 Statistical Inference for Causal Effects (pages 171–192): Fabrizia Mealli, Barbara Pacini and Donald B. Rubin
Chapter 11 Bayesian Networks Applied to Customer Surveys (pages 193–215): Ron S. Kenett, Giovanni Perruca and Silvia Salini
Chapter 12 Log?Linear Model Methods (pages 217–229): Stephen E. Fienberg and Daniel Manrique?Vallier
Chapter 13 CUB Models: Statistical Methods and Empirical Evidence (pages 231–258): Maria Iannario and Domenico Piccolo
Chapter 14 The Rasch Model (pages 259–281): Francesca De Battisti, Giovanna Nicolini and Silvia Salini
Chapter 15 Tree?Based Methods and Decision Trees (pages 283–307): Giuliano Galimberti and Gabriele Soffritti
Chapter 16 PLS Models (pages 309–331): Giuseppe Boari and Gabriele Cantaluppi
Chapter 17 Nonlinear Principal Component Analysis (pages 333–356): Pier Alda Ferrari and Alessandro Barbiero
Chapter 18 Multidimensional Scaling (pages 357–390): Nadia Solaro
Chapter 19 Multilevel Models for Ordinal Data (pages 391–411): Leonardo Grilli and Carla Rampichini
Chapter 20 Quality Standards and Control Charts Applied to Customer Surveys (pages 413–438): Ron S. Kenett, Laura Deldossi and Diego Zappa
Chapter 21 Fuzzy Methods and Satisfaction Indices (pages 439–456): Sergio Zani, Maria Adele Milioli and Isabella Morlini