Modern analysis of customer satisfaction surveys: Comparison of models and integrated analysis

Applied Stochastic Models in Business and Industry

Volumn 27, Issue 5, 2011, Pages 465-475

  Kenett, Ron S ^a,b   Salini, Silvia ^c  

^a KPA LTD   (Israel)

^b UNIVERSITY OF TURIN   (Italy)

^c UNIVERSITY OF MILAN   (Italy)

Author keywords

Annual Customer Satisfaction Survey (ACSS); categorical data analysis; information quality (InfoQ); nominal data; ordinal data; statistical models

Indexed keywords

CATEGORICAL DATA ANALYSIS; CUSTOMER SATISFACTION SURVEY; INFORMATION QUALITY; NOMINAL DATA; ORDINAL DATA; STATISTICAL MODELS;

DATA REDUCTION; INFORMATION ANALYSIS; INTELLIGENT NETWORKS; QUALITY CONTROL; SALES; SURVEYS;

CUSTOMER SATISFACTION;

EID: 80054803192     PISSN: 15241904     EISSN: 15264025     Source Type: Journal    
DOI: 10.1002/asmb.927     Document Type: Article

References (33)

1. Hand DJ, Mannila H, Smyth P,. Principles of data mining, MIT Press: Cambridge, MA, USA, 2001.
2. Kenett RS, Salini S,. New Frontiers: Bayesian networks give insight into survey-data analysis. Quality Progress 2009: 31-36.
3. Kenett RS, Salini S,. Modern Analysis of Customer Satisfaction Surveys: with applications using R, John Wiley and Sons: Chichester: UK, 2011.
4. Salini S, Kenett RS,. Bayesian Networks of Customer Satisfaction Survey Data. Journal of Applied Statistics 2009; 36 (11): 1177-1189.
5. Kenett RS, Shmueli G,. 2011. On Information Quality, Technical Report Robert H. Smith School Research Paper No RHS 06-100. Available at SSRN:.
6. Kenett RS,. Two Methods for Comparing Pareto Charts.
7. Quality Technology and Quantitative Management. Special Issue on Non-Standard Analysis of Customer Survey Data, Corradetti R, Furlan R, Salini S, (eds). Chung Hua University: Hsinchu, Taiwan ROC, 2008.
8. Pearl J,. Causality: Models, Reasoning, and Inference. Cambridge University Press: UK, 2000.
9. Lauritzen SL, Spiegelhalter DJ,. Local computations with probabilities on graphical structures and their application to expert systems. Journal of the Royal Statistical Society, Series B (Methodological) 1988; 50 (2): 157-224.
10. Kenett RS,. Cause and Effect Diagrams. Encyclopaedia of Statistics in Quality and Reliability, Ruggeri F, Kenett RS, Faltin F, (eds). Wiley: UK, 2007.
11. Kenett RS, Perruca G, Salini S,. Bayesian Networks. Modern Analysis of Customer Satisfaction Surveys, Kenett RS, Salini S, (eds). John Wiley and Sons: Chichester: UK, 2011b.
12. Piccolo D,. On the moments of a mixture of uniform and shifted binomial random variables. Quaderni di Statistica 2003; 5: 85-104.
13. Iannario M, Piccolo D,. CUB Models: Statistical Methods and Empirical Evidence. Modern Analysis of Customer Satisfaction Surveys, Kenett RS, Salini S, (eds). John Wiley and Sons: Chichester: UK, 2011.
14. Rasch G,. Probabilistic models for some intelligence and attainment tests, Copenhagen, Danish Institute for Educational Research, expanded edition (1980) with foreword and afterword by B.D. Wright. The University of Chicago Press: Chicago, 1960.
15. De Battisti F, Nicolini G, Salini S,. The Rasch Model to Measure Service Quality. The ICFAI Journal of Services Marketing 2005; III (3): 58-80.
16. De Battisti F, Nicolini G, Salini S,. The Rasch Model in Customer Satisfaction Survey Data. Quality Technology & Quantitative Management 2010; 7 (1): 15-34.
17. De Battisti F, Nicolini G, Salini S,. The Rasch Model. Modern Analysis of Customer Satisfaction Surveys., Kenett RS, Salini S, (eds). John Wiley and Sons: Chichester: UK, 2011.
18. Andrich D,. Rasch models for measurement. Sage: Beverly Hills, USA, 1988.
19. Baker FB,. Methodology review: item parameter estimation under the one, two and three-parameter logistic models. Applied Psychological Measurement 1987; XI (2): 111-141.
20. Bertoli-Barsotti L,. An order-preserving property of the maximum likelihood estimates for the Rasch model. Statistics and Probability Letters 2003; 61: 91-96.
21. Bertoli-Barsotti L,. On the existence and uniqueness of JLM estimates for the Partial Credit Model. Psychometrika 2005; 70 (3): 517-531. (Pubitemid 41771192)
22. Kenett RS, Zacks S,. Modern Industrial Statistics: Design and Control of Quality and Reliability. Duxbury Press: San Francisco, 1998. 1998, Spanish edition 2000, 2nd paperback edition 2002, Chinese edition, 2004.
23. Kenett RS, Deldossi L, Zappa D,. Quality standards and control charts applied to customer surveys. Modern Analysis of Customer Satisfaction Surveys, Kenett RS, Salini S, (eds). John Wiley and Sons: Chichester: UK, 2011a.
24. GeNIe. Decision Systems Laboratory. University of Pittsburgh: USA, 2006.
25. Mair P, Hatzinger R,. Extended Rasch Model: The eRm package for the Application of IRT models in R. Journal of Statistical Software 2007; 20 (9): 1-20.
26. Rasch G,. Probabilistic models for some intelligence and attainment tests, (Copenhagen, Danish Institute for Educational Research), expanded edition (1980) with foreword and after word by B.D. Wright, The University of Chicago Press: Chicago, 1960/1980.
27. MININTAB. Software for Quality Improvement, 2011.
28. Fuchs C, Kenett RS,. Missing Data and Imputation. Encyclopedia of Statistics in Quality and Reliability, Ruggeri F, Kenett RS, Faltin F, (eds). Wiley: UK, 2007.
29. Harel O,. Strategies for Data Analysis with Two Types of Missing Values: From Theory to Application. Lambert Academic Publishing: Saarbrucken, Germany, 2009.
30. Harel O, Schafer JL,. Partial and latent ignorability in missing-data problems. Biometrika 2009; 96: 37-50.
31. Ferrari P, Barbiero A,. Nonlinear Principal Component Analysis. Modern Analysis of Customer Satisfaction Surveys, Kenett RS, Salini S, (eds). John Wiley and Sons: Chichester: UK, 2011.
32. Galimberti G, Soffitti G,. Tree Based methods and Decision Trees. Modern Analysis of Customer Satisfaction Surveys, Kenett RS, Salini S, (eds). John Wiley and Sons: Chichester: UK, 2011.
33. Boari G, Cantaluppi G,. PLS Models. Modern Analysis of Customer Satisfaction Surveys., Kenett RS, Salini S, (eds). John Wiley and Sons: Chichester: UK, 2011.