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Complementary Use of Rasch Models and Nonlinear Principal Components Analysis in the Assessment of the Opinion of Europeans About Utilities

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  • Pier Ferrari
  • Silvia Salini

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  • Pier Ferrari & Silvia Salini, 2011. "Complementary Use of Rasch Models and Nonlinear Principal Components Analysis in the Assessment of the Opinion of Europeans About Utilities," Journal of Classification, Springer;The Classification Society, vol. 28(1), pages 53-69, April.
    • Handle: RePEc:spr:jclass:v:28:y:2011:i:1:p:53-69
    DOI: 10.1007/s00357-011-9081-0
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    References listed on IDEAS

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    1. Pier Ferrari & Paola Annoni & Giancarlo Manzi, 2010. "Evaluation and comparison of European countries: public opinion on services," Quality & Quantity: International Journal of Methodology, Springer, vol. 44(6), pages 1191-1205, October.
    2. Fiorio, Carlo V. & Florio, M. & Salini, S. & Ferrari, P.A., 2007. "Consumers' Attitudes on Services of General Interest in the EU: Accessibility, Price and Quality 2000-2004," Privatisation Regulation Corporate Governance Working Papers 12195, Fondazione Eni Enrico Mattei (FEEM).
    3. Silvia Salini & Ron Kenett, 2009. "Bayesian networks of customer satisfaction survey data," Journal of Applied Statistics, Taylor & Francis Journals, vol. 36(11), pages 1177-1189.
    4. Rich, Richard, 1988. "The Economic Development of Japan c. 1868–1941. By W. J. Macpherson. Houndmills, Basingstoke, Hampshire: Macmillan Education Ltd., 1987. Pp. 93. $8.50," The Journal of Economic History, Cambridge University Press, vol. 48(3), pages 760-761, September.
    5. Green, Paul E & Srinivasan, V, 1978. "Conjoint Analysis in Consumer Research: Issues and Outlook," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 5(2), pages 103-123, Se.
    6. Pieralda FERRARI & Paola ANNONI & Silvia SALINI, 2005. "A comparison between alternative models for environmental ordinal data: Nonlinear PCA vs Rasch Analysis," Departmental Working Papers 2005-12, Department of Economics, Management and Quantitative Methods at Università degli Studi di Milano.
    7. Silvia SALINI & Ron S. KENETT, 2007. "Bayesian networks of customer satisfaction survey data," Departmental Working Papers 2007-33, Department of Economics, Management and Quantitative Methods at Università degli Studi di Milano.
    8. Maurizio Vichi & Roberto Rocci & Henk A.L. Kiers, 2007. "Simultaneous Component and Clustering Models for Three-way Data: Within and Between Approaches," Journal of Classification, Springer;The Classification Society, vol. 24(1), pages 71-98, June.
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    Cited by:

    1. Galeotti, Marzio & Rubashkina, Yana & Salini, Silvia & Verdolini, Elena, 2018. "Environmental policy performance and its determinants: Application of a three-level random intercept model," Energy Policy, Elsevier, vol. 114(C), pages 134-144.
    2. Federico ANDREIS & Pier Alda FERRARI, 2015. "Customer Satisfaction Evaluation Using Multidimensional Item Response Theory Models," Departmental Working Papers 2015-25, Department of Economics, Management and Quantitative Methods at Università degli Studi di Milano.
    3. Giancarlo MANZI & Pier Alda FERRARI, "undated". "Statistical methods for evaluating satisfaction with public services Abstract: Contrary to private enterprises, public enterprises can be unaware of the impact of their performance when providing serv," CIRIEC Working Papers 1404, CIRIEC - Université de Liège.
    4. Luisa ANDERLONI & Emanuele BACCHIOCCHI & Daniela VANDONE, 2011. "Household financial vulnerability: an empirical analysis," Departmental Working Papers 2011-02, Department of Economics, Management and Quantitative Methods at Università degli Studi di Milano, revised 03 Nov 2011.
    5. Federica Cugnata & Silvia Salini, 2014. "Model-based approach for importance–performance analysis," Quality & Quantity: International Journal of Methodology, Springer, vol. 48(6), pages 3053-3064, November.
    6. Federico Andreis & Pier Alda Ferrari, 2014. "Multidimensional item response theory models for dichotomous data in customer satisfaction evaluation," Journal of Applied Statistics, Taylor & Francis Journals, vol. 41(9), pages 2044-2055, September.

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