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Customer Satisfaction Measurement Models: Generalised Maximum Entropy Approach

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  • Amjad D. Al-Nasser

Abstract

This paper presents the methodology of the Generalised Maximum Entropy (GME) approach for estimating linear models that contain latent variables such as customer satisfaction measurement models. The GME approach is a distribution free method and it provides better alternatives to the conventional method; Namely, Partial Least Squares (PLS), which used in the context of costumer satisfaction measurement. A simplified model that is used for the Swedish customer satis faction index (CSI) have been used to generate simulated data in order to study the performance of the GME and PLS. The results showed that the GME outperforms PLS in terms of mean square errors (MSE). A simulated data also used to compute the CSI using the GME approach.

Suggested Citation

  • Amjad D. Al-Nasser, 2005. "Customer Satisfaction Measurement Models: Generalised Maximum Entropy Approach," Econometrics 0503013, University Library of Munich, Germany.
    • Handle: RePEc:wpa:wuwpem:0503013
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    References listed on IDEAS

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    1. Herman Wold, 1980. "Model Construction and Evaluation When Theoretical Knowledge Is Scarce," NBER Chapters, in: Evaluation of Econometric Models, pages 47-74, National Bureau of Economic Research, Inc.
    2. Golan, Amos & Judge, George & Karp, Larry, 1996. "A maximum entropy approach to estimation and inference in dynamic models or Counting fish in the sea using maximum entropy," Journal of Economic Dynamics and Control, Elsevier, vol. 20(4), pages 559-582, April.
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    Cited by:

    1. Bustos-Reyes, César Augusto & González-Benito, Óscar, 2008. "Store and store format loyalty measures based on budget allocation," Journal of Business Research, Elsevier, vol. 61(9), pages 1015-1025, September.
    2. Rosa Bernardini Papalia & Enrico Ciavolino, 2011. "GME Estimation of Spatial Structural Equations Models," Journal of Classification, Springer;The Classification Society, vol. 28(1), pages 126-141, April.
    3. Laura Trinchera & Giorgio Russolillo, 2010. "On the use of Structural Equation Models and PLS Path Modeling to build composite indicators," Working Papers 30-2010, Macerata University, Department of Studies on Economic Development (DiSSE), revised Oct 2010.

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    Keywords

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    JEL classification:

    • C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General
    • C2 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables
    • C3 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables
    • C4 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics
    • C5 - Mathematical and Quantitative Methods - - Econometric Modeling
    • C8 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs

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