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Customer Satisfaction Measurement Models: Generalised Maximum Entropy Approach

  • Amjad D. Al-Nasser

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.

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File URL: http://econwpa.repec.org/eps/em/papers/0503/0503013.pdf
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Paper provided by EconWPA in its series Econometrics with number 0503013.

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Length: 14 pages
Date of creation: 10 Mar 2005
Date of revision:
Handle: RePEc:wpa:wuwpem:0503013
Note: Type of Document - pdf; pages: 14
Contact details of provider: Web page: http://econwpa.repec.org

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  1. 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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