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Random Component Threshold Models in a Customer Satisfaction Evaluation

Random Component Threshold Models in a Customer Satisfaction Evaluation
Random Component Threshold Models in a Customer Satisfaction Evaluation
The degree of customer satisfaction is measured on an ordinal scale in evaluating a customer opinion programme. Two random component threshold models are fitted to the results data. Estimation of the parameters in the models and variance components are given by residual maximum likelihood method. The predicted values of the probability of selecting a specific response category are given for all customers. A threshold is selected and customers are then divided into happy and unhappy groups.
M04/06
Southampton Statistical Sciences Research Institute, University of Southampton
Saei, Ayoub
d9202095-5650-4b3d-9b13-a8d16e10b338
Alimoradi, Soroush
056e4c68-d045-4c0d-8561-0866779b695c
Saei, Ayoub
d9202095-5650-4b3d-9b13-a8d16e10b338
Alimoradi, Soroush
056e4c68-d045-4c0d-8561-0866779b695c

Saei, Ayoub and Alimoradi, Soroush (2004) Random Component Threshold Models in a Customer Satisfaction Evaluation (S3RI Methodology Working Papers, M04/06) Southampton, UK. Southampton Statistical Sciences Research Institute, University of Southampton 17pp.

Record type: Monograph (Project Report)

Abstract

The degree of customer satisfaction is measured on an ordinal scale in evaluating a customer opinion programme. Two random component threshold models are fitted to the results data. Estimation of the parameters in the models and variance components are given by residual maximum likelihood method. The predicted values of the probability of selecting a specific response category are given for all customers. A threshold is selected and customers are then divided into happy and unhappy groups.

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Published date: 2004

Identifiers

Local EPrints ID: 8179
URI: http://eprints.soton.ac.uk/id/eprint/8179
PURE UUID: 0351fa89-6daf-46e7-9021-0cacc6abc08d

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Date deposited: 11 Jul 2004
Last modified: 15 Mar 2024 04:51

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Contributors

Author: Ayoub Saei
Author: Soroush Alimoradi

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