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- W2007543263 abstract "Effective measurement and analysis of service quality are a critical first phase in quality improvement. Patients' expectations and perceptions of service quality in hospitals play an important role in their loyalty to the organization and buying the services in the future for next time. The services will not improve unless the quality of needs is specified. Models based on expectations and perceptions of patients have a special place that are used in different ranges of services. This study discusses the development of neural network models for this purpose. A valid neural network model for service quality is initially developed. Customer data from a SERVQUAL survey at the Qazvin University of Medical Sciences' hospitals provide the basis for model development. Different definitions of service quality measurement are modeled using the neural network approach. We compared these models in hospitals by using neural networks as a powerful tool in non-linear processing. The perception-minus-expectation model of service quality was found not to be as accurate as the perception-only model in predicting service quality. In conclusion, the obtained results showed that our artificial neural network-based model approach is very promising and may be effectively used for developing which model is better to use in quality services measurement." @default.
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- W2007543263 date "2013-04-01" @default.
- W2007543263 modified "2023-10-16" @default.
- W2007543263 title "The comparison of methods for measuring quality of hospital services by using neural networks: A case study in Iran (2012)" @default.
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- W2007543263 doi "https://doi.org/10.1179/2047971912y.0000000024" @default.
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