Abstract
This study conducts a customer survey and performs an analysis using factor analysis, artificial neural networks, and logistic regression analysis to gain an in-depth understanding of the impact of hotel service attributes on customer satisfaction. The results show that among the four hotel service attributes (personnel services, room quality, dining quality, and business and travel services), “personnel services” has the greatest impact on customer satisfaction, whereas “business and travel services” has the lowest impact. Artificial neural network is more accurate than logistic regression analysis for predicting customer satisfaction. Artificial neural networks achieved an accuracy rate of 93%. Although logistic regression analysis has an accuracy rate of 87% for predicting customer satisfaction, it only scores 23.77% for predicting “unsatisfied customers.” Artificial neural network is more suitable than logistic regression analysis for predicting customer satisfaction.
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© 2013 Springer-Verlag Berlin Heidelberg
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Huang, HC. (2013). Research on the Influential Factors of Customer Satisfaction for Hotels: The Artificial Neural Network Approach and Logistic Regression Analysis. In: Du, Z. (eds) Proceedings of the 2012 International Conference of Modern Computer Science and Applications. Advances in Intelligent Systems and Computing, vol 191. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-33030-8_71
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DOI: https://doi.org/10.1007/978-3-642-33030-8_71
Publisher Name: Springer, Berlin, Heidelberg
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