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Deep learning model based on expectation-confirmation theory to predict customer satisfaction in hospitality service

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Abstract

Customer satisfaction is one of the most important measures in the hospitality industry. Therefore, several psychological and cognitive theories have been utilized to provide appropriate explanations of customer perception. Owing to recent rapid developments in artificial intelligence and big data, novel methodologies have presented to examine several psychological theories applied in the hospitality industry. Within this framework, this study combines deep learning techniques with the expectation-confirmation theory to elucidate customer satisfaction in hospitality services. Customer hotel review comments, hotel information, and images were employed to predict customer satisfaction with hotel service. The results show that the proposed fused model achieved an accuracy of 83.54%. In addition, the recall value that predicts dissatisfaction improved from 16.46–33.41%. Based on the findings of this study, both academic and managerial implications for the hospitality industry are presented.

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Notes

  1. https://www.kaggle.com/ycalisar/hotel-reviews-dataset-enriched.

  2. https://brandirectory.com/rankings/hotels/table.

  3. https://pypi.org/project/icrawler/.

  4. https://github.com/cjhutto/vaderSentiment.

  5. https://www.nltk.org/.

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Acknowledgements

This research was supported by the National Research Foundation of Korea funded by the Korean Government (NRF-2020R1C1C1004324). This work was supported by Institute of Information and communications Technology Planning and Evaluation (IITP) grant funded by the Korea government (MSIT) (No. 2021-0-00358, AI \(\cdot\) Big data based Cyber Security Orchestration and Automated Response Technology Development).

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Authors and Affiliations

  1. Department of Applied Artificial Intelligence, Sungkyunkwan University, Seoul, Republic of Korea

    Soyoung Oh & Eunil Park

  2. Raon Data, Seoul, Republic of Korea

    Honggeun Ji & Jina Kim

  3. Jaume I University, Castellon, Spain

    Angel P. del Pobil

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  1. Soyoung Oh
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  2. Honggeun Ji
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  4. Eunil Park
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Correspondence to Eunil Park.

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Oh, S., Ji, H., Kim, J. et al. Deep learning model based on expectation-confirmation theory to predict customer satisfaction in hospitality service. Inf Technol Tourism 24, 109–126 (2022). https://doi.org/10.1007/s40558-022-00222-z

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