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Using an Ontology-Based Neural Network and DEA to Discover Deficiencies of Hotel Services

Tzu-An Chiang, Z. H. Che, Yi-Ling Huang, Chang-You Tsai

Source Title: International Journal on Semantic Web and Information Systems (IJSWIS)18(1)

ISSN: 1552-6283|EISSN: 1552-6291|EISBN13: 9781799893967|DOI: 10.4018/IJSWIS.306748

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MLA

Chiang, Tzu-An, et al. "Using an Ontology-Based Neural Network and DEA to Discover Deficiencies of Hotel Services." IJSWIS vol.18, no.1 2022: pp.1-19. http://doi.org/10.4018/IJSWIS.306748

APA

Chiang, T., Che, Z. H., Huang, Y., & Tsai, C. (2022). Using an Ontology-Based Neural Network and DEA to Discover Deficiencies of Hotel Services. International Journal on Semantic Web and Information Systems (IJSWIS), 18(1), 1-19. http://doi.org/10.4018/IJSWIS.306748

Chicago

Chiang, Tzu-An, et al. "Using an Ontology-Based Neural Network and DEA to Discover Deficiencies of Hotel Services," International Journal on Semantic Web and Information Systems (IJSWIS) 18, no.1: 1-19. http://doi.org/10.4018/IJSWIS.306748

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Abstract

Companies can gain critical real-time insights into customer requirements and service evaluation by mining social media. To acquire the service performance and improve the service deficiencies for hotels, this research proposes a benchmark-based performance evaluation model for hotel service to enable hotel managers to assess the service performance. In the case of non-benchmark service hotels, the identification and improvement model for non-benchmark criteria can recognize and analyze the required quantities of performance improvements for non-benchmark criteria. For understanding the causes of service deficiencies, this research mines the online posts and creates a hierarchical ontology of service deficiencies for hotels. A hierarchical ontology-based neural network is proposed to automatically identify the causes of service deficiencies. This study employs an online forum as a case to achieve the identification accuracy of causes of service deficiencies of 92.68%. The analytical result can demonstrate the significant effectiveness and practical value of the proposed methodology.