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

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.