Boosting Hong Kong’s tourism with LLM-based tourist satisfaction index
In support of the long-term sustainability of the tourism sector, the Research Centre for Digital Transformation of Tourism (RCdTT) of PolyU’s School of Hotel and Tourism Management (SHTM) has introduced a large language model (LLM)-based assessment framework harnessing artificial intelligence, LLM, and big data analytics. The framework, named “the Hong Kong Tourist Satisfaction Index (HKTSI), aims to offer more precise and targeted advice for strengthening tourism service quality and bolstering Hong Kong’s global competitiveness.
HKTSI was developed by a PolyU research team led by Professor Haiyan Song, Principal Investigator and SHTM Associate Dean, RCdTT Director, and Mr and Mrs Chan Chak Fu Professor in International Tourism. It is an enhanced version of the TSI framework initially introduced in 2009. The team has transformed the framework by adopting an interdisciplinary approach that integrates theories from management science, economics and computer science, and leverages advanced LLM technology, providing a more comprehensive and accurate analysis.
The team utilised this innovative model to evaluate the satisfaction level of inbound tourists to Hong Kong from 2012 to 2024 across different tourism-related sectors, temporal scales and regions. Findings revealed that while performance variations across different regions were observed, the TSI rebounded and reached its highest-ever recorded score following the temporary decline during the pandemic. Prof. Song highlighted the significance of the framework in facilitating decision-making and planning by policymakers and industry practitioners.
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