What are people saying about Artificial Intelligence in Tourism? – Computational Linguistic Analysis on YouTube Conversation

Chulmo Koo, College of Hotel & Tourism Management, Kyung Hee University

As much as AI has replaced the human in industries and daily life, many companies have developed AI applications such as a knowledge-based recommendation or voice-recognition systems. Recently, AI applications have extended to the service industry as well, where a human interaction is a key factor of business success. In the domain of the hospitality and tourism industry, interest in the use of AI has increased with expecting higher competitive advantages (Bowen and Morosan, 2018). AI technologies can provide prompt attention and customized service. Once the system is well stabilized, the costs can be reduced by replacing human resources.

In tourism, one thing for sure is that services and service products are intangible. In addition, customer evaluation is subjective to interaction with service providers, which means that human flexibility dealing with customer needs has played a great role in terms of service delivery and service failure recovery (Choi et al, 2019). Can we expect the same situation to AI machines? It might be more difficult to apply AI technologies and satisfy customers in the hospitality and tourism industry due to the lack of human like features.

This study investigates the question, “what do people expect from AI in tourism?” Traditional approaches to investigate exploratory events have focused on direct interview, online user-generated reviews and survey data. The limit of those approaches is mainly laid in researcher’s unintended intervention to interviewees and difficulty to find information rich cases. To overcome this, in this study, we collected data from YouTube video clips. The level of analysis is voice recording data included in the movie clips. We used a voice recognition program to extract interviews. The sample size was 225 videos and the total length of play time was about 263,873 seconds (73 hours). Time range was from 2011 to 2019.

Based on the cognitive dissonance theory and “curse of knowledge” posed by Camerer, Loewenstein and Weber (1989), we hypothesized that there are differences between professional interviewees and the customers who had experienced AI features relating to tourism or hospitality services. Latent semantic indexing results showed that implementing AI services would become skewed to robot workers in a hotel and autonomous travelling with intelligent apps. To compare professional- and customer data, we conducted Wilcoxon signed tests with sentiment decomposition of valence aware dictionary for semantic reasoning (Hutto and Gilbert, 2014) to learn that cognitive dissonance to smart tourism with AI has decreased rapidly and negative expectations to AI’s capability are higher.

This work contributed to smart tourism research for two reasons. First, we introduced a new way of investigating high-tech phenomenon by analyzing YouTube big data. This approach can supplement traditional approaches including interview, survey and online review data. Second, we found that attitudes to AI implementation are differentiated by professional reviewers and experienced customers.

Reference

[1] Bowen, J., & Morosan, C. (2018). Beware hospitality industry: the robots are coming. Worldwide Hospitality and Tourism Themes, 10(6), 726-733.

[2] Camerer, C., Loewenstein, G., & Weber, M. (1989). The curse of knowledge in economic settings: An experimental analysis. Journal of political Economy, 97(5), 1232-1254.

[3] Choi, S., Liu, S. Q., & Mattila, A. S. (2019). “How may I help you?” Says a robot: Examining language styles in the service encounter. International Journal of Hospitality Management, 82, 32-38.

[4] Hutto, C. J. & Gilbert, E. E. (2014). VADER: A parsimonious rule-based model for sentiment analysis of social media text. Eighth International Conference on Weblogs and Social Media (ICWSM-14). Ann Arbor, MI, June 2014.