A Big-Data Analysis of Public Perceptions of Service Robots Amid Covid-19

Yıl 2021, Cilt: 9 Sayı: 1, 234 - 242, 01.06.2021

Yaozhi Zhang

https://doi.org/10.30519/ahtr.799210

Cited By: 6

Öz

This research note investigates public perceptions of robotic services in the hospitality and tourism industry in the context of COVID-19. Relevant comments from YouTube videos were crawled and analysed by Natural Language Processing (NLP) techniques including explorative analysis, sentiment analysis, and topic modelling. The results reveal that while there are supporters and opponents toward robotic services during the pandemic, the overall public sentiment is neutral, and confirm that the health factor and a series of social-cultural factors encompassing the employment concern, political influence, and cultural norm should be involved as more significant variables for COVID-Tourism research. Some practical suggestions for robotic services amidst COVID-19 are accordingly put forward.

Anahtar Kelimeler

COVID-19, service robot, public perception, hospitality and tourism industry

Kaynakça

• Abdelhamied, H. H. S. (2011). Customers' perceptions of floating restaurants in Egypt. Anatolia, 22(1), 1-15. https://doi.org/10.1080/13032917.2011.556212
• Amatulli, C., De Angelis, M., & Stoppani, A. (2019). Analyzing online reviews in hospitality: data-driven opportunities for predicting the sharing of negative emotional content. Current issues in tourism, 22(15), 1904-1917. https://doi.org/10.1080/13683500.2019.1594723
• Gössling, S., Scott, D., & Hall, C. M. (2021). Pandemics, tourism and global change: a rapid assessment of COVID-19. Journal of sustainable tourism, 29(1), 1-20. https://doi.org/10.1080/09669582.2020.1758708
• Gretzel, U., Fuchs, M., Baggio, R., Hoepken, W., Law, R., Neidhardt, J., Pesonen, J., Zanker, M., & Xiang, Z. (2020). e-Tourism beyond COVID-19: a call for transformative research. Information technology & tourism, 22(2), 187-203. https://doi.org/10.1007/s40558-020-00181-3
• Guo, Y., Barnes, S. J., & Jia, Q. (2017). Mining meaning from online ratings and reviews: Tourist satisfaction analysis using latent dirichlet allocation. Tourism management 59, 467-483. https://doi.org/10.1016/j.tourman.2016.09.009
• Ivanov, S., Gretzel, U., Berezina, K., Sigala, M., & Webster, C. (2019). Progress on robotics in hospitality and tourism: a review of the literature. Journal of Hospitality and Tourism Technology, 10(4), 489-521. https://doi.org/10.1108/JHTT-08-2018-0087
• Ivanov, S., Webster, C., & Garenko, A. (2018). Young Russian adults' attitudes towards the potential use of robots in hotels. Technology in Society, 55, 24-32. https://doi.org/10.1016/j.techsoc.2018.06.004
• Jiang, Y., & Wen, J. (2020). Effects of COVID-19 on hotel marketing and management: a perspective article. International journal of contemporary hospitality management, 32(8), 2563-2573. https://doi.org/10.1108/IJCHM-03-2020-0237
• Kuo, C.-M., Chen, L.-C., & Tseng, C.-Y. (2017). Investigating an innovative service with hospitality robots. International Journal of Contemporary Hospitality Management, 29(5), 1305-1321. https://doi.org/10.1108/IJCHM-08-2015-0414
• Lu, L., Cai, R., & Gursoy, D. (2019). Developing and validating a service robot integration willingness scale. International Journal of Hospitality Management, 80, 36-51. https://doi.org/10.1016/j.ijhm.2019.01.005
• Seyitoğlu, F., & Ivanov, S. (2020). Service robots as a tool for physical distancing in tourism. Current issues in tourism, 1-4. https://doi.org/10.1080/13683500.2020.1774518
• Shin, H., & Kang, J. (2020). Reducing perceived health risk to attract hotel customers in the COVID-19 pandemic era: Focused on technology innovation for social distancing and cleanliness. International Journal of Hospitality Management, 91, 102664. https://doi.org/10.1016/j.ijhm.2020.102664
• Sigala, M. (2020). Tourism and COVID-19: Impacts and implications for advancing and resetting industry and research. Journal of Business Research, 117, 312-321. https://doi.org/10.1016/j.jbusres.2020.06.015
• Tan, P.-N., Steinbach, M., & Kumar, V. (2014). Introduction to data mining. Pearson.
• Tavakoli, M., Carriere, J., & Torabi, A. (2020). Robotics, Smart Wearable Technologies, and Autonomous Intelligent Systems for Healthcare During the COVID‐19 Pandemic: An Analysis of the State of the Art and Future Vision. Advanced intelligent systems, 2000071. https://doi.org/10.1002/aisy.202000071
• Wan, L. C., Chan, E. K., & Luo, X. (2020). ROBOTS COME to RESCUE: How to reduce perceived risk of infectious disease in Covid19-stricken consumers? Annals of Tourism Research, 103069. https://doi.org/10.1016/j.annals.2020.103069
• Wen, J., Wang, W., Kozak, M., Liu, X., & Hou, H. (2020). Many brains are better than one: the importance of interdisciplinary studies on COVID-19 in and beyond tourism. Tourism recreation research, 1-4. https://doi.org/10.1080/02508281.2020.1761120
• Yu, C.-E. (2020). Humanlike robots as employees in the hotel industry: Thematic content analysis of online reviews. Journal of Hospitality Marketing & Management, 29(1), 22-38. https://doi.org/10.1080/19368623.2019.1592733
• Zeng, Z., Chen, P.-J., & Lew, A. A. (2020). From high-touch to high-tech: COVID-19 drives robotics adoption. Tourism geographies, 1-11. https://doi.org/10.1080/14616688.2020.1762118
• Zenker, S., & Kock, F. (2020). The coronavirus pandemic – A critical discussion of a tourism research agenda. Tourism management 81, 104164. https://doi.org/10.1016/j.tourman.2020.104164