Research Article
BibTex RIS Cite

Artificial intelligence and robotic technologies in tourism and hospitality industry

Year 2020, , 353 - 380, 30.12.2020
https://doi.org/10.48070/erusosbilder.838193

Abstract

Artificial intelligence applications and robotic technologies, which are rapidly spreading and widely used throughout the world, are discussed by different disciplines in the literature. The field of tourism draws attention as one of the disciplines in which studies on these issues have been carried out in recent years. In this context, robots come to the fore in the application areas of the tourism sector. However, it is known that there are many artificial intelligence applications that are becoming widespread or likely to become widespread day by day in the tourism sector. From this point of view, in this conceptual study, firstly artificial intelligence applications and robotic technologies were evaluated, the development of these technologies was revealed, then the current technologies used in the tourism and hospitality industry were examined, and as a result, the future of these technologies in the tourism and hospitality industry was discussed. In this context, it can be said that this study, in which the current situation is revealed and sector-experienced writers make inferences for the future, is an important study that can contribute to the literature and industry practitioners.

References

  • Abadicio, M. (2019, November 22). AI in the travel and tourism industry – Current applications. https://emerj.com/ai-sector-overviews/ai-travel-tourism-industry-current-applications/
  • Abu Shawar, B., & Atwell, E. (2007). Chatbots: Are they really useful?. LDV-Forum, 22(1), 29–49.
  • Alom, M. Z., Taha, T. M., Yakopcic, C., Westberg, S., Sidike, P., Nasrin, M. S., … Asari, V. K. (2019). A state-of-the-art survey on deep learning theory and architectures. Electronics, 8, 292, 1–66. https://doi.org/10.3390/electronics8030292
  • Alpaydin, E. (2014). Introduction to machine learning (Third Ed.). The MIT Press.
  • Ang, B. (2016, February 07). Robot Lucy at your service at newly opened Rong Heng Seafood. https://www.straitstimes.com/lifestyle/food/robot-lucy-at-your-service-at-newly- opened-rong-heng-seafood
  • Assaf, A. G., & Tsionas, M. G. (2019). Forecasting occupancy rate with bayesian compression methods. Annals of Tourism Research, 75, 439–449. https://doi.org/10.1016/j.annals.2018.12.009
  • Barry, C., & Pele, C. (2018, April 02). Meet Italy’s robot concierge. https://www.stuff.co.nz/travel/news/102771691/meet-italys-robot-concierge
  • Berezina, K., Ciftci, O., & Cobanoglu, C. (2019). Robots, Artificial Intelligence, and Service Automation in Restaurants. In S. Ivanov & C. Webster (Eds.), Robots, Artificial Intelligence, and Service Automation in Travel, Tourism and Hospitality (pp. 185–219). Emerald Publishing Limited.
  • Berliner, H. J., & Ebeling, C. (1990). Hitech. In T. A. Marsland & J. Schaeffer (Eds.), Computers, Chess, and Cognition (pp. 79–109). Springer.
  • Buchanan, B., Sutherland, G., & Feigenbaum, E. A. (1969). Heuristic DENDRAL - A program for generating explanatory hypotheses in organic chemistry. In B. Meltzer & D. Michie (Eds.), Machine Intelligence 4 (pp. 209–254). Edinburgh University Press.
  • CAICT. (2018). 2018 world artificial intelligence industry development blue book. http://www.caict.ac.cn/kxyj/qwfb/bps/201809/P020180918696200669434.pdf
  • Chen, H. (2019). Success factors impacting artificial intelligence adoption --- Perspective from the telecom industry in China. [Unpublished Doctoral Dissertation]. Department of Business Administration-Information Technology, Old Dominion University.
  • Chen, K. Y., & Wang, C. H. (2007). Support vector regression with genetic algorithms in forecasting tourism demand. Tourism Management, 8(1), 215–226. https://doi.org/10.1016/j.tourman.2005.12.018
  • Chen, R., Liang, C. Y., Hong, W. C., & Gu, D. X. (2015). Forecasting holiday daily tourist flow based on seasonal support vector regression with adaptive genetic algorithm. Applied Soft Computing Journal, 26, 435–443. https://doi.org/10.1016/j.asoc.2014.10.022
  • Cheong, A., Lau, M. W. S., Foo, E., Hedley, J., & Bo, J. W. (2016). Development of a robotic waiter system. IFAC-PapersOnLine, 49(21), 681–686. https://doi.org/10.1016/j.ifacol.2016.10.679
  • Chestler, D. (2016). The future is now: How robots are storming the travel industry. https://www.siteminder.com/r/trends-advice/hotel-travel-industry-trends/future-robots-storming- travel-industry/
  • CHIP Online. (2018, March 2018). Divan İstanbul’da akıllı otel deneyimi yaşanıyor. https://www.chip.com.tr/haber/divan-istanbulda-akilli-otel-deneyimi-yasaniyor_74904.html
  • Chow, W. S., Shyu, J. C., & Wang, K. C. (1998). Developing a forecast system for hotel occupancy rate using integrated ARIMA models. Journal of International Hospitality, Leisure & Tourism Management, 1(3), 55–80. https://doi.org/10.1300/J268v01n03_05
  • Clarke, R. (2014). Understanding the drone epidemic. Computer Law and Security Review, 30(3), 230–246. https://doi.org/10.1016/j.clsr.2014.03.002
  • Claveria, O., Monte, E., & Torra, S. (2015). Tourism demand forecasting with neural network models: Different ways of treating information. International Journal of Tourism Research, 17, 492–500. https://doi.org/10.1002/jtr.2016
  • CRM Medya Turizm. (2020, November 18). Otelcilik Sektöründe Yapay Zeka Uygulamaları. https://www.crmturizm.com/otelcilik-sektorunde-yapay-zeka-uygulamalari/
  • Crook, J. (2014, August 13). Starwood introduces robotic butlers at aloft hotel in Cupertino. https://techcrunch.com/2014/08/13/starwood-introduces-robotic-butlers-at-aloft-hotel- in-palo-alto/#:~:text=Starwood%2C%20one%20of%20the%20world's,around%20guests%20and%20use%20elevators
  • Davis, L. K. (2016, March 9). Hilton and IBM pilot “Connie,” The world’s first Watson-enabled hotel concierge robot. https://www.ibm.com/blogs/watson/2016/03/watson-connie/
  • Deloitte. (2018). Global artificial intelligence industry whitepaper. https://www2.deloitte.com/cn/en/pages/technology-media-and-telecommunications/articles/global-ai- development-white-paper.html#
  • Donaire, J. A., Galí, N., & Gulisova, B. (2020). Tracking visitors in crowded spaces using zenith images: Drones and time-lapse. Tourism Management Perspectives, 35, 100680. https://doi.org/10.1016/j.tmp.2020.100680
  • Elkins, K. (2015, May 07). This restaurant has a new secret weapon: A robot that slices the perfect noodle faster than any human. https://www.businessinsider.in/This-restaurant- has-a-new-secret-weapon-a-robot-that-slices-the-perfect-noodle-faster-than-any-human/articleshow/47188856.cms
  • Fesenmaier, D. R., Xiang, Z., Pan, B., & Law, R. (2011). A framework of search engine use for travel planning. Journal of Travel Research, 50(6), 587–601. https://doi.org/10.1177/0047287510385466
  • Filloon, W. (2016, July 19). Bratwurst-cooking robot is a feat of German engineering. https://www.eater.com/2016/7/19/12227128/bratwurst-robot-sausage-cooking-germany
  • Future Travel Experience. (2013, August). Customer service robots becoming a reality for airports and airlines. https://www.futuretravelexperience.com/2013/08/customer- service-robots-becoming-a-reality-for-airports-and-airlines/
  • Gil, D., Hobson, S., Mojsilović, A., Puri, R., & Smith, J. R. (2020). AI for management: An overview. In J. Canals & F. Heukamp (Eds.). The Future of Management in an AI World (pp. 03–19). IESE Business Collection.
  • Giuliani, M., Petrick, R. P. A., Foster, M. E., Gaschler, A., Isard, A., Pateraki, M., & Sigalas, M. (2013, December). Comparing task-based and socially intelligent behaviour in a robot bartender. Paper presented at the ICMI 2013 – 2013 ACM International Conference on Multimodal Interaction (pp. 263–270). http://dx.doi.org/10.1145/2522848.2522869
  • Hilton Worldwide. (2016, March 09). Hilton and IBM pilot “Connie,” The world’s first Watson-enabled hotel concierge. https://newsroom.hilton.com/corporate/news/hilton-and-ibm- pilot-connie-the-worlds-first-watsonenabled-hotel-concierge
  • Hong, W. C., Dong, Y., Chen, L. Y., & Wei, S. Y. (2011). SVR with hybrid chaotic genetic algorithms for tourism demand forecasting. Applied Soft Computing Journal, 11(2), 1881–1890. https://doi.org/10.1016/j.asoc.2010.06.003
  • Hotelmanagement.net. (2016, December 20). Wynn Las Vegas adds Amazon Echo to all guestrooms. https://www.hotelmanagement.net/tech/wynn-las-vegas-adds-amazon- echo-to-all-hotel-rooms
  • Hristova, Y. (2019). Face recognition for the hospitality industry. https://roombre.com/en/blog/hotel-technology/face-recognition-for-the-hospitality-industry.html
  • Hu, W., Singh, R. R. P., & Scalettar, R. T. (2017). Discovering phases, phase transitions, and crossovers through unsupervised machine learning: A critical examination. Physical Review E, 95(6), 062122. https://doi.org/10.1103/PhysRevE.95.062122
  • Huang, T., Chen, C. C., & Schwartz, Z. (2019). Do I book at exactly the right time? Airfare forecast accuracy across three price-prediction platforms. Journal of Revenue and Pricing Management, 18, 281–290. https://doi.org/10.1057/s41272-019-00193-7
  • Hwang, J., & Kim, H. (2019). Consequences of a green image of drone food delivery services: The moderating role of gender and age. Business Strategy and the Environment, 28, 872–884. https://doi.org/10.1002/bse.2289
  • Hwang, J., Cho, S. B., & Kim, W. (2019). Consequences of psychological benefits of using eco-friendly services in the context of drone food delivery services. Journal of Travel and Tourism Marketing, 36(7), 835–846. https://doi.org/10.1080/10548408.2019.1586619
  • Hwang, J., Kim, H., & Kim, W. (2019). Investigating motivated consumer innovativeness in the context of drone food delivery services. Journal of Hospitality and Tourism Management, 38, 102–110. https://doi.org/10.1016/j.jhtm.2019.01.004
  • Hwang, J., Kim, W., & Kim, J. J. (2020). Application of the value-belief-norm model to environmentally friendly drone food delivery services: The moderating role of product involvement. International Journal of Contemporary Hospitality Management, 32(5), 1775-1794. https://doi.org/10.1108/IJCHM-08-2019-0710
  • Hwang, J., Lee, J. S., & Kim, H. (2019). Perceived innovativeness of drone food delivery services and its impacts on attitude and behavioral intentions: The moderating role of gender and age. International Journal of Hospitality Management, 81, 94–103. https://doi.org/10.1016/j.ijhm.2019.03.002
  • International Federation of Robotics [IFR]. (2020, August 24). Topics and Definitions. https://ifr.org/
  • Ivanov, S., & Webster, C. (2017, October 19-21). Adoption of robots, artificial intelligence and service automation by travel, tourism and hospitality companies – a cost-benefit analysis. Paper presented at the International Scientific Conference on Contemporary Tourism – Traditions and Innovations, Sofia University (pp. 1-9). https://ssrn.com/abstract=3007577
  • Ivanov, S., & Webster, C. (2019). Conceptual framework of the use of robots, artificial intelligence and service automation in travel, tourism, and hospitality companies. In S. Ivanov & C. Webster, (Eds.), Robots, Artificial Intelligence, and Service Automation in Travel, Tourism and Hospitality (pp. 7-37). Emerald Publishing Limited.
  • Ivanov, S., & Webster, C. (2020). Robots in tourism: A research agenda for tourism economics. Tourism Economics, 26(7), 1065–1085. https://doi.org/10.1177/1354816619879583
  • Ivanov, S., Webster, C., & Berezina, K. (2017). Adoption of robots and service automation by tourism and hospitality companies. Revista Turismo & Desenvolvimento, 27(28), 1501–1517. https://ssrn.com/abstract=2964308
  • iTranslate. (2020, October 17). iTranslate Translator. https://itranslate.com/apps
  • Joshi, A. V. (2020). Essential Concepts in Artificial Intelligence and Machine Learning. In A. V. Joshi (Ed.). Machine Learning and Artificial Intelligence (pp.9-20). Springer Nature Switzerland.
  • Kaplan, A., & Haenlein, M. (2019). Siri, Siri, in my hand: Who’s the fairest in the land? On the interpretations, illustrations, and implications of artificial intelligence. Business Horizons, 62, 15–25. https://doi.org/10.1016/j.bushor.2018.08.004
  • Kim, M., & Qu, H. (2014). Travelers’ behavioral intention toward hotel self-service kiosks usage. International Journal of Contemporary Hospitality Management, 26(2), 225–245. https://doi.org/10.1108/IJCHM-09-2012-0165
  • Kon, S. C., & Turner, L. W. (2005). Neural network forecasting of tourism demand. Tourism Economics, 11(3), 301–328. https://doi.org/10.5367/000000005774353006
  • 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
  • Law, R. (1998). Room occupancy rate forecasting: A neural network approach. International Journal of Contemporary Hospitality Management, 10(6), 234–239. https://doi.org/10.1108/09596119810232301
  • Law, R. (2000). Back-propagation learning in improving the accuracy of neural network-based tourism demand forecasting. Tourism Management, 21(4), 331–340. https://doi.org/10.1016/S0261-5177(99)00067-9
  • Law, R., & Au, N. (1999). A neural network model to forecast Japanese demand for travel to Hong Kong. Tourism Management, 20, 89–97. https://doi.org/10.1016/S0261- 5177(98)00094-6
  • Law, R., Li, G., Fong, D. K. C., & Han, X. (2019). Tourism demand forecasting: A deep learning approach. Annals of Tourism Research, 75, 410–423. https://doi.org/10.1016/j.annals.2019.01.014
  • Lewis-Kraus, G. (2016, February 03). Check in with the velociraptor at the world’s first robot hotel. https://www.wired.com/2016/03/robot-henn-na-hotel-japan/
  • Li, X., Pan, B., Law, R., & Huang, X. (2017). Forecasting tourism demand with composite search index. Tourism Management, 59, 57–66. https://doi.org/10.1016/j.tourman.2016.07.005
  • Lin, J. (2017). Robots are taking Singapore’s hotel industry by storm – here’s where to go for some robot hospitality. Retrieved June 1, 2020, from https://www.businessinsider.com/robots-are-taking-singapores-hotel-industry-by-storm-heres-where-to-go-for-some-robot-hospitality
  • Lui, K. (2016, November 16). Watch Domino’s pull off the world’s first commercial pizza delivery by drone. https://fortune.com/2016/11/16/dominos-new-zealand-first-commercial- pizza-delivery-drone/
  • Markoff, J. (2014, August 11). ‘Beep,’ says the bellhop. https://www.nytimes.com/2014/08/12/technology/hotel-to-begin-testing-botlr-a-robotic-bellhop.html
  • Marston, J. (2017, December 21). Quick-service restaurants are quickly turning to facial recognition. https://thespoon.tech/quick-service-restaurants-are-quickly-turning-to-facial- recognition/
  • Martin, E. (2018, March 21). Here’s exactly when to buy plane tickets to get the best deals. https://www.cnbc.com/2018/03/21/best-time-to-get-cheap-plane-tickets.html
  • McCarthy, J. (2007, November 12). What is artificial intelligence?. http://jmc.stanford.edu/articles/whatisai/whatisai.pdf
  • McCorduck, P. (2004). Machines who think : A personal inquiry into the history and prospects of artificial intelligence. A K Peters/CRC Press.
  • Melián-González, S., Gutiérrez-Taño, D., & Bulchand-Gidumal, J. (2019). Predicting the intentions to use chatbots for travel and tourism. Current Issues in Tourism. https://doi.org/10.1080/13683500.2019.1706457
  • Microsoft. (2020, October 17). Microsoft Translator. https://translator.microsoft.com/
  • Millward, S. (2015, February 10). Singapore restaurant shows off autonomous drone waiters. https://www.techinasia.com/singapore-restaurant-autonomous-drone-waiters
  • Murphy, J., Hofacker, C., & Gretzel, U. (2017). Dawning of the age of robots in hospitality and tourism: Challenges for teaching and research. European Journal of Tourism Research, 15, 104–111.
  • Neapolitan, R. E., & Jiang, X. (2018). Artificial Intelligence with an Introduction to Machine Learning (Second Ed.). CRC Press Taylor & Francis Group.
  • Nicas, J., & Michaels, D. (2012, August 28). The Self-Service Airport. https://www.wsj.com/articles/SB10000872396390443545504577567501420272414
  • Niculescu, A. I., Jiang, R., Kim, S., Yeo, K. H., D’Haro, L. F., Niswar, A., & Banchs, R. E. (2014, August 27-29). SARA: Singapore’s automated responsive assistant, a multimodal dialogue system for touristic information. Paper presented at the 11th International Conference on Mobile Web and Information Systems, MobiWIS 2014 (pp. 153-164). https://doi.org/10.1007/978-3-319-10359-4_13
  • Oxford Learner’s Dictionaries. (2020, October 16). Drone. https://www.oxfordlearnersdictionaries.com/definition/english/drone_1?q=drone
  • Özen, I. A. (2020). Internet of things in tourism: A proposal of the information system for Cappadocia hot-air ballooning. In E. Çeltek (Ed.). Handbook of Research on Smart Technology Applications in the Tourism Industry (pp. 131-154). IGI Global.
  • Pan, B., & Yang, Y. (2017). Forecasting destination weekly hotel occupancy with big data. Journal of Travel Research, 56(7), 957–970. https://doi.org/10.1177/0047287516669050
  • Park, S. (2020). Multifaceted trust in tourism service robots. Annals of Tourism Research, 81, 102888. https://doi.org/10.1016/j.annals.2020.102888
  • Phaneuf, A. (2020, February 12). 7 real examples of brands and businesses using chatbots to gain an edge. https://www.businessinsider.com/business-chatbot-examples
  • Pinillos, R., Marcos, S., Feliz, R., Zalama, E., & Gómez-García-Bermejo, J. (2016). Long-term assessment of a service robot in a hotel environment. Robotics and Autonomous Systems, 79, 40–57. https://doi.org/10.1016/j.robot.2016.01.014
  • Rajagopal, A. (2019, November 12). Singapore hotels help make a case for facial recognition tech. https://hospitalitytech.com/singapore-hotels-help-make-case-facial- recognition-tech
  • Rasmussen, C. E., & Williams, C. K. I. (2006). Gaussian Processes for Machine Learning. The MIT Press.
  • Revfine. (2020, October 15). 4 ways facial recognition can be used in the travel industry. https://www.revfine.com/facial-recognition-travel-industry/
  • ReviewPro. (2016, September 21). Are robots changing the way that guest experience is measured in the hotel industry?. https://www.reviewpro.com/blog/robots-changing-way- guest-experience-measured-hotel-industry/
  • Ritter, C. (2019). User-based barriers to the adoption of artificial intelligence in healthcare. [Unpublished Doctoral Dissertation]. Department of Business Administration, Capella University.
  • Russel, S., & Norvig, P. (2016). Artificial intelligence—A modern approach (3rd Edition). Pearson Education Limited.
  • Samala, N., Katkam, B. S., Bellamkonda, R. S., & Rodriguez, R. V. (2020). Impact of AI and robotics in the tourism sector: A critical insight. Journal of Tourism Futures. https://doi.org/10.1108/JTF-07-2019-0065
  • Saygin, A. P., Cicekli, I., & Akman, V. (2000). Turing test: 50 years later. Minds and Machines, 10(4), 463–518. https://doi.org/10.1023/A:1011288000451
  • SayHi. (2020, October 17). SayHi. https://www.sayhi.com/tr/translate/
  • Schwab, K. (2016). The Fourth Industrial Revolution. World Economic Forum.
  • Schwahn, L. (2017, October 23). When is the best time to buy airline tickets?. https://www.nerdwallet.com/article/finance/best-time-to-buy-plane-tickets
  • Shamim, S., Cang, S., Yu, H., & Li, Y. (2017). Examining the feasibilities of industry 4.0 for the hospitality sector with the lens of management practice, Energies, 10(4), 1-19. https://doi.org/10.3390/en10040499
  • Sloan, G. (2014, November 01). Robot bartenders? This new cruise ship has them. https://www.freep.com/story/cruiselog/2014/11/01/quantum-robot-bar-cruise/18308319/
  • Stankov, U., Kennell, J., Morrison, A. M., & Vujičić, M. D. (2019). The view from above: The relevance of shared aerial drone videos for destination marketing. Journal of Travel and Tourism Marketing, 36(7), 808–822. https://doi.org/10.1080/10548408.2019.1575787
  • Sushirobo.com. (2020, June 12). Sushi Machines. https://sushirobo.com/
  • Sutton, R. S., & Barto, A. G. (2018). Reinforcement Learning, Second Edition: An Introduction - Complete Draft (Second Ed.). The MIT Press.
  • The International Organization for Standardization [ISO]. (2012). ISO 8373:2012(en) Robots and robotic devices — Vocabulary. https://www.iso.org/obp/ui/#iso:std:iso:8373:ed- 2:v1:en
  • Troitino, C. (2018, June 21). Meet the world’s first fully automated burger robot: Creator debuts the big mac killer. https://www.forbes.com/sites/christinatroitino/2018/06/21/meet- the-worlds-first-fully-automated-burger-robot-creator-debuts-the-big-mac-killer/#1dcfa0a06a89
  • Tsang, W. K., & Benoit, D. F. (2020). Gaussian processes for daily demand prediction in tourism planning. Journal of Forecasting, 39(3), 551–568. https://doi.org/10.1002/for.2644
  • Tsaur, R. C., & Kuo, T. C. (2011). The adaptive fuzzy time series model with an application to Taiwan’s tourism demand. Expert Systems with Applications, 38(8), 9164–9171. https://doi.org/10.1016/j.eswa.2011.01.059
  • Tung, V. W. S., & Au, N. (2018). Exploring customer experiences with robotics in hospitality. International Journal of Contemporary Hospitality Management, 30(7), 2680–2697. https://doi.org/10.1108/IJCHM-06-2017-0322
  • Turing, A. M. (1950). Computing machinery and intelligence-AM Turing. Mind, 59(236), 433–460.
  • Tussyadiah, I. (2020). A review of research into automation in tourism: Launching the annals of tourism research curated collection on artificial intelligence and robotics in tourism. Annals of Tourism Research, 81, 102883. https://doi.org/10.1016/j.annals.2020.102883
  • Tussyadiah, I. P., Zach, F. J., & Wang, J. (2020). Do travelers trust intelligent service robots? Annals of Tourism Research, 81, 102886. https://doi.org/10.1016/j.annals.2020.102886
  • Wang, C. H. (2004). Predicting tourism demand using fuzzy time series and hybrid grey theory. Tourism Management, 25, 367–374. https://doi.org/10.1016/S0261- 5177(03)00132-8
  • Wang, L. (2016). Discovering phase transitions with unsupervised learning. Physical Review B, 94(19), 195105. https://doi.org/10.1103/PhysRevB.94.195105
  • Wolfe, F. (2019, October 10). Facial-recognition tech creates service, security options. https://www.hotelmanagement.net/tech/facial-recognition-tech-creates-service-security- options
  • Wu, L. (2017, December 31). Big burger is watching you, and other ways facial recognition software is entering foodservice. https://www.forbes.com/sites/lesliewu/2017/12/31/big-burger-is-watching-you-and-other-ways-facial-recognition-software-is-entering-foodservice/
  • Yamazaki, K., Yamazaki, A., Okada, M., Kuno, Y., Kobayashi, Y., Hoshi, Y., … Heath, C. (2009, April 04-09). Revealing gauguin: Engaging visitors in robot guide’s explanation in an art museum. Paper presented at the 27th Annual CHI Conference on Human Factors in Computing Systems (pp. 1437-1446).
  • Yang L., Henthorne T.L., & George B. (2020). Artificial intelligence and robotics technology in the hospitality industry: Current applications and future trends. In B. George & J. Paul (Eds.). Digital Transformation in Business and Society (pp. 211-228). Palgrave Macmillan.
  • Yıldız, S. (2019). Turist rehberliği mesleğinde robot rehberlerin yükselişi. Süleyman Demirel Üniversitesi Vizyoner Dergisi, 10(23), 164–177. https://doi.org/10.21076/vizyoner.481225
  • Yotel New York. (2020, June 18). Everything you need, and nothing you don’t. https://www.yotel.com/en/hotels/yotel-new-york/your-stay
  • Zalama, E., García-Bermejo, J. G., Marcos, S., Domínguez, S., Feliz, R., Pinillos, R., & López, J. (2014). Sacarino, a service robot in a hotel environment. In M. Armada, A. Sanfeliu & M. Ferre (Eds.) Robot 2013: First Iberian Robotics Conference (vol. 2) - Advances in Intelligent Systems and Computing (pp. 3–14). Springer. https://doi.org/10.1007/978-3-319-03653-3_1

Turizm ve ağırlama endüstrisinde yapay zekâ ve robotik teknolojiler

Year 2020, , 353 - 380, 30.12.2020
https://doi.org/10.48070/erusosbilder.838193

Abstract

Dünya genelinde hızla yayılan ve yaygın olarak kullanılmaya başlanan yapay zekâ uygulamaları ile robotik teknolojiler konularının literatürde farklı disiplinlerce ele alındığı görülmektedir. Turizm alanı da bu konularda son yıllarda çalışmaların gerçekleştirildiği disiplinlerden biri olarak dikkat çekmektedir. Bu bağlamda, turizm sektörünün uygulama alanlarında robotlar ön plana çıkmaktadır. Ancak turizm sektöründe her geçen gün kullanımı giderek yaygınlaşan veya yaygınlaşma ihtimali olan pek çok yapay zekâ uygulamalarının da olduğu bilinmektedir. Bu noktadan hareketle, kavramsal bir çalışma özelliği taşıyan bu çalışmada literatürden hareketle, öncelikle yapay zekâ uygulamaları ve robotik teknolojiler değerlendirilmiş, bu teknolojilerinin gelişimi ortaya konulmuş, ardından turizm ve ağırlama endüstrisinde kullanılan güncel teknolojiler irdelenmiş ve sonuç olarak bu teknolojilerin turizm ve ağırlama endüstrisindeki geleceği tartışılmıştır. Bu bağlamda, mevcut durumun ortaya konulduğu ve sektör deneyimli yazarların geleceğe dönük çıkarımlarda bulunduğu bu çalışmanın literatüre ve sektör uygulayıcılarına katkılar sağlayabilecek nitelikte önemli bir çalışma olduğu söylenebilir.

References

  • Abadicio, M. (2019, November 22). AI in the travel and tourism industry – Current applications. https://emerj.com/ai-sector-overviews/ai-travel-tourism-industry-current-applications/
  • Abu Shawar, B., & Atwell, E. (2007). Chatbots: Are they really useful?. LDV-Forum, 22(1), 29–49.
  • Alom, M. Z., Taha, T. M., Yakopcic, C., Westberg, S., Sidike, P., Nasrin, M. S., … Asari, V. K. (2019). A state-of-the-art survey on deep learning theory and architectures. Electronics, 8, 292, 1–66. https://doi.org/10.3390/electronics8030292
  • Alpaydin, E. (2014). Introduction to machine learning (Third Ed.). The MIT Press.
  • Ang, B. (2016, February 07). Robot Lucy at your service at newly opened Rong Heng Seafood. https://www.straitstimes.com/lifestyle/food/robot-lucy-at-your-service-at-newly- opened-rong-heng-seafood
  • Assaf, A. G., & Tsionas, M. G. (2019). Forecasting occupancy rate with bayesian compression methods. Annals of Tourism Research, 75, 439–449. https://doi.org/10.1016/j.annals.2018.12.009
  • Barry, C., & Pele, C. (2018, April 02). Meet Italy’s robot concierge. https://www.stuff.co.nz/travel/news/102771691/meet-italys-robot-concierge
  • Berezina, K., Ciftci, O., & Cobanoglu, C. (2019). Robots, Artificial Intelligence, and Service Automation in Restaurants. In S. Ivanov & C. Webster (Eds.), Robots, Artificial Intelligence, and Service Automation in Travel, Tourism and Hospitality (pp. 185–219). Emerald Publishing Limited.
  • Berliner, H. J., & Ebeling, C. (1990). Hitech. In T. A. Marsland & J. Schaeffer (Eds.), Computers, Chess, and Cognition (pp. 79–109). Springer.
  • Buchanan, B., Sutherland, G., & Feigenbaum, E. A. (1969). Heuristic DENDRAL - A program for generating explanatory hypotheses in organic chemistry. In B. Meltzer & D. Michie (Eds.), Machine Intelligence 4 (pp. 209–254). Edinburgh University Press.
  • CAICT. (2018). 2018 world artificial intelligence industry development blue book. http://www.caict.ac.cn/kxyj/qwfb/bps/201809/P020180918696200669434.pdf
  • Chen, H. (2019). Success factors impacting artificial intelligence adoption --- Perspective from the telecom industry in China. [Unpublished Doctoral Dissertation]. Department of Business Administration-Information Technology, Old Dominion University.
  • Chen, K. Y., & Wang, C. H. (2007). Support vector regression with genetic algorithms in forecasting tourism demand. Tourism Management, 8(1), 215–226. https://doi.org/10.1016/j.tourman.2005.12.018
  • Chen, R., Liang, C. Y., Hong, W. C., & Gu, D. X. (2015). Forecasting holiday daily tourist flow based on seasonal support vector regression with adaptive genetic algorithm. Applied Soft Computing Journal, 26, 435–443. https://doi.org/10.1016/j.asoc.2014.10.022
  • Cheong, A., Lau, M. W. S., Foo, E., Hedley, J., & Bo, J. W. (2016). Development of a robotic waiter system. IFAC-PapersOnLine, 49(21), 681–686. https://doi.org/10.1016/j.ifacol.2016.10.679
  • Chestler, D. (2016). The future is now: How robots are storming the travel industry. https://www.siteminder.com/r/trends-advice/hotel-travel-industry-trends/future-robots-storming- travel-industry/
  • CHIP Online. (2018, March 2018). Divan İstanbul’da akıllı otel deneyimi yaşanıyor. https://www.chip.com.tr/haber/divan-istanbulda-akilli-otel-deneyimi-yasaniyor_74904.html
  • Chow, W. S., Shyu, J. C., & Wang, K. C. (1998). Developing a forecast system for hotel occupancy rate using integrated ARIMA models. Journal of International Hospitality, Leisure & Tourism Management, 1(3), 55–80. https://doi.org/10.1300/J268v01n03_05
  • Clarke, R. (2014). Understanding the drone epidemic. Computer Law and Security Review, 30(3), 230–246. https://doi.org/10.1016/j.clsr.2014.03.002
  • Claveria, O., Monte, E., & Torra, S. (2015). Tourism demand forecasting with neural network models: Different ways of treating information. International Journal of Tourism Research, 17, 492–500. https://doi.org/10.1002/jtr.2016
  • CRM Medya Turizm. (2020, November 18). Otelcilik Sektöründe Yapay Zeka Uygulamaları. https://www.crmturizm.com/otelcilik-sektorunde-yapay-zeka-uygulamalari/
  • Crook, J. (2014, August 13). Starwood introduces robotic butlers at aloft hotel in Cupertino. https://techcrunch.com/2014/08/13/starwood-introduces-robotic-butlers-at-aloft-hotel- in-palo-alto/#:~:text=Starwood%2C%20one%20of%20the%20world's,around%20guests%20and%20use%20elevators
  • Davis, L. K. (2016, March 9). Hilton and IBM pilot “Connie,” The world’s first Watson-enabled hotel concierge robot. https://www.ibm.com/blogs/watson/2016/03/watson-connie/
  • Deloitte. (2018). Global artificial intelligence industry whitepaper. https://www2.deloitte.com/cn/en/pages/technology-media-and-telecommunications/articles/global-ai- development-white-paper.html#
  • Donaire, J. A., Galí, N., & Gulisova, B. (2020). Tracking visitors in crowded spaces using zenith images: Drones and time-lapse. Tourism Management Perspectives, 35, 100680. https://doi.org/10.1016/j.tmp.2020.100680
  • Elkins, K. (2015, May 07). This restaurant has a new secret weapon: A robot that slices the perfect noodle faster than any human. https://www.businessinsider.in/This-restaurant- has-a-new-secret-weapon-a-robot-that-slices-the-perfect-noodle-faster-than-any-human/articleshow/47188856.cms
  • Fesenmaier, D. R., Xiang, Z., Pan, B., & Law, R. (2011). A framework of search engine use for travel planning. Journal of Travel Research, 50(6), 587–601. https://doi.org/10.1177/0047287510385466
  • Filloon, W. (2016, July 19). Bratwurst-cooking robot is a feat of German engineering. https://www.eater.com/2016/7/19/12227128/bratwurst-robot-sausage-cooking-germany
  • Future Travel Experience. (2013, August). Customer service robots becoming a reality for airports and airlines. https://www.futuretravelexperience.com/2013/08/customer- service-robots-becoming-a-reality-for-airports-and-airlines/
  • Gil, D., Hobson, S., Mojsilović, A., Puri, R., & Smith, J. R. (2020). AI for management: An overview. In J. Canals & F. Heukamp (Eds.). The Future of Management in an AI World (pp. 03–19). IESE Business Collection.
  • Giuliani, M., Petrick, R. P. A., Foster, M. E., Gaschler, A., Isard, A., Pateraki, M., & Sigalas, M. (2013, December). Comparing task-based and socially intelligent behaviour in a robot bartender. Paper presented at the ICMI 2013 – 2013 ACM International Conference on Multimodal Interaction (pp. 263–270). http://dx.doi.org/10.1145/2522848.2522869
  • Hilton Worldwide. (2016, March 09). Hilton and IBM pilot “Connie,” The world’s first Watson-enabled hotel concierge. https://newsroom.hilton.com/corporate/news/hilton-and-ibm- pilot-connie-the-worlds-first-watsonenabled-hotel-concierge
  • Hong, W. C., Dong, Y., Chen, L. Y., & Wei, S. Y. (2011). SVR with hybrid chaotic genetic algorithms for tourism demand forecasting. Applied Soft Computing Journal, 11(2), 1881–1890. https://doi.org/10.1016/j.asoc.2010.06.003
  • Hotelmanagement.net. (2016, December 20). Wynn Las Vegas adds Amazon Echo to all guestrooms. https://www.hotelmanagement.net/tech/wynn-las-vegas-adds-amazon- echo-to-all-hotel-rooms
  • Hristova, Y. (2019). Face recognition for the hospitality industry. https://roombre.com/en/blog/hotel-technology/face-recognition-for-the-hospitality-industry.html
  • Hu, W., Singh, R. R. P., & Scalettar, R. T. (2017). Discovering phases, phase transitions, and crossovers through unsupervised machine learning: A critical examination. Physical Review E, 95(6), 062122. https://doi.org/10.1103/PhysRevE.95.062122
  • Huang, T., Chen, C. C., & Schwartz, Z. (2019). Do I book at exactly the right time? Airfare forecast accuracy across three price-prediction platforms. Journal of Revenue and Pricing Management, 18, 281–290. https://doi.org/10.1057/s41272-019-00193-7
  • Hwang, J., & Kim, H. (2019). Consequences of a green image of drone food delivery services: The moderating role of gender and age. Business Strategy and the Environment, 28, 872–884. https://doi.org/10.1002/bse.2289
  • Hwang, J., Cho, S. B., & Kim, W. (2019). Consequences of psychological benefits of using eco-friendly services in the context of drone food delivery services. Journal of Travel and Tourism Marketing, 36(7), 835–846. https://doi.org/10.1080/10548408.2019.1586619
  • Hwang, J., Kim, H., & Kim, W. (2019). Investigating motivated consumer innovativeness in the context of drone food delivery services. Journal of Hospitality and Tourism Management, 38, 102–110. https://doi.org/10.1016/j.jhtm.2019.01.004
  • Hwang, J., Kim, W., & Kim, J. J. (2020). Application of the value-belief-norm model to environmentally friendly drone food delivery services: The moderating role of product involvement. International Journal of Contemporary Hospitality Management, 32(5), 1775-1794. https://doi.org/10.1108/IJCHM-08-2019-0710
  • Hwang, J., Lee, J. S., & Kim, H. (2019). Perceived innovativeness of drone food delivery services and its impacts on attitude and behavioral intentions: The moderating role of gender and age. International Journal of Hospitality Management, 81, 94–103. https://doi.org/10.1016/j.ijhm.2019.03.002
  • International Federation of Robotics [IFR]. (2020, August 24). Topics and Definitions. https://ifr.org/
  • Ivanov, S., & Webster, C. (2017, October 19-21). Adoption of robots, artificial intelligence and service automation by travel, tourism and hospitality companies – a cost-benefit analysis. Paper presented at the International Scientific Conference on Contemporary Tourism – Traditions and Innovations, Sofia University (pp. 1-9). https://ssrn.com/abstract=3007577
  • Ivanov, S., & Webster, C. (2019). Conceptual framework of the use of robots, artificial intelligence and service automation in travel, tourism, and hospitality companies. In S. Ivanov & C. Webster, (Eds.), Robots, Artificial Intelligence, and Service Automation in Travel, Tourism and Hospitality (pp. 7-37). Emerald Publishing Limited.
  • Ivanov, S., & Webster, C. (2020). Robots in tourism: A research agenda for tourism economics. Tourism Economics, 26(7), 1065–1085. https://doi.org/10.1177/1354816619879583
  • Ivanov, S., Webster, C., & Berezina, K. (2017). Adoption of robots and service automation by tourism and hospitality companies. Revista Turismo & Desenvolvimento, 27(28), 1501–1517. https://ssrn.com/abstract=2964308
  • iTranslate. (2020, October 17). iTranslate Translator. https://itranslate.com/apps
  • Joshi, A. V. (2020). Essential Concepts in Artificial Intelligence and Machine Learning. In A. V. Joshi (Ed.). Machine Learning and Artificial Intelligence (pp.9-20). Springer Nature Switzerland.
  • Kaplan, A., & Haenlein, M. (2019). Siri, Siri, in my hand: Who’s the fairest in the land? On the interpretations, illustrations, and implications of artificial intelligence. Business Horizons, 62, 15–25. https://doi.org/10.1016/j.bushor.2018.08.004
  • Kim, M., & Qu, H. (2014). Travelers’ behavioral intention toward hotel self-service kiosks usage. International Journal of Contemporary Hospitality Management, 26(2), 225–245. https://doi.org/10.1108/IJCHM-09-2012-0165
  • Kon, S. C., & Turner, L. W. (2005). Neural network forecasting of tourism demand. Tourism Economics, 11(3), 301–328. https://doi.org/10.5367/000000005774353006
  • 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
  • Law, R. (1998). Room occupancy rate forecasting: A neural network approach. International Journal of Contemporary Hospitality Management, 10(6), 234–239. https://doi.org/10.1108/09596119810232301
  • Law, R. (2000). Back-propagation learning in improving the accuracy of neural network-based tourism demand forecasting. Tourism Management, 21(4), 331–340. https://doi.org/10.1016/S0261-5177(99)00067-9
  • Law, R., & Au, N. (1999). A neural network model to forecast Japanese demand for travel to Hong Kong. Tourism Management, 20, 89–97. https://doi.org/10.1016/S0261- 5177(98)00094-6
  • Law, R., Li, G., Fong, D. K. C., & Han, X. (2019). Tourism demand forecasting: A deep learning approach. Annals of Tourism Research, 75, 410–423. https://doi.org/10.1016/j.annals.2019.01.014
  • Lewis-Kraus, G. (2016, February 03). Check in with the velociraptor at the world’s first robot hotel. https://www.wired.com/2016/03/robot-henn-na-hotel-japan/
  • Li, X., Pan, B., Law, R., & Huang, X. (2017). Forecasting tourism demand with composite search index. Tourism Management, 59, 57–66. https://doi.org/10.1016/j.tourman.2016.07.005
  • Lin, J. (2017). Robots are taking Singapore’s hotel industry by storm – here’s where to go for some robot hospitality. Retrieved June 1, 2020, from https://www.businessinsider.com/robots-are-taking-singapores-hotel-industry-by-storm-heres-where-to-go-for-some-robot-hospitality
  • Lui, K. (2016, November 16). Watch Domino’s pull off the world’s first commercial pizza delivery by drone. https://fortune.com/2016/11/16/dominos-new-zealand-first-commercial- pizza-delivery-drone/
  • Markoff, J. (2014, August 11). ‘Beep,’ says the bellhop. https://www.nytimes.com/2014/08/12/technology/hotel-to-begin-testing-botlr-a-robotic-bellhop.html
  • Marston, J. (2017, December 21). Quick-service restaurants are quickly turning to facial recognition. https://thespoon.tech/quick-service-restaurants-are-quickly-turning-to-facial- recognition/
  • Martin, E. (2018, March 21). Here’s exactly when to buy plane tickets to get the best deals. https://www.cnbc.com/2018/03/21/best-time-to-get-cheap-plane-tickets.html
  • McCarthy, J. (2007, November 12). What is artificial intelligence?. http://jmc.stanford.edu/articles/whatisai/whatisai.pdf
  • McCorduck, P. (2004). Machines who think : A personal inquiry into the history and prospects of artificial intelligence. A K Peters/CRC Press.
  • Melián-González, S., Gutiérrez-Taño, D., & Bulchand-Gidumal, J. (2019). Predicting the intentions to use chatbots for travel and tourism. Current Issues in Tourism. https://doi.org/10.1080/13683500.2019.1706457
  • Microsoft. (2020, October 17). Microsoft Translator. https://translator.microsoft.com/
  • Millward, S. (2015, February 10). Singapore restaurant shows off autonomous drone waiters. https://www.techinasia.com/singapore-restaurant-autonomous-drone-waiters
  • Murphy, J., Hofacker, C., & Gretzel, U. (2017). Dawning of the age of robots in hospitality and tourism: Challenges for teaching and research. European Journal of Tourism Research, 15, 104–111.
  • Neapolitan, R. E., & Jiang, X. (2018). Artificial Intelligence with an Introduction to Machine Learning (Second Ed.). CRC Press Taylor & Francis Group.
  • Nicas, J., & Michaels, D. (2012, August 28). The Self-Service Airport. https://www.wsj.com/articles/SB10000872396390443545504577567501420272414
  • Niculescu, A. I., Jiang, R., Kim, S., Yeo, K. H., D’Haro, L. F., Niswar, A., & Banchs, R. E. (2014, August 27-29). SARA: Singapore’s automated responsive assistant, a multimodal dialogue system for touristic information. Paper presented at the 11th International Conference on Mobile Web and Information Systems, MobiWIS 2014 (pp. 153-164). https://doi.org/10.1007/978-3-319-10359-4_13
  • Oxford Learner’s Dictionaries. (2020, October 16). Drone. https://www.oxfordlearnersdictionaries.com/definition/english/drone_1?q=drone
  • Özen, I. A. (2020). Internet of things in tourism: A proposal of the information system for Cappadocia hot-air ballooning. In E. Çeltek (Ed.). Handbook of Research on Smart Technology Applications in the Tourism Industry (pp. 131-154). IGI Global.
  • Pan, B., & Yang, Y. (2017). Forecasting destination weekly hotel occupancy with big data. Journal of Travel Research, 56(7), 957–970. https://doi.org/10.1177/0047287516669050
  • Park, S. (2020). Multifaceted trust in tourism service robots. Annals of Tourism Research, 81, 102888. https://doi.org/10.1016/j.annals.2020.102888
  • Phaneuf, A. (2020, February 12). 7 real examples of brands and businesses using chatbots to gain an edge. https://www.businessinsider.com/business-chatbot-examples
  • Pinillos, R., Marcos, S., Feliz, R., Zalama, E., & Gómez-García-Bermejo, J. (2016). Long-term assessment of a service robot in a hotel environment. Robotics and Autonomous Systems, 79, 40–57. https://doi.org/10.1016/j.robot.2016.01.014
  • Rajagopal, A. (2019, November 12). Singapore hotels help make a case for facial recognition tech. https://hospitalitytech.com/singapore-hotels-help-make-case-facial- recognition-tech
  • Rasmussen, C. E., & Williams, C. K. I. (2006). Gaussian Processes for Machine Learning. The MIT Press.
  • Revfine. (2020, October 15). 4 ways facial recognition can be used in the travel industry. https://www.revfine.com/facial-recognition-travel-industry/
  • ReviewPro. (2016, September 21). Are robots changing the way that guest experience is measured in the hotel industry?. https://www.reviewpro.com/blog/robots-changing-way- guest-experience-measured-hotel-industry/
  • Ritter, C. (2019). User-based barriers to the adoption of artificial intelligence in healthcare. [Unpublished Doctoral Dissertation]. Department of Business Administration, Capella University.
  • Russel, S., & Norvig, P. (2016). Artificial intelligence—A modern approach (3rd Edition). Pearson Education Limited.
  • Samala, N., Katkam, B. S., Bellamkonda, R. S., & Rodriguez, R. V. (2020). Impact of AI and robotics in the tourism sector: A critical insight. Journal of Tourism Futures. https://doi.org/10.1108/JTF-07-2019-0065
  • Saygin, A. P., Cicekli, I., & Akman, V. (2000). Turing test: 50 years later. Minds and Machines, 10(4), 463–518. https://doi.org/10.1023/A:1011288000451
  • SayHi. (2020, October 17). SayHi. https://www.sayhi.com/tr/translate/
  • Schwab, K. (2016). The Fourth Industrial Revolution. World Economic Forum.
  • Schwahn, L. (2017, October 23). When is the best time to buy airline tickets?. https://www.nerdwallet.com/article/finance/best-time-to-buy-plane-tickets
  • Shamim, S., Cang, S., Yu, H., & Li, Y. (2017). Examining the feasibilities of industry 4.0 for the hospitality sector with the lens of management practice, Energies, 10(4), 1-19. https://doi.org/10.3390/en10040499
  • Sloan, G. (2014, November 01). Robot bartenders? This new cruise ship has them. https://www.freep.com/story/cruiselog/2014/11/01/quantum-robot-bar-cruise/18308319/
  • Stankov, U., Kennell, J., Morrison, A. M., & Vujičić, M. D. (2019). The view from above: The relevance of shared aerial drone videos for destination marketing. Journal of Travel and Tourism Marketing, 36(7), 808–822. https://doi.org/10.1080/10548408.2019.1575787
  • Sushirobo.com. (2020, June 12). Sushi Machines. https://sushirobo.com/
  • Sutton, R. S., & Barto, A. G. (2018). Reinforcement Learning, Second Edition: An Introduction - Complete Draft (Second Ed.). The MIT Press.
  • The International Organization for Standardization [ISO]. (2012). ISO 8373:2012(en) Robots and robotic devices — Vocabulary. https://www.iso.org/obp/ui/#iso:std:iso:8373:ed- 2:v1:en
  • Troitino, C. (2018, June 21). Meet the world’s first fully automated burger robot: Creator debuts the big mac killer. https://www.forbes.com/sites/christinatroitino/2018/06/21/meet- the-worlds-first-fully-automated-burger-robot-creator-debuts-the-big-mac-killer/#1dcfa0a06a89
  • Tsang, W. K., & Benoit, D. F. (2020). Gaussian processes for daily demand prediction in tourism planning. Journal of Forecasting, 39(3), 551–568. https://doi.org/10.1002/for.2644
  • Tsaur, R. C., & Kuo, T. C. (2011). The adaptive fuzzy time series model with an application to Taiwan’s tourism demand. Expert Systems with Applications, 38(8), 9164–9171. https://doi.org/10.1016/j.eswa.2011.01.059
  • Tung, V. W. S., & Au, N. (2018). Exploring customer experiences with robotics in hospitality. International Journal of Contemporary Hospitality Management, 30(7), 2680–2697. https://doi.org/10.1108/IJCHM-06-2017-0322
  • Turing, A. M. (1950). Computing machinery and intelligence-AM Turing. Mind, 59(236), 433–460.
  • Tussyadiah, I. (2020). A review of research into automation in tourism: Launching the annals of tourism research curated collection on artificial intelligence and robotics in tourism. Annals of Tourism Research, 81, 102883. https://doi.org/10.1016/j.annals.2020.102883
  • Tussyadiah, I. P., Zach, F. J., & Wang, J. (2020). Do travelers trust intelligent service robots? Annals of Tourism Research, 81, 102886. https://doi.org/10.1016/j.annals.2020.102886
  • Wang, C. H. (2004). Predicting tourism demand using fuzzy time series and hybrid grey theory. Tourism Management, 25, 367–374. https://doi.org/10.1016/S0261- 5177(03)00132-8
  • Wang, L. (2016). Discovering phase transitions with unsupervised learning. Physical Review B, 94(19), 195105. https://doi.org/10.1103/PhysRevB.94.195105
  • Wolfe, F. (2019, October 10). Facial-recognition tech creates service, security options. https://www.hotelmanagement.net/tech/facial-recognition-tech-creates-service-security- options
  • Wu, L. (2017, December 31). Big burger is watching you, and other ways facial recognition software is entering foodservice. https://www.forbes.com/sites/lesliewu/2017/12/31/big-burger-is-watching-you-and-other-ways-facial-recognition-software-is-entering-foodservice/
  • Yamazaki, K., Yamazaki, A., Okada, M., Kuno, Y., Kobayashi, Y., Hoshi, Y., … Heath, C. (2009, April 04-09). Revealing gauguin: Engaging visitors in robot guide’s explanation in an art museum. Paper presented at the 27th Annual CHI Conference on Human Factors in Computing Systems (pp. 1437-1446).
  • Yang L., Henthorne T.L., & George B. (2020). Artificial intelligence and robotics technology in the hospitality industry: Current applications and future trends. In B. George & J. Paul (Eds.). Digital Transformation in Business and Society (pp. 211-228). Palgrave Macmillan.
  • Yıldız, S. (2019). Turist rehberliği mesleğinde robot rehberlerin yükselişi. Süleyman Demirel Üniversitesi Vizyoner Dergisi, 10(23), 164–177. https://doi.org/10.21076/vizyoner.481225
  • Yotel New York. (2020, June 18). Everything you need, and nothing you don’t. https://www.yotel.com/en/hotels/yotel-new-york/your-stay
  • Zalama, E., García-Bermejo, J. G., Marcos, S., Domínguez, S., Feliz, R., Pinillos, R., & López, J. (2014). Sacarino, a service robot in a hotel environment. In M. Armada, A. Sanfeliu & M. Ferre (Eds.) Robot 2013: First Iberian Robotics Conference (vol. 2) - Advances in Intelligent Systems and Computing (pp. 3–14). Springer. https://doi.org/10.1007/978-3-319-03653-3_1
There are 112 citations in total.

Details

Primary Language English
Subjects Business Administration
Journal Section Makaleler / Articles
Authors

Reha Kılıçhan 0000-0003-2570-5771

Mustafa Yılmaz 0000-0003-3255-3788

Publication Date December 30, 2020
Submission Date December 9, 2020
Acceptance Date December 18, 2020
Published in Issue Year 2020

Cite

APA Kılıçhan, R., & Yılmaz, M. (2020). Artificial intelligence and robotic technologies in tourism and hospitality industry. Erciyes Üniversitesi Sosyal Bilimler Enstitüsü Dergisi(50), 353-380. https://doi.org/10.48070/erusosbilder.838193

ERCİYES AKADEMİ | 2021 | sbedergi@erciyes.edu.tr Bu eser Creative Commons Atıf-Gayri Ticari-Türetilemez 4.0 Uluslararası Lisansı ile lisanslanmıştır.