Progressive technological advancement of Artificial Intelligence (AI) such as Chatbots is changing the frontline services within the hospitality and tourism industry. Known as an automated program that mimics human interaction both via chat or voice assistant with the customers, chatbots can be found in numerous service-based websites and mobile apps including Online Travel Agency (OTA). User experience is a critical factor in the success of chatbots for customer service. Despite the growing number of hospitality and tourism firms adopting chatbots to deliver customer care, little attention has been paid towards chatbot users’ reactions, particularly from the OTA standpoint. Underpinning the technology acceptance model (TAM), this paper proposed an examination of OTA chatbots’ antecedents covering perceived ease of use (PEOU), perceived playfulness (PP) and perceived usefulness (PU); towards users’ experience and satisfaction. The outcome of this study would bring valuable insights to both academicians and practitioners as more and more hospitality and tourism services are evolving rapidly within the digital business environment.
Abbas, A. (2019). Chatbot 2019 Trends and Stats with Insider Reports. Medium. Retrieved June 12, 2022, from https://chatbotslife.com/chatbot-2019- trends-and-stats-with-insider-reports-fb71697deee4.
Azjen, I., Fishben, M. (1980). Understanding attitudes and predicting social behaviour. Englewood Cliffs, NJ: Prentice-Hall.
Ambawat, M., & Wadera, D. (2019). A review of chatbots adoption from the consumer’s perspectives. Journal of the Gujarat Research Society, 21(11), 11.
Araujo, T. (2018). Living up to the chatbot hype: The influence of anthropomorphic designcues and communicative agency framing on conversational agent and company perceptions. Computers in Human Behavior, 85, 183-189.
Bhattacherjee, A. (2001). Understanding information systems continuance: an expectation-confirmation model. MIS quarterly, 351-370.
Bilgihan, A., Kandampully, J., & Zhang, T. (2016), ‘Towards a unified customer experience in online shopping environments: Antecedents and outcomes’, International Journal of Quality and Service Sciences 8(1), 102–119. https://doi.org/10.1108/IJQSS-07- 2015-0054
Bowen, J., & Morosan, C. (2018). Beware hospitality industry: the robots are coming. Worldwide Hospitality and Tourism Themes, 10 (6), 726-733.
Brill, T. M., Munoz, L., & Miller, R. J. (2019). Siri, Alexa, and other digital assistants: astudy of customer satisfaction with artificial intelligence applications. Journal of Marketing Management. https://doi.org/10.1080/0267257X.2019.1687571.
Chan, W. T. Y., & Leung, C. H. (2021). Mind the Gap: Discrepancy Between Customer Expectation and Perception on Commercial Chatbots Usage. Asian Journal of Empirical Research, 11(1), 1-10.
Chang, Y.-W., Hsu, P.-Y., & Yang, Q.-M. (2018). Integration of online and offline channels: a view of O2O commerce. Internet Research, 28(4), 926–945. doi:10.1108/intr-01-2017-002.
Chen, H.-L., Widarso, G.V. & Sutrisno, H., 2020, 'A chatBot for learning Chinese: Learning achievement andtechnologyacceptance', JournalofEducationalComputingResearch 58(6),11611189. https://doi.org/10.1177/0735633120929622 .
Chung, M.-J., Ko, E.-J., Joung, H.-R., & Kim, S.-J. (2018). Chatbot e-service and customer satisfaction regarding luxury brands. Journal of Business Research, 117, 587–595. https://doi.org/10.1016/j.jbusres.2018.10.004
Ciechanowski, L., Przegalinska, A., Magnuski, M., & Gloor, P. (2019). In the shades of theuncanny valley: An experimental study of human–chatbot interaction. Future Generation Computer Systems, 92, 539-548.
Davis, F. D. (1989), ‘Perceived usefulness, perceived ease of use, and user acceptance of information technology’, MIS Quarterly 13(3), 319–340.
https://doi.org/10.2307/249008
De Haan, H., Snijder, J., Van Nimwegen, C., & Beun, R. J. (2018), 'Chatbot personality and customer satisfaction', Bachelor thesis, Utrecht University, viewed 06 April 2019, from https://www.scribd.com/document/472909794/Chatbot-Personality-and-Customer-Satisfaction-Bachelor-Thesis-Information-Sciences-Hayco-de-Haan
Diaz, J. A. (2019), 'How to improve your customer experience using chatbots', We are marketing, viewed 06 May 2019, from https://www.wearemarketing.com/blog/.
Djelassi, S., Diallo, M. F.m & Zielke, S. (2018), ‘How self-service technology experience evaluation affects waiting time and customer satisfaction? A moderated mediation model’, Decision Support Systems 111, 38–47. https://doi.org/10.1016/j.dss.
Feine, J., Morana, S., & Gnewuch, U. (2019). Measuring service encounter satisfaction with customer service chatbots using sentiment analysis.
Folstad, A., Araujo, T., Papadopoulos, S., Law, E. L.-C., Luger, E., Goodwin, M., & Brandtzaeg, P. B. (Eds.). (2021). Chatbot Research and Design. Lecture Notes inComputer Science. doi:10.1007/978-3-030-68288-0
Folstad, A., Nordheim, C. B., & Bjorkli, C. A. (2018). What makes users trust a chatbot for customer service? An exploratory interview study. In International conference on internet science (pp. 194-208). Springer, Cham.
Global Hospitality Portal. (n.d.). Hotel industry analysis and market statistics | Global Hospitality Portal. Retrieved May 25, 2019, from https://www.soegjobs.com/hotel- industry-analysis-market-statistics/
Gretzel, U., Fesenmaier, D. R., & O’Leary, J. T. (2006). The transformation of consumer behaviour. In Tourism business frontiers (pp. 9-18). Routledge.
Gumus, N., & Cark, O. (2021). The Effect of Customers’ Attitudes Towards Chatbots on their Experience and Behavioural Intention in Turkey. Interdisciplinary Description of Complex Systems: INDECS,19(3), 420-436.
Haung, T.-L., & Liao, S. (2015), ‘A model of acceptance of augmented-reality interactive technology: The moderating role of cognitive innovativeness’, Electronic CommerceResearch 15(2), 269–295. https://doi.org/10.1007/s10660-014-9163-2
Huang, D. H., & Chueh, H. E. (2020). An analysis of use intention of pet disease consultation chatbot. In 2020 The 4th International Conference on E- Society, E- Education and E-Technology (pp. 1-5).
Huang, D. H., & Chueh, H. E. (2021). Chatbot usage intention analysis: Veterinary consultation. Journal of Innovation & Knowledge, 6(3), 135-144.
Hermawan, D. (2022). The effects of web quality, perceived benefits, security and data privacy on behavioral intention and e-WOM of online travel agencies. International Journal of Data and Network Science, 6(3), 1005-1012.
Holzwarth, M., Janiszewski, C., & Neumann, M. M. (2006). The influence of avatars on online consumer shopping behavior. Journal of marketing, 70(4), 19-36.
Irgashevich, S. T., Odilovich, O. A., & Mamadaliyevich, G. E. (2022). Internet Technologies In The Tourism Industry. Web of Scientist: International Scientific Research Journal, 3(9), 57-64.
Jain, M., Kumar, P., Kota, R., & Patel, S. N. (2018). ‘Evaluation and informing the design of chatbots’, Session 18: Interacting with Conversational Agents of the DIS (Designing Interactive Systems) 2018 conference, June 9–13, 2018, Hong Kong,pp. 895–906.
Jasni, W. N. F. W., Jamaluddin, M. R., & Hanafiah, M. H. (2020). Online travel agencies (OTAs) e-service quality, brand image, customer satisfaction and loyalty. Journal of Tourism, Hospitality & Culinary Arts, 12 (2), 96-111.
Junnonyang, E. (2021). Integrating TAM, perceived risk, trust, relative advantage, government support, social influence and user satisfaction as predictors of mobile government adoption behavior in Thailand. International Journal of eBusiness and eGovernment Studies, 13(1), 159-178.
Komalasari, F. P., & Budiman, S. F. (2018). Customer Retention Strategy Through Customer Satisfaction and Customer Loyalty: The Study on Traveloka Loyalty Program. TRJ (Tourism Research Journal), 2(1), 69-75.
Kourtesopoulou, A., Theodorou, S. D., Kriemadis, A., & Papaioannou, A. (2019). The impact of online travel agencies web service quality on customer satisfaction and purchase intentions. In Smart Tourism as a Driver for Culture and Sustainability (pp. 343-356). Springer, Cham.
Kvale, K., Sell, O. A., Hodnebrog, S., & Folstad, A. (2019). Improving conversations: lessons learnt from manual analysis of chatbot dialogues. In International workshop on chatbot research and design (pp. 187-200). Springer, Cham.
Letheren, K., Russell-Bennett, R., & Whittaker, L. (2020). Black, white or grey magic? Ourfuture with artificial intelligence. Journal of Marketing Management, 36(3- 4), 216- 232.
Li, L., Lee, K. Y., Emokpae, E., & Yang, S. B. (2021). What makes you continuously use chatbot services? Evidence from chinese online travel agencies. Electronic Markets,31(3), 575-599.
Lubbe, I., & Ngoma, N. (2021). Useful chatbot experience provides technological satisfaction: An emerging market perspective. South African Journal of Information Management, 23(1), 1-8.
Luo, X., Tong, S., Fang, Z., & Qu, Z. (2019). Frontiers: Machines vs. humans: The impact of artificial intelligence chatbot disclosure on customer purchases. Marketing Science, 38(6), 937-947.
Lv, X., Li, N., Xu, X., & Yang, Y. (2020). Understanding the emergence and developmentof online travel agencies: a dynamic evaluation and simulation approach. Internet Research, ahead-of-print(ahead-of-print). doi:10.1108/intr- 11-2019-0464
Miguel, O. M., & Huertas, A. (2022). Technological Attributes that Predict Tourists’ Intention to Visit Destination, Recommend and Destination Image: Empirical Evidence from the Malaga Chatbot. In Advances in Tourism, Technology and Systems (pp. 155-166). Springer, Singapore.
Min, S. R., & Lee, S. M. (2020). A study on the behavior of the user according to the distribution development of online travel agency. The Journal of Distribution Science, 18(6), 25-35.f
Mkpojiogu, E. O., & Hashim, N. L. (2016). Understanding the relationship between Kano model’s customer satisfaction scores and self-stated requirements importance. SpringerPlus, 5(1), 1-22.
Moon, J. W., & Kim, Y. G. (2001), ‘Extending the TAM for the world-wide-web context’, Information and Management 38(4), 217–230. https://doi.org/10.1016/S0378-7206(00)00061-6.
Mouhcine, H. B. (2021). The Role of User Satisfaction in Continuance Intention to Use Chatbots within the Technology Acceptance Model (TAM) (Doctoral dissertation,Marmara Universitesi (Turkey)).
Nica, I., Tazl, O. A., & Wotawa, F. (2018). Chatbot-based tourist recommendations usingmodel-based reasoning. In Proceedings of the20th International Workshop on Configuration, Graz, Austria, 25–30.
Nguyen, Q. N., Sidorova, A., & Torres, R. (2022). User interactions with chatbot interfaces vs. Menu-based interfaces: An empirical study. Computers in Human Behavior, 128, 107093.
Park, S., Yin, Y., & Son, B. G. (2019). Understanding of online hotel booking process: A multiple method approach. Journal of Vacation Marketing, 25(3), 334-348
Pillai, R., & Sivathanu, B. (2020). Adoption of AI-based chatbots for hospitality and tourism. International Journal of Contemporary Hospitality Management.
Rafique, H., Almagrabi, A. O., Shamim, A., Anwar, F., & Bashir, A. K. (2020). Investigating the acceptance of mobile library applications with an extended technology acceptance model (TAM). Computers & Education, 145, 103732.
Ray, A., & Bala, P. K. (2021). User generated content for exploring factors affecting intention to use travel and food delivery services. International Journal of Hospitality Management, 92, 102730.
Rezgo. (2019). What is an OTA (online Travel Agency)? Tour & Activity Industry Terms.Retrieved May 25, 2019, from https://www.rezgo.com/glossary/ota.
Roscoe, J. T. (1975) Fundamental Research Statistics for the Behavioral Science, International Series in Decision Process, 2nd Edition, Holt, Rinehart and Winston, Inc., New York.
Shen, Y. (2018). How to Improve Customer Loyalty to Online Travel Agencies: A research on Expedia, an online travel booking platform.
Sidaoui, K., Jaakkola, M., & Burton, J. (2020). AI feel you: customer experience assessment via chatbot interviews. Journal of Service Management, ahead-of- print(ahead-of-print). doi:10.1108/josm-11-2019-0341.
Talwar, S., Dhir, A., Kaur, P., & Mantymaki, M. (2020). Why do people purchase from online travel agencies (OTAs)? A consumption values perspective. International Journal of Hospitality Management, 88, 102534.
Tussyadiah, I. P., Zach, F. J., & Wang, J. (2020). Do travelers trust intelligent service robots? Annals of Tourism Research, 81, 102886.
Tuzovic, S., & Paluch, S. (2018). Conversational commerce–a new era for service businessdevelopment? In Service business development (pp. 81-100). Springer Gabler, Wiesbaden.
Ukpabi, D. C., Aslam, B., & Karjaluoto, H. (2019). Chatbot adoption in tourism services: A conceptual exploration. In Robots, artificial intelligence, and service automation in travel, tourism and hospitality. Emerald Publishing Limited.
Waldmann, A. (2021). User satisfaction and trust in chatbots: testing the chatbot usability scale and the relationship of trust and satisfaction in the interaction with chatbots (Bachelor's thesis, University of Twente).
Wang, C., Harris, J., & Patterson, P. (2013), ‘The roles of habit, self-efficacy, and satisfactionin driving continued use of self-service technologies: A longitudinal study’, Journal of Service Research 16(3), 400–414. https://doi.org/10.1177/1094670512473200.
Zeithaml, V. A. (2013). Services marketing: Integrating customer focus across the firm.