The Intention To Use Chatbot For Hospitality And Tourism In Algeria

Oum Elkheir MALKI; Abderrahim CHENINI

doi:10.34174/jevrre28

Authors

Oum Elkheir MALKI Ghardaia University, Algeria
Abderrahim CHENINI Ghardaia University, Algeria

DOI:

https://doi.org/10.34174/jevrre28

Keywords:

chatbot, intention, attitude, hospitality, TAM

Abstract

The hospitality sector is trying to take advantage of modern technologies. Chatbots are one of these technologies that hospitality organizations seek to use,

However, the intention of customers to deal with it and use it are still the subject of many studies.

Through this study, we try to explain the intention to use chatbot using the technology acceptance model, the hypotheses have been tested through structural equations with PLS.

The study was conducted on a sample of 75 individuals students of computer science at the University of Laghouat, Algeria, who has prior knowledge of chatbots.

The study concluded that the attitudes towards a chatbots are greatly affected by the perceived usefulness and that the intentions to use chatbots are affected by the attitudes directly and the perceived usefulness indirectly, and there is no significant effect of ease of use on the attitudes and the intention to use indirectly.

Downloads

Download data is not yet available.

Author Biographies

Oum Elkheir MALKI, Ghardaia University, Algeria

Lab Quantitative and qualitative applications for the economic, social and environmental promotion of Algerian companies
Abderrahim CHENINI, Ghardaia University, Algeria

Lab Quantitative and qualitative applications for the economic, social and environmental promotion of Algerian companies

References

[1]. Adamopoulou, E., & Moussiades, L. (2020). Chatbots: History, technology, and applications. machine learning with applications , 02.

[2]. Ajibade, p. (2018). Technology Acceptance Model Limitations and Criticisms: Exploring the Practical Applications and Use in Technology-related Studies, Mixed-method, and Qualitative Researches. Library Philosophy and Practice , 09.

[3]. Amalia, a., & Suprayogi, m. (2019, Octobre). Amalia, A., & Suprayogi, M. (2019, October). Engaging millennials on using chatbot messenger for eco-tourism. Third international conference on sustainable innovation , 484-487.

[4]. Bulchand-Gidumal, j. (2022). Impact of Artiﬁcial Intelligence in Travel, Tourism, and Hospitality. Cham:springer international publishing.

[5]. Calvaresi, d., & al, e. (2021). The Evolution of Chatbots in Tourism: A Systematic Literature Review. Proceedings of the ENTER 2021 eTourism Conference (pp. 19-22). Springer International Publishing.

[6]. Chi, o. h., Gursoy, d., & Chi, c. g. (2022). Tourists’ attitudes toward the use of artificially intelligent (AI) devices in tourism service delivery: moderating role of service value seeking. Journal of Travel Research , 61 (01), 170-185.

[7]. Dash, m., & Bakshi, s. (2019). An Exploratory Study of Customer Perceptions of Usage of Chatbots in the Hospitality Industry. International Journal on Customer Relations , 07 (02), 27-33.

[8]. Davis, f. d., Bagozzi, r. p., & Warshaw, p. r. (1989). User acceptance of computer technology: A comparison of two theoretical models. Management science , 35 (08), 982-1003.

[9]. Flandrin, p., & al, e. (2021). Smart technologies in hospitality: effects on activity, work design and employment. A case study about chatbot usage. Proceedings of the 17th “Ergonomie et Informatique Avancée” Conference, (pp. 1-11).

[10]. Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of marketing research , 18 (01), 39-50.

[11]. Gaafar, h. a. (2020). Artificial Intelligence in Egyptian Tourism Companies: Implementation and Perception. Journal of Association of Arab Universities for Tourism and Hospitality , 18 (01), 66-78.

[12]. Hair, J. F., & al, e. (2019). When to use and how to report the results of PLS-SEM. European business review , 31 (1), 2-24.

[13]. Hassan, r., Koles, b., Zaman, m., & Paul, j. (2021). The potential of chatbots in travel and tourism services in the context of social distancing. International Journal of Technology Intelligence and Planning , 13 (01), 63-83.

[14]. Huang, y.-c., Lan lan, c., Chia-Pin, y., & Joseph, c. (2019). Examining an extended technology acceptance model with experience construct on hotel consumers adoption of mobile applications. Journal of Hospitality Marketing & Management , 28 (08), 957-980.

[15]. Ivanov, s., & Webster, c. (2017). Adoption of robots and service automation by tourism and hospitality companies. Revista Turismo & Desenvolvimento , 27 (28), 1501-1517.

[16]. Ivanov, s., & Webster, c. (2019). Economic fundamentals of the use of robots, artificial intelligence, and service automation in travel, tourism, and hospitality. In Robots, artificial intelligence, and service automation in travel, tourism and hospitality (pp. 39-55). Emerald publishing limited.

[17]. Ivanov, s., & Webstr, c. (2019). Conceptual framework of the use of robots, artificial intelligence and service automation in travel, tourism, and hospitality companies. In Robots, artificial intelligence, and service automation in travel, tourism and hospitality (pp. 7-37). Emerald Publishing Limited.

[18]. Jamsek, S., & Culiberg, B. (2020). Introducing a three‐tier sustainability framework to examine bike‐sharing system use: An extension of the technology acceptance model. International Journal of Consumer Studies , 44 (02), 140-150.

[19]. Ju, X., Martin Martin, O., & Chocarro, R. (2022). Determinants of mobile social media use, customer heterogeneity, and international microsegmentation. International Journal of Consumer Studies , 46 (4), 1127-1148.

[20]. Jung, timothy. (2014). A PLS Analysis of hotel guests’ acceptance of social media networks. 12 th APacCHRIE Conference. kuala lampur.

[21]. Kaushik, a., & al, e. (2015). Tourist behaviour towards self-service hotel technology adoption: Trust and subjective norm as key antecedents. Tourism Management Perspectives , 16, 278-289.

[22]. Kim, t. g., Lee, j. h., & Law, r. (2008). An empirical examination of the acceptance behaviour of hotel front office systems: An extended technology acceptance model. Tourism management , 29 (03), 500-513.

[23]. Kong, f., & al, e. (2021). Technology acceptance model of mobile social media among Chinese college students. Journal of Technology in Behavioral Science , 06, 365-369.

[24]. Kotler, p., & al, e. (2021). Marketing 5.0: Technology for humanity. John Wiley & Sons.

[25]. Lasek, m., & Jessa, s. (2013). CHATBOTS FOR CUSTOMER SERVICE ON HOTELS’ WEBSITES. Information Systems in Management , 02 (02), 146-158.

[26]. Liu, y., Henseler, j., & Liu, y. (2022). What makes tourists adopt smart hospitality? An inquiry beyond the technology acceptance model. Digital Business , 2 (2), 100042.

[27]. Lukanova, g., & Ilievra, g. (2019). Robots, Artificial Intelligence, and Service Automation in Hotels. In Robots, artificial intelligence, and service automation in travel, tourism and hospitality (pp. 157-183). Emerald publishing limited.

[28]. Melian-Gonzalez, S., & al, e. (2021). Predicting the intentions to use chatbots for travel and tourism. Current Issues in Tourism , 24 (02), 192-210.

[29]. Nadarzynski, T., & al, e. (2019). Nadarzynski, Tom, et al. "Acceptability of artificial intelligence (AI)-led chatbot services in healthcare: A mixed-methods study. Digital health , 5.

[30]. Park, k., Park, n., & Heo, w. (2018). Factors Infl ue ncing Intranet Acceptance in Restaurant Industry: Use of Technology Acceptance Model. International Business Research , 11 (10), 1.

[31]. Pillai, r., & Sivathanu, b. (2020). Adoption of AI-based chatbots for hospitality and tourism. International Journal of Contemporary Hospitality Management , 32 (10), 3199-3226.

[32]. Rafiq, f., & al, e. (2022). Examining Consumer’s Intention to Adopt AI-Chatbots in Tourism Using Partial Least Squares Structural Equation Modeling Method. Mathematics , 10 (13), 2190.

[33]. Sagnier, c., & al, e. (2020). User Acceptance of Virtual Reality: An Extended Technology Acceptance Model. International Journal of Human–Computer Interaction , 36 (11), 993-1007.

[34]. Sarstedt, M., & al, e. (2020). Beyond a tandem analysis of SEM and PROCESS: Use of PLS-SEM for mediation analyses. International Journal of Market Research , 62 (03), 288-299.

[35]. Toader, d.-c., & al, e. (2020). The effect of social presence and chatbot errors on trust. sustainbility , 12 (01), 256.

[36]. Ukpabi, d., 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.

[37]. Venkatesh, V., & Bala, H. (2008). Technology acceptance model 3 and a research agenda on interventions. Decision sciences , 39 (02), 273-315.

[38]. Venkatesh, v., & Davis, f. (1996). A model of the antecedents of perceived ease of use: Development and test. Decision sciences , 27 (03), 451-481.

[39]. Zlatanov, s., & Popesku, j. (2019). Current applications of artificial intelligence in tourism and hospitality. Sinteza 2019-International Scientific Conference on Information Technology and Data Related Research, (pp. 84-90). Singidunum University.