The Impact of AI Chatbot Implementation on Customer Satisfaction: A Study of Food and Beverage (F&B) Businesses in Labuan Bajo, Indonesia
DOI:
https://doi.org/10.65792/jombinov.v2i3.55Keywords:
Artificial Intelligence Chatbot, Digital Trust, Customer Satisfaction, Technology Acceptance Model, Food and Beverage Business, Premium Tourism DestinationAbstract
This research aims to analyze the impact of AI chatbot implementation on customer satisfaction in the food and beverage (F&B) business in Labuan Bajo by examining the role of customer digital trust as a mediating variable. This research uses an explanatory quantitative approach with purposive sampling technique on 131 F&B customers who have experience interacting with AI chatbots. The data were analyzed using the Partial Least Squares Structural Equation Modeling (PLS-SEM) method with the help of the SmartPLS 4 application to test the relationships between variables in the research model. The implementation of AI chatbots has been proven to have a positive and significant impact on digital trust and customer satisfaction directly. Additionally, digital trust also has a positive and significant impact on customer satisfaction. The results of the mediation test indicate the presence of complementary partial mediation, meaning that more than half of the AI chatbot's influence on customer satisfaction occurs thru the enhancement of customer digital trust. This research enriches the TAM and ERP by providing a mechanistic explanation of the conditions under which the relationship between AI chatbots and customer satisfaction holds, while also being the first study to test this mechanism in F&B businesses at Indonesia's super-priority tourist destinations. F&B business operators need to develop chatbots that not only focus on response speed but also build credibility and customer trust. Meanwhile, local governments can use these findings as a basis for designing more effective digitalization support programs for MSMEs that meet the needs of business operators. The research sample was dominated by domestic tourists and collected thru a cross-sectional design at a single destination, so the generalization of the findings needs to be done with caution. Future research is recommended to use a longitudinal design and a comparative approach between destinations to obtain a broader understanding.
Downloads
References
Adam, M., Wessel, M., & Benlian, A. (2021). AI-based chatbots in customer service and their effects on user compliance. Electronic Markets, 31(2), 427–445. https://doi.org/10.1007/s12525-020-00414-7
Al-Adwan, A. S., Jafar, R. M. S., & Sitar-Tăut, D.-A. (2024). Breaking into the black box of consumers’ perceptions on metaverse commerce: An integrated model of UTAUT 2 and dual-factor theory. Asia Pacific Management Review, 29(4), 477–498. https://doi.org/10.1016/j.apmrv.2024.09.004
Al-Shafei, M. (2025). Navigating Human-Chatbot Interactions: An Investigation into Factors Influencing User Satisfaction and Engagement. International Journal of Human–Computer Interaction, 41(1), 411–428. https://doi.org/10.1080/10447318.2023.2301252
Chacon, A. (2026). Behavioral Responses to AI Agents in Customer Service. In Encyclopedia of Artificial Intelligence in Marketing (pp. 1–13). Springer Nature Switzerland. https://doi.org/10.1007/978-3-031-75316-9_144-1
Dubey, A. D., & Meena, R. (2025). Novel Cognitive Trust Model in Travel Chatbots. NMIMS Management Review, 33(4), 316–331. https://doi.org/10.1177/09711023251379994
Elisa Imania, & Umu Arifatul Syfa. (2026). Kabupaten Manggarai Barat Dalam Angka 2026. BPS Kabupaten Manggarai Barat.
Hair Jr., J. F., M. Hult, G. T., M. Ringle, C., Sarstedt, M., Castillo Apraiz, J., Cepeda Carrión, G. A., & Roldán, J. L. (2019). Manual de Partial Least Squares Structural Equation Modeling (PLS-SEM) (Segunda Edición). OmniaScience. https://doi.org/10.3926/oss.37
Henseler, J., Ringle, C. M., & Sarstedt, M. (2016). Testing measurement invariance of composites using partial least squares. International Marketing Review, 33(3), 405–431. https://doi.org/10.1108/IMR-09-2014-0304
Hitti, S., & Ramadan, A. (2026). Humanizing the customer experience with AI chatbots: a study in the food services industry toward achieving SDG 11 and SDG 12. Journal of Business and Socio-Economic Development, 6(2), 209–231. https://doi.org/10.1108/JBSED-05-2025-0153
Jr, J., Sarstedt, M., Ringle, C., & Gudergan, S. (2023). Advanced Issues in Partial Least Squares Structural Equation Modeling (2nd ed.).
Klaasvakumok J. Kamuri. (2026). Yang Disingkirkan Oleh AI (Artificial Intelligence). CV. Vocezmi Learnov.
Kock, N., & Hadaya, P. (2018). Minimum sample size estimation in PLS‐SEM: The inverse square root and gamma‐exponential methods. Information Systems Journal, 28(1), 227–261. https://doi.org/10.1111/isj.12131
Podsakoff, P. M., MacKenzie, S. B., & Podsakoff, N. P. (2012). Sources of Method Bias in Social Science Research and Recommendations on How to Control It. Annual Review of Psychology, 63(1), 539–569. https://doi.org/10.1146/annurev-psych-120710-100452
Ranieri, A., Di Bernardo, I., & Mele, C. (2024). Serving customers through chatbots: positive and negative effects on customer experience. Journal of Service Theory and Practice, 34(2), 191–215. https://doi.org/10.1108/JSTP-01-2023-0015
Rizomyliotis, I., Kastanakis, M. N., Giovanis, A., Konstantoulaki, K., & Kostopoulos, I. (2022). “How mAy I help you today?” The use of AI chatbots in small family businesses and the moderating role of customer affective commitment. Journal of Business Research, 153, 329–340. https://doi.org/10.1016/j.jbusres.2022.08.035
Sidlauskiene, J., Joye, Y., & Auruskeviciene, V. (2023). AI-based chatbots in conversational commerce and their effects on product and price perceptions. Electronic Markets, 33(1), 24. https://doi.org/10.1007/s12525-023-00633-8
Sugiyono. (2022). Metode Penelitian Kualitatif Untuk Penelitian Yang Bersifat: Eksploratif, Entrepretif, Interaktif, dan Konstruktif. Alfabeta.
Thu, H. L. T., Cong, M. N., Huy, T. N., Le, L. T. K., & Thanh, D. D. (2026). Mapping the Research Landscape of AI Chatbot Adoption in Tourism and Hospitality. International Journal of Knowledge and Systems Science, 17(1), 1–23. https://doi.org/10.4018/IJKSS.402722
Tuong Cat Tran Pham, Tai Huynh, Phuc-Thien Tran, & Anh Quynh Ly. (2025). Exploring How Ai Chatbots Influence Customer Loyalty Among Generation Z onE-Commerce Platforms. Advances in Consumer Research, 2(5), 2473-2486.
Xu, Y., Niu, N., & Zhao, Z. (2023). Dissecting the mixed effects of human-customer service chatbot interaction on customer satisfaction: An explanation from temporal and conversational cues. Journal of Retailing and Consumer Services, 74, 103417. https://doi.org/10.1016/j.jretconser.2023.103417
Zhao, X., Lynch, J. G., & Chen, Q. (2010). Reconsidering Baron and Kenny: Myths and Truths about Mediation Analysis. Journal of Consumer Research, 37(2), 197–206. https://doi.org/10.1086/651257
Downloads
Published
Issue
Section
License
Copyright (c) 2026 Absiani S. Ndun, Klaasvakumok J. Kamuri, Andrias U. T. Anabuni (Author)
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
