Original scientific paper
https://doi.org/10.37741/t.74.4.7
Predicting Customer Intentions to Use Hotel Chatbots: The Role of Perceived Competence and Usefulness
Buket Yasar
; Department of Business and Economics, The University of Virginia's College at Wise, Wise, VA, United States
*
Emrah Ozkul
; Department of Tourism Management, Kocaeli University, İzmit, Türkiye
* Corresponding author.
Abstract
This research examines the adoption of AI-powered chatbots in the hospitality industry by extending the
conventional Technology Acceptance Model (TAM) to include perceived competence and perceived understandability.
Using data from 266 hotel guests, the study applies Partial Least Squares Structural Equation
Modeling (PLS-SEM) to test the hypothesized relationships. The results indicate that perceived competence
and perceived understandability significantly shape customers’ perceptions of ease of use and usefulness.
Among these, perceived ease of use emerged as the dominant factor influencing customers’ attitudes toward
hotel chatbots, which in turn strongly affected their behavioral intentions. In contrast, perceived usefulness
showed no meaningful association with attitude development in this context. The study contributes to the
hospitality chatbot literature by extending TAM in the hotel context by including perceived understandability
and perceived competence, and it offers practical guidance for improving chatbot adoption in hotel settings.
Keywords
hotel chatbots; perceived competence; perceived understandability; AI in hospitality; PLS-SEM
Hrčak ID:
353273
URI
Publication date:
11.11.2026.
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