Year
2025
Abstract
This study proposes an investigation on the antecedents of medical tourism destination preference among Indonesian patients, with a specific focus on the novel moderating role of Artificial Intelligence (AI) chatbots. Driven by a significant financial drain from outbound medical travel, this study aims to understand the key factors that influence Indonesian patients to seek care abroad. The proposed conceptual framework posits that medical tourism destination preference is positively predicted by medical technology advancement, service quality, price transparency, and geographical accessibility. Patient experience quality is also hypothesized to mediate these relationships, serving as a critical psychological bridge. The most innovative aspect of this conceptual paper is the examination of how the perceived intelligence and humanness of AI chatbots moderate the associations between the antecedents and patient experience quality, and subsequently, destination preference. The research will employ a quantitative approach using PLS-SEM on data from Indonesian medical tourists, whose results would then offer value-adding significance both academically and practically.
Keywords:
Medical Tourism; Destination Preference; Artificial Intelligence, Chatbots, Indonesia
Recommended Citation
Eddy, Eddy; Sihombing, Sabrina O.; and Antonio, Ferdi, "Predicting Medical Tourism Destination Preference of Indonesian Patients: The Roles of Patient Experience Quality, Perceived AI Intelligence and Humanness" (2026). International Conference on Business and Management Research (ICBMR). 18.
https://scholarhub.ui.ac.id/icbmr/2025/1/18
Included in
Management Sciences and Quantitative Methods Commons, Marketing Commons, Technology and Innovation Commons, Tourism and Travel Commons
Predicting Medical Tourism Destination Preference of Indonesian Patients: The Roles of Patient Experience Quality, Perceived AI Intelligence and Humanness
This study proposes an investigation on the antecedents of medical tourism destination preference among Indonesian patients, with a specific focus on the novel moderating role of Artificial Intelligence (AI) chatbots. Driven by a significant financial drain from outbound medical travel, this study aims to understand the key factors that influence Indonesian patients to seek care abroad. The proposed conceptual framework posits that medical tourism destination preference is positively predicted by medical technology advancement, service quality, price transparency, and geographical accessibility. Patient experience quality is also hypothesized to mediate these relationships, serving as a critical psychological bridge. The most innovative aspect of this conceptual paper is the examination of how the perceived intelligence and humanness of AI chatbots moderate the associations between the antecedents and patient experience quality, and subsequently, destination preference. The research will employ a quantitative approach using PLS-SEM on data from Indonesian medical tourists, whose results would then offer value-adding significance both academically and practically.