The Emergence of Smart Chatbots in Online Health Services: Unveiling Adoption Intentions and Influencing Factors

The use of mobile health applications, or M-Health Applications, has surged in popularity in recent years, especially since the onset of the COVID-19 pandemic. Users of M-health care applications generally seek easy, cost-effective, and reliable services online. However, the integration of chatbots with M-health care services represents a groundbreaking development, yet its adoption rate remains relatively low. Therefore, this study aims to delve into the factors influencing the adoption intention of Online Health Services integrated with smart chatbots. Applying the Unified Theory of Acceptance and Use of Technology (UTAUT) along with the Technology Acceptance Model (TAM) theory, this study conceptualize structural model for this research. This study gathered data from 499 respondents in Indonesia, employing purposive sampling techniques. The data underwent analysis using Partial Least Squares Structural Equation Modelling (PLS-SEM) for statistical analysis. The findings reveal that Performance Expectancy (PE), Effort Expectancy (EE), Social Influence (SI), Facilitating Conditions (FC), and Trust (TR) positively influence Intention to Use (IU) Smart Chatbots. However, Perceived Risk (PR) was found to have no significant impact on Intention to Use (IU) of Smart Chatbots. These findings hold both theoretical and practical significance, shedding light on the factors influencing the adoption behavior of mobile health applications integrated with smart chatbots. As a result, they offer valuable guidance for stakeholders associated with the online health-care service industry, policymakers regarding how to improve Smart Chatbots service using for Online Health. Moreover, researchers will understand behavioral intention of users which can be used as reference for future study.