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Factors Influencing Users’ Behavioral Intention towards Adoption of Teleconsultation Technology: A Combined TAM-BRT Approach
Author(s) -
Vikash Sachan,
Narender Singh Bhati,
Prashasti Jain
Publication year - 2025
Publication title -
ieee access
Language(s) - English
Resource type - Magazines
SCImago Journal Rank - 0.587
H-Index - 127
eISSN - 2169-3536
DOI - 10.1109/access.2025.3621909
Subject(s) - aerospace , bioengineering , communication, networking and broadcast technologies , components, circuits, devices and systems , computing and processing , engineered materials, dielectrics and plasmas , engineering profession , fields, waves and electromagnetics , general topics for engineers , geoscience , nuclear engineering , photonics and electrooptics , power, energy and industry applications , robotics and control systems , signal processing and analysis , transportation
Healthcare infrastructure is of paramount importance in developing countries. Integrating healthcare services with technological innovations, such as artificial intelligence, supply chain automation, medical robotics, and teleconsultation technology, has consistently played a crucial role in enhancing operational efficiency. Unfortunately, inadequate user acceptance can undermine these inherent benefits. Although most studies have examined the behavioral intention from a healthcare provider’s perspective, investigating factors influencing users’ adoption intention is vital. This research focuses on users’ viewpoints to investigate the factors influencing their technology adoption intention through a combination of the Technology Acceptance Model (TAM) and the Behavioral Reasoning Theory (BRT) model. This study included 403 individuals. The research framework was tested using SmartPLS 4 with advanced partial least squares-based structural equation modeling. The results of the structural model indicate that factors under the ’reasons for’ category, such as compatibility, convenience, and self-efficacy, have a positive but indirect influence on behavioral intention. However, trust did not have any significant effect. Interestingly, the risk barrier and technological anxiety do not have an indirect negative impact on users’ behavioral intention, personal inertia exerts a significant indirect negative impact on users’ behavioral intention. The findings provide significant contributions and implications for healthcare service providers, policymakers, health insurance companies, and future researchers in the healthcare domain.

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