Analyzing User Acceptance of AI Based Water Quality Monitoring through the UTAUT2 Framework
Year: 2025
Type: article
Study design: Observational Study
Abstract: This research explores the factors influencing user acceptance and utilization of AI-enhanced water quality systems by applying the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2) framework. AI technology has become increasingly important in improving water quality management by analyzing real-time data from multiple sources, helping to enhance environmental sustainability and public health. This study aims to identify and analyze the factors that affect user behavioral intention toward adopting AI-based water quality systems, particularly focusing on perceived usefulness, ease of use, social norms, and motivation. Data were collected from 357 respondents who had used AI-based water quality systems for at least three months and analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM) with SmartPLS software. The findings indicate that perceived ease of use, social norms, and motivation have a significant influence on behavioral intention to adopt the systems, while perceived usefulness shows no significant effect. These results validate the UTAUT2 model applicability to AI-driven environmental technologies and provide practical guidance for developers and policymakers to enhance user engagement, affordability, and usability of AI-based water quality systems to promote sustainable environmental management and public well-being.
Institutions: Satya Wacana Christian University, Universitas Raharja
Language: English
Subfield: Information Systems and Management
Field: Decision Sciences
Domain: Social Sciences
Open Access status: hybrid
OpenAlex ID: W7204479754