Impact of AI on Air Quality Monitoring Systems: A Structural Equation Modeling Approach Using UTAUT
Keywords:
Artificial Intelligence, Structural Equation Modeling (PLS-SEM), SmartPLS, Air QualityAbstract
Artificial Intelligence (AI) technology in air quality systems is a potential solution to the complex challenges of global air pollution. This study applies the Unified Theory of Acceptance and Use of Technology (UTAUT) model with the participation of 100 respondents to investigate the factors affecting the adoption of this technology. Related variables include performance expectations, effort expectations, social influence, favorable conditions, usage behavior, trust in technology, perception of air quality issues and environmental impact is felt. This study explores the essential factors influencing the adoption and acceptance of this technology. The Structural Equation Modeling (SEM) method, with the support of smartPLS 4, was applied as the primary method to analyze the complex interaction between these variables. The main results of this study show that aspects such as performance expectations, effort expectations and facilitation significantly impact the intention to use this technology. On the other hand, social influence is also said to have a prominent impact. Through these findings, this paper provides relevant strategic guidance in developing promotional efforts and implementing this technology. In addition, the integrated theoretical framework proposed in this study offers valuable support for policymakers, technology developers, and practitioners in the environmental field. Collaborative efforts to improve air quality and contribute to sustainability are the main objectives of this research.
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