Predicting the Determinants of Artificial Intelligence in Green Energy Technologies Adoption Intention at the Household Level Using Structural Equation Modeling
2024 9th International Conference on Business and Industrial Research (ICBIR)
(2024), pp. 0823-0828
Alexander A. Hernandez
a
,
Victor James C. Escolano
b
,
Muhammad Syukur
c
,
Darrel Cardaña
d
,
Erlito M. Albina
a
,
Ace C. Lagman
e
a College of Technology, Lyceum of the Philippines University, Manila, Philippines
b College of Liberal Arts, Technological University of the Philippines, Manila, Philippines
c Sustainability and Entrepreneurship Research Center (SERC), Mae Fah Luang University, Chiang Rai, Thailand
d College of Technology and Allied Sciences, Bohol Island State University-Bilar Campus, Bohol, Philippines
e College of Computer Studies and Multimedia Arts, FEU Institute of Technology, Manila, Philippines
Abstract: Sustainability is a present concern in many developing countries, where the role of the household is pivotal in realizing its benefits. This study aims to explore artificial intelligence in green energy technologies (AIGET) adoption intention among household-level respondents selected in the National Capital Region (NCR), Philippines. The study has 446 respondents and analyzed using partial least squares and structural equation modeling approaches (PLS-SEM). Among the factors tested, results revealed that perceived usefulness is the strongest predictor of AIGET adoption intention. Factors such as usefulness, ease of use, subjective norms, and perceived risk have a positive effect on attitude. This confirms that attitude has a positive impact on behavioral intention on AIGET. Finally, this study shows that household-level participants have a positive interest in adopting AIGET, considering its usefulness and ease of use. This study presents useful theoretical and practical contributions to further its uptake in the Philippines and other developing countries.