FEU Institute of Technology

Educational Innovation and Technology Hub

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Dania Mariz C. Notado

1 Publications
Predicting Generation Z Green Vehicle Purchase Intention Using Machine Learning Approaches

2026 International Conference on Artificial Intelligence, Computer, Data Sciences and Applications (ACDSA), (2026), pp. 1-6

Conference Paper | Published: February 7, 2026

Abstract
This paper explores the prediction of Filipino consumers' purchase intention regarding electric vehicles (EVs) as a green vehicle to support sustainable transportation alternative in the Philippines. Despite the growing awareness and government initiatives, EV purchase intention and adoption studies remain limited among Generation Z as consumer group. To address this gap, the study collected data from 479 Filipino generation Z commuters in the National Capital Region (NCR), Philippines, analyzed using different machine learning techniques, namely, Decision Trees, Random Forest, Gradient Boosting, XGBoost, K-Nearest Neighbors, and Support Vector Machine. Findings suggest that Green Perceived Value (GPV) emerged as the most important factor green vehicle purchase intention. Meantime, among the machine learning techniques, XGBoost performs best with a predictive accuracy of 87%. Researhch and practical implications are discussed.

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