Influence of Smart Pricing Tool on Electric Vehicle Adoption and Carbon Reduction in Kota Kinabalu, Sabah: Regression-based Assessment

Abstract

The decarbonisation of urban transport remains a critical component of Malaysia’s climate response strategy, particularly as electric vehicle (EV) adoption progresses more slowly than regional and global trends. This study investigates how EV charging price interventions can influence potential adoption behaviour in Kota Kinabalu, Sabah, while quantifying the associated carbon dioxide (CO₂) reduction potential. A structured survey of 376 private vehicle owners was conducted to evaluate willingness to transition to EVs under varying charging price conditions. A linear regression model and calibrated logistic function were developed to forecast adoption probability across multiple price scenarios. Results reveal a strong inverse relationship between charging cost and adoption likelihood (R² = 0.9517), indicating that price adjustments remain one of the most impactful levers for accelerating EV uptake. Complementary sustainability analysis shows that shifting from internal combustion engine vehicles to EVs could reduce emissions by 73% for every 100 km travelled. Scenario forecasting from 2025 to 2030 demonstrates that aggressive pricing strategies may triple adoption rates and yield substantial cumulative CO₂ savings. To support policy and planning, a Smart EV Pricing Tool was developed to simulate adoption and emission outcomes across different economic pathways. Findings highlight the importance of pricing reform as an adaptive climate-responsive mechanism and provide a data-driven foundation for transport decarbonisation efforts in Malaysia.