PREDICTING THE ADOPTION OF ELECTRIC BIKES IN UGANDA: A MACHINE LEARNING APPROACH TO UNDERSTANDING CONSUMER BEHAVIOR
The transition to sustainable mobility is a critical imperative for Uganda, which is characterized by a heavy reliance on fossil fuel-powered motorcycle taxis (boda bodas) that contribute to urban pollution and economic strain. This study employed an explainable machine learning approach to predict and analyze electric bike (e-bike) adoption patterns among Uganda's boda boda operators.