The effectiveness of fare collection systems (FCS) plays a critical role in
ensuring operational efficiency and passenger convenience in public rail
transit, including Metro Rail Transit Line 3 (MRT-3). However, the current
contactless smart card-based FCS faces challenges such as technical
malfunctions, long queues, and limited payment options. While modernization
efforts focus on automated payment solutions, passenger acceptance remains a key
determinant of its successful adoption. This study examined the demographic and
preference-based factors affecting FCS adoption using a two-phase approach:
statistical association tests assessed demographic influences, while Partial
Least Square - Structural Equation Modeling (PLS-SEM) evaluated behavioral
predictors. Findings revealed that income level and frequency of use are the
strongest predictors of FCS preference, highlighting economic constraints and
travel habits as key factors in its adoption. The PLS-SEM results revealed that
performance expectancy is the strongest predictor of behavioral intention to
adopt an improved FCS, followed by effort expectancy and facilitating
conditions, emphasizing the need for efficiency, ease of use, government support
and fare incentives. Social influence, however, shows an insignificant effect.
Based on these insights, the study proposed strategies to enhance FCS adoption,
including diversified payment options, improved accessibility, and targeted
awareness campaigns.