Commuters' acceptance of autonomous taxis: A PLS-SEM case study on sustainable transportation in the Philippines

The study explored the factors that influence public acceptance of cyber taxis in the Philippines as a hailing service by focusing on environmental concerns and the need for sustainable urban transportation. The study's structure was based on the Sustainability Theory of Planned Behavior (STPB), examining perception through purposive sampling technique of 401 respondents from the Philippines regarding the implementation of cyber taxis in their daily lives. To examine the factors that affect the Filipino's response to their acceptance, the study analyzed key variables such as Subjective Norm, Perceived Environmental Concern, Attitude, Perceived Economic Concern, Perceived Behavioral Control, Perceived Authority Support, Behavioral Intention, and Acceptance – all of which were seen to be key aspects in understanding the behavioral nature of the Filipino's level of acceptance. The data gathered from respondents were analyzed through SmartPLS version 4 utilizing Partial Least Squares Structural Modeling (PLS-SEM) with Bootstrapping method to identify the connection of significance between the key latent variables. Results showed that behavioral intention strongly predicts cyber taxi acceptance (β: 0.868 ± 0.901 direct effect), while economic concern significantly influences subjective norms (β: 0.479 ± 0.663 total effect) and perceived control (β: 0.380 ± 0.513 total effect). Moreover, attitude (β: 0.474 ± 0.430 direct effect) was found to be the strongest driver of behavioral intention of accepting cyber taxis, as both environmental and economic perceptions were the key influential factors. The paper analyzes the factors that influence Filipinos' acceptance of cyber taxis as a potential public transportation option in the Philippines, utilizing the Sustainability Theory of Planned Behavior model and PLS-SEM to provide a comprehensive understanding of how behavioral constructs mediate and influence acceptance.