Investigating Factors Influencing the Adoption of Intelligent Public Transport Systems for Congestion Reduction in Developing Cities

Abstract

Abstract Rapid urbanization has exacerbated mobility challenges in developing cities, necessitating the adoption of suitable public transport systems to enhance efficiency, reduce congestion, and promote sustainable urban mobility. This study investigates the factors influencing intelligent public transportation system adoption, especially Bus Rapid Transit, in Kinshasa, capital city of the Democratic Republic of the Congo, where public transportation remains fragmented, underfunded, and dominated by informal transit modes. While previous interventions, such as the “ Robot Roulage ” system, have focused on traffic regulation, they fail to address structural inefficiencies hindering commuter safety and mobility. This research integrates the Unified Theory of Acceptance and Use of Technology (UTAUT) as the primary theoretical model, complemented by the Technology–Organization–Environment (TOE) framework, TRUST model, and Task-Technology Fit (TTF) model to examine commuter adoption behavior and organizational readiness. Employing structural equation modeling on survey data from 240 respondents, findings indicate that performance expectancy, effort expectancy, task-technology fit, and trust in technology significantly influence intelligent public transport system (IPTS) adoption. Policy recommendations emphasize investment in real-time tracking systems, transparent governance structures, and public–private partnerships to facilitate intelligent public transport system scalability. This study offers empirical insights for urban planners, policymakers, and transit authorities seeking to implement context-specific, technology-driven public transport solutions in rapidly growing developing cities.