UPDATING THE TOLL ROAD SERVICE QUALITY (TRSQ) MODEL THROUGH THE INTEGRATION OF AI-BASED TECHNOLOGICAL INNOVATIONS
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Abstract
Toll roads can play a vital role in supporting mobility, logistics, and regional economic growth. However, issues such as congestion, declining road quality, and limited real-time information systems often hinder service performance. This study aims to update the Toll Road Service Quality (TRSQ) model by integrating artificial intelligence (AI)-based technological innovations as a mediating variable to enhance excellent toll road services. Using a quantitative explanatory approach, data were collected from 480 users of the Pemalang–Batang Toll Road via a questionnaire survey. Data analysis employed SmartPLS to test causal relationships among TRSQ variables, which include information, accessibility, reliability, mobility, safety and security, rest areas, and responsiveness. Results show that all TRSQ variables significantly influence service excellence, both directly and through technology as a mediator. Priority indicators identified include toll gate queue length, availability of road markings and information boards, traffic flow, real-time traffic updates, and service comfort. The study highlights the urgency of applying AI-based intelligent transportation systems—such as innovative CCTV, remote sensors, and automated information management—to optimise toll road performance, improve user satisfaction, and strengthen sustainable transport services.
Keywords: artificial intelligence, smartpls, technological innovation, toll road service, TRSQ model, user satisfaction
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