Ride-Hailing Quality Gaps and Improvement Priorities: SERVQUAL-Kano Study in Mid-Sized Indonesian City
Keywords:
Customer Satisfaction, Kano Model, Ride-Hailing, Service Quality, SERVQUALAbstract
Digitalization has accelerated ride-hailing growth by offering urban commuters convenience and flexibility. In Indonesia, rising usage has intensified competition among platforms such as Grab and its rivals. Despite its extensive reach, Grab continues to face negative perceptions concerning pricing, inconsistent service, and suboptimal user experiences, which erode customer satisfaction and loyalty. Malang City was selected for its high mobility and rapidly growing user base. As a mid-size city with moderate density and growing transport demand, Malang is suitable for studying ride-hailing beyond megacities. This study integrates SERVQUAL and the Kano Model to identify, classify, and prioritize service attributes influencing GrabBike user satisfaction. A purposive sample of 385 respondents completed an online survey (Google Forms) between December 2025 and January 2026. The overall quality ratio (Q) was 0.85, and Tangibles was the lowest performing dimension. RL4 (fare suitability) recorded the largest gap (-1.65), a critical priority. Kano classification yielded 7 Must-Be, 3 One-Dimensional, 3 Attractive, 1 Indifferent, and 1 Reverse attributes. This integrated approach constitutes a novel, data-driven framework for prioritizing service enhancements. The findings provide guidance to remedy dissatisfiers and invest in delight-enhancing attributes, while establishing local quality benchmarks for policymakers.
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