Designing an Integrated Ride-Hailing Aggregator App: A User-Centric Approach

Abstract

The rapid proliferation of ride-hailing services such as Uber, Bolt, and Lyft has significantly transformed urban mobility, offering users flexible, on-demand transportation options. However, the coexistence of multiple platforms has led to service fragmentation, requiring users to switch between apps to compare prices, availability, and estimated wait times - a process that introduces complexity and negatively impacts user experience. In response to this challenge, this dissertation proposes the design and evaluation of NextRide, a user-centered prototype for a ride hailing aggregator application. This project adopts a user experience (UX)-focused methodology, leveraging design research models such as the Double Diamond and Garrett's Elements of User Experience to guide the iterative development process. Based on an in-depth literature review, user interviews, surveys, and usability testing, the prototype was developed in Figma and integrates key functionalities that allow users to visualize and compare available transport services in real time, aiming to reduce cognitive load and decision-making time. To evaluate the effectiveness of the proposed solution, usability testing was conducted with eight participants using the System Usability Scale (SUS). The prototype achieved an average score of 86.25, indicating a high level of usability and user satisfaction. Participants highlighted the platform's intuitive interface, clarity of navigation, and value in aggregating key transport information in one place. The results validate the hypothesis that aggregating ride-hailing services into a single platform can substantially enhance decision efficiency, streamline the user journey, and improve satisfaction. This work contributes to the field of UX design for urban mobility and opens future directions for developing fully integrated multimodal transport solutions aligned with the smart city paradigm.