Designing for Coordination: A Multidimensional Maturity Assessment of Mobility-as-a-Service Platform Implementation – The Case of WeTaxi

Abstract

This research investigates the design, operationalization, and scaling of Mobility-as-a-Service (MaaS) platforms. The objective is to develop a structured understanding of how these integrated systems function within multi-actor service operations. MaaS is promoted as a digital solution for seamless mobility, but research on this topic remains fragmented. Literature focuses on technological or policy aspects, while limited insights were provided concerning the operational mechanism and technological readiness of the platforms used to coordinate services, actors, and processes.

Accordingly, this study questions "How are Maas platforms designed and operationalized to integrate heterogeneous mobility services while ensuring coordination reliability and user-centric performance?" To address this gap, the research aims to (1) identify the key functional, managerial, and user-related dimensions of MaaS platforms, (2) develop an analytical requirement framework that captures the interdependencies between the mentioned dimensions, and (3) apply this framework to WeTaxi, an Italian MaaS operator with national multimodal coverage, as the empirical case, to examine how MaaS systems are implemented and managed.

Methodologically, a theory-driven, multidimensional requirement framework comprising eighteen criteria across functional, user, and managerial dimensions was developed from the literature on servitization, platform ecosystems, interoperability, and Al in mobility. A qualitative case study methodology was adopted, combining secondary data on platform architecture with primary data from a semi-structured interview with WeTaxi management. Evidence was analysed through deductive coding. evidence mapping, and pattern matching against theoretical expectations, culminating in a five-level maturity assessment with explicit justification and confidence ratings applied to each requirement, the platform's business model, and its Al-related capabilities, using a dedicated Al Mapping Matrix.

The findings reveal a pronounced asymmetry in platform maturity. Functional requirements (average 3.83) and user requirements (3.67) show high maturity, reflecting a sophisticated abstraction and orchestration architecture that achieves advanced multimodal integration, unified booking and payment, and a frictionless interface. Managerial requirements average only 3.17, with ecosystem governance scoring 2-the lowest level recorded and the platform's most acute structural limitation. The Al Mapping Matrix shows that WeTaxi's most operationally valuable capabilities are rule-based automation rather than genuine Al, with Al-driven functions for demand-responsive transport, intermodal optimisation, and personalisation still under development. WeTaxi thus emerges as a technically advanced but institutionally constrained operator, whose internal abstraction layer substitutes for absent ecosystem-wide governance, compensating for, but not resolving, the coordination costs that institutional fragmentation imposes.

Interpreted against the literature, these findings show that technical integration can advance substantially through internal architectural design even where governance is underdeveloped, but that this substitution carries a structural ceiling: governance, not technology, is the principal rate-limiting factor for further MaaS maturity. The study also demonstrates that automation and Al are frequently conflated, and that the transition to AI-enabled operations is itself contingent on governance and data-sharing conditions the platform cannot establish unilaterally. A five-stage maturity roadmap is proposed, sequencing technical, commercial, governance, and Al development as interdependent rather than parallel tracks. The thesis concludes that MaaS implementation is best understood as an ecosystem transformation challenge rather than a purely technological one, and offers a replicable maturity assessment methodology together with evidence-based implications for MaaS operators, mobility service providers, platform developers, and policymakers.