Ceccotti, Maria Cristina (2026) Measuring impacts of Mobility as a Service through the evaluation of Key Performance Indices (KPIs): “MaaS4Italy” as a case study. [Tesi di dottorato]

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Tipologia del documento: Tesi di dottorato
Lingua: English
Titolo: Measuring impacts of Mobility as a Service through the evaluation of Key Performance Indices (KPIs): “MaaS4Italy” as a case study
Autori:
Autore
Email
Ceccotti, Maria Cristina
ceccottimariacristina@gmail.com
Data: 4 Febbraio 2026
Numero di pagine: 192
Istituzione: Università degli Studi di Napoli Federico II
Dipartimento: Ingegneria Civile, Edile e Ambientale
Dottorato: Ingegneria dei sistemi civili
Ciclo di dottorato: 37
Coordinatore del Corso di dottorato:
nome
email
Papola, Andrea
papola@unina.it
Tutor:
nome
email
Bifulco, Gennaro Nicola
[non definito]
Data: 4 Febbraio 2026
Numero di pagine: 192
Parole chiave: MaaS; Mobility as a Service; KPI
Settori scientifico-disciplinari del MIUR: Area 08 - Ingegneria civile e Architettura > ICAR/05 - Trasporti
Informazioni aggiuntive: 37° Ciclo PON “Ricerca e Innovazione” 2014-2020
Depositato il: 21 Feb 2026 18:45
Ultima modifica: 12 Ago 2026 05:38
URI: https://www.fedoa.unina.it/id/eprint/16895

Abstract

Mobility as a Service (MaaS) has emerged as a promising paradigm for integrating multiple transport modes into a single digital ecosystem, aiming to improve efficiency, accessibility and sustainability of urban mobility. Despite growing interest from policymakers and researchers, empirical evidence on MaaS impacts remains fragmented, and standardized evaluation frameworks are still lacking. This PhD thesis develops a comprehensive and standard-based methodological framework for measuring the impacts of MaaS through Key Performance Indicators (KPIs). The proposed approach integrates behavioural, operational, governance, economic and environmental dimensions, combining user-centred indicators with transport-system performance metrics. The framework is grounded in European interoperability standards, including Transmodel, NeTEx, SIRI and OpRa, ensuring methodological robustness, comparability and scalability across heterogeneous urban contexts. The methodology is empirically validated through the Italian national programme “MaaS4Italy”, used like a baseline, which includes three metropolitan pilots (Naples, Rome and Milan). Particular emphasis is placed on the MaaS4Naples case study, where the availability of detailed operational and transactional data enables the extension of the national KPI framework to explicitly link MaaS outcomes with public transport performance. Results demonstrate that MaaS impacts are strongly conditioned by the structural characteristics of local mobility systems, governance maturity and data readiness. The analysis highlights that MaaS primarily reduces cognitive and transactional barriers to multimodality, while sustained behavioural change depends on the reliability and accessibility of the underlying transport network. The study also shows that significant multimodal behaviour can emerge even in public-transport-only MaaS ecosystems when tariff, informational and operational integration are achieved. Overall, the thesis provides a transferable evaluation framework for MaaS, contributing both to academic research and to evidence-based policymaking for sustainable and equitable urban mobility.

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