The increasing complexity of urban mobility systems and the shift toward sustainable multimodal transport require assessment frameworks capable of representing the complexity of quality in a context where multiple transport systems operate and interact with each other (i.e., non-motorised mobility, e-micromobility, Local Public Transport). Despite extensive research on transport quality, existing approaches remain fragmented, predominantly mode-specific, and rarely address the full travel chain. This PhD thesis responds to this gap by developing a comprehensive Multimodal Quality Assessment Framework that combines objective measurements, subjective evaluations, and a structured quality gaps management process to support evidence-based mobility planning. The research begins with a systematic review of the literature, identifying conceptual fragmentation and the absence of a unified multimodal perspective. Building on this foundation, a new definition of multimodal transport quality is proposed and operationalised through the Logical Framework Approach (LFA). A first rigorous methodological phase is dedicated to the selection of Key Quality Parameters (KQPs), combining expert judgements, AHP-derived weighting, Monte Carlo simulations, and citation/bibliometric validation. This integrated process leads to a robust and transferable set of KQPs suitable for diverse urban contexts. A second methodological phase focuses on the measurement of these parameters through both objective and subjective measurements. Objective measurements are based on the Mystery Client (MC), while subjective measurements are captured through the Customer Satisfaction (CS). MC and CS represent the two tools used to carry out objective and subjective quality measurements, referring specifically to the four quality dimensions: designed, delivered, perceived, and expected. Finally, a third methodological phase addresses the management dimension, identifying quality gaps across the four quality dimensions, and translating these gaps into targeted preventive or corrective measures. The quality assessment framework is applied to the case study of Verona, where multimodal quality is assessed through both MC field measurements and Customer Satisfaction CS surveys. The integrated evaluation of designed, delivered, perceived, and expected quality enables a detailed Quality Gap Analysis, revealing substantial misalignments across criteria and the analysed O-D pairs. The findings support the formulation of targeted preventive and corrective measures aimed at improving accessibility, availability, comfort, customer care, environmental impact, information, safety & security, and time. Overall, the thesis advances the scientific understanding of multimodal quality and offers a transferable, policy-relevant tool for guiding strategic decisions in sustainable urban mobility planning. The framework provides public authorities and operators with a structured, user-centred approach to diagnosing and monitoring system quality and designing effective interventions, contributing to more efficient and sustainable multimodal mobility systems.
La crescente complessità dei sistemi di mobilità urbana e la transizione verso un sistema di trasporto multimodale e sostenibile richiedono quadri di valutazione capaci di rappresentare in modo sistemico la qualità in un contesto in cui molteplici sistemi di trasporto operano e interagiscono tra loro (ad esempio, la mobilità non motorizzata, la micromobilità elettrica e il Trasporto Pubblico Locale). Sebbene la qualità dei trasporti sia stata ampiamente indagata in letteratura, gli approcci esistenti risultano frammentati, prevalentemente specifici per modalità e solo raramente in grado di considerare l’intera esperienza di viaggio. La presente tesi di dottorato colma tale lacuna attraverso lo sviluppo di un quadro completo di valutazione della qualità multimodale, che integra misurazioni oggettive, valutazioni soggettive e un processo strutturato di gestione delle lacune di qualità, con l’obiettivo di supportare una pianificazione della mobilità basata sull’evidenza. La ricerca prende avvio da una revisione sistematica della letteratura, che evidenzia la frammentazione concettuale esistente e l’assenza di una prospettiva multimodale unificata. Su queste basi, viene proposta e resa operativa una nuova definizione di qualità del trasporto multimodale mediante l’applicazione del Logical Framework Approach (LFA). Una prima fase metodologica, rigorosamente strutturata, è dedicata alla selezione dei Parametri Chiave di Qualità (KQPs). Tale processo integra giudizi di esperti, ponderazioni derivate dall’Analytic Hierarchy Process (AHP), simulazioni Monte Carlo e validazione citazionale e bibliometrica, conducendo alla definizione di un insieme robusto e trasferibile di KQPs, adattabile a differenti contesti urbani. La seconda fase metodologica è finalizzata alla misurazione dei KQPs attraverso un’integrazione di misurazioni oggettive e soggettive. Le misurazioni oggettive sono condotte mediante la tecnica del Mystery Client (MC), mentre le misurazioni soggettive sono rilevate tramite indagini di Customer Satisfaction (CS). MC e CS costituiscono i due strumenti adottati per valutare la qualità nelle sue quattro dimensioni fondamentali: progettata, erogata, percepita e attesa. La terza fase metodologica affronta la dimensione gestionale, identificando le lacune qualitative nelle quattro dimensioni della qualità e traducendole in misure preventive e correttive mirate, volte a ridurre i divari riscontrati. Il framework di valutazione della qualità è applicato al caso di studio di Verona, dove la qualità multimodale viene analizzata attraverso misurazioni sul campo mediante MC e tramite indagini di CS. La valutazione integrata della qualità progettata, erogata, percepita e attesa consente un’analisi approfondita del divario di qualità, evidenziando disallineamenti significativi tra criteri e coppie O-D analizzate. I risultati ottenuti supportano la definizione di misure preventive e correttive mirate al miglioramento dell’accessibilità, della disponibilità, del comfort, dell’assistenza clienti, dell’impatto ambientale, dell’informazione, della sicurezza e del tempo. Nel complesso, la tesi contribuisce all’avanzamento della comprensione scientifica della qualità multimodale e propone uno strumento trasferibile e rilevante per le politiche pubbliche, in grado di orientare le decisioni strategiche nell’ambito della pianificazione della mobilità urbana sostenibile. Il framework fornisce alle autorità pubbliche e agli operatori un approccio strutturato e incentrato sull’utente per diagnosticare, monitorare e migliorare la qualità del sistema, supportando la progettazione di interventi efficaci e promuovendo sistemi di mobilità multimodale più efficienti e sostenibili.
Quality as a Driver of Sustainable Multimodal Mobility: From an Assessment Framework to Policy Applications in Urban Contexts
Ferretto, Laura
2026
Abstract
The increasing complexity of urban mobility systems and the shift toward sustainable multimodal transport require assessment frameworks capable of representing the complexity of quality in a context where multiple transport systems operate and interact with each other (i.e., non-motorised mobility, e-micromobility, Local Public Transport). Despite extensive research on transport quality, existing approaches remain fragmented, predominantly mode-specific, and rarely address the full travel chain. This PhD thesis responds to this gap by developing a comprehensive Multimodal Quality Assessment Framework that combines objective measurements, subjective evaluations, and a structured quality gaps management process to support evidence-based mobility planning. The research begins with a systematic review of the literature, identifying conceptual fragmentation and the absence of a unified multimodal perspective. Building on this foundation, a new definition of multimodal transport quality is proposed and operationalised through the Logical Framework Approach (LFA). A first rigorous methodological phase is dedicated to the selection of Key Quality Parameters (KQPs), combining expert judgements, AHP-derived weighting, Monte Carlo simulations, and citation/bibliometric validation. This integrated process leads to a robust and transferable set of KQPs suitable for diverse urban contexts. A second methodological phase focuses on the measurement of these parameters through both objective and subjective measurements. Objective measurements are based on the Mystery Client (MC), while subjective measurements are captured through the Customer Satisfaction (CS). MC and CS represent the two tools used to carry out objective and subjective quality measurements, referring specifically to the four quality dimensions: designed, delivered, perceived, and expected. Finally, a third methodological phase addresses the management dimension, identifying quality gaps across the four quality dimensions, and translating these gaps into targeted preventive or corrective measures. The quality assessment framework is applied to the case study of Verona, where multimodal quality is assessed through both MC field measurements and Customer Satisfaction CS surveys. The integrated evaluation of designed, delivered, perceived, and expected quality enables a detailed Quality Gap Analysis, revealing substantial misalignments across criteria and the analysed O-D pairs. The findings support the formulation of targeted preventive and corrective measures aimed at improving accessibility, availability, comfort, customer care, environmental impact, information, safety & security, and time. Overall, the thesis advances the scientific understanding of multimodal quality and offers a transferable, policy-relevant tool for guiding strategic decisions in sustainable urban mobility planning. The framework provides public authorities and operators with a structured, user-centred approach to diagnosing and monitoring system quality and designing effective interventions, contributing to more efficient and sustainable multimodal mobility systems.| File | Dimensione | Formato | |
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https://hdl.handle.net/20.500.14242/384753
URN:NBN:IT:UNIBS-384753