Research on MaaS Usage Intention and Influence Mechanism

To promote the sustainable development of urban smart transportation systems, this study constructs a structural equation model (SEM) based on the Technology Acceptance Model (TAM), incorporating extended variables including social influence, environmental awareness, privacy concerns, and service similarity to investigate users’ behavioral intentions toward Mobility as a Service (MaaS). The research systematically examines key factors influencing user adoption behavior and their underlying mechanisms, providing theoretical foundations and practical guidance for optimizing MaaS system design and policy making. Using SEM as the core analytical framework, this study employs mediation analysis, moderation analysis, and multigroup comparison to empirically examine the direct and indirect effects among variables, as well as group heterogeneity. Data were collected through an online questionnaire survey, with Analysis of Variance (ANOVA) applied to identify the differential impacts of demographic and travel behavior characteristics on users’ intentions and related psychological constructs, thereby supporting precise user segmentation and evidence-based policy interventions. Key findings include the following: (1) Social influence, ease of use, and environmental awareness boost MaaS adoption, while privacy concerns hinder it. (2) Freelancers/self-employed weaken the positive effects of usefulness, ease of use, and social influence on adoption. (3) Service similarity and ease of use effects vary significantly between single-mode and multimodal commuters. The findings extend the theoretical boundaries of TAM and provide both theoretical and practical support for the development of sustainable urban transportation systems.

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Publication Details

Journal
Applied Sciences
Published
2025-08-28
DOI
https://doi.org/10.3390/app15179453
Citations
1
Primary Topic
Service-Oriented Architecture and Web Services
Type
article
Field-Weighted Citation Impact
3.25
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article

Research on MaaS Usage Intention and Influence Mechanism

Yao Zhang, Anning Ni, Linjie Gao, Fengyu Guo et al.
1 citations
Applied Sciences
Service-Oriented Architecture and Web Services
3.25
article

Research on MaaS Usage Intention and Influence Mechanism

Yao Zhang, Anning Ni, Linjie Gao, Fengyu Guo, Xu Zhao
article en
1 citations

Abstract

To promote the sustainable development of urban smart transportation systems, this study constructs a structural equation model (SEM) based on the Technology Acceptance Model (TAM), incorporating extended variables including social influence, environmental awareness, privacy concerns, and service similarity to investigate users’ behavioral intentions toward Mobility as a Service (MaaS). The research systematically examines key factors influencing user adoption behavior and their underlying mechanisms, providing theoretical foundations and practical guidance for optimizing MaaS system design and policy making. Using SEM as the core analytical framework, this study employs mediation analysis, moderation analysis, and multigroup comparison to empirically examine the direct and indirect effects among variables, as well as group heterogeneity. Data were collected through an online questionnaire survey, with Analysis of Variance (ANOVA) applied to identify the differential impacts of demographic and travel behavior characteristics on users’ intentions and related psychological constructs, thereby supporting precise user segmentation and evidence-based policy interventions. Key findings include the following: (1) Social influence, ease of use, and environmental awareness boost MaaS adoption, while privacy concerns hinder it. (2) Freelancers/self-employed weaken the positive effects of usefulness, ease of use, and social influence on adoption. (3) Service similarity and ease of use effects vary significantly between single-mode and multimodal commuters. The findings extend the theoretical boundaries of TAM and provide both theoretical and practical support for the development of sustainable urban transportation systems.

Applied SciencesVol. 15(17)
Shanghai Jiao Tong University (CN)
Openalex Percentile: Top 7%
Service-Oriented Architecture and Web Services
3.25
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Research on MaaS Usage Intention and Influence Mechanism — Yao Zhang, Anning Ni, et al. · Applied Sciences (2025) | TGRS Research Map | TGRS