Assessing the user acceptance of mobility-as-a-service platforms: a case study of Shenzhen, China

Purpose This study aims to explore the factors influencing user acceptance of mobility-as-a-service (MaaS) platforms in Shenzhen and to provide recommendations for future implementation and development. Design/methodology/approach Using data from 232 valid questionnaires collected from Shenzhen residents, this study applies the Unified Theory of Acceptance and Use of Technology to construct a structural equation model for MaaS acceptance. Relevant hypotheses were proposed and tested using analysis of variance. Findings The results indicate that comfort attitude, effort expectancy and performance expectancy considerably and positively influence users’ willingness to accept MaaS platforms. Performance expectancy mediates the effect of effort expectancy on willingness to accept. Although social influence had a positive impact, it was not significant. Research limitations/implications This study is primarily limited to Shenzhen and may not fully reflect the acceptance of MaaS by residents in other cities or regions. Moreover, the research relies solely on survey data, which may be subject to self-reporting biases. Future research should expand to a broader geographical area and consider using actual behavioral data to enhance the reliability and generalizability of the results. Practical implications The findings are significantly relevant for policymakers and urban transport planners. Understanding the key factors influencing residents’ acceptance of MaaS, such as comfort and performance expectancy, can enhance the design and promotion of MaaS projects to achieve higher user attraction and satisfaction. Emphasizing the simplification of user interfaces and operation processes can improve user experience and foster widespread adoption. Social implications The study reveals that social influence has a minimal impact on MaaS acceptance, suggesting that public education and promotional strategies need to be redesigned to focus more on communicating personal benefits and specific advantages. Additionally, emphasizing the role of MaaS in increasing public transport usage and reducing private car dependency could help promote sustainable transportation development and improve urban traffic conditions. Originality/value This study provides a comprehensive analysis of the factors affecting MaaS acceptance in Shenzhen, offering new insights into user behavior within the context of urban mobility. This study contributes to the understanding of user acceptance in developing regions and proposes actionable recommendations, including pilot projects and service plans, to support the effective deployment of MaaS platforms in Shenzhen.

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Publication Details

Journal
Industrial Management & Data Systems
Published
2025-04-01
DOI
https://doi.org/10.1108/imds-10-2024-1017
Citations
3
Primary Topic
Transportation and Mobility Innovations
Type
article
Field-Weighted Citation Impact
2.05
Controls
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article

Assessing the user acceptance of mobility-as-a-service platforms: a case study of Shenzhen, China

Yinlian Zeng, Le Yu, Zhipeng Cai, Yating Liu et al.
3 citations
Industrial Management & Data Systems
Transportation and Mobility Innovations
2.05
article

Assessing the user acceptance of mobility-as-a-service platforms: a case study of Shenzhen, China

Yinlian Zeng, Le Yu, Zhipeng Cai, Yating Liu, Siyuan Yu
article en
3 citations

Abstract

Purpose This study aims to explore the factors influencing user acceptance of mobility-as-a-service (MaaS) platforms in Shenzhen and to provide recommendations for future implementation and development. Design/methodology/approach Using data from 232 valid questionnaires collected from Shenzhen residents, this study applies the Unified Theory of Acceptance and Use of Technology to construct a structural equation model for MaaS acceptance. Relevant hypotheses were proposed and tested using analysis of variance. Findings The results indicate that comfort attitude, effort expectancy and performance expectancy considerably and positively influence users’ willingness to accept MaaS platforms. Performance expectancy mediates the effect of effort expectancy on willingness to accept. Although social influence had a positive impact, it was not significant. Research limitations/implications This study is primarily limited to Shenzhen and may not fully reflect the acceptance of MaaS by residents in other cities or regions. Moreover, the research relies solely on survey data, which may be subject to self-reporting biases. Future research should expand to a broader geographical area and consider using actual behavioral data to enhance the reliability and generalizability of the results. Practical implications The findings are significantly relevant for policymakers and urban transport planners. Understanding the key factors influencing residents’ acceptance of MaaS, such as comfort and performance expectancy, can enhance the design and promotion of MaaS projects to achieve higher user attraction and satisfaction. Emphasizing the simplification of user interfaces and operation processes can improve user experience and foster widespread adoption. Social implications The study reveals that social influence has a minimal impact on MaaS acceptance, suggesting that public education and promotional strategies need to be redesigned to focus more on communicating personal benefits and specific advantages. Additionally, emphasizing the role of MaaS in increasing public transport usage and reducing private car dependency could help promote sustainable transportation development and improve urban traffic conditions. Originality/value This study provides a comprehensive analysis of the factors affecting MaaS acceptance in Shenzhen, offering new insights into user behavior within the context of urban mobility. This study contributes to the understanding of user acceptance in developing regions and proposes actionable recommendations, including pilot projects and service plans, to support the effective deployment of MaaS platforms in Shenzhen.

Industrial Management & Data SystemsVol. 126(1)
Chinese University of Hong Kong, Shenzhen (CN), Shenzhen Technology University (CN)
Openalex Percentile: Top 14%
Transportation and Mobility Innovations
2.05
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