Proceedings of the 3rd International Conference on Big Data Economy and Digital Management, BDEDM 2024, January 12–14, 2024, Ningbo, China

Research Article

A Study on the Influencing Factors of Digital Governance Capacity Based on Technology Acceptance Model

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  • @INPROCEEDINGS{10.4108/eai.12-1-2024.2347166,
        author={Wenyan  Pan and Shengwei  Chu and Weipeng  Zhang and Ju  Wang and Zheng  Dong},
        title={A Study on the Influencing Factors of Digital Governance Capacity Based on Technology Acceptance Model},
        proceedings={Proceedings of the 3rd International Conference on Big Data Economy and Digital Management, BDEDM 2024, January 12--14, 2024, Ningbo, China},
        publisher={EAI},
        proceedings_a={BDEDM},
        year={2024},
        month={6},
        keywords={digital government; technology acceptance model; innovation diffusion theory; structural equation modelling},
        doi={10.4108/eai.12-1-2024.2347166}
    }
    
  • Wenyan Pan
    Shengwei Chu
    Weipeng Zhang
    Ju Wang
    Zheng Dong
    Year: 2024
    A Study on the Influencing Factors of Digital Governance Capacity Based on Technology Acceptance Model
    BDEDM
    EAI
    DOI: 10.4108/eai.12-1-2024.2347166
Wenyan Pan1,*, Shengwei Chu1, Weipeng Zhang1, Ju Wang1, Zheng Dong2
  • 1: Wuhan University of Technology
  • 2: Technical University of Denmark
*Contact email: panwenyan@whut.edu.cn

Abstract

Building a digital government in China presents new opportunities and challenges in the context of the technological revolution. It is fundamental for Internet power and digital China strategy, supporting innovative governance concepts, forming a new pattern of digital governance and promoting a service-oriented government. This paper focuses on factors that influence public willingness to use digital government technologies. By integrating innovation diffusion theory with the technology acceptance model framework, a research model is constructed, and data from 314 questionnaires are used for empirical testing. Results show that the model can explain 42% of public behavioral intention to use digital government technologies, providing new ideas for subsequent promotion.