关键词: 政务数字人, 数字政府, 公众接纳意愿, 期望一致, 技术接受

Abstract:

[Purpose/Significance] In the digital age, government digital avatars represent a significant innovative application of the integration of generative artificial intelligence and digital government. These digital avatars aim to enhance the efficiency, accessibility, and responsiveness of public services. This study aims to explore the factors and pathways that influence public acceptance of government digital avatars, providing a theoretical basis and practical insights for improving these services and enhancing the user experience. Unlike previous studies that have focused primarily on technological and functional aspects, this research emphasizes users' perceptions and expectations, filling the gap in existing research on user experience. This innovation of this paper lies in the integration of the Expectation Confirmation Theory (ECT) and the Technology Acceptance Model (TAM) and the extension of other user perception factors to systematically analyze how these factors together influence public acceptance. [Method/Process] The study adopts a comprehensive approach, integrating the Expectation Confirmation Theory (ECT) and the Technology Acceptance Model (TAM), and extends the framework to include additional user perception factors such as perceived information quality, perceived intelligence, perceived convenience, perceived attractiveness, perceived usefulness, and AI trust. Structured questionnaires were used to collect data from a diverse sample, measuring constructs such as expectation confirmation, satisfaction, and various user perception factors. The data were analyzed using structural equation modeling (SEM), which provides robust statistical insights into the relationships between these constructs. In addition, mediation effect models were used to examine indirect effects, providing a comprehensive understanding of how these factors influence public acceptance. Data were collected from a diverse group of respondents to ensure the findings are broadly applicable and representative. [Results/Conclusions] The results suggest that expectation confirmation significantly increases public satisfaction with government digital avatars, which in turn positively affects their acceptance. Perceived information quality, perceived intelligence, perceived convenience, perceived attractiveness, perceived usefulness, and AI trust serve as critical mediators in this relationship. In particular, high levels of perceived quality and intelligence significantly increase satisfaction and acceptance, while convenience and attractiveness also play an important role. AI trust emerges as a critical factor, mediating the impact of user perceptions on acceptance. However, the study does have some limitations. First, the lack of understanding of the professional backgrounds of the research population may lead to differences in acceptance between different professional groups. Future research should look more closely at different occupational groups to gain a fuller understanding. Second, the sample consisted mainly of respondents from younger demographic groups, which may affect the generalizability of the conclusions. Future research should broaden the geographical and demographic coverage of the sample to increase diversity and representativeness. In addition, the lack of qualitative research limits the depth of understanding of users' deep-seated views and needs about government digital avatars. Future research should include qualitative components, such as in-depth interviews and focus group discussions, to explore the actual experiences and specific needs of users and to complement the quantitative findings. This study provides practical recommendations for improving user satisfaction and acceptance, and for supporting the development of effective digital governance solutions. By specifically optimizing government digital avatar services, public satisfaction and trust in digital government services can be increased, further promoting the application and development of digital avatar technology in digital government.

Key words: government digital human avatar, digital government, public acceptance intention, ECT, TAM