Under the dual impetus of China's digitalization strategy and rural revitalization initiatives, rural social governance has entered a key phase of digital transformation. As artificial intelligence (AI) and big data technologies are increasingly integrated into governance platforms, the capacity for AI-augmented human-data collaboration is becoming essential to effective multi-stakeholder interaction. Sustainable multi-stakeholder collaboration (SMC) represents both a core requirement and central value of rural digital governance. This study investigates the determinants of SMC and proposes strategies to enhance stakeholder synergy. Through grounded theory analysis of semi-structured interviews with 26 rural digital governance practitioners, six key factors were identified: (1) awareness intensity, (2) technical adaptability, (3) institutional completeness, (4) scenario compatibility, (5) interest relevance, and (6) situational appeal. These factors were validated via structural equation modeling (SEM) using 1,370 questionnaire responses. The results show that all six factors significantly promote SMC (β = 0.109–0.184, p < 0.001), with awareness intensity and interest relevance having stronger effects. Based on the findings, this study proposes strategies including strengthening publicity and guidance, implementing tiered training, promoting data interoperability, safeguarding public rights, optimizing evaluation mechanisms, and refining institutional frameworks to support sustainable collaboration. This research advances understanding of sustainable governance and provides insights for policy development and implementation of digital technologies in rural China. By highlighting the cognitive and technological dimensions of stakeholder collaboration, it offers an empirical basis for integrating AI-supported human-data interaction into rural governance, paving the way for more adaptive and inclusive digital governance systems.
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Xiaofang Yan
Academy of Medical Sciences
Hong Chen
Tianjin University
Disability and Rehabilitation Assistive Technology
Hunan Agricultural University
Chongqing Technology and Business University
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Yan et al. (Fri,) studied this question.
synapsesocial.com/papers/68d90a0641e1c178a14f650b — DOI: https://doi.org/10.1080/17483107.2025.2564370