人工智能对全民健身公共服务资源配置效率的影响来自省级面板数据的经验证据

    Impact of Artificial Intelligence on Resource Allocation Efficiency of Public Service for Sports and FitnessEmpirical Evidence Based on Provincial Panel Data

    • 摘要: 全民健身公共服务资源配置长期存在供需错配、信息不对称与跨部门协同不畅等问题,制约配置效率的提升,人工智能的快速发展为破解此类难题提供了新的可能路径。基于战略三角观,选取2013—2022年我国30个省级面板数据,运用双重机器学习模型,实证考察人工智能对全民健身公共服务资源配置效率的影响,并对体育产业结构升级、技术扩散与政府治理能力3条路径进行检验。研究发现:1)人工智能显著提升全民健身公共服务资源配置效率,可有效缓解既有配置损耗;2)人工智能通过推动体育产业结构升级与加快技术扩散2条路径实现效率提升,而政府治理能力路径未通过显著性检验,反映出跨部门数据共享与制度协同仍是当前“人工智能+”赋能全民健身的关键梗阻;3)宏观环境与体育发展环境均能强化人工智能对配置效率的提升。基于研究发现,提出推动体育产业智能化升级、构建人工智能技术扩散网络、破解政府治理能力路径的制度瓶颈和实施差异化推进策略等政策建议。

       

      Abstract: Resource allocation of public service for sports and fitness is suffered from efficiency losses such as supply-demand mismatch, information asymmetry, and poor cross-departmental coordination for a long time, the rapid development of artificial intelligence (AI) offers a promising solution for these problems. Drawing on the strategic triangle perspective and using panel data from 30 provinces of China from 2013 to 2022, this study employs a double machine learning model to examine the impact of AI on the resource allocation efficiency of public service for sports and fitness, with a parallel test of three concurrent pathways: sports industrial structure upgrading, technology diffusion, and government governance capacity. The results shows that: 1) AI can significantly improve the resource allocation efficiency of public service for sports and fitness, and can effectively mitigate the existing allocation losses. 2) AI enhances efficiency by promoting sports industrial structure upgrading and accelerating technology diffusion, whereas the government governance capacity fails to pass the significance test, reflecting that cross-departmental data sharing and institutional coordination remain critical bottlenecks for the AI+ initiative in empowering national fitness. 3) Both macro-environment and sports-specific environment strengthens AI’s positive effect on resource allocation efficiency. Based on these findings, this study provides following recommendations: promoting intelligent upgrading of the sports industry, building technology diffusion networks, removing governance barriers, and implementing differentiated allocation strategies.

       

    /

    返回文章
    返回