管理评论 ›› 2023, Vol. 35 ›› Issue (9): 300-311.

• 公共管理 • 上一篇    下一篇

工业机器人应用对城市空气污染治理的影响研究

李宏兵, 郑庆彪, 李震, 孙丽棠   

  1. 北京邮电大学经济管理学院, 北京 100876
  • 收稿日期:2022-01-04 出版日期:2023-09-28 发布日期:2023-10-31
  • 通讯作者: 李震(通讯作者),北京邮电大学经济管理学院讲师,博士。
  • 作者简介:李宏兵,北京邮电大学经济管理学院教授,博士生导师,博士;郑庆彪,北京邮电大学经济管理学院,硕士;孙丽棠,北京邮电大学经济管理学院博士研究生。
  • 基金资助:
    国家社会科学基金一般项目(22BJL095)。

Industrial Intelligence and Urban Air Pollution Control in China: Empirical Evidence from the Application of Industrial Robots

Li Hongbing, Zheng Qingbiao, Li Zhen, Sun Litang   

  1. School of Economics and Management, Beijing University of Posts and Telecommunications, Beijing 100876
  • Received:2022-01-04 Online:2023-09-28 Published:2023-10-31

摘要: 本文基于国际机器人联合会(IFR)的工业机器人应用数据和中国地级及以上城市层面PM2.5排放浓度数据,利用2SLS、空间计量模型等多种计量方法,实证检验了工业机器人应用对城市空气污染治理的影响。研究发现,工业机器人应用显著降低了中国城市空气污染水平,这一效应在金融发展程度较高、财政支持较低、信息基础设施建设水平较高以及智慧城市试点城市中表现更加明显,且在地理区位特征上呈现出显著的异质性。同时,上述影响主要通过城市产业结构升级和科技水平提升的机制实现。基于SAR与SDM模型的空间溢出效应分析,也发现城市工业机器人应用的减污效应具有双向空间溢出效应,因此空气污染的地理相关性使其减污效应被低估。

关键词: 工业智能化, 空气污染, 减污效应, 空间溢出效应

Abstract: Based on industrial robot application data from the International Federation of Robotics (IFR) and the global PM2.5 emissions concentration data provided by Atmospheric Composition Analysis Group (ACAG), we study the influence of industrial intelligence on air pollution control in China's cities by using bidirectional fixed effects model, 2SLS, spatial econometric model and so on. We find that industrial robot application significantly reduces the level of China's urban air pollution. This effect is more obvious in cities with higher-level financial development, lower-level financial support, higher level information infrastructure construction and smart city pilot demonstration. Moreover, there is obvious heterogeneity in geographical location characteristics. At the same time, the above effect is mainly achieved through the transformation and upgrading of urban industrial structure, and the improvement of scientific and technological level. Based on the spatial spillover effect analysis of SAR and SDM models, it is also found that the pollution reduction effect of urban industrial robot application has a two-way spatial spillover effect. Therefore, the geographical correlation of air pollution causes the pollution reduction effect to be underestimated.

Key words: industrial intelligence, air pollution, pollution reduction effect, spatial spillover effect