数智化赋能城市绿色低碳转型——基于空间溢出效应研究

Digital Intelligence Empowers Urban Green and Low-Carbon Transition—Based on the Study of Spatial Spillover Effects

摘要: 推动城市绿色低碳转型是实现高质量发展与践行“双碳”战略的必由之路，充分发挥数智化的赋能作用则是加快这一转型进程的关键引擎。本文选取2014~2023年全国277个地级市的面板数据，运用熵权法构建数智化指标体系，通过构建多种计量模型系统检验数智化对城市碳排放强度的影响机制、非线性关系及空间溢出效应。结果表明：第一，数智化对城市碳排放强度具有显著的抑制作用，能有效推动城市绿色低碳转型，且这一结论具有稳健性；第二，数智化的碳减排效应存在显著异质性，在非资源型城市、大城市及东部地区更加明显；第三，数智化主要通过产业结构升级、绿色技术创新、资源配置优化三条路径驱动城市绿色低碳转型；第四，数智化对城市碳排放强度的影响存在基于其自身发展水平的门槛效应；第五，数智化发展对碳排放强度存在显著的空间溢出效应。本研究为数智化赋能城市绿色低碳转型提供了经验证据，也为政府制定分层分类的低碳转型政策提供了理论参考与实践依据。

Abstract: Promoting urban green and low-carbon transition is an inevitable path to achieving high-quality development and implementing the dual carbon strategy, and leveraging the enabling role of digital intelligence is a key engine to accelerate this process. Using panel data of 277 prefecture-level cities in China from 2014 to 2023, this paper constructs a digital intelligence index system via the entropy weight method, and systematically examines the nonlinear relationship and spatial spillover effect of digital intelligence on urban carbon emission intensity through multiple econometric models. The results show that: 1) Digital intelligence significantly inhibits urban carbon emission intensity and effectively promotes urban green and low-carbon transition, and this conclusion is robust. 2) The carbon emission reduction effect of digital intelligence exhibits significant heterogeneity, being more pronounced in non-resource-based cities, large cities, and eastern regions. 3) Digital intelligence drives urban green and low-carbon transition mainly through three channels: industrial structure upgrading, green technology innovation, and resource allocation efficiency optimization. 4) The impact of digital intelligence on carbon emission intensity has a threshold effect based on its own development level. 5) Digital intelligence development generates a significant spatial spillover effect on carbon emission intensity. This study provides empirical evidence for digital intelligence enabling urban green and low-carbon transition, and offers theoretical reference and practical basis for governments to formulate differentiated and categorized low-carbon transformation policies.