Ecology and Environmental Sciences ›› 2026, Vol. 35 ›› Issue (10): 1649-1660.DOI: 10.16258/j.cnki.1674-5906.2026.10.014

• Research Article [Environmental Science] • Previous Articles    

Digital Economy Driven Ecological Transition in Northeast China’s Counties: Urban-Rural Transmission Mechanism and Spatial Effects

Li Ji(), Yang Ronghui*()   

  1. School of Business Administration, Lanzhou University of Finance and Economics, Lanzhou 730020, P. R. China
  • Received:2026-03-30 Revised:2026-08-21 Accepted:2026-09-04 Online:2026-10-18 Published:2026-10-21

数字经济驱动东北县域生态转型与城乡融合的协同演化与空间效应

李季(), 杨蓉慧*()   

  1. 兰州财经大学工商管理学院, 甘肃 兰州 730020
  • 通讯作者: E-mail: 2541830490@qq.com
  • 作者简介:李季(1983年生),男,副教授,博士,主要研究方向为企业环境创新与技术管理,土地利用与规划管理等。E-mail: 512625974@qq.com
  • 基金资助:
    甘肃省软科学项目(25JRZA084);甘肃省自然科学基金项目(26JRRA678);甘肃省教育厅“创新之星”项目(2026CXZX-900)

Abstract:

[Objective] This study aims to investigate the synergistic evolutionary relationship among the digital economy, ecological transition, and urban-rural integration in county-level areas of Northeast China and to reveal the spatial spillover effects and transmission mechanisms through which the digital economy influences ecological transition. By focusing on counties, this study provides a more refined understanding of the green effects of digitalization in old industrial and resource-dependent regions. [Methods] Based on balanced panel data for 147 counties in Liaoning, Jilin, and Heilongjiang from 2010 to 2024, comprehensive evaluation index systems were constructed for the digital economy, ecological transition, and urban-rural integration. Each system comprised four dimensions and 16 indicators. The entropy method was used to measure the development levels of the three systems. A coupling coordination model was employed to evaluate their synergistic development, while the Dagum Gini coefficient was applied to decompose regional disparities. Global Moran’s I was used to examine spatial autocorrelation. A two-way fixed-effects Spatial Durbin Model (SDM) was constructed to identify the direct and spatial spillover effects of the digital economy on ecological transition, and a mediating effect model was used to examine the transmission role of urban-rural integration. Heterogeneity analyses were conducted according to resource endowment, spatial location, and digital foundation. [Results] From 2010 to 2024, the development levels of the three systems increased continuously. The digital economy index increased from 0.213 to 0.601, representing a cumulative growth rate of 182%, which exceeded the growth rates of ecological transition (96.5%) and urban-rural integration (122%). The coupling coordination degree increased from 0.346 to 0.667, indicating a transition from mild imbalance to moderate coordination. Regional disparities generally narrowed, although intra-regional differences remained the dominant source of disparity, accounting for 39.4% of the total. Synergistic development exhibited significant positive spatial autocorrelation, with Global Moran’s I increasing from 0.184 to 0.336. The digital economy significantly promoted ecological transition, with direct and indirect effects of 0.218 and 0.146, respectively; the indirect effect accounted for 40.1% of the total effect. Urban-rural integration exerted a significant partial mediating effect, accounting for 28.9% of the total effect. The ecological promotion effect was stronger in non-resource-based counties (0.294), core urban agglomeration counties (0.315), and highly digitized regions (0.347) than in resource-based counties (0.186), peripheral counties (0.174), and low-digitized regions (0.139). [Conclusion] The digital economy, ecological transition, and urban-rural integration in Northeast China’s counties exhibit an increasingly coordinated and spatially interconnected evolutionary pattern. The digital economy not only directly promotes ecological transition but also generates cross-regional spillovers, while urban-rural integration serves as an important transmission pathway. The green effects of digitalization demonstrate significant spatial and contextual heterogeneity. Therefore, differentiated development strategies should be adopted according to county characteristics, while cross-regional collaborative governance should be strengthened to enhance spatial spillovers and promote coordinated digital, ecological, and urban-rural development in Northeast China.

Key words: digital economy, ecological transition, urban-rural integration, spatial spillover effects, three provinces of Northeast China

摘要:

【目的】探讨数字经济、生态转型与城乡融合的协同演化特征、空间关联及作用机制,揭示数字经济驱动东北县域绿色发展的内在逻辑,为老工业基地县域绿色转型与城乡协同发展提供经验证据。【方法】研究基于2010-2024年东北三省县域面板数据,构建“数字驱动-城乡传导-生态响应”三系统评价体系,综合运用熵值法、耦合协调模型、Dagum基尼分解、空间杜宾模型和中介效应模型,分析三系统协同发展特征、空间效应及作用路径。【结果】三系统综合发展水平持续提升,耦合协调度由0.346提高至0.667,由轻度失调演进至中度协调,区域内差异是协同发展不均衡的主要来源。三系统协同发展呈显著空间正相关,且数字经济对生态转型具有显著的直接促进和空间溢出效应,直接效应和间接效应分别为0.218和0.146。城乡融合发挥显著部分中介作用,中介效应占总效应的28.9%。)数字经济生态促进效应具有明显异质性,在非资源型县域、核心城市圈和高数字化地区更显著。【结论】东北县域数字经济、生态转型与城乡融合呈现协同增强但非同步演进特征,数字经济对生态转型具有本地驱动与空间扩散的双重作用,城乡融合构成重要传导路径;其绿色效应具有明显的条件依赖性,产业基础、区域联系和数字化水平是影响数字经济绿色效应释放的重要因素。

关键词: 数字经济, 生态转型, 城乡融合, 空间溢出效应, 东北三省

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