Abstract:

The Yellow River Basin functions as a crucial ecological barrier, a significant economic zone, and a vital area for poverty alleviation in China, playing an indispensable role in the nation’s socioeconomic development and ecological security. Historically recognized as the cradle of Chinese civilization, its fertile alluvial plains have sustained intensive agricultural production for millennia, facilitating dense population settlements and a relatively elevated level of urbanization compared to other inland regions. Simultaneously, the basin is endowed with abundant mineral resources, particularly coal, oil, natural gas, and rare earth elements whose extraction has propelled rapid industrialization since the mid-20th century. This dual foundation of longstanding agrarian activity and energy-intensive industry has positioned the basin as a strategic pillar within China’s national development framework. However, decades of intensive resource extraction have led to significant environmental degradation, including widespread soil erosion, desertification, water scarcity, and biodiversity loss. Resource utilization remains predominantly inefficient and extensive, with numerous industries continuing to operate with outdated technologies and obsolete production methods. These interrelated challenges underscore a central dilemma: how to reconcile urgent ecological restoration with sustained economic growth? The inherent fragility of the basin’s ecosystem constrains conventional pathways of industrial expansion, rendering traditional development models unsustainable. Consequently, fostering scientifically informed and coordinated development in the basin has emerged as a strategic priority not only for regional revitalization but also as a benchmark for China’s broader green transformation agenda. Therefore, resolving obstacles in national sustainable development requires achieving synergy between ecological protection (EP) and high-quality development (HQD). Digital technology appears as a transformational facilitator in this setting. Digitalization has emerged as a major force behind stability and expansion in China's economy due to its high resilience and cross-sectoral integration capabilities. Big data analytics, blockchain, cloud computing, artificial intelligence (AI), and the Internet of Things (IoT) provide previously unheard-of chances to optimize resource allocation, increase environmental monitoring, boost industrial efficiency, and facilitate smart governance. The following leads to a key study question: Can digital technology effectively act as a catalyst to achieve synergistic progress between HQD and EP in the Yellow River Basin? Understanding how technology innovation supports green transitions in intricate socio-ecological systems requires answering this question. Using panel data from 67 prefecture-level cities in the Yellow River Basin from 2011 to 2022, a period that includes both the rapid rollout of digital infrastructure and changing environmental regulatory frameworks, this research aims to thoroughly investigate this problem. Building a thorough assessment index system for both the EP and HQD dimensions is the first step in the study. Using a goal-criteria-indicator framework, the degree of coupling and coordination between ecological conservation and high-quality development is evaluated. Three criteria layers with 14 indicators—such as wastewater discharge per GDP unit, urban population density, and yearly average PM_2.5 concentration—are used to quantify ecological protection. Thirteen variables, including the GDP growth rate, the fiscal revenue to GDP ratio, and the Engel coefficient, are included in the three criteria tiers of high-quality development. The temporal and geographical dynamics of coordination between EP and HQD are quantitatively assessed using a modified Coupling Coordination Degree (CCD) model based on this framework. A Digital Economy Index is created using metrics pertaining to digital infrastructure and application levels to evaluate the impact of digital technology. Several approaches are then used to do econometric analysis. First, unobserved city-specific heterogeneity is controlled for using a Fixed Effects (FE) model. Second, the transmission routes via which digital technology affects CCD are identified using a Mediating Effect Model. Third, to account for spatial autocorrelation and network externalities that are inherent in digital diffusion processes, a Spatial Durbin Model (SDM) is used to capture any spillover effects among nearby cities. The empirical study yields five main implications: 1) A consistent upward trend in total CCD between EP and HQD suggests growing synergy. The middle and lower reaches exhibit significantly higher coordination levels than the upper reaches, indicating a clear spatial gradient. The economy of the upper reach remains underdeveloped with a monolithic industrial base, hindering its ability to meet HQD requirements. This disparity reflects structural imbalances. Conversely, substantial advancements in industrial reorganization and upgrading have occurred in the medium and lower levels, fostering closer alignment of economic and ecological objectives. 2) There is a statistically significant U-shaped relationship between digitization and CCD; it initially begins negatively before becoming positive beyond a certain threshold. This indicates that rebound effects or ineffective implementation may exacerbate resource consumption and environmental stress during the early phases of digital adoption. However, as digital maturity reaches a certain level, it facilitates systemic optimization, green innovation, and efficiency improvements, enhancing coordination. This finding is consistent across various robustness tests, including winsorization and sample truncation. 3) Three main mediating channels have been identified: Green Technological Innovation (as evidenced by utility model and green innovation patents), Human Capital Agglomeration and Energy-Saving Effects. Their estimated mediating effect shares are 25.2%, 17.4%, 14.3% and 23.7%, respectively. Notably, the total mediating proportion of Green Technological Innovation reaches 42.6%, confirming the centrality of these mechanisms. 4) The effects of digital technology vary greatly across sub-regions. The benchmark U-shaped relationship is replicated only by non-resource-based cities and the Guanzhong Plain Urban Agglomeration. Resource-dependent cities struggle to convert digital inputs into ecological-economic synergy due to structural rigidity and path dependence. 5) Digital technology creates a “siphon effect,” concentrating advantages in technologically advanced areas. However, at more developed stages, a beneficial “spillover effect” emerges, as innovations spread to other regions, promoting regional convergence. In light of these insights, three strategic proposals are put forth: First, develop a three-dimensional collaboration approach that integrates “green transformation, talent support, and technology empowerment.” This includes creating a technological application system encompassing “smart energy, intelligent transportation, and green manufacturing,” and launching a “Digital Yellow River Talent Program.” Second, establish a basin-wide coordinating organization and implement a distinct regional digital economy plan, fostering innovation highlands in urban clusters with advanced digital infrastructure. Third, to mitigate pollution rebound and optimize synergy, enhance digital statistics monitoring, strengthen fundamental systems for data property rights, trade, circulation, and income distribution, and implement a dynamic policy adjustment mechanism.

Key words: digital technology, Yellow River Basin, ecological protection, high-quality development, coupling coordination degree

摘要：

数字技术是否有助于黄河流域生态保护和高质量发展协同推进是关系到黄河流域绿色转型的核心问题之一。基于2011－2022年黄河流域67个地级城市的面板数据，选取经修正的耦合协调度模型，测度了黄河流域生态保护与高质量发展的耦合协调度，并采用固定效应模型、机制分析模型和空间杜宾模型考察了数字技术对该耦合协调度的影响机制和溢出效应。研究表明，1）黄河流域生态保护和高质量发展耦合协调度呈现U型增长的趋势，总体呈现中、下游地区高于上游地区的格局。2）黄河流域生态保护和高质量发展耦合协调度与数字技术之间呈现出先降低后升高的U型关系；运用多种稳健性检验方法得出该结果仍然成立。3）绿色技术创新（绿色发明和绿色实用新型专利）、人力资本积累、节能效应是数字技术提升耦合协调度的重要渠道，中介效应占比分别为25.2%、17.4%、14.3%和23.7%。4）数字技术对不同城市群、资源禀赋型城市的耦合协调度影响效果差异性较大。5）数字技术对耦合协调度的影响效果初期呈现虹吸效应，在成熟期则出现溢出效应。该研究可为数字技术发展及黄河流域全面绿色转型提供决策参考。

关键词: 数字技术, 黄河流域, 生态保护, 高质量发展, 耦合协调度