Abstract:

The Third Plenary Session of the Twentieth Central Committee of the Communist Party of China proposed “improving the institutional mechanisms for developing new quality productive forces in accordance with local conditions,” providing a strategic guideline for advancing the transformation and upgrading of regional productivity. As a new form of productive force characterized by innovation-driven dynamics and efficiency-oriented goals, the development of new quality productive forces is crucial for enhancing regional vitality and restructuring economic systems toward high-quality development. However, the implementation of this national strategy at the local level has revealed significant challenges, particularly the trend of policy convergence and homogeneous industrial planning across regions, which risks undermining local comparative advantages and aggravating inefficient competition.

Drawing on the theory of government attention, which posits that the allocation of attention determines the prioritization of policy resources and institutional efforts, this study investigates how local governments interpret and implement the central directive on new quality productive forces. Specifically, the study collects and analyzes political affairs texts related to new quality productive forces, published on the official websites of thirty provincial-level governments between 2023 and 2024. Using topic modeling based on the BERTopic algorithm, generative artificial intelligence techniques, and machine learning methods such as the random forest algorithm, the study systematically identifies the focus areas of government attention and examines their regional variations.

The findings reveal three major patterns. First, local governments demonstrate a structure of “five-dimensional focus and coexistence of dual tendencies” in their attention, covering five domains: new means of labor, new types of laborers, industrial sectors, application scenarios, and enabling environments. This indicates both differentiated governance strategies and converging policy orientations across regions. Second, policy imitation behavior is prevalent and primarily manifests as “late-developing region catch-up” and “peer-level learning.” This results in a spatial paradox in which industrial policy similarity increases with geographical distance, reflecting a widespread tendency to emulate economically advanced regions regardless of local resource endowments or development conditions. Third, regional heterogeneity in governance strategies is evident. Eastern provinces, which possess strong innovation capabilities and relatively high fiscal autonomy, tend to demonstrate desirable convergence characterized by targeted adaptation. In contrast, central provinces, constrained by weak industrial foundations and fragmented development trajectories, are more prone to undesirable convergence and may fall into a governance dilemma of “resource involution.”

To address the risks of excessive policy convergence and foster truly localized development of new quality productive forces, this study proposes three governance recommendations. First, the central government should strengthen top-level design, promote layered and classified policy guidance, improve regional coordination mechanisms, and align national strategies with the specific conditions and needs of localities. Second, local governments should enhance regional cooperation and policy synergy, avoid blind imitation, and build cross-regional industrial cooperation platforms to promote rational division of labor and resource allocation. Third, governments at all levels should coordinate differentiated innovation strategies in key industries with the collaborative development of related sectors, clarify industrial roles based on regional development stages, and prevent inefficient duplication. These recommendations aim to support a more adaptive, efficient, and coordinated institutional framework for the development of new quality productive forces in China.

Key words: new quality productivity forces, place-based adaptation, attention allocation, governance

摘要：

党的二十届三中全会提出“健全因地制宜发展新质生产力体制机制”。作为创新驱动、效率导向的先进生产力形态,新质生产力对激发区域动能、优化经济结构具有重要意义。基于政府注意力理论,本文运用BERTopic、生成式人工智能与机器学习方法,对2023-2024年间30省市政府门户网站的时政动态文本进行分析,识别地方政府对新质生产力的关注重点与区域特征。研究发现:(1)地方政府注意力呈现“五维度聚焦、双重性并存”的特征,涵盖新型劳动资料、新型劳动者、产业领域、应用场景与支撑环境5个方面,体现区域治理路径的差异性与政策取向的趋同性。(2)政策模仿行为以“后发追赶型”与“同群借鉴型”为主,呈现出“地理距离越远、产业注意力越趋同”的空间悖论。(3)东部地区因创新能力强、财政自主性高,更倾向于合意性趋同;而中部地区因产业基础薄弱、发展路径碎片化,易陷入非合意性趋同甚至“资源内卷化”的治理困境。总体而言,本文从注意力配置视角揭示了地方在新质生产力治理中的策略分化,为推动因地制宜的发展机制提供理论支撑与实证依据。

关键词: 新质生产力, 因地制宜, 注意力分配, 政府治理