数字产业集群政策是否推动了区域创新合作？——基于生产性与非生产性关联视角

朱世婧

（南开大学）

摘要：推动区域创新合作是应对未来全球科技与产业竞争、提升国家创新体系整体效能的关键举措。本文以数字产业集群政策为切入点，使用2009—2023年跨城联合申请专利数量衡量地区间创新合作水平，并从生产性关联与非生产性关联两个维度分析数字产业集群政策对区域创新合作的影响及其作用机制。研究结果表明，数字产业集群建设能够有效推动区域创新合作。机制分析发现，生产性关联通过商品贸易深化分工合作，依托数字技术加速资本流动以支撑创新合作；非生产性关联则通过增强正式制度协同与非正式制度联系降低合作不确定性，并推动人才集聚、知识溢出以提升创新资源配置效率，共同强化区域创新合作成效。异质性分析结果显示，数字产业集群建设对区域创新合作的正向作用在整体上有助于突破地理限制，促进边缘地区和中西部地区更广泛地融入区域创新网络。本文的研究为深入理解城市发展的动力活力，贯彻落实中央城市工作会议精神，推动城市发展取得新成就提供有益启示。

关键词：数字产业集群政策；创新合作；非生产性关联；区域创新；知识溢出

作者简介：朱世婧，南开大学经济学院博士研究生，通信作者，天津，300071。

基金项目：国家社会科学基金重点项目“生态位视域下现代化城市发展动力及空间形态演化研究”（24AJY018）

引用格式：朱世婧. 数字产业集群政策是否推动了区域创新合作？：基于生产性与非生产性关联视角[J]. 经济与管理研究，2026，47（8）：136-151.

Has the Digital Industrial Cluster Policy Boosted Regional Innovation Cooperation?

—From the Perspective of Productive and Non-Productive Linkages

ZHU Shijing

(Nankai University, Tianjin 300071)

Abstract: Promoting regional innovation cooperation is a critical measure for addressing future global competition in technology and industry and enhancing the overall efficiency of national innovation systems. From 2013 to 2017, the Ministry of Science and Technology of China launched three batches of Innovative Industrial Cluster pilots, among which 24 clusters were explicitly designated as digital industrial clusters (DIC). A comparison between pilot and non-pilot regions reveals that the number of patent cooperation applications in both regions has shown a continuous upward trend over time. However, the gap between pilot and non-pilot regions has been widening, providing preliminary evidence of the promoting effect of the DIC policy on regional innovation cooperation.

This paper treats the implementation of the DIC policy as a quasi-natural experiment and employs a difference-in-differences (DID) approach to evaluate the impact of the policy on regional innovation cooperation. The empirical results indicate that the DIC policy enhances regional innovation cooperation.

Then, this paper explores the underlying mechanisms based on a productive–non-productive integration framework. The analysis of productive linkages covers two dimensions: commodity markets and factor markets. In commodity markets, the DIC policy expands commodity trade to deepen the division of labor and collaboration, ultimately supporting innovation cooperation. In factor markets, the policy prioritizes rapid linkages and flexible allocation of highly mobile capital across cities, effectively supporting high-risk and highly uncertain innovation cooperation. The analysis of non-productive linkages focuses on institutional and technological linkages. For institutional linkages, the DIC policy strengthens inter-regional institutional connections through the construction of both formal and informal institutions, thereby enhancing the willingness for regional innovation cooperation. Regarding technological linkages, the DIC policy improves the efficiency of innovation resource allocation by promoting talent aggregation, knowledge spillovers, and technological complementarity, collectively strengthening the outcomes of regional innovation cooperation.

In the heterogeneity analysis, this paper examines both distance heterogeneity and city-pair heterogeneity. The analysis of distance heterogeneity suggests that the DIC construction coordinates with the transportation infrastructure policy to shape new models of innovation cooperation. The analysis of city-pair heterogeneity indicates that the DIC policy helps transform established patterns of innovation distribution, break geographical constraints, and enhance core radiation, enabling greater participation of the peripheral, central, and western regions.

This paper provides valuable insights for grasping the intrinsic requirements of urban development vitality, implementing the guiding principles of the Central Urban Work Conference, and achieving new accomplishments in urban development.

Keywords: digital industrial cluster policy; innovation cooperation; non-productive linkage; regional innovation; knowledge spillover

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