黄河流域绿色技术创新网络演化特征及其机制

向博文, 徐颖, 徐高峰

doi:10.13306/j.1672-3813.2026.01.003

复杂系统与复杂性科学 >

2026 , Vol. 23 >Issue 1: 17 - 25

DOI: https://doi.org/10.13306/j.1672-3813.2026.01.003

复杂网络

黄河流域绿色技术创新网络演化特征及其机制

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1.武汉大学城市设计学院, 武汉 430072;
2.华中科技大学建筑与城市规划学院, 武汉 430074;
3.北京交通大学建筑与艺术学院, 北京 100044

向博文(1993-),男,广东广州人,博士研究生,主要研究方向为创新网络演化。

收稿日期: 2024-01-17

修回日期: 2024-04-21

网络出版日期: 2026-02-13

基金资助

教育部“春晖计划”合作科研项目(HZKY20220044)

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Evolutionary Mechanism of Green Technology Innovation Network in the Yellow River Basin

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1. School of Urban Design, Wuhan University, Wuhan 430072,China;
2. School of Architecture and Urban Planning, Huazhong University of Science and Technology, Wuhan 430074,China;
3. School of Architecture and Design, Beijing Jiaotong University, Beijing 100044,China

Received date: 2024-01-17

Revised date: 2024-04-21

Online published: 2026-02-13

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摘要

为揭示黄河流域绿色技术创新合作格局及其影响因素,利用社会网络分析法与指数随机图模型分析2011—2019年黄河流域绿色技术创新网络的空间演化特征及其机制。研究发现:黄河流域绿色创新网络的规模与合作强度持续上升,但联系紧密度有所下降;黄河流域中上游地区在阶段1(2011—2013年)为西安单核心创新集群,并在阶段2(2017—2019年)分化为青海、宁—陕—豫和甘—内蒙古—晋3个创新集群;下游地区在阶段1分别形成济南、青岛单核心创新集群,并在阶段2整合为山东半岛城市群创新集群;组织与文化邻近有利于城际创新,但也强化了省域和文化的“边界效应”;城市群与流域并未形成“边界效应”,但所形成的政策和流域邻近性未能促进城际合作;地理与技术邻近、城市的经济规模、创新水平以及绿色创新水平对于城际创新合作呈正面影响。

本文引用格式

向博文, 徐颖, 徐高峰 . 黄河流域绿色技术创新网络演化特征及其机制[J]. 复杂系统与复杂性科学, 2026 , 23(1) : 17 -25 . DOI: 10.13306/j.1672-3813.2026.01.003

Abstract

To study the evolutionary mechanism of green technology innovation network in the Yellow River Basin, this study, using social network analysis and the index random graph model, analyzed the evolution characteristics and mechanisms of green technology innovation networks in the Yellow River Basin from 2011 to 2019. The findings are as follows: The scale and cooperation intensity of the innovation network continuously increased, with small-world and scale-free properties remaining significant, but connection closeness decreased. In the upstream Yellow River Basin, it transitioned from a single-core innovation cluster centered around Xi'an in Phase One (2011-2013) to three innovation clusters: Qinghai, Ning-Shaan-Yu, and Gan-Inner Mongolia-Jin in Phase Two (2017-2019). In the downstream region, single-core clusters around Jinan and Qingdao in Phase One integrated into the Shandong Peninsula Urban Agglomeration innovation cluster in Phase Two. Organizational and cultural proximity facilitate intercity innovation but also amplify provincial and cultural "boundary effects." City clusters and basin proximity did not create "boundary effects," but policy and basin proximity did not promote intercity cooperation. Geographic and technological proximity, city scale, innovation levels, and green innovation levels positively impact intercity innovation. This study's "proximity-boundary" analysis framework contributes to understanding innovation network impact mechanisms and provides theoretical and policy support for optimizing the green innovation system in the basin.

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