Type identification and influencing factors of brokerage cities in the Yangtze River Economic Belt: A case study of strategic emerging industries

doi:10.3969/j.issn.1004-9479.2025.09.20230833

Abstract

Abstract:

Brokerage cities are the key actors to maintain the technology transfer between cities. Taking the Yangtze River Economic Belt as the research region, based on the transfer data of invention patents of strategic emerging industries from 2001 to 2020, this paper constructs a technology transfer network, and uses brokerage city scores, RCA index and panel data Logit model to identify five types of brokerage cities in the Yangtze River Economic Belt (Coordinator, Gatekeeper, Representative, Itinerant and Liaison city-regions） and analyzes the influencing factors of their formation. The results show that：① The distribution pattern of brokerage cities in the Yangtze River Economic Belt shows a high concentration toward the three major urban agglomerations， among which， Coordinators and Representatives are mainly concentrated in the Yangtze River Delta region， Itinerants and Liaisons are mainly concentrated in the Yangtze River middle reaches and Chengdu-Chongqing urban agglomerations， and the distribution of Gatekeepers are relatively balanced. ②Knowledge stock is an important endowment to assume the role of brokerage cities in the Yangtze River Economic Belt. ③In addition， Coordinators attach importance to local technology transfer ability and technology absorptive ability to maintain intra-region technology transfer activities and knowledge base updating, while Gatekeepers and Representatives are significantly affected by technology absorptive and diffusing ability respectively. Itinerants and Liaisons rely on technology diffusing capacity to promote the export and application of new technologies to innovation-developed regions, so as to realize the innovative value of technological interactions between developed and underdeveloped regions.

Key words: brokerage cities, technology transfer network, strategic emerging industries, Yangtze River Economic Belt

摘要：

中介城市是维系城市间技术转移的关键主体。本文以长江经济带为研究区域，基于2001—2020年战略性新兴产业的发明专利转移数据构建技术转移网络，结合中介城市得分、显性比较优势和面板Logit模型等方法，将长江经济带中介城市分为协调型、守门员型、代表型、顾问型和联络型5种类型，并分析其形成的影响因素，结果表明：①除守门员型城市分布较为均衡外，其他类型中介城市呈现向城市群高度集聚的趋势。其中，协调型、代表型城市主要集中在长三角城市群；顾问型、联络型城市主要集中在长江中游和成渝城市群。②知识存量是长江经济带中介城市的重要禀赋。③不同类型中介城市受到不同因素的影响：协调型城市为维系区域内部技术转移活动和知识库更新，重视本地技术转移能力和技术吸收能力的培养；守门员型和代表型城市因参考与外部区域互动的方向而分别受到技术吸收和扩散能力的显著影响；顾问型和联络型城市强调技术扩散能力，积极推进创新欠发达区域向发达区域的新技术输出和应用过程。

关键词: 中介城市, 技术转移网络, 战略性新兴产业, 长江经济带

Yuanyuan WAN, Xianzhong CAO, Gang ZENG, Jinliao HE, Lei YE. Type identification and influencing factors of brokerage cities in the Yangtze River Economic Belt: A case study of strategic emerging industries[J]. World Regional Studies, 2025, 34(9): 103-115.

万媛媛, 曹贤忠, 曾刚, 何金廖, 叶雷. 长江经济带中介城市类型识别与影响因素研究[J]. 世界地理研究, 2025, 34(9): 103-115.

Figures/Tables 6

References 39

[1]	周灿, 曾刚, 曹贤忠. 中国城市创新网络结构与创新能力研究. 地理研究, 2017, 36(7): 1297-1308.
	ZHOU C, ZENG G, CAO X. Chinese inter-city innovation networks structure and city innovation capability. Geographical Research, 2017, 36(7): 1297-1308.
[2]	SIGLER T, NEAL Z, MARTINUS K. Brokerage as an urban and regional process between systems and scales. Regional Studies, 2023, 57(2): 209-214.
[3]	BURT R. Structural holes : The social structure of competition. Cambridge: Harvard University Press, 1992.
[4]	BIANCHI C, GALASO P, PALOMEQUE S. The trade-offs of brokerage in inter-city innovation networks. Regional Studies, 2023, 57(2): 225-238.
[5]	BIANCHI C, GALASO P, PALOMEQUE S. Knowledge complexity and brokerage in inter-city networks. The Journal Of Technology Transfer, 2023, 48: 1773-1799.
[6]	SIGLER T, NEAL Z, MARTINUS K. The brokerage roles of city-regions in global corporate networks. Regional Studies, 2023, 57(2): 239-250.
[7]	刘承良, 管明明, 段德忠. 中国城际技术转移网络的空间格局及影响因素. 地理学报, 2018, 73(8): 1462-1477.
	LIU C, GUAN M, DUAN D. Spatial pattern and influential mechanism of interurban technology transfer network in China. Acta Geographica Sinica, 2018, 73(8): 1462-1477.
[8]	刘通, 刘承良. "全球—地方"视角下中国创新网络演化格局与内生机制. 世界地理研究, 2024, 33(9): 57-70.
	LIU T, LIU C. The evolution pattern and endogenous mechanism of China's innovation network: From the "glocal" perspective. World Regional Studies, 2024, 33(9): 57-70.
[9]	KIM K, KOGLER D F, ZABETTA M. New collaborations and novel innovations: The role of regional brokerage and collaboration intensity. European Planning Studies, 2023, 32(6):1251-1272.
[10]	宓泽锋, 傅竞萱, 项煜辉, 等. 新兴产业区域创新一体化与地方化的关系探究——以长三角新材料产业为例. 世界地理研究, 2023, 32(6): 87-97.
	MI Z, FU J, XIANG Y, et al. Research on the relationship between regional innovation integration and localization of emerging industries: A case study of new material industry in Yangtze River Delta. World Regional Studies, 2023, 32(6): 87-97.
[11]	樊杰, 王亚飞, 陈东, 等. 长江经济带国土空间开发结构解析. 地理科学进展, 2015, 34(11): 1336-1344.
	FAN J, WANG Y, CHEN D, et al. Analysis on the spatial development structure of the Yangtze River Economic Belt. Progress in Geography, 2015, 34(11): 1336-1344.
[12]	陆大道. 建设经济带是经济发展布局的最佳选择——长江经济带经济发展的巨大潜力. 地理科学, 2014, 34(7): 769-772.
	LU D. Economic belt construction is the best choice of economic development layout: The enormous potential for the Changjiang River Economic Belt. Scientia Geographica Sinica, 2014, 34(7): 769-772.
[13]	钟业喜, 冯兴华, 文玉钊.长江经济带经济网络结构演变及其驱动机制研究. 地理科学, 2016, 36(1): 10-19.
	ZHONG Y, FENG X, WEN Y. The evolvement and driving mechanism of economic network structure in the Changjiang River Economic Zone. Scientia Geographica Sinica, 2016, 36(1): 10-19.
[14]	GOULD R V, FERNANDEZ R M. Structures of mediation: A formal approach to brokerage in transaction networks. Sociological Methodology, 1989(19): 89-126.
[15]	YANG B, ZHU S. Diversity in brokerage cities: The evolution of urban positionality in China's financial system. Regional Studies, 2023, 57(2): 251-267.
[16]	毛炜圣, 钟业喜, 吴思雨. 长江经济带战略性新兴产业创新能力时空演化及空间溢出效应. 长江流域资源与环境, 2020, 29(6): 1268-1279.
	MAO W, ZHONG Y, WU S. Spatial-temporal evolution and spillover effects of strategic emerging industry innovation ability in the Yangtze River Economic Belt. Resources and Environment in the Yangtze Basin, 2020, 29(6): 1268-1279.
[17]	段德忠, 杜德斌, 谌颖, 等. 中国城市创新技术转移格局与影响因素. 地理学报, 2018, 73(4): 738-754.
	DUAN D, DU D, CHEN Y, et al. Technology transfer in China's city system: Process, pattern and influencing factors. Acta Geograpgica Sinica, 2018, 73(4): 738-754.
[18]	王帮娟, 王涛, 刘承良. 中国技术转移枢纽及其网络腹地的时空演化. 地理学报, 2023, 78(2): 293-314.
	WANG B, WANG T, LIU C, et al. Spatiotemporal dynamics of China's technology transfer hubs and their hinterworlds. Acta Geograpgica Sinica, 2023, 78(2): 293-314.
[19]	CAO Z, DERUDDER B, DAI L, et al. 'Buzz-and-pipeline' dynamics in Chinese science: The impact of interurban collaboration linkages on cities' innovation capacity. Regional Studies, 2022, 56(2): 290-306.
[20]	FRIEDMAN R, PODOLNY J. Differentiation of boundary spanning roles: Labor negotiations and implications for role conflict. Administrative Science Quarterly, 1992, 37(1): 28-47.
[21]	BATHELT H. Clusters and knowledge: local buzz, global pipelines and the process of knowledge creation. Progress in Human Geography, 2004, 28(1): 31-56.
[22]	李语杨, 谷人旭, 王腾飞, 等. 长三角地区知识守门人空间演变与作用机制研究. 地理科学进展, 2021, 40(6): 925-936.
	LI Y, GU R, WANG T, et al. Spatial evolution and mechanism of knowledge gatekeepers in the Yangtze River Delta region. Progress in Geography, 2021, 40(6): 925-936.
[23]	MARTINUS K, SIGLER T, IACOPINI I, et al. The brokerage role of small states and territories in global corporate networks. Growth and Change, 2021, 52(1): 12-28.
[24]	毛熙彦, 贺灿飞. 区域发展的"全球-地方"互动机制研究. 地理科学进展, 2019, 38(10): 1449-1461.
	MAO X, HE C. A review of global-local interactions for regional development. Progress in Geography, 2019, 38(10): 1449-1461.
[25]	LLOPIS O, D'ESTE P. Brokerage that works: Balanced triads and the brokerage roles that matter for innovation. Journal of Product Innovation Management, 2022, 39(4): 492-514.
[26]	CANATO A, GIANGRECO A. Gurus or wizards? A review of the role of management consultants. European Management Review, 2011, 8(4): 231-244.
[27]	AUDRETSCH D B. From the entrepreneurial university to the university for the entrepreneurial society. The Journal of Technology Transfer, 2014, 39(3): 313-321.
[28]	吕拉昌,辛晓华,陈东霞.城市创新基础设施空间格局与创新产出:基于中国290个地级及以上城市的实证分析. 人文地理, 2021,36(4): 104-113.
	LYU L, XIN X, CHEN D. Urban innovation infrastructure and innovation output: An empirical analysis based on 290 cities at the prefecture level orabove in China. Human Geography, 2021, 36(4): 104-113.
[29]	于英杰, 吕拉昌. 中国城市知识创新职能空间分异及其影响因素. 地理学报, 2023, 78(2): 315-333.
	YU Y, LYU L. Spatial pattern of urban knowledge innovation function in China and its influencing factors. Acta Geographica Sinica, 2023, 78(2): 315-333.
[30]	戴靓, 曹湛, 马海涛, 等. 中国城市知识合作网络结构演化的影响机制. 地理学报, 2023, 78(2): 334-350.
	DAI L, CAO Z, MA H, et al. The influencing mechanisms of evolving structures of China's intercity knowledge collaboration networks. Acta Geographica Sinica, 2023, 78(2): 334-350.
[31]	李凤娇, 刘家明, 姜丽丽. 东北地区战略性新兴产业发展水平时空演变与影响因素研究. 地理科学进展, 2022, 41(4): 541-553.
	LI F, LIU J, JIANG L. Spatio-temporal change of strategic emerging industries in Northeast China and influencing factors. Progress in Geography, 2022, 41(4): 541-553.
[32]	ROPER S, HEWITT-DUNDAS N. Knowledge stocks, knowledge flows and innovation: Evidence from matched patents and innovation panel data. Research Policy, 2015, 44(7): 1327-1340.
[33]	万媛媛, 王秋玉, 曾刚, 等. 高校与生物医药企业创新结网的影响机制——以长三角为例. 经济地理, 2022, 42(7): 146-158.
	WAN Y, WANG Q, ZENG G, et al. Influencing mechanism of formation of innovation network between universities and biomedical firms: A case study of Yangtze River Delta. Economic Geography, 2022, 42(7): 146-158.
[34]	CALOGHIROU Y, GIOTOPOLOS I, KONTOLAIMOU A, et al. Industry-university knowledge flows and product innovation: How do knowledge stocks and crisis matter? Research Policy, 2021, 50(3): 104-195.
[35]	AARSTAD J, KVITASTEIN O. Enterprise R&D investments, product innovation and the regional industry structure. Regional Studies, 2020, 54(3): 366-376.
[36]	李琳, 韩宝龙. 地理与认知邻近对高技术产业集群创新影响——以我国软件产业集群为典型案例. 地理研究, 2011, 30(9): 1592-1605.
	LI L, HAN B. An empirical research on how geographic proximity and cognitive proximity work on the innovation performance of high-tech industrial cluster. Geographical Research, 2011, 30(9): 1592-1605.
[37]	JIN N, YANG N, FAWAD SHARIF S, et al. Influence of knowledge flow and knowledge stock on the technological niche through absorptive capacity in the R&D network.Technology Analysis & Strategic Management,2023,35(12): 1533-1546.
[38]	马海涛, 徐楦钫, 江凯乐. 中国城市群技术知识多中心性演化特征及创新效应. 地理学报, 2023, 78(2): 273-292.
	MA H, XU X, JIANG K, et al. The evolutionary characteristics and innovation effects of technological knowledge polycentricity in Chinese urban agglomerations. Acta Geographica Sinica, 2023, 78(2): 273-292.
[39]	马海涛, 黄晓东, 李迎成. 粤港澳大湾区城市群知识多中心的演化过程与机理. 地理学报, 2018, 73(12): 2297-2314.
	MA H, HUANG X, LI Y, et al. The evolution and mechanisms of megalopolitan knowledge polycentricity of Guangdong-Hong Kong-Macao Greater Bay Area. Acta Geographica Sinica, 2018, 73(12): 2297-2314.

类型	示意图	特征
协调型城市		推动本地技术转移，一体化程度较高区域的网络中心城市
守门员型城市		技术吸收能力强，可吸收外部知识并向本地转移
代表型城市		技术扩散能力强，转移区域内部创新资源向外部城市扩散
顾问型城市		具备特定且专业化的知识基础，促进技术反梯度转移过程
联络型城市		兼具技术吸收、扩散能力，对跨界技术梯度转移具有直接作用

类型	示意图	特征
协调型城市		推动本地技术转移，一体化程度较高区域的网络中心城市
守门员型城市		技术吸收能力强，可吸收外部知识并向本地转移
代表型城市		技术扩散能力强，转移区域内部创新资源向外部城市扩散
顾问型城市		具备特定且专业化的知识基础，促进技术反梯度转移过程
联络型城市		兼具技术吸收、扩散能力，对跨界技术梯度转移具有直接作用

变量	变量名称	具体指标	平均值	标准差	最小值	最大值
因变量	是否协调型城市		0.257	0.437	0.000	1.000
	是否守门员型城市		0.107	0.309	0.000	1.000
	是否代表型城市		0.088	0.283	0.000	1.000
	是否顾问型城市		0.045	0.207	0.000	1.000
	是否联络型城市		0.050	0.219	0.000	1.000
自变量	知识存量	城市人均发明专利授权数量（件/万人）	0.384	0.601	0.000	3.659
	创新源	城市普通高等学校数量/所	1.673	0.898	0.000	4.443
	产业结构	城市第二产业占地区生产总值比重/%	3.817	0.223	2.691	4.329
	本地转移能力	城市内部发明专利转移数量/次	1.368	1.700	0.000	7.456
	技术吸收能力	城市发明专利转入数量/次	1.491	1.768	0.000	8.321
	技术扩散能力	城市发明专利转出数量/次	1.268	1.737	0.000	7.702

变量	变量名称	具体指标	平均值	标准差	最小值	最大值
因变量	是否协调型城市		0.257	0.437	0.000	1.000
	是否守门员型城市		0.107	0.309	0.000	1.000
	是否代表型城市		0.088	0.283	0.000	1.000
	是否顾问型城市		0.045	0.207	0.000	1.000
	是否联络型城市		0.050	0.219	0.000	1.000
自变量	知识存量	城市人均发明专利授权数量（件/万人）	0.384	0.601	0.000	3.659
	创新源	城市普通高等学校数量/所	1.673	0.898	0.000	4.443
	产业结构	城市第二产业占地区生产总值比重/%	3.817	0.223	2.691	4.329
	本地转移能力	城市内部发明专利转移数量/次	1.368	1.700	0.000	7.456
	技术吸收能力	城市发明专利转入数量/次	1.491	1.768	0.000	8.321
	技术扩散能力	城市发明专利转出数量/次	1.268	1.737	0.000	7.702

省市	协调型城市	守门员型城市	代表型城市	顾问型城市	联络型城市
上海市	—	上海	上海	—	上海
江苏省	南京、无锡、盐城、徐州、南通、泰州、常州、镇江、扬州、连云港、淮安、宿迁	苏州、南通、泰州、徐州、盐城、扬州	苏州、南京、无锡、南通、常州	—	苏州
浙江省	杭州、绍兴、宁波、嘉兴、金华、温州、台州、湖州、衢州、丽水、舟山	绍兴、金华、台州、嘉兴	杭州、宁波、绍兴、湖州、温州	—	—
安徽省	合肥、蚌埠、芜湖、滁州、宣城、安庆、宿州、马鞍山、六安、阜阳、铜陵、淮南、亳州、黄山、淮北、池州	宣城、淮北	合肥、芜湖、蚌埠、宿州、马鞍山、六安	—	—
江西省	—	南昌、宜春、九江、吉安、景德镇、抚州、萍乡、新余、鹰潭	宜春	南昌、赣州、宜春、吉安、上饶、九江、抚州、鹰潭、萍乡、景德镇、新余	南昌、赣州、宜春、吉安、上饶、景德镇、萍乡、鹰潭
湖北省	—	武汉、宜昌、荆州、襄阳、黄石、黄冈、咸宁、鄂州、十堰、随州	孝感	武汉、宜昌、荆门、孝感、襄阳、荆州、黄石、黄冈、咸宁、十堰	武汉、宜昌、襄阳、荆门、孝感、十堰、咸宁
湖南省	—	长沙、湘潭、株洲、郴州、常德、岳阳、怀化、永州、益阳、衡阳、娄底、邵阳、张家界	—	长沙、湘潭、株洲、永州、岳阳、常德、衡阳、郴州、益阳、怀化、娄底、邵阳	长沙、株洲、湘潭、岳阳、衡阳、常德、益阳
重庆市	—	重庆	—	重庆	重庆
四川省	遂宁、雅安、宜宾、广安、南充、达州、巴中	眉山、遂宁、自贡、乐山、南充、宜宾、资阳、巴中、达州	成都、绵阳、德阳、攀枝花、遂宁、广元、泸州、广安、内江、	成都、绵阳、德阳、攀枝花、泸州、遂宁、乐山、内江	成都、绵阳、德阳、眉山、广元、自贡、资阳
贵州省	六盘水	贵阳、六盘水	遵义	贵阳、遵义、安顺	贵阳、遵义、安顺
云南省	丽江、临沧、昭通、保山	昆明、曲靖、玉溪、丽江、普洱、保山	昭通、临沧	昆明、曲靖、玉溪	昆明