MULTILAYER INNOVATION NETWORK HINTERLAND AND DETERMINANTS OF SHANDONG PENINSULA URBAN AGGLOMERATION FROM A NATIONAL-LOCAL PERSPECTIVE

SHENG Ke-rong; CHEN Jia-yi; LI Ya-ze

doi:10.13959/j.issn.1003-2398.2026.03.010

PDF(23439 KB)

HUMAN GEOGRAPHY ›› 2026, Vol. 41 ›› Issue (3) : 98-108. DOI: 10.13959/j.issn.1003-2398.2026.03.010

REGION

MULTILAYER INNOVATION NETWORK HINTERLAND AND DETERMINANTS OF SHANDONG PENINSULA URBAN AGGLOMERATION FROM A NATIONAL-LOCAL PERSPECTIVE

SHENG Ke-rong, CHEN Jia-yi, LI Ya-ze

Author information +

History +

Abstract

Focusing on the Shandong Peninsula urban agglomeration, this study examines the spatiotemporal patterns and influencing factors of multilayer hinterland relationships within urban innovation networks from both national and local spatial perspectives. The analysis is based on a multilayer innovation network constructed from intercity patent transfers, scientific co-authorships, and venture capital investments, using data from the years 2010, 2015, 2020, and 2023. Three conclusions are drawn. First, in terms of self-network size,the proportion of weak components and reach efficiency, the Shandong Peninsula urban agglomeration has been increasingly integrated into China's multi-level innovation network, with its network structure gradually evolving towards a polycentric and decentralized pattern. Second, at the local scale, the multilayer hinterland ties are especially strong within the Provincial Capital Economic Circle and between it and the Jiaodong Economic Circle, while the Lunan Economic Circle exhibits relatively weak internal and external connections.At the national scale, multilayer hinterland linkages are primarily concentrated with cities in the BeijingTianjin-Hebei, Yangtze River Delta, and Guangdong-Hong Kong-Macao urban agglomerations. Third, the paired cities' innovation capacity, administrative rank, level of digital economy development, and high-speed rail connectivity have positive effects on multilayer hinterland relationships, while GDP gradients and geographic distance exert negative impacts.

Key words

national-local scale / multilayer innovation network hinterland / ego network / multidimensional proximity / Shandong Peninsula Urban Agglomeration

Cite this article

EndNote

Ris (Procite)

Bibtex

Download Citations

SHENG Ke-rong, CHEN Jia-yi, LI Ya-ze. MULTILAYER INNOVATION NETWORK HINTERLAND AND DETERMINANTS OF SHANDONG PENINSULA URBAN AGGLOMERATION FROM A NATIONAL-LOCAL PERSPECTIVE[J]. HUMAN GEOGRAPHY. 2026, 41(3): 98-108 https://doi.org/10.13959/j.issn.1003-2398.2026.03.010

References

[1] Taylor P. Urban hinterworlds:Geographies of corporate service provision under conditions of contemporary globalisation[J]. Geography, 2001,86(1):51-60.
[2] 盛科荣,李扬,孙威.中国城市网络腹地空间格局及影响因素[J].经济地理,2021,41(3):66-76.[Sheng Kerong, Li Yang, Sun Wei. Spatial patterns and influencing factors of urban hinterworld in China[J]. Economic Geography, 2021,41(3):66-76.]
[3] Feng Z, Cai H, Chen Z, et al. Influence of an interurban innovation network on the innovation capacity of China:A multiplex network perspective[J]. Technological Forecasting and Social Change, 2022,180,121651. https://doi.org/10.1016/j.techfore.2022.121651.
[4] Higham K, Contisciani M, De Bacco C. Multilayer patent citation networks:A comprehensive analytical framework for studying explicit technological relationships[J]. Technological forecasting and social change, 2022, 179:121628. https://doi.org/10.1016/j. techfore.2022.121628.
[5] Taylor P. World City Network:A Global Urban Analysis[M]. London:Routledge, 2004:101-125.
[6] 李涛,周锐.长三角地区网络腹地划分的关联测度方法比较[J].地理学报,2016,71(2):236-250.[Li Tao, Zhou Rui. Urban hinterworld in Yangtze River Delta:Empirical comparison of two networkbased methods[J]. Acta Geographica Sinica, 2016,71(2):236-250.]
[7] 赵渺希,唐子来.基于网络关联的长三角区域腹地划分[J].经济地理,2010,30(3):371-376.[Zhao Miaoxi, Tang Zilai. The hinterland division of Yangtze river delta region:Based on network connection[J]. Economic Geography, 2010,30(3):371-376.]
[8] 朱鹏程,曹卫东,张宇,等.人口流动视角下长三角城市空间网络测度及其腹地划分[J].经济地理,2019,39(11):41-48,133.[Zhu Pengcheng,Cao Weidong, Zhang Yu, et al. Measurement of urban spatial network and its hinterland division in Yangtze River Delta from the perspective of population flow[J]. Economic Geography, 2019,39(11):41-48,133.]
[9] 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[J].地理学报,2023,78(2):293-314.[Wang Bangjuan, Wang Tao,Liu Chenliang. Spatiotemporal dynamics of China's technology transfer hubs and their hinterworlds[J]. Acta Geographica Sinica,2023,78(2):293-314.]
[10] Burger M, Van Der Knaap G, Wall R. Polycentricity and the multiplexity of urban networks[J]. European Planning Studies, 2014,22(4),816-840.
[11] Sun S L, Chen V Z, Sunny S A, et al. Venture capital as an innovation ecosystem engineer in an emerging market[J]. International Business Review, 2019,28(5):101485. https://doi.org/10.1016/j.ibus rev.2018.02.012.
[12] De Domenico M. More is different in real-world multilayer networks[J]. Nature Physics, 2023,19(9):1247-1262.
[13] 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[J].地理学报,2018,73(8):1462-1477.[Liu Chengliang, Guan Mingming, Duan Dezhong. Spatial pattern and influential mechanism of interurban technology transfer network in China[J]. Acta Geographica Sinica, 2018,73(8):1462-1477.]
[14] 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[J].地理学报,2023,78(2):334-350.[Dai Liang, Cao Zhan, Ma Haitao, et al. The influencing mechanisms of evolving structures of China's intercity knowledge collaboration networks[J]. Acta Geographica Sinica, 2023,78(2):334-350.]
[15] 党兴华,张晨.基于STERGM的风险投资网络演化动力研究[J].科研管理,2022,43(5):182-190.[Dang Xinghua, Zhang Chen. Research on the evolutionary dynamics of venture capital networks based on STERGM[J]. Science Research Management, 2022,43(5):182-190.]
[16] 沈文成,李培庆,姚雯雯,等.多重流空间视角下的中国城市网络空间结构特征及组织模式[J].地理研究,2023,42(2):514-533.[Shen Wencheng, Li Peiqing, Yao Wenwen, et al. The structural characteristics and spatial organization pattern of China's urban network based on the multiple flow[J]. Geographical Research, 2023,42(2):514-533.]
[17] 王钊,崔悦,彭佳捷,等.全国-地方视角下长江中游城市群多尺度经济网络演化研究[J].人文地理,2024,39(6):89-97.[Wang Zhao,Cui Yue, Peng Jiajie, et al. Evolution of multi-scale economic networks in the urban agglomeration in the middle reaches of the Yangtze River from a national-local perspective[J]. Human Geography, 2024,39(6):89-97.]
[18] Bathelt H, Malmberg A, Maskell P. Clusters and knowledge:Local buzz, global pipelines and the process of knowledge creation[J].Progress in Human Geography, 2004,28(1):31-56.
[19] Boschma R, Martin R. The Handbook of Evolutionary Economic Geography[M]. Cheltenham:Edward Elgar, 2010:120-135.
[20] Huggins R, Thompson P. A network-based view of regional growth[J]. Journal of Economic Geography, 2014,14(3):511-545.
[21] 赵涛,张智,梁上坤.数字经济、创业活跃度与高质量发展:来自中国城市的经验证据[J].管理世界,2020,36(10):65-76.[Zhao Tao,Zhang Zhi, Liang Shangkun. Digital economy, entrepreneurial activity and high-quality development:Empirical evidence from Chinese cities[J]. Management World, 2020,36(10):65-76.]
[22] 袁航,朱承亮.国家高新区推动了中国产业结构转型升级吗[J].中国工业经济,2018(8):60-77.[Yuan Hang, Zhu Chenglaing. Have national high-tech zones promoted the transformation and upgrading of China's industrial structure[J]. China Industrial Economics,2018(8):60-77.]
[23] 郭峰,王靖一,王芳,等.测度中国数字普惠金融发展:指数编制与空间特征[J].经济学(季刊),2020,19(4):1401-1418.[Guo Feng,Wang Jingyi, Wang Fang, et al. Measuring the development of digital inclusive finance in China:Index compilation and spatial characteristics[J]. China Economic Quarterly, 2020,19(4):1401-1418.]
[24] 饶悦,沈丽珍,汪侠.基于大型科研基础设施共享的区域创新网络研究——以山东省为例[J].地理研究,2021,40(6):1840-1856.[Rao Yue, Shen Lizhen, Wang Xia. Research on regional innovation network based on large-scale scientific research infrastructure sharing:Take Shandong as an example[J]. Geographical Research, 2021,40(6):1840-1856.]
[25] 刘清春,宗文丽,赵培雄,等.基于上市企业联系的山东省城市网络结构演变特征及影响因素研究[J].世界地理研究,2024,33(4):88-102.[Liu Qinchun, Zong Wenli, Zhao Peixiong, et al. Research on the evolution characteristics and influencing factors of urban network structure in Shandong Province:Based on the connection of listed enterprises[J]. World Regional Studies, 2024,33(4):88-102.]
[26] Castells M. The Informational City:Information Technology, Economic Restructuring, and the Urban-Regional Process[M]. Oxford:Blackwell, 1989:126-171.
[27] Camagni R P. From city hierarchy to city network:Reflections about an emerging paradigm[M]//Lakshmanan T R, Nijkamp P.Structure and Change in the Space Economy. Springer, Berlin, Heidelberg, 1993:66-87.
[28] (1)本文还将样本划分为群内关系和群外关系进行分组回归。结果显示,在群内关系回归中,行政等级、产业结构高级化指数的系数规模相对较大;而在群外关系回归中,创新指数、数字经济发展指数、经济梯度、高铁连通性和地理距离变量的系数规模更为突出。受篇幅所限,具体结果未在文中呈现。