Area Identification,Factor Evaluation,and Innovation Performance Improvement of Innovation Districts:A Case Study of Beijing

LI Tiantian; NIE Jingxin; ZHENG Tianming

doi:10.3969/j.issn.1000-0232.2025.08.002

Abstract：As part of China's deep industry-city-creativity integration project,new innovation districts are emerging across the country,and in-depth study of the spatial scope and performance impact of these spaces is required.A case study examining three aspects of their evolution was carried out:First,innovation districts were identified based on the superposition of multi-subject clustering.Second,a method of identifying innovation districts based on multiple factors was proposed based on relevant studies,and an element evaluation system for the"subject-space-function-network"was established.Finally,the factors influencing innovation performance were analyzed at two levels,providing the theoretical basis to improve the performance of innovation districts.A total of 42 innovation districts were discovered in the Sixth Ring Road of Beijing,showing a spatial distribution pattern of concentrated large districts and more dispersed small districts with diversified land use structures.Assessing the element agglomeration levels,subject diversity,accessibility to parks,and the policy support index focused on the subject,space,and function dimensions,respectively.The network element levels differed significantly among districts.According to a clustering analysis based on K-Means,innovation districts can be divided into three types according to their element agglomeration level,including the campus type led by the subject and network,the park type led by the subject and function,and the platform type led by the space and network.The spatial distribution characteristics of these three types differed significantly,and their innovation performance was positively affected by different combinations of four-dimensional elements.Among them,the campus type led by subject and network had a higher level of overall element agglomeration.This type was the most mature,but it displayed a significant lack of synergy of functional elements.For the park type led by subject and function,the industrial attribute of spatial functions was far stronger than the quality attribute,resulting in"space-function"separation and influencing the agglomeration of network elements.The platform type led by space and network was primarily focused on creative activities with intensive capital,which was where network elements were primarily concentrated.However,its innovation performance was generally low due to many shortcomings.Further analysis showed that improving the element agglomeration level can promote innovation performance.The effects of different factors on the innovation performance of innovation districts were analyzed.The study found that the intensity of patent cooperation,subject density,number of innovation organizations,and transportation accessibility were generally key factors.This study formulated element allocation strategies for three types of innovation districts according to the main problems identified,aiming to improve their performance.This included the"Campus Plus"strategy for the campus-type districts based on potential exploration of existing innovation districts and element implantation,the"Park Plus"strategy for the park-type districts based on space-function relation reconstruction,and the"Platform Plus"strategy for the platform-type districts based on the reconfiguration of shape-flow coupling and capacity expansion.The three types of innovation districts proposed according to spatial characteristics and element allocation not only reflect their unique ecosystems but also highlight the advantages and shortcomings of innovation elements,thus providing more targeted references for the construction of innovation districts.