A Multi-Layer Approach to Assess Urban Innovation Districts

Abstract Clustering of innovation– the driving core behind regional innovation systems (RISs)– is a crucial contributor to economic prosperity. Such clusters are often denoted as innovation districts. While spatial characteristics, including accessibility to innovation services, rich amenities, and mixed land-use, have been associated with heightened regional innovativeness in previous studies, there is a gap in our knowledge on how to identify the boundaries of innovation districts within RIS. To fill this research gap, we propose a (data-driven) multi-layer approach consisting of a set of indicators depicting four RIS sub-systems (knowledge generation, knowledge exploitation, regional policy, and living environment sub-systems) and three different levels of spatial characteristics (clustering, coupling and coordination, and spatial mixing). The feasibility of the suggested “innovation district evaluation framework” is tested based on multi-source point of interest and patent data collected in Qingdao, China. The paper argues that the framework is a valuable tool assisting evidence-based development of specialized or diversified planning strategies to enhance the innovativeness of cities and to facilitate knowledge-based urban development.

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Publication Details

Journal
Applied Spatial Analysis and Policy
Published
2025-07-18
DOI
https://doi.org/10.1007/s12061-025-09692-0
Primary Topic
Regional Economics and Spatial Analysis
Type
article
Field-Weighted Citation Impact
0.00

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article

A Multi-Layer Approach to Assess Urban Innovation Districts

Teemu Makkonen, Yanxu Jiang, Naixia Mou, Linfei Han
Applied Spatial Analysis and Policy
Regional Economics and Spatial Analysis
article

A Multi-Layer Approach to Assess Urban Innovation Districts

Teemu Makkonen, Yanxu Jiang, Naixia Mou, Linfei Han
article en

Abstract

Abstract Clustering of innovation– the driving core behind regional innovation systems (RISs)– is a crucial contributor to economic prosperity. Such clusters are often denoted as innovation districts. While spatial characteristics, including accessibility to innovation services, rich amenities, and mixed land-use, have been associated with heightened regional innovativeness in previous studies, there is a gap in our knowledge on how to identify the boundaries of innovation districts within RIS. To fill this research gap, we propose a (data-driven) multi-layer approach consisting of a set of indicators depicting four RIS sub-systems (knowledge generation, knowledge exploitation, regional policy, and living environment sub-systems) and three different levels of spatial characteristics (clustering, coupling and coordination, and spatial mixing). The feasibility of the suggested “innovation district evaluation framework” is tested based on multi-source point of interest and patent data collected in Qingdao, China. The paper argues that the framework is a valuable tool assisting evidence-based development of specialized or diversified planning strategies to enhance the innovativeness of cities and to facilitate knowledge-based urban development.

Applied Spatial Analysis and PolicyVol. 18(3)
University of Eastern Finland (FI), Beijing Jiaotong University (CN), Karelia University of Applied Sciences (FI), Zhejiang Tongji Vocational College of Science and Technology (CN), Shandong University of Science and Technology (CN)
Itä-Suomen Yliopisto, Kuopion Yliopistollinen Sairaala
Industry, innovation and infrastructure
Openalex Percentile: Top 72%
Regional Economics and Spatial Analysis
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A Multi-Layer Approach to Assess Urban Innovation Districts — Teemu Makkonen, Yanxu Jiang, et al. · Applied Spatial Analysis and Policy (2025) | TGRS Research Map | TGRS