Innovation Capability Index of China’s National Innovative Cities: Based on Hierarchical Data Envelopment Analysis Method

Urban innovation capacity is increasingly critical to city development, and quantitative assessments of innovative cities’ innovation capability can be achieved via the composite index method, which fully integrates multidimensional indicators. This study develops a hierarchical data envelopment analysis (H-DEA) method to establish a composite index evaluation model for innovation capacity, which features flexible and objective two-level indicators—an advantage that avoids subjective weight assignment and adapts well to the hierarchical structure of innovation evaluation indicators. The proposed H-DEA model is applied to evaluate 67 innovative cities in China, yielding composite scores and rankings that are further compared with those from the traditional weighting method. Sensitivity analysis is conducted by adjusting different upper and lower bounds of the H-DEA model to verify its robustness. Additionally, these 67 cities are divided into four regions, with region-specific weights assigned to the evaluation indicators in the model. The results show that the eastern region has the highest average innovation capacity (0.3783), where technological innovation (weight 0.27) serves as a key driving force; the western region has the lowest average innovation capacity (0.3235), and its innovative cities should prioritize improving outcome transformation capacity (weight 0.1357). Overall, technological innovation receives the highest average weight (0.2422), while outcome transformation capacity gets the lowest (0.1647).

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Journal
Mathematics
Published
2026-03-03
DOI
https://doi.org/10.3390/math14050863
Primary Topic
Efficiency Analysis Using DEA
Type
article
Field-Weighted Citation Impact
0.00

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article

Innovation Capability Index of China’s National Innovative Cities: Based on Hierarchical Data Envelopment Analysis Method

Linyan Zhang, Ziyan Li, Zixuan Zhang, Jian J. Zhang
Mathematics
Efficiency Analysis Using DEA
article

Innovation Capability Index of China’s National Innovative Cities: Based on Hierarchical Data Envelopment Analysis Method

Linyan Zhang, Ziyan Li, Zixuan Zhang, Jian J. Zhang
article en

Abstract

Urban innovation capacity is increasingly critical to city development, and quantitative assessments of innovative cities’ innovation capability can be achieved via the composite index method, which fully integrates multidimensional indicators. This study develops a hierarchical data envelopment analysis (H-DEA) method to establish a composite index evaluation model for innovation capacity, which features flexible and objective two-level indicators—an advantage that avoids subjective weight assignment and adapts well to the hierarchical structure of innovation evaluation indicators. The proposed H-DEA model is applied to evaluate 67 innovative cities in China, yielding composite scores and rankings that are further compared with those from the traditional weighting method. Sensitivity analysis is conducted by adjusting different upper and lower bounds of the H-DEA model to verify its robustness. Additionally, these 67 cities are divided into four regions, with region-specific weights assigned to the evaluation indicators in the model. The results show that the eastern region has the highest average innovation capacity (0.3783), where technological innovation (weight 0.27) serves as a key driving force; the western region has the lowest average innovation capacity (0.3235), and its innovative cities should prioritize improving outcome transformation capacity (weight 0.1357). Overall, technological innovation receives the highest average weight (0.2422), while outcome transformation capacity gets the lowest (0.1647).

MathematicsVol. 14(5)
Beijing Institute of Big Data Research (CN), Beijing Information Science & Technology University (CN)
National Social Science Fund of China
Industry, innovation and infrastructure
Openalex Percentile: Top 40%
Efficiency Analysis Using DEA
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Innovation Capability Index of China’s National Innovative Cities: Based on Hierarchical Data Envelopment Analysis Method — Linyan Zhang, Ziyan Li, et al. · Mathematics (2026) | TGRS Research Map | TGRS