Joint Capability Configuration in Regional Innovation Systems: City-Boundary Evidence from Research-to-Industry Patent Transfers

Integrating innovation and industrial chains is essential for translating scientific knowledge into industrial value. This study examines how cities’ joint capability configuration relates to research institution-to-firm patent transfers and how this relationship varies across city boundaries. We construct a city-level capacity alignment index (CAI) combining the common level and balance of innovation-chain and industrial-chain capabilities. The analysis uses a 2010–2023 panel of 41 Yangtze River Delta (YRD) cities and 239,148 registered invention-patent transfer events. Fixed-effects, stacked-equation, and city-pair Poisson pseudo-maximum likelihood models examine capability–transfer associations, with firm-to-firm transfers as a comparison channel. In the baseline models, CAI is positively associated with contemporaneous log transfer intensity in both channels, with a stronger research-channel association. Both common level and balance are positively associated with research-transfer intensity, with a stronger association for common level. City-level log-intensity models show positive CAI associations with within-city and intra-YRD cross-city research transfers, with a stronger within-city association. This spatial contrast is greater in the research channel than in the firm channel. These findings distinguish the transfer associations of capability strength and balance and show how the overall CAI–transfer association varies across spatial and organizational settings in the YRD.

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Publication Details

Journal
Systems
Published
2026-10-01
DOI
https://doi.org/10.3390/systems14101222
Primary Topic
Innovation and Knowledge Management
Type
article
Field-Weighted Citation Impact
0.00
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Joint Capability Configuration in Regional Innovation Systems: City-Boundary Evidence from Research-to-Industry Patent Transfers

Nannan Yu, Bo Yu, Yingnan Zhao
Systems
Innovation and Knowledge Management
article

Joint Capability Configuration in Regional Innovation Systems: City-Boundary Evidence from Research-to-Industry Patent Transfers

Nannan Yu, Bo Yu, Yingnan Zhao
article en

Abstract

Integrating innovation and industrial chains is essential for translating scientific knowledge into industrial value. This study examines how cities’ joint capability configuration relates to research institution-to-firm patent transfers and how this relationship varies across city boundaries. We construct a city-level capacity alignment index (CAI) combining the common level and balance of innovation-chain and industrial-chain capabilities. The analysis uses a 2010–2023 panel of 41 Yangtze River Delta (YRD) cities and 239,148 registered invention-patent transfer events. Fixed-effects, stacked-equation, and city-pair Poisson pseudo-maximum likelihood models examine capability–transfer associations, with firm-to-firm transfers as a comparison channel. In the baseline models, CAI is positively associated with contemporaneous log transfer intensity in both channels, with a stronger research-channel association. Both common level and balance are positively associated with research-transfer intensity, with a stronger association for common level. City-level log-intensity models show positive CAI associations with within-city and intra-YRD cross-city research transfers, with a stronger within-city association. This spatial contrast is greater in the research channel than in the firm channel. These findings distinguish the transfer associations of capability strength and balance and show how the overall CAI–transfer association varies across spatial and organizational settings in the YRD.

SystemsVol. 14(10)
Harbin Institute of Technology (CN)
Industry, innovation and infrastructure
Openalex Percentile: Top 8%
Innovation and Knowledge Management
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Joint Capability Configuration in Regional Innovation Systems: City-Boundary Evidence from Research-to-Industry Patent Transfers — Nannan Yu, Bo Yu, et al. · Systems (2026) | TGRS Research Map | TGRS