Abstract
As digital technologies become embedded in urban production and governance, high-quality urban development depends not only on growth in technology volume but also on whether key digital technologies form stable spatial co-location and complementary configurations within cities. This study examines 41 cities in the Yangtze River Delta, utilizing CNIPA-issued patents with enterprise applicants from 2000 to 2024. Patents are classified into seven key digital technology types, and multi-order co-location patterns are identified from point-level neighborhood relations among geocoded patent applicant locations within each city-year unit. These point-based co-location results are then aggregated into city-year configuration indicators for comparison with economic performance. The analysis evaluates both contemporaneous and lagged links with city-level economic performance, and applies year-grouped cross-validation with an interpretable predictive model to identify influential configurations and their marginal contributions using XGBoost-SHAP. The results show that city economic performance aligns less with the simple expansion of patent counts or technology categories than with stable and increasingly complex cross-technology co-location configurations. Configuration dynamics combine persistence with adjustment: a small set of combinations remains repeatedly influential in predictive models and is associated with later expansion and recombination. The model-based associations exhibit both an intensity threshold and a time lag: higher and more stable co-location intensity is more often associated with positive predicted economic differences. These findings suggest that digital policy and industrial spatial planning may benefit from paying greater attention to cross-technology configuration capacity. At the same time, the evaluation should consider the time process through which spatial co-location is absorbed and converted into economic outcomes.
| Original language | English |
|---|---|
| Article number | 104119 |
| Journal | Applied Geography |
| Volume | 195 |
| DOIs | |
| State | Published - Oct 2026 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 11 Sustainable Cities and Communities
Keywords
- Key digital technologies
- Spatial co-location pattern mining
- XGBoost-SHAP model
- Yangtze river delta
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