ArticleScientific data2025
Spatio-Temporal Geographic Networks for Value Co-Creation and Technology Transfer in China with Patent Data.
Article in Scientific data, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
2 citing papers in PubMed.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
Abstract
With the increasing complexity of technology, cross-regional joint patent applications and patent transfers have become a prominent component of knowledge activities, attracting substantial attention of academic researchers. To examine the state and distribution characteristics of inter-city knowledge flows, this study utilizes patent data from the China National Intellectual Property Administration database and conducts in-depth data exploration to construct two urban knowledge networks (UKN). Specifically, over 1.23 million value co-creation patents are extracted to develop the urban value co-creation knowledge network (UKN-C), while more than 1.42 million technology transfer patents are refined to establish the urban technology transfer knowledge network (UKN-T). Both UKNs start with cities as nodes and knowledge connections between cities as edges. The edges of UKN-C are weighted by the volume of value co-creation patents, whereas the edges of UKN-T are weighted by the volume of technology transfer patents. To facilitate further research, the geographically explicit and spatial-temporal knowledge flow networks have been released in a simple and accessible format.
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.