Evidence map›Paper›PMID 40659636›Full record

ArticleScientific data2025

Spatio-Temporal Geographic Networks for Value Co-Creation and Technology Transfer in China with Patent Data.

Yi Su, Ao Lv, Pengfei Zhi, Jiahui Chai, Jingjing Tian

Abstract read
In one paragraph

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.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Yi SuHarbin Engineering University, Harbin, China.
Ao LvHarbin Engineering University, Harbin, China. lvao@hrbeu.edu.cn.ORCID http://orcid.org/0009-0005-2711-3026
Pengfei ZhiHarbin Engineering University, Harbin, China.
Jiahui ChaiHarbin Engineering University, Harbin, China.
Jingjing TianJilin University, Changchun, China.

Funding

National Natural Science Foundation of China (National Science Foundation of China) 72474058
6 · The paper itself

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

PMID40659636
PMCPMC12259858

What OpenQuestion holds

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Registered trials

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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.