ArticleThe Journal of technology transfer2022
Identifying the implementation effect of technology transfer policy using system dynamics: a case study in Liaoning, China.
Article in The Journal of technology transfer, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 1 of them a synthesis that pooled it.
What it found
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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
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Who cites it
2 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Dynamics and challenges of technology transfer in Colombia: a systematic literature review.Frontiers in research metrics and analytics · 2025Pooled it
- Measuring the synergy between technological and management innovation in megaprojects: Empirical evidence from China.PloS one · 2025Article
Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Given that technology transfer provides an important boost for promoting national economic development, technology transfer policy (TTP) has attracted more and more attention from academia and industry. The government issued many policies. However, the implementation effect of TTP still needs to be clarified. This study is carried out from the progressive level of "text content-influence path-implementation effect.'' It aims to adopt a systematic analysis method to analyze policy tools and policy implementation stages, then builds a conceptual framework of the influence path of TTP. Then the relationship between variables in the qualitative model was clarified, and the system dynamics (SD) model was used to build a quantitative model with four feedback loops. Finally, taking Liaoning, China as an example, the system simulation and sensitivity analysis of the main parameters are implemented in Vensim PLE. Different policy tools have different roles in the TTP impact stages of research, transfer, and industrialization. Based on the data of 2013-1019, the SD model constructed in this paper can be used to predict the implementation effect of TTP during 2020-2015. Simulation and sensitivity analysis results provide practical enlightenment for government departments to improve the implementation effect of the existing TTP. This study also provides other researchers with a systematic understanding for improving the implementation effect of TTP with a "text content-influence path-implementation effect" conduction chain and provides new insights for further research on TTP.
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Registered trials
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