ArticleHeliyon2024
Dynamic simulation of policy-driven green technology innovation networks: Digital empowerment and collaborative efficiency.
Article in Heliyon, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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
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
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
To delve into the intricate dynamics of green innovation, it is imperative to establish a policy-driven green innovation network and optimize its multi-entity collaborative mechanism. Given the dynamic complexity of a technological innovation network composed of multiple entities, this paper examines the interactions among four subsystems based on system dynamics (SD) simulation: resource input, innovation performance, policy-driven, and digital empowerment subsystem. Furthermore, we analyze the combined effects of policy-driven initiatives and the role of digital platforms in facilitating innovation efficiency based on empirical evidence. The results indicate that: (1) Government can effectively promote green development by enforcing stronger environmental regulations, such as increasing carbon trading price, while enhancing the emission reduction efficiency of innovative products. (2) Increased per capita R&D investment, along with financial, tax, fiscal incentives for innovation investment, will increase the rate of innovation achievements. (3) Government should strengthen talent policy during anticipated increases in talent numbers and reduce the intensity of introductions during expected declines. (4) By implementing incentive policies to develop S&T platforms, government can broaden innovation network cooperation, promotes resource aggregation, and leverages multi-entity cohort effects.
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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.