ArticleHeliyon2023
Evolutionary game study of crowdsourcing open innovation synergy mechanism.
Article in Heliyon, 2023. 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
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
0 citing papers in PubMed, 11 citations in OpenAlex.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Open innovation crowdsourcing can help enterprises meet the challenges of a rapidly changing environment and improve their innovation performance. This study introduces network externalities as influencing factors of the crowdsourcing open innovation synergy mechanism. This study constructed the game payment matrix of the crowdsourcing open innovation synergy mechanism, and the evolutionary game method obtained the equilibrium solution of the crowdsourcing open innovation synergy mechanism. The impact of changes in the main influencing factors on the issuers' and receivers' willingness to collaborate and innovate was explored through numerical and case studies. The study shows that the higher the synergy benefit and its allocation coefficient need to be within a reasonable range for the willingness to collaborate and innovate to increase; the lower the original cost of both parties, and the higher the cost reduction coefficient under the policy support of the crowdsourcing platform, the higher the willingness to collaborate and innovate; the higher the network externality and the lower the penalty for breach of contract, the higher the desire to collaborate and innovate. The study recommends strengthening non-school education to guide innovation for all, and refining relevant policies to tailor innovation to local conditions. This study provides a new perspective and theoretical guidance for enterprises to build a crowdsourcing open innovation synergy mechanism and is a valuable reference for open innovation management.
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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.