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Record W4377008668 · doi:10.23977/cpcs.2023.070105

Evolution and Equilibrium of Collaborative Innovation System of Low-Carbon Technology: Simulation of a Multi-stakeholders Game Model

2023· article· en· W4377008668 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueComputing Performance and Communication systems · 2023
Typearticle
Languageen
FieldDecision Sciences
TopicInnovation Diffusion and Forecasting
Canadian institutionsnot available
Fundersnot available
KeywordsGovernment (linguistics)PremiseBounded rationalityInvestment (military)BusinessEvolutionary game theoryEvolutionarily stable strategyIndustrial organizationKnowledge managementMarketingEconomicsGame theoryMicroeconomicsComputer sciencePolitical science

Abstract

fetched live from OpenAlex

Low-carbon technology innovation is different from ordinary technology research, which has high investment, high risk and great uncertainty. It is very hard for enterprises and research institutions to succeed independently, and almost impossible for them to cooperate actively. Due to the different objective of participants, the expectation of innovation is reflected in the initial collaborative intention, which is a pivotal factor influencing the stability of collaborative innovation. On the premise of bounded rationality, this paper constructs multiple stakeholders evolutionary game model involving government, enterprises and scientific institutions. The influence of initial strategy probabilities of three participants is analysed in detail through simulation. The findings are as follows: (1) The evolution of government strategy is not affected by the initial collaboration probabilities of enterprises and research institutions. Eventually government strategies evolve into stimulation and support. (2) The strategy evolution of enterprises and research institutions is significantly affected by the initial strategy probabilities of three participants. The higher the initial probability of government support, the higher the possibility of enterprises and scientific institutions participating in collaboration. At the same time, the initial collaboration probabilities of enterprises and research institutions have a significant impact on each other, and the higher initial collaboration probability of one participant, the higher the probability of the other participating in collaboration. (3) Through the scenario simulation of two extreme probabilities, it is found that enterprises, compared with research institutions, play a more decisive role in collaborative low-carbon technology innovation under the support of the government. Therefore, if the government wants to realize the low-carbon technology collaborative innovation, the essential point is to stimulate collaboration enthusiasm of enterprises.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.078
Threshold uncertainty score0.419

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.006
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.175
GPT teacher head0.361
Teacher spread0.186 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it