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Empirical Research on the Relationship between the Subdivided Indicators of the Sustainable Development Rate and the Enterprise R&D Input

2010· article· en· W1937861757 on OpenAlexvenueno aff
Chen Haisheng, Liang Ge, Cao Xiaoli

Bibliographic record

VenueCanadian social science · 2010
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicInnovation Policy and R&D
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesRegression analysisSustainable developmentEconomicsMathematicsPolitical scienceEconometricsWelfare economicsStatisticsPhilosophy

Abstract

fetched live from OpenAlex

This paper divided sustainable development rate into return on total assets, equity multiplier, retained earning ratio,and tested their relationships with the R&D input. By applying the cross-section regression method, it builts up the regression model through the empirical research on 93 listed high-tech companies in electronic, medical, and new material industries, in which the influence of those three indicators on the R&D input was tested. The results implied that the coefficient of return on total assets, retained earnings ratio, and the equity multiplier was 0.101, 0.0018 and -0.007 respectively. Finally, this paper analyzed those coefficients and proposed the comprehensive solution for how to take rational financial action to promote the R&D input in different conditions. Key words: Sustainable Development Rate, Return on total assets, Equity Multiplier, Retained Earning Ratio, R&D Intensity Resume: L’article present divise le rythme du developpement durable en rendement de l’actif total, multiplicateur de capitaux propres, ratio du rapport, et teste leur relation avec la contribution de R&D. En applicant la methode de regression en coupe transversable, il construit le modele de regression a travers les recherches empiriques sur 93 entreprises cotees de haute technologie dans les domaines electronique et medical ainsi que l’industrie de nouveaux materiaux, dans lesquels l’influence de ces trois indicateurs sur la contribution de R&D ont ete experimentee. Les resultats impliquent que le coefficient de rendement de l’actif total, le ratio du rapport et le multiplicateur de capitaux propres sont respectivement 0.101, 0.0018 et -0.007. Finalement, l’acticle a analyse ces coefficients et propose une solution synthetique favorable a la prise des politiques financieres raisonables afin de promouvoir la contribution de R&D dans de differentes conditions. Mots-Cles: rythme du developpement durable, rendement de l’actif total, multiplicateur de capitaux propres, ration du rapport, intensite de R&D

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.

How this classification was reachedexpand

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)0.009
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesScience and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.566
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0090.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0040.003
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.117
GPT teacher head0.341
Teacher spread0.224 · 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

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2010
Admission routes1
Has abstractyes

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