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Record W2608218194 · doi:10.5430/afr.v6n2p181

The Impact of Social Responsibility on Corporate Performance: Evidence from Taiwan

2017· article· en· W2608218194 on OpenAlexvenueno aff
Yun-Chia Yan, Li-Chuan Chou, Ta-Cheng Chang, John D’Arcy

Bibliographic record

VenueAccounting and Finance Research · 2017
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCorporate Social Responsibility Reporting
Canadian institutionsnot available
Fundersnot available
KeywordsCorporate social responsibilityBusinessAccountingCorporate governanceContext (archaeology)Order (exchange)Relation (database)Listing (finance)Scale (ratio)Construct (python library)Dimension (graph theory)Public relationsFinancePolitical science

Abstract

fetched live from OpenAlex

Prior studies show a mixed relation between corporate social responsibility (CSR) and corporate financial performance (CFP). This paper attempts to address the issue by using listing companies from Taiwan during 2007-2010. Contrary to prior studies that use qualitative approaches to construct a CSR index, in order to examine the relation between CSR and CFP this study directly adopts the CSR score with a scale from zero to 100 points from the CSRHub database of companies’ social, environmental, and governance performance. We find that (1) there is a positive and significant interaction between CSR and CFP, (2) high score CSR firms tend to outperform low score CSR firms and (3) the governance dimension of CSR has a more significant and positive association with stock price returns than other dimensions (community, employees, and environment) of CSR. Our results, therefore, provide additional information regarding the relation between CSR and CFP within the context of emerging markets.

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)0.011
metaresearch head score (Gemma)0.015
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science and technology studies, Scholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.127
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0110.015
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0050.001
Scholarly communication0.0010.002
Open science0.0010.001
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 head0.160
GPT teacher head0.401
Teacher spread0.241 · 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; a candidate call from one teacher head, not a consensus.

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

Citations12
Published2017
Admission routes1
Has abstractyes

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