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Record W4381052078 · doi:10.20525/ijrbs.v12i4.2552

Does corporate social responsibility provide protection against systemic risks? Evidence from Taiwan during the US-China trade war

2023· article· en· W4381052078 on OpenAlexaboutno aff
Po-Jung Chen, Chih-Yu Yang

Bibliographic record

VenueInternational Journal of Research in Business and Social Science (2147-4478) · 2023
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCorporate Social Responsibility Reporting
Canadian institutionsnot available
Fundersnot available
KeywordsCorporate social responsibilityBusinessChinaReceiptStock (firearms)Quarter (Canadian coin)Volatility (finance)Value (mathematics)AccountingFinancePublic relationsLaw

Abstract

fetched live from OpenAlex

This paper examines the protection against systemic risks of the financial and stock performance of firms in receipt of ‘corporate social responsibility’ (CSR) awards. The data we obtained from the Taiwan Economic Journal (TEJ) in 2016-2018, comprised of CSR-award-recipient firms (CSR firms) voted for by the Common Wealth and Global Views magazines, for a sample period running from the third quarter of 2017 to the third quarter of 2018. Our empirical results reveal that in terms of their financial performance, as compared to non-CSR-award-recipient (non-CSR) firms, CSR firms failed to demonstrate any better protection against systemic risks (such as the US-China trade war). However, the stock performance of CSR firms clearly provided better protection than that of non-CSR firms; the reason for this observation is assumed to be the higher operational costs faced by CSR firms seeking to continue to pursue their CSR goals when encountering systemic risks. Nevertheless, participation in CSR is found to have an insurance-like effect on firm value, which clearly helps to increase the confidence of investors and reduce stock volatility

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)0.018
metaresearch head score (Gemma)0.008
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience 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 score0.328
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0180.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.005
Science and technology studies0.0020.002
Scholarly communication0.0010.004
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 head0.138
GPT teacher head0.383
Teacher spread0.245 · 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

Citations2
Published2023
Admission routes1
Has abstractyes

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Same venueInternational Journal of Research in Business and Social Science (2147-4478)Same topicCorporate Social Responsibility ReportingFrench-language works237,207