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Record W1772273256 · doi:10.1002/csr.1321

Market Responses to Firms' Voluntary Climate Change Information Disclosure and Carbon Communication

2013· article· en· W1772273256 on OpenAlexaff
Su‐Yol Lee, Y Park, Robert D. Klassen

Bibliographic record

VenueCorporate Social Responsibility and Environmental Management · 2013
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCorporate Social Responsibility Reporting
Canadian institutionsWestern University
Fundersnot available
KeywordsVoluntary disclosureBusinessCapital marketEnterprise valueShareholderValue (mathematics)TurnoverEvent studyShareholder valueSample (material)AccountingMonetary economicsCorporate governanceFinanceEconomics

Abstract

fetched live from OpenAlex

Abstract Despite the importance of the Carbon Disclosure Project (CDP), the question of how firms' voluntary carbon disclosure influences capital markets and shareholder value remains unanswered. Using the event study methodology with a sample of firms from the CDP Korea 2008 and 2009, this paper investigates market responses to firms' voluntary carbon information disclosure. The results suggest that the market is likely to respond negatively to firms' carbon disclosure, implying that investors tend to perceive carbon disclosure as bad news and thus are concerned about potential costs facing firms for addressing global warming. In addition, the study examines the moderating effect of frequent carbon communication on the relationship between carbon disclosure and shareholder value. The results suggest that a firm can mitigate negative market shocks from its carbon disclosure by releasing its carbon news periodically through the media in advance of its carbon disclosure. Copyright © 2013 John Wiley & Sons, Ltd and ERP Environment.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.254
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.002
Open science0.0000.001
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 head0.025
GPT teacher head0.223
Teacher spread0.197 · 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

Citations235
Published2013
Admission routes1
Has abstractyes

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