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Record W4385973895 · doi:10.5267/j.uscm.2023.7.013

The role of investor recognition mediates the effect of sustainability reporting quality on firm value

2023· article· en· W4385973895 on OpenAlexvenueno aff
Ni Made Sri Rukmiyati, Ida Bagus Anom Purbawangsa, I Gde Kajeng Baskara, Ica Rika Candraningrat

Bibliographic record

VenueUncertain Supply Chain Management · 2023
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCorporate Social Responsibility Reporting
Canadian institutionsnot available
Fundersnot available
KeywordsSustainabilityBusinessSustainability reportingQuality (philosophy)Stock exchangeEnterprise valueAccountingStructural equation modelingValue (mathematics)Agency costCorporate sustainabilityCorporate governanceMarketingFinanceShareholderComputer science

Abstract

fetched live from OpenAlex

The objective of this research is to examine the impact of sustainability reporting quality on firm value through investor recognition. This quantitative study investigates the relationship between sustainability reporting quality and firm value, focusing on non-financial sector companies listed on the Indonesia Stock Exchange (IDX) between 2017 and 2020. The sample size for this study was 320. The analysis employed a multivariate approach using a structural equation model (SEM) based on Partial Least Squares (PLS). The research findings demonstrate that the quality of sustainability reporting can increase firm value because investors view the quality of reporting as reflecting sustainable practices that have been implemented properly. Furthermore, the study confirms that sustainability reporting quality positively influences investor recognition. This research contributes empirically by highlighting the mediating role of investor recognition in the relationship between sustainability reporting quality and firm value. This study provides evidence that investor recognition of sustainability reporting quality contributes to an enhancement in firm value from an agency theory and signaling theory perspective.

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)0.022
metaresearch head score (Gemma)0.019
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.429
Threshold uncertainty score0.989

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0220.019
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0010.000
Scholarly communication0.0000.000
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 head0.028
GPT teacher head0.296
Teacher spread0.268 · 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

Citations6
Published2023
Admission routes1
Has abstractyes

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