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Record W4394886245 · doi:10.5267/j.uscm.2024.2.013

Carbon emission disclosure and PROPER: Are they attractive to foreign investors?

2024· article· en· W4394886245 on OpenAlexvenueno aff
Luky Patricia Widianingsih, Cliff Kohardinata

Bibliographic record

VenueUncertain Supply Chain Management · 2024
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCorporate Social Responsibility Reporting
Canadian institutionsnot available
Fundersnot available
KeywordsBusinessCarbon fibersMonetary economicsFinancial systemMaterials scienceEconomicsComposite material

Abstract

fetched live from OpenAlex

This study examines the effect of carbon emission disclosure and the Public Disclosure Program for Environmental Compliance (PROPER) on foreign ownership of manufacturing companies in Indonesia from 2018 to 2022 that publish annual reports or sustainability reports, registered with the Ministry of Environment and Forestry PROPER, and carbon emissions disclosure in the annual report and/or sustainability report. The analysis method uses the ordinary least squared (OLS) approach to study 28 PROPER manufacturing companies used as samples. The control variable used is return on equity (ROE), this is based on the idea that foreign investors are willing to invest in other countries to get a return on the equity or capital channeled to the company. The results show that carbon emissions disclosure has a significant positive effect on foreign ownership. Conversely, PROPER did not have any significant positive effect on foreign ownership. The results show interesting results that foreign investors are proven to consider environmental aspects in making decisions to invest in companies in Indonesia. On the other hand, the Indonesian government needs to ensure that its PROPER ratings can also provide benefits to foreign investors to attract their investment decisions.

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.600
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
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 head0.257
Teacher spread0.232 · 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

Citations4
Published2024
Admission routes1
Has abstractyes

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