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Record W4311309723 · doi:10.1108/ijaim-05-2022-0099

Corporate social responsibility transparency and trade credit financing

2022· article· en· W4311309723 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueInternational Journal of Accounting and Information Management · 2022
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicWorking Capital and Financial Performance
Canadian institutionsSaint Mary's University
Fundersnot available
KeywordsTransparency (behavior)Corporate social responsibilityMarket liquidityAccountingCorporate governanceBusinessStock exchangeOrdinary least squaresOriginalityEconomicsFinanceEconometricsQualitative research

Abstract

fetched live from OpenAlex

Purpose This study aims to examine whether a company’s corporate social responsibility (CSR) transparency (reflected in two separate dimensions of social transparency and environmental transparency) affects a company’s dependence on expensive trade credit (TC) financing. Design/methodology/approach The authors use a panel of S&P 500 index companies between 2012 and 2019 and ordinary least squares estimators. Transparency ratings represented by Bloomberg scores capture both the quantity and quality of verified CSR practice information. Findings CSR transparency (CSRT) is negatively associated with a firm’s dependence on expensive TC financing. This study’s results continue to hold after a battery of robustness tests like substitute proxies for TC, use of two-stage least squares regression, industry-adjusted dependent variable, generalized linear model and bootstrapping approach. This association is stronger among companies with higher information asymmetry (IASY) and lower quality regarding governance and financial reporting. Further investigation indicates that potential channels through which CSRT mitigates a company’s reliance on TC financing are the cost of debt (CoD) and stock liquidity. This study’s findings suggest that transparent companies have a lower CoD and higher stock liquidity. This helps these companies to be more financially flexible and eventually less dependent on expensive TC financing. Originality/value By combining two separate research lines of TC and CSR, this study adds to both works of literature as it is the first (to the best of the authors’ knowledge) to present evidence of the effect of CSRT proxied by Bloomberg scores on a company’s reliance on TC (a real economic decision and financial policy). Additionally, this study documents the moderating effects of financial reporting quality, IASY and corporate governance on the relationship between CSRT and TC financing. In conclusion, this study provides empirical evidence regarding the potential mechanisms of CoD and stock liquidity, through which CSRT influences a company’s reliance on TC financing.

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.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.644
Threshold uncertainty score0.388

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.004
Open science0.0000.000
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 head0.014
GPT teacher head0.213
Teacher spread0.199 · 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