Corporate disclosures on curbing bribery and the UK Bribery Act 2010: evidence from UK companies
Bibliographic record
Abstract
Purpose This study aims to investigate whether United Kingdom (UK)-based companies have changed their voluntary disclosures on curbing the bribery of foreign officials in response to the UK Bribery Act 2010, and if so whether and how such disclosure changes substantively reflected allegations of bribery of foreign officials by news media. Design/methodology/approach By using the notions of institutional pressure and decoupling and applying content and thematic analysis, the authors examined, in particular, disclosures on curbing bribery by the largest 100 companies listed on the London Stock Exchange in periods before and after the Bribery Act (2007–2012). News media reports covering incidents of bribery of foreign officials and related corporate disclosures before and after the Act were thoroughly examined to problematise corporate anti-bribery disclosure practices. Findings The study finds a significant change in disclosure on curbing bribery before and after the enactment of the UK Bribery Act, consistent with the notion of institutional coercive pressure. However, decoupling is also found: organisations' disclosures did not substantively reflect incidents of bribing foreign public officials, mostly from underprivileged developing nations. Research limitations/implications This study acknowledges a limitation stemming from using media reports that focus on bribery incidents in identifying actual cases or incidents of bribery. As some of the incidents identified from news media reports appeared to be allegations, not convictions for bribery, companies could have defensible reasons for not disclosing some aspects of them. Practical implications Regulators should think why new or more regulations without substantive requirement are not helpful to curb corporate decoupling and injustice. The regulators should address the crisis that multinational companies (MNCs) being suppliers of bribery are much more harmful for the underprivileged communities in developing nations. Accordingly, this paper provides practical insights into how stakeholders ought to critically interpret MNCs' accounts of their involvement in bribery. Originality/value This study contributes to the accounting literature by problematising MNCs' operations in underprivileged countries. The findings suggest that not only public officials in developing countries as creators of bribery but also Western-based MNCs as the suppliers of bribery contribute to perpetuating unethical practices and injustices to the underprivileged communities in developing countries. This research is imperative as this is one of the first known studies that provides evidence of the actions including disclosure-related actions companies have taken in response to the UK Bribery Act.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.044 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".