The Impact of Changing External Auditors, Auditor Tenure, and Audit Firm Type on the Quality of Financial Reports on the Saudi Stock Exchange
Bibliographic record
Abstract
The purpose of this study is to examine the influences of external auditor firm type, auditor tenure, and external auditor changes on the quality of Saudi Arabian financial reports. In particular, this study examines the quality of financial reports of companies listed on the Saudi Stock Exchange using a widely accepted evaluation model modified by JonesThis study aims to determine whether Big Four and non-Big Four audit firms, auditor tenures of three or more years, and external auditor changes have any impact on the quality of financial reports of Saudi-listed companies. This study uses 175 firm-year observations of 35 companies listed on the Tadawul Saudi Stock Exchange between 2017 and 2021. Using discretionary accruals (DACC) as modified by Jones to measure the quality of financial reports, the findings illustrate that there is a significant negative relationship between Big Four audit firms and DACC. However, the study also shows a significant positive correlation between auditor tenure and DACC. The research revealed that there is no significant relationship between auditor change and DACC. These results have practical implications for policy development. According to the outcomes of this research, there are numerous ramifications for both companies and the government in Saudi Arabia in terms of enhancing the relationship between companies and audit firms and determining the most suitable auditor tenure to improve the quality of financial reports.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.035 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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 source (direct Gemma or distilled Codex), 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".