The effect of supply chain glitches on shareholder wealth
Bibliographic record
Abstract
Abstract This paper estimates the shareholder wealth affects of supply chain glitches that resulted in production or shipment delays. The results are based on a sample of 519 glitches announcements made during 1989–2000. Shareholder wealth affects are estimated by computing the abnormal stock returns (actual returns adjusted for industry and market‐wide influences) around the date when information about glitches is publicly announced. Supply chain glitch announcements are associated with an abnormal decrease in shareholder value of 10.28%. Regression analysis is used to identify factors that influence the direction and magnitude of the change in the stock market’s reaction to glitches. We find that larger firms experience a less negative market reaction, and firms with higher growth prospects experience a more negative reaction. There is no difference between the stock market’s reaction to pre‐1995 and post‐1995 glitches, suggesting that the market has always viewed glitches unfavorably. Capital structure (debt–equity ratio) has little impact on the stock market’s reaction to glitches. We also provide descriptive results on how sources of responsibility and reasons for glitches affect shareholder wealth.
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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 | 0.001 | 0.013 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".