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Record W2077226410 · doi:10.1016/j.jom.2003.02.003

The effect of supply chain glitches on shareholder wealth

2003· article· en· W2077226410 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

VenueJournal of Operations Management · 2003
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicSupply Chain and Inventory Management
Canadian institutionsWestern University
Fundersnot available
KeywordsShareholderShareholder valueEquity (law)Stock marketMonetary economicsDebtStock (firearms)EconomicsBusinessFinanceCorporate governanceLaw

Abstract

fetched live from OpenAlex

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.

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)0.002
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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.832
Threshold uncertainty score0.484

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.237
Teacher spread0.223 · 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