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Record W2020406008 · doi:10.1002/mde.1104

The profitability‐risk tradeoff of just‐in‐time manufacturing technologies

2003· article· en· W2020406008 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

VenueManagerial and Decision Economics · 2003
Typearticle
Languageen
FieldDecision Sciences
TopicAdvanced Statistical Process Monitoring
Canadian institutionsUniversity of WaterlooUniversity of Toronto
FundersBen-Gurion University of the NegevHebrew University of Jerusalem
KeywordsProfitability indexRevenueArgument (complex analysis)ManufacturingBusinessIndustrial organizationEconomicsOperations managementEconometricsAccountingFinanceMarketing

Abstract

fetched live from OpenAlex

Abstract Qualitative survey studies and a recent quantitative study by Callen et al. (2000) indicate that JIT manufacturing is more profitable than conventional non‐JIT manufacturing. This study tests the hypothesis that the excess profitability of JIT manufacturing just compensates for the additional operational risks of JIT technology relative to conventional manufacturing. An often‐suggested alternative hypothesis is that JIT manufacturing dominates conventional manufacturing in reducing costs and increasing revenues and that risk is not an issue. The multivariate results unambiguously reject the hypothesis that excess JIT profits are compensation for additional risk. We find that profitability is inversely related to risk, especially for JIT plants . We also find that the JIT plants in our sample are more profitable than non‐JIT plants even after adjusting for risk , consistent with the dominance argument. Copyright © 2003 John Wiley & Sons, Ltd.

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)0.003
metaresearch head score (Gemma)0.008
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.978
Threshold uncertainty score0.909

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.042
GPT teacher head0.323
Teacher spread0.281 · 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