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Record W2022959048 · doi:10.5430/ijba.v5n3p30

Management of Supply Chain: X-to-order Concepts vs Make-to-stock Model

2014· article· en· W2022959048 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.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueInternational Journal of Business Administration · 2014
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicProduct Development and Customization
Canadian institutionsnot available
Fundersnot available
KeywordsSupply chainBuild to orderOrder (exchange)Supply chain managementStock (firearms)Industrial organizationPersonalizationComputer scienceProduction (economics)BusinessOrder processingStock managementProcess managementMarketingMicroeconomicsEconomicsFinance

Abstract

fetched live from OpenAlex

In a challenging market, companies’ ability to act faster is considered a basic advantage. From a value chain aspect, when a company cannot change its internal production processes and the external supply streams according to the demand requirements, this may lead to sales reduction or stock left-overs. X-to-order concepts [where X=Α(ssemble), Μ(ake)/Β(uilt) and Ε(ngineer)], are key types of supply chain planning, where the production process starts after the orders are placed. Those methods have caught the attention of both researchers and businesses because of the advantages they offer in business procedures and the customization of consumers needs. The aim of this paper is to present the framework of supply chain management of the X-to-order concepts in comparison to the make-to-stock model and depict the main differences between these two approaches.

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)0.000
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.556
Threshold uncertainty score0.633

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
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 head0.015
GPT teacher head0.264
Teacher spread0.249 · 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