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Record W2022740004 · doi:10.1504/ijpm.2013.056175

Synchronising marketing and supply chain management policies for improving system performance

2013· article· en· W2022740004 on OpenAlex
Suresh Kumar Goyal, Richa Jain

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

VenueInternational Journal of Procurement Management · 2013
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicDigital Platforms and Economics
Canadian institutionsConcordia University
Fundersnot available
KeywordsPublicitySupply chainBusinessSupply chain managementMarketingProduct (mathematics)Demand chainIndustrial organizationService managementOperations managementEconomicsMathematics

Abstract

fetched live from OpenAlex

The present study endorses a view that gives competitive edge to a firm and bolsters its strength. The firm needs to synchronise its marketing as well as supply chain management techniques together. With the launching of a new product, several factors come into play that affects its demand rate over a period of time. Along with – time, price, advertising expenditure, message efficiency – we have deliberated the effects of a new factor, i.e., word of mouth publicity. A simple supply chain of a single supplier and a single retailer has been considered. A joint total cost policy has been formulated for the supply chain, which is also exemplified with a numerical. The optimal solution obtained is checked for stability w.r.t various system parameters. Results obtained have been interpreted analytically.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.750
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0020.004
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 head0.009
GPT teacher head0.195
Teacher spread0.186 · 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