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The Influence of Supply Chain Collaboration on Process, Relational and Product Innovations

2010· book-chapter· en· W2498477153 on OpenAlexaff
Luc Cassivi, Pierre Hadaya, Élisabeth Lefebvre, Louis A. Lefebvre

Bibliographic record

VenueIGI Global eBooks · 2010
Typebook-chapter
Languageen
FieldBusiness, Management and Accounting
TopicInnovation and Knowledge Management
Canadian institutionsPolytechnique MontréalUniversité du Québec à Montréal
Fundersnot available
KeywordsBusinessPerspective (graphical)Upstream (networking)Supply chainProduct (mathematics)Downstream (manufacturing)Process (computing)Product innovationProcess managementRelational viewKnowledge managementNew product developmentIndustrial organizationMarketingEngineeringComputer science

Abstract

fetched live from OpenAlex

This chapter focuses on the impact of strategic and tactical collaborative actions as well as e-collaboration tools efficiency on process and relational innovations which in turn should influence product innovations. The results of this study show that tactical collaborative actions are more geared to lead firms to innovate rather than strategic actions. Findings also suggest that relational innovation has an effect on product innovation for the upstream perspective, whilst process innovation influences product innovation for the downstream perspective.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.007
Threshold uncertainty score0.024

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.002
Science and technology studies0.0010.002
Scholarly communication0.0050.004
Open science0.0000.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0070.001

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 head0.012
GPT teacher head0.234
Teacher spread0.221 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2010
Admission routes1
Has abstractyes

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