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Record W2074171563 · doi:10.1504/ijspm.2008.022052

Spreadsheet vs. multiagent-based simulations in the study of decision making in supply chains

2008· article· en· W2074171563 on OpenAlexafffundabout
Thierry Moyaux, Brahim Chaib-draa, Sophie D’Amours

Bibliographic record

VenueInternational Journal of Simulation and Process Modelling · 2008
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicSupply Chain and Inventory Management
Canadian institutionsUniversité Laval
FundersUniversité Laval
KeywordsSupply chainComputer scienceContext (archaeology)Focus (optics)Bullwhip effectMulti-agent systemOperations researchSupply chain managementSimulationIndustrial engineeringArtificial intelligenceEngineering

Abstract

fetched live from OpenAlex

A game called the Quebec Wood Supply Game (QWSG) is a role-playing simulation based on the Beer Game for teaching Supply Chain (SC) dynamics, and, in particular, the bullwhip effect. In this context, this paper describes and compares two simulators based on the QWSG which may be used to study decision making and its impact on SC dynamics. We first focus on the direct implementation of the QWSG in a spreadsheet program. This spreadsheet model is the base on which we next build a more complex MultiAgent Based Simulation (MABS) in which JACK™ agents represent companies. Finally, we compare the respective advantages of each simulator. We identify the features of a SC model making a spreadsheet simulation impossible, and those for which a spreadsheet simulation is better, as good as, or worse than MABS.

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)0.003
metaresearch head score (Gemma)0.011
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.038
Threshold uncertainty score0.075

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.011
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.067
GPT teacher head0.327
Teacher spread0.260 · 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 designSimulation or modeling
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

Citations4
Published2008
Admission routes3
Has abstractyes

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Same venueInternational Journal of Simulation and Process ModellingSame topicSupply Chain and Inventory ManagementFrench-language works237,207