MétaCan
Menu
Back to cohort
Record W2121105484 · doi:10.22146/gamaijb.5630

FORMALIZING PRODUCT COST DISTORTION: The Impact of Volume-Related Allocation Bases on Cost Information

2003· article· en· W2121105484 on OpenAlexaff
Johnny Jermias

Bibliographic record

VenueGadjah Mada International Journal of Business · 2003
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicAccounting and Organizational Management
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsActivity-based costingDistortion (music)Product (mathematics)Volume (thermodynamics)Computer scienceTotal costTarget costingTotal absorption costingOperations managementEconometricsOperations researchMathematicsEconomicsMicroeconomicsPhysicsAccountingTelecommunications

Abstract

fetched live from OpenAlex

The purpose o f this study is to formally analyze product cost distortions resulting from the process of allocating costs to products based on Activity-Based Costing (ABC) and the conventional product costing systems. The model developed in this paper rigorously shows the impact of treating costs that are not volume related as if they are. The model demonstrates that the source of product cost distortion is the difference between the proportion of driver used by each product in ABC and the proportion of the base used by the same product in the conventional costing systems. The difference arises because the conventional costing systems ignore the existence of batch-related and product-related costs. The model predicts a positive association between volume and size diversity with product cost distortions. When interaction between volume and size diversity exists, the distortion is either mitigated or exacerbated. The magnitude of the distortion is jointly determined by the size of the differences and the size of the total indirect costs.

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 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)0.001
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: Empirical
Teacher disagreement score0.523
Threshold uncertainty score0.497

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.003
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 head0.011
GPT teacher head0.233
Teacher spread0.222 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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
Published2003
Admission routes1
Has abstractyes

Explore more

Same venueGadjah Mada International Journal of BusinessSame topicAccounting and Organizational ManagementFrench-language works237,207