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Costos Basados en las Actividades (ABC): aplicando una herramienta para la gestión estratégica en empresas de servicios

2021· article· es· W3184115994 on OpenAlexaff
Marcela Porporato, Josefina Tiepermann Recalde

Bibliographic record

VenueCuadernos Latinoamericanos de Administración · 2021
Typearticle
Languagees
FieldBusiness, Management and Accounting
TopicQuality and Supply Management
Canadian institutionsYork University
Fundersnot available
KeywordsHumanitiesPolitical sciencePhilosophy

Abstract

fetched live from OpenAlex

Este articulo reporta los antecedentes, proceso y cambios experimentados en una empresa de servicios cuando se cambia la asignación de costos que a su vez informa la fijación de precios. El foco está más en la práctica que en el desarrollo teórico, por ello se detallan los pasos seguidos en una empresa de servicios en el sector automotriz operando la provincia de Córdoba (Argentina). El investigador ha sido parte del cambio por lo que el método se asemeja a un “interventionist research” (Jonsson y Lukka, 2007). Adoptar una reasignación de costos en función del método del costeo basado en las actividades (ABC) tiene el potencial de generar ventajas estratégicas según las ideas detrás del gerenciamiento basado en actividades (ABM) según documentó Gosselin (2007). Una de ellas es usar los precios como señales a los clientes que se autoseleccionan y mejoran la mezcla de clientes de la empresa. Emplear el ABC destaca las ineficiencias de los procesos de la empresa, ya que, al momento de generar el mapa de procesos de la misma, se detectaron ciertas actividades que causan costos significativamente más altos y otras que no agregan valor. El método de ABC identifica las mejores oportunidades para iniciar una mejora de procesos.

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 categoriesMeta-epidemiology (narrow), Scholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.504
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0040.001

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 head0.021
GPT teacher head0.300
Teacher spread0.279 · 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; both teacher heads agree on what is shown here.

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

Citations23
Published2021
Admission routes1
Has abstractyes

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