MétaCan
Menu
Back to cohort
Record W2987711911 · doi:10.5430/ijfr.v11n1p274

Strategic Costing Models as Strategic Management Accounting Techniques at Private Universities in Riau, Indonesia

2019· article· en· W2987711911 on OpenAlexvenueno aff
Evi Marlina, Hendri Ali Ardi, Siti Samsiah, Kirmizi Ritonga, Amris Rusli Tanjung

Bibliographic record

VenueInternational Journal of Financial Research · 2019
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicAccounting and Organizational Management
Canadian institutionsnot available
Fundersnot available
KeywordsActivity-based costingTarget costingManagement accountingCost accountingStrategic planningBusinessProcess managementProduct cost managementKnowledge managementAccountingComputer scienceMarketingCost engineering

Abstract

fetched live from OpenAlex

As a strategic management in accounting, strategic coasting has attracted the practioners and scholars because the significant influences to comptetitive advantage and organizational performance. This study is aim to explore integrated strategic costing model as an effort to improve competitive advantage and performance of higher education institution. This study also provide the guideline for effectively and efficiently of cost control. A specific strategic costing –activity based costing, value chain costing, quality costing, lifecycle costing and target costing- was elaborated through literature review form each attributes simultaneously and according to comprehensive model that integrated each of principles. The study concluded the scheme is compatible and complete each other according to theoretical point of view due to the integrated implementation of the principles and attributes contribute to organization performance improve. We also argue that the scheme is contribute to distribution of strategic costing attribute and exploitation of organization resources. A new management system proposing to the incorporation of strategic costing attributes into the management of higher education organization resources, and some recommendations for practical use are presented.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.236
Threshold uncertainty score0.739

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0000.001
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 head0.047
GPT teacher head0.311
Teacher spread0.264 · 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 designTheoretical or conceptual
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

Citations11
Published2019
Admission routes1
Has abstractyes

Explore more

Same venueInternational Journal of Financial ResearchSame topicAccounting and Organizational ManagementFrench-language works237,207