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Record W2606882125 · doi:10.5430/afr.v6n2p136

The Impact of Supply Chain Management on Financial Performance and Responsibility Accounting Agribusiness Case from Egypt

2017· article· en· W2606882125 on OpenAlexvenueno aff
Mohamed Aly Wahdan, Mohamed Ashraf Emam

Bibliographic record

VenueAccounting and Finance Research · 2017
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicQuality and Supply Management
Canadian institutionsnot available
Fundersnot available
KeywordsProfitability indexAgribusinessSupply chainBusinessSupply chain managementProductivityFinancial managementAccountingCost accountingManagement accountingFinanceIndustrial organizationMarketingAgricultureEconomics

Abstract

fetched live from OpenAlex

This paper presents the impact of applying the supply chain management (SCM) on the agribusiness field to optimize productivity and decreasing cost which will have a direct impact on the net income of the organization. The main two research questions are: is there a significant impact of supply chain management on financial performance? and is there a significant relationship between supply chain management and financial performance as well as responsibility accounting? To answer the research questions, data was collected from financial statements of agribusiness case from Egypt and the survey was conducted. The findings of the study indicated that there is a significant impact of supply chain management on financial performance through enhancing the productivity, decreasing the cost and improving profitability. Moreover, applying the efficient supply chain management can improve the use of responsibility accounting through the efficient usage for the budget of the crop.

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.060
Threshold uncertainty score0.120

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0020.001
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.340
Teacher spread0.293 · 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 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

Citations11
Published2017
Admission routes1
Has abstractyes

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