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Record W2949627959 · doi:10.5539/ibr.v12n7p76

Inventory Management and Operational Performance of Manufacturing Firms in South-East Nigeria

2019· article· en· W2949627959 on OpenAlexvenueno aff
Stella Mbah, Jeffery Obiezekwem, Azuka Monday Okuoyibo

Bibliographic record

VenueInternational Business Research · 2019
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicSupply Chain and Inventory Management
Canadian institutionsnot available
Fundersnot available
KeywordsGeneral partnershipBusinessOperations managementDescriptive statisticsIndustrialisationMarketingEconomicsFinanceStatistics

Abstract

fetched live from OpenAlex

This study aims to ascertain the relationship between inventory management and operational performance of quoted manufacturing firms in the south-east; one of the geographic regions with high industrialization prospects in Nigeria. To achieve this, operational performance of manufacturing firms and their association with components of inventory management; inventory cost, just-in-time approach, materials requirement planning and strategic supplier partnership, was examined through a questionnaire. Three hundred and seventy-one copies of a questionnaire issued to five hundred and thirty-eight sampled respondents of four quoted manufacturing firms in the south-east region of Nigeria were properly filled and found relevant to the study. The study used SPSS and Excel-based descriptive statistics to analyze the data collected. Regression analysis was used to test the hypotheses of the study. Study results conclude that there is a positive significant relationship between; inventory cost, just in time approach, materials requirement planning and strategic supplier partnership and operational performance of quoted manufacturing firms in the south-east region, Nigeria. The study recommends among others that, manufacturing firms in south-east Nigeria should adopt inventory practices such as strategic supplier partnership, just-in-time approach, materials requirement planning and inventory cost control due to the significant effect these practices have on operational performance.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.055
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.040
GPT teacher head0.283
Teacher spread0.243 · 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.

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

Citations14
Published2019
Admission routes1
Has abstractyes

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