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Record W3033338886 · doi:10.5430/jms.v11n2p41

Inventory Control and Financial Performance of Listed Conglomerate Firms in Nigeria

2020· article· en· W3033338886 on OpenAlexvenueno aff
Folajimi Festus Adegbie, Appolos N. Nwaobia, Grace Oyeyemi Ogundajo, Olusoji David Olunuga

Bibliographic record

VenueJournal of Management and Strategy · 2020
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicManagement and Optimization Techniques
Canadian institutionsnot available
Fundersnot available
KeywordsCronbach's alphaProcurementBusinessPopulationAuditInventory valuationOperations managementAccountingControl (management)Production (economics)Inventory controlMarketingFinanceEconomicsManagementService (business)

Abstract

fetched live from OpenAlex

Inventory constitutes the substantial portion of the cost of production of firms. Conglomerate firms faced a challenge pf dwindling return due to the huge cost of production of which inventory constitute the larger portion. Studies have shown that effective inventory management which entails forecasting, acquisition, transportation, inspection, material handling, storing, warehousing, suppliers’ management and inventory security are germane in reducing the cost of production to the barest minimum and enhance the returns. This study examined the effect of inventory control (inventory procurement control, inventory security control and inventory usage control) on the financial performance of listed conglomerate firms in Nigeria. The study adopted both field and empirical survey research design. The population of the study constitutes the entire six (6) listed conglomerates as at 31st December, 2018. The target population represent 108 staff of the finance and store sections out of which seventy-two were selected using quota sampling techniques for the administration of structure questionnaire, while total enumeration technique was used for the secondary data. The research instrument was validated by checking the constructs of the questions in the questionnaire using content validity. Cronbach Alpha reliability test was carried out and the result showed that the research instrument is reliable with an overall value of 0.988 which is greater than 0.70-0.80 threshold. 68 out of 72 administered structured questionnaire were retrieved representing 94.4% retrieved and used for the analysis. Secondary data extracted from the audited annual reports and accounts for a period of twenty-two (22) years yielding 110 unbalanced firm year observations were used. Descriptive and inferential statistics were employed for testing the hypotheses. The findings revealed that: inventory control significantly affects financial performance of listed conglomerate firms in Nigeria (Adj.R2= 0.873, F(3,65)=10.19, p< 0.1); inventory procurement control has significant positive effect on financial performance (β= .628, R2= 0.565, t(67)= 3.494, p <0.1); inventory security control exerts significant positive effect on financial performance (β= .535, R2= 0.706, t(67)= 2.684, p< 0.1); and inventory usage control significantly and positively influence financial performance (β= .531, R2= 0.492, t(67)= 2.844, p <0.1). Also, inventory turnover period exerted insignificant positive effect on financial performance (β= 4.64, R2= 0.006, t(108)= 0.83, p> 0.1). The study concluded that inventory control significantly influence financial performance of listed conglomerate firms in Nigeria. The study recommended that management of the firm should improve on suppliers’ strategic relationship and provides adequate automated security for monitoring the movements of inventory in the firm.

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)0.001
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 score0.024
Threshold uncertainty score0.047

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.014
GPT teacher head0.206
Teacher spread0.193 · 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

Citations3
Published2020
Admission routes1
Has abstractyes

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