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Record W2883907839 · doi:10.17722/ijme.v11i1.1000

Potential Global Competitiveness of Sri Lankan Virgin Coconut Oil Industry

2018· article· en· W2883907839 on OpenAlexvenueno aff
Pivithuru Janak Kumarasinghe, Savinda Perera

Bibliographic record

VenueInternational Journal of Management Excellence · 2018
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicGlobal Trade and Competitiveness
Canadian institutionsnot available
Fundersnot available
KeywordsSri lankaCoconut oilBusinessLikert scaleQuality (philosophy)PopulationSupply and demandRaw materialAgricultural economicsCommerceEconomicsMarketingMathematicsFood scienceSocioeconomics

Abstract

fetched live from OpenAlex

The study focuses on Sri Lankan virgin coconut oil industry because of it is one of the upcoming export products and also its position as one of the key player in the global market. Sri Lankan coconut industry is one of the major foreign exchange and employment generation source and element of the Sri Lankan nation. The study attempted to unearth the determinants of export competitiveness of virgin coconut oil industry in Sri Lanka by drawing attention on Porter’s theory of the competitive advantage of nations. The target population of the study consisted with individual firms which are engaging in virgin coconut oil export in Sri Lanka is two hundred and nineteen. The study used a likert scale to measure the chosen variables. Based on the Pearson Correlation analysis researcher can say that there is significance strong positive relationship between Availability of Raw materials, Quality of demand and Market share of export with the Export Competitiveness. According to regression analysis researcher can say that availability of Raw materials, Local market, Quality of demand and Market share of export has significance positive affect on Advantage of Export Competitiveness.

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)0.000
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.579
Threshold uncertainty score0.979

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.011
GPT teacher head0.248
Teacher spread0.237 · 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 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

Citations0
Published2018
Admission routes1
Has abstractyes

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