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Record W2155872099 · doi:10.5267/j.msl.2013.01.034

The effect of social capital on knowledge creation in Petrochemical Industry

2013· article· en· W2155872099 on OpenAlexvenueno aff
Mohammad Reza Saadi, Narjes Pahlavani

Bibliographic record

VenueManagement Science Letters · 2013
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicIntellectual Capital and Performance Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsPetrochemicalBusinessSocial capitalIndustrial organizationCapital (architecture)MarketingKnowledge managementEnvironmental economicsCommerceOperations managementComputer scienceEconomicsEngineeringSociologyWaste managementSocial scienceHistory

Abstract

fetched live from OpenAlex

Knowledge creation and innovation are primary competitive advantage in the modern economy.Social capital, on the other hand, is one the most important components of organizations, which could help share knowledge within organization and create competitive advantage.The purpose of this paper is to investigate the impact of social capital on knowledge creation in petrochemical industry.The survey designs a questionnaire and distributes it among some experts who worked for petrochemical industry.The study investigates the impact of social capital in terms of three components of cognitive, relational and structural capitals on knowledge creation.Cronbach alpha in combined form is calculated as 0.79, which validates the overall survey.Structural equation modeling has been used to examine the proposed study and the results have confirmed that all three items positively influence knowledge creation, significantly.

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)0.002
metaresearch head score (Gemma)0.013
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 score0.004
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.013
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0000.002
Research integrity0.0000.001
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 head0.006
GPT teacher head0.224
Teacher spread0.218 · 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

Citations7
Published2013
Admission routes1
Has abstractyes

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