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Record W2171217443 · doi:10.5267/j.msl.2013.06.029

A study on mediating role of organizational learning on relationship between market orientation and organizational performance

2013· article· en· W2171217443 on OpenAlexvenueno aff
Azar Kafashpoor, Mohammad Reza Hosseini Moghadam, Masoud Monazzami Borhani, Samira Sabaghian

Bibliographic record

VenueManagement Science Letters · 2013
Typearticle
Languageen
FieldSocial Sciences
TopicKnowledge Management and Sharing
Canadian institutionsnot available
Fundersnot available
KeywordsMarket orientationOrganizational learningOrganizational performanceBusinessOrganizational commitmentKnowledge managementOrientation (vector space)PsychologyComputer scienceMarketingSocial psychologyMathematics

Abstract

fetched live from OpenAlex

Increasing intensity of competition among organizations in current century has caused everlasting search for ways to gain competitive advantage and win the competition.In this regard, organizational learning certainly counts as a competitive advantage to gain for today's managers.This study aims to discuss the mediating role of organizational learning in the relationship between market orientation and organizational performance.The study population includes all of the employees in the Central Office of Ferdowsi University of Mashhad.As 170 samples were randomly stratified and selected, information obtained was analyzed using SPSS software ver.20.While results support the significance of organizational learning's mediating role in the relationship between intelligence generation and intelligence dissemination with organizational performance, this role was declared insignificant in the relationship between responsiveness and organizational 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 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)0.003
metaresearch head score (Gemma)0.008
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 score0.006
Threshold uncertainty score0.021

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.008
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0060.000

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 head0.018
GPT teacher head0.264
Teacher spread0.246 · 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
Published2013
Admission routes1
Has abstractyes

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