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Record W102593465

Entrepreneurship Intention Among Malaysian Business Students L'ESPRIT D'ENTREPRISE CHEZ LES ETUDIANTS EN COMMERCE MALAISIENS

2010· article· fr· W102593465 on OpenAlexvenueno aff
Zahariah Mohd Zain, Amalina Mohd Akram, Erlane K Ghani

Bibliographic record

VenueCanadian social science · 2010
Typearticle
Languagefr
FieldBusiness, Management and Accounting
TopicEntrepreneurship Studies and Influences
Canadian institutionsnot available
Fundersnot available
KeywordsEntrepreneurshipPersonalityBig Five personality traitsPsychologyMarketingPublic relationsSociologySocial psychologyBusinessPolitical science
DOInot available

Abstract

fetched live from OpenAlex

Research on entrepreneurship intention has and continues to be of interest to researchers due to its importance to the development for many countries. The literature on entrepreneurship intention has examined various issues with many focusing on the factors that influence entrepreneurship intention. However, most of these studies were conducted in a non-Malaysian setting. This study examines entrepreneurship intention among Malaysian Business Students. Using a questionnaire survey on undergraduate business students in a Malaysian public university, this study examines whether business students have an intention to pursue entrepreneurship. It also examines whether personality traits and environmental factors influence the students to become entrepreneurs. The results indicate that more than half of the respondents have an intention to become entrepreneurs and their decisions are attributed by the influence from their family members, academics and attending courses on entrepreneurship. The results also show that out of the two factors: personality traits and environmental, personality traits play an important role in influencing the students' decision to become entrepreneurs. The findings implicate that academics need to play a significant role in encouraging more students to become entrepreneurs by providing more awareness on the benefits of becoming entrepreneurs and in turn, contributing to the growth of the country's economies and global 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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesScience and technology studies, Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.104
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0030.004
Scholarly communication0.0020.003
Open science0.0020.001
Research integrity0.0000.001
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 head0.015
GPT teacher head0.250
Teacher spread0.236 · 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; both teacher heads agree on what is shown here.

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

Citations8
Published2010
Admission routes1
Has abstractyes

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