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Record W2977800066 · doi:10.5267/j.msl.2019.9.020

The impact of individual and environmental characteristics on students’ entrepreneurial intention

2019· article· en· W2977800066 on OpenAlexvenueno aff
Cong Doanh Duong, Huu Xuyen Nguyen, Thi Viet Nga Ngo, Van Hau Nguyen, Thị Phương Linh Nguyễn

Bibliographic record

VenueManagement Science Letters · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicVocational and Entrepreneurial Education
Canadian institutionsnot available
Fundersnot available
KeywordsPsychologyBusinessMarketingSocial psychologyApplied psychology

Abstract

fetched live from OpenAlex

The primary objective of this study is to investigate the effects of personal attitude toward entrepreneurship, self-efficacy (individual characteristics) and social capital, country norms (environmental characteristics) on entrepreneurial intention among students at universities and colleges in Vietnam. By collecting data from 210 students in Vietnam, authors employ the quantitative approach such as certain descriptive statistics, explorative factor analysis (EFA), KMO and Bartlett test, correlation coefficient analysis, ANOVA test and multiple regression analysis to test hypothesizes. The study investigates the relationship between entrepreneurial attitude, self-efficacy, social capital, country norms and entrepreneurial intention. The result of this research indicates that a large proportion of students only study and only a small percentage of them study and run their own business. In terms of willingness to take the risks, the highest figure belongs to the neutral level. In addition, the correlation coefficient and multiple regressions analysis indicate that all four factors were positively associated with entrepreneurial intention. Specially, country norms are seen as the most influential factors on entrepreneurial intention, followed by social capital, personal attitude, and self-efficacy, respectively.

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)0.001
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.039
Threshold uncertainty score0.304

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.293
Teacher spread0.282 · 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

Citations30
Published2019
Admission routes1
Has abstractyes

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