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Record W4402710866 · doi:10.34190/ecie.19.1.2400

The Role of Cognitive Style in Influencing Entrepreneurial Self-Efficacy and Subsequent Entrepreneurial Intention

2024· article· en· W4402710866 on OpenAlexaff
Salma Nader Abbass Hussein, Hadia Hamdy Abdelaziz

Bibliographic record

VenueEuropean Conference on Innovation and Entrepreneurship · 2024
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicEntrepreneurship Studies and Influences
Canadian institutionsUniversity of Prince Edward Island
Fundersnot available
KeywordsPsychologyStyle (visual arts)Cognitive styleSelf-efficacyCognitionEntrepreneurshipSocial psychologyBusinessArt

Abstract

fetched live from OpenAlex

Cognitive style has been largely acknowledged to highly contribute to explaining variances in individuals’ behavior. However, very few researchers studied the role of cognitive style in influencing entrepreneurial self-efficacy along the entrepreneurial intention process. Therefore, the purpose of this research is to study how differences in preferences towards linear, non-linear and balanced thinking style would affect individuals’ self-perceptions towards entrepreneurial self-efficacy and subsequent intentions to create a new business. This study’s findings reported that non-linear thinking style is negatively correlated to entrepreneurial self-efficacy which subsequently affects entrepreneurial intentions negatively. While linear thinking style was positively correlated to entrepreneurial self-efficacy which in return affects entrepreneurial intentions positively. Moreover, thinking style balance was found to be positively correlated to entrepreneurial self-efficacy that exceeds the magnitude of the Linear-Entrepreneurial Self-Efficacy relationship which subsequently affects intentions positively. Furthermore, the relationship between entrepreneurial self-efficacy and entrepreneurial intentions had higher significance and was stronger in effect for individuals with balanced thinking style than for those with linear and non-linear thinking style.

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)0.001
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 score0.617
Threshold uncertainty score0.980

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
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 head0.027
GPT teacher head0.249
Teacher spread0.221 · 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
Published2024
Admission routes1
Has abstractyes

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