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Record W4388670052 · doi:10.1177/14657503231214389

The relationship between entrepreneurial intention and behavior: A meta-analytic review

2023· review· en· W4388670052 on OpenAlexaff
Ean Tsou, Piers Steel, Oleksiy Osiyevskyy

Bibliographic record

VenueThe International Journal of Entrepreneurship and Innovation · 2023
Typereview
Languageen
FieldBusiness, Management and Accounting
TopicEntrepreneurship Studies and Influences
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsPsychologyVariance (accounting)Meta-analysisEntrepreneurshipSocial psychologyTheory of planned behaviorAction (physics)Computer scienceControl (management)Economics

Abstract

fetched live from OpenAlex

A vibrant literature studying antecedents of entrepreneurial intentions is largely motivated by an often implicit assumption that they will be followed by subsequent entrepreneurial behaviors or actions. A much smaller number of studies actually test this assumption. Their results suggest that while the entrepreneurial intention–behavior relationship is usually present, its strength turns out highly contextual. This meta-analysis intends to integrate and summarize the available research base on the entrepreneurial intention–behavior relationship, assessing the moderating impacts of environmental, demographic and methodological factors. Data from 75 studies (150,703 individuals) were included in the analysis. Our results indicate that the focal relationship is robust across environmental contexts, populations, and methodologies except for the measures used for entrepreneurial behavior, the use of a database compared to collecting new data, and the duration of time between intention and behavior. Additionally, entrepreneurial intentions were found to account for only 17% of the variance in entrepreneurial behaviors as opposed to the commonly expected and cited 37%. Our findings suggest theoretical and methodological considerations for future work aimed at exploring and overcoming the non-trivial intention–behavior gap and we encourage the discovery of cognitive and behavioral factors reinforcing the intention–action translation at different levels of analysis and over time.

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)0.003
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.928
Threshold uncertainty score0.787

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0000.001
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 head0.269
GPT teacher head0.388
Teacher spread0.119 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations34
Published2023
Admission routes1
Has abstractyes

Explore more

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