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Record W2902545636 · doi:10.5539/ass.v14n12p104

Entrepreneurial Leadership: A Review of Measures, Antecedents, Outcomes and Moderators

2018· review· en· W2902545636 on OpenAlexvenueno aff
Sushant Ranjan

Bibliographic record

VenueAsian Social Science · 2018
Typereview
Languageen
FieldBusiness, Management and Accounting
TopicEntrepreneurship Studies and Influences
Canadian institutionsnot available
Fundersnot available
KeywordsEntrepreneurial leadershipMindsetFutures studiesAmbidexterityCreativityPsychologyFraming (construction)Social capitalProactivityEthical leadershipPublic relationsMarketingBusinessEntrepreneurshipSociologySocial psychologyPolitical science

Abstract

fetched live from OpenAlex

The current study presents the review on entrepreneurial leadership since year 1980. Concept of entrepreneurial leadership, and its development so far were captured. Drawing on the comprehensive literature review of 50 studies, we have presented the measures used in the prior literature to capture the main construct of entrepreneurial leadership. Dimensions such as strategic factors, communicative factors, personal factors, motivational factors and leadership behaviors contribute to form entrepreneurial leadership. Various antecedents of entrepreneurial leadership such as human capital, social capital, entrepreneurial mindset, ambidexterity, and uncertainty absorbing, challenge framing, clearing path, commitment building and limits specification were identified. Outcomes such as wealth creation, strategic management of resources, innovation performance, startup performance and creativity were also identified. The possible traits of entrepreneurial leaders such as performance oriented, ambitious, informed, extra insight visionary foresight, confidence builder, diplomatic, effective bargainer, convincing, encourage, inspirational, enthusiastic, team builder, improvement-oriented, integrator, intellectual stimulation and positive attitudes are found.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.968
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0010.001
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 head0.088
GPT teacher head0.327
Teacher spread0.239 · 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.

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

Citations22
Published2018
Admission routes1
Has abstractyes

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