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Entrepreneurial Charisma: A Key to Employee Identification?

2006· article· en· W2092318160 on OpenAlexaffabout
Francine Schlosser, Zelimir W Todorovic

Bibliographic record

VenueJournal of Small Business & Entrepreneurship · 2006
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicEntrepreneurship Studies and Influences
Canadian institutionsUniversity of Windsor
Fundersnot available
KeywordsProactivityEntrepreneurial orientationBusinessMarketingValue (mathematics)CharismaBig Five personality traitsInterpersonal communicationPersonalityLeadership styleWork (physics)Empirical researchOrder (exchange)EntrepreneurshipPsychologyPublic relationsSocial psychology

Abstract

fetched live from OpenAlex

Entrepreneurial businesses are an important driver of modern day economies. A firm that adopts a strategy of calculated risks and demonstrates proactiveness and innovation reflects an entrepreneurial orientation (EO). In order to create an entrepreneurial orientation and associated performance outcomes, it is necessary to understand the role of individuals and the interpersonal processes that shape values, norms, and behaviors. Incorporating research from the literature of social psychology, this study examines the effect of individual and organizational variables on employees who work for an entrepreneurial venture. A cross-sectional study of 78 employees of small Canadian businesses empirically demonstrates how an entrepreneurial strategic orientation and a charismatic leadership style encourage employees to identify with the entrepreneurial organization. Empirical results indicate that personality and strategic direction play an important part in creating value for the entrepreneurial firm.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.010
metaresearch head score (Gemma)0.053
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.010
Threshold uncertainty score0.054

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.053
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0040.002
Scholarly communication0.0040.003
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0090.001

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 head0.021
GPT teacher head0.227
Teacher spread0.206 · 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 source (direct Gemma or distilled Codex), 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

Citations12
Published2006
Admission routes2
Has abstractyes

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