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Record W2397672574 · doi:10.5539/ibr.v9n8p1

Environmental Conditions, Entrepreneur Alertness and Social Capital on Performance

2016· article· en· W2397672574 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueInternational Business Research · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicQualitative Comparative Analysis Research
Canadian institutionsnot available
FundersSoochow UniversityNational Natural Science Foundation of ChinaNational Dong Hwa UniversityBowling Green State UniversityBoston College
KeywordsQualitative comparative analysisAlertnessEquifinalityEntrepreneurshipLISRELSocial capitalOpenness to experienceAntecedent (behavioral psychology)Causality (physics)Set (abstract data type)Causal modelStructural equation modelingMarketingPsychologyClassical economicsEconomicsBusinessSocial psychologySociologyComputer scienceMathematics

Abstract

fetched live from OpenAlex

<p>This study addresses the important question of causal complexity as it relates to the influence of social capital, entrepreneurial alertness and the entrepreneurship environment on business performance. Using a relatively new methodological approach, namely fuzzy-set qualitative comparative analysis (fsQCA), this paper aims to investigate alternative complex antecedent conditions (or causal recipes) that lead to high performance. Based on a survey of 194 entrepreneurs in China, this paper shows that business performance is likely to be the result of a combination of causal factors. This study finds that: (1) four different configurations of social capital, entrepreneurial alertness and entrepreneurship environment were “equifinal” causes of high performance, and (2) market openness should fit other environmental conditions to achieve high performance. This study contributes to research on entrepreneurship by applying the ideas of “equifinality” and “fit” to entrepreneurial characteristics and environment theory.</p>

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.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.464
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.002
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0050.001

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 head0.131
GPT teacher head0.471
Teacher spread0.341 · 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