MétaCan
Menu
Back to cohort
Record W4385224056 · doi:10.5465/amproc.2023.268bp

How Institutional Logics Influence Growth: A Field Experiment with Tunisian Women Entrepreneurs

2023· article· en· W4385224056 on OpenAlexaff
Kylie Heales, Angelique Slade Shantz, Desirée F. Pacheco, Luciano Barin Cruz, Charlene Zietsma

Bibliographic record

VenueAcademy of Management Proceedings · 2023
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicEntrepreneurship Studies and Influences
Canadian institutionsHEC MontréalUniversity of Alberta
Fundersnot available
KeywordsEntrepreneurshipInstitutional theoryAffect (linguistics)EmpowermentContext (archaeology)Institutional logicPromotion (chess)Field (mathematics)Investment (military)Social psychologySociologyPublic relationsPsychologyEconomicsPolitical scienceEconomic growthPoliticsSocial science

Abstract

fetched live from OpenAlex

Entrepreneurial training programmes promoting women’s entrepreneurship in low- and middle-income countries command significant global attention and concomitant resources. Despite this broad investment, many ventures in these contexts fail to grow. Prior research suggests that institutionalized patterns of behaviors, in part dictated by institutional logics, may cause this lack of growth. In the context of Tunisian female entrepreneurship, this research explores the effects of community and market logics on entrepreneurial growth outcomes. Using a field experiment, we demonstrate that institutional logics affect the growth aspirations of entrepreneurs through individual empowerment and emotional energy. This research has theoretical implications for institutional logics, entrepreneurial growth, and emotions literatures. Firstly, institutional logics affect entrepreneurial growth outcomes. Secondly, logics are processed by individuals through both cognitive (empowerment) and social (emotions) constructs and we contribute to knowledge of the integrated macro to micro psychological and social processes of institutional logics. Finally, cultural differences explain why logics do not have the expected effects we think they may in the promotion of Western neoliberal entrepreneurial training programs.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.652
Threshold uncertainty score0.947

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.002
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 head0.021
GPT teacher head0.232
Teacher spread0.212 · 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 designTheoretical or conceptual
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

Citations1
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueAcademy of Management ProceedingsSame topicEntrepreneurship Studies and InfluencesFrench-language works237,207