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Record W4416687832 · doi:10.1111/joms.70037

Entrepreneurial Market Leadership Claims, Cultural Resonance, and Investor Evaluations in Nascent Markets: The Goldilocks Effect

2025· article· en· W4416687832 on OpenAlexaff
Xiumei Li, Jade Lo, Derek Harmon, V. K. Narayanan

Bibliographic record

VenueJournal of Management Studies · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicDiverse Aspects of Tourism Research
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsGoldilocks principleEntrepreneurshipResource (disambiguation)CognitionProcess (computing)Cultural diversityCultural background

Abstract

fetched live from OpenAlex

Abstract Cultural entrepreneurship research emphasizes entrepreneurs’ use of cultural resources to influence audience evaluations through resonance. However, the process by which such cultural resonance is achieved remains underexplored, particularly as an intermediary outcome. We investigate how cultural resonance may be attained by focusing on entrepreneurs’ use of a prevalent cultural resource in nascent markets: market leadership claims. Incorporating insights from social psychological research, we propose that the frequency of these claims becomes an important prompt in triggering investors’ cognitive processing and affects the attainment of cultural resonance. Specifically, we theorize a ‘Goldilocks effect’: a venture’s increased claiming frequency initially enhances resonance with investors, resulting in more favourable evaluations, but excessive claims reduce it, resulting in less favourable evaluations. Using a multimethod approach comprising an archival study and an experiment, we find support for our theory. These findings offer new insights into research on cultural entrepreneurship, discursive strategy, and nascent market strategies.

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)0.005
metaresearch head score (Gemma)0.001
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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.482
Threshold uncertainty score0.386

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.078
GPT teacher head0.412
Teacher spread0.334 · 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
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

Citations0
Published2025
Admission routes1
Has abstractyes

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