MétaCan
Menu
Back to cohort
Record W4316372813 · doi:10.1108/ijoem-09-2021-1358

The role of trust and e-WOM in the crowdfunding participation: the case of equity crowdfunding platforms in financial services in Iran

2023· article· en· W4316372813 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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueInternational Journal of Emerging Markets · 2023
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicFinTech, Crowdfunding, Digital Finance
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsStructural equation modelingEquity (law)OriginalityBusinessMarketingBusiness administrationPsychologySocial psychologyPolitical science

Abstract

fetched live from OpenAlex

Purpose The aim of this research is to examine the roles of trust and electronic word-of-mouth (e-WOM) in crowdfunding (CF) participation for equity CF by taking into account the following antecedents of trust and e-WOM: intrinsic motivation (IM), extrinsic motivation (EM), deterrents, venture quality (VQ), third-party seal (TPS), value congruence (VC) and perceived accreditation (PA). Design/methodology/approach In this research, a survey among 408 active and potential funders in Iran was conducted. The statistical analysis used partial least squares structural equation modeling (PLS-SEM). Findings The results of this research revealed a significant influence of trust and e-WOM on participation in CF for equity CF. Extrinsic motivation had the greatest impact on trust and VC had the greatest impact on e-WOM. Originality/value This research extends the equity CF research area to CF success and considers the effects of some parameters on CF participation. This research provides many theoretical and practical implications.

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)0.003
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.066
Threshold uncertainty score0.334

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.024
GPT teacher head0.304
Teacher spread0.280 · 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