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Record W4404184207 · doi:10.1142/s0219877024500573

Operation Research — The Influence of Venture Capital on the Growth of E-Commerce Listed Enterprises

2024· article· en· W4404184207 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 Innovation and Technology Management · 2024
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicPrivate Equity and Venture Capital
Canadian institutionsCARE Canada
Fundersnot available
KeywordsBusinessVenture capitalSocial venture capitalE-commerceBusiness administrationIndustrial organizationMarketingCommerceAccountingFinance

Abstract

fetched live from OpenAlex

Venture capital (VC) is essential for the growth of small and medium enterprises (SMEs) in developed e-commerce countries. SMEs play a crucial role in the economic development of both developing and developed countries. This paper proposes the influence of VC on the growth of e-commerce in SMEs using the propensity score matching (PSM) method. PSM is defined as the statistical analysis of observational data, where a statistical matching method attempts to evaluate the impacts of a treatment or policy. The experimental results show that the effect of e-commerce on SMEs who received VC financing experience improves the performance of employment growth and sales. Our findings reveal that VC significantly enhances employment rates and sales performance in e-commerce sectors. The study underscores the critical role of VC in driving innovation and growth within SMEs, providing valuable insights for investors and policymakers aiming to foster economic development.

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)0.000
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: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.394
Threshold uncertainty score0.171

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.026
GPT teacher head0.305
Teacher spread0.278 · 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