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Record W4408116277 · doi:10.3390/jrfm18030131

Financial Systems and Their Influence on Entrepreneurial Development: Insights for Building Sustainable and Inclusive Ecosystems

2025· article· en· W4408116277 on OpenAlexvenueno aff
Olha Prokopenko, Diana Sitenko, Zamzagul Zhanybayeva, Iryna Lomachynska, Айбота Рахметова

Bibliographic record

VenueJournal of risk and financial management · 2025
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicPrivate Equity and Venture Capital
Canadian institutionsnot available
Fundersnot available
KeywordsBusinessSustainable developmentEcosystemEnvironmental resource managementFinanceEconomicsEcology

Abstract

fetched live from OpenAlex

The relationship between financial systems and entrepreneurial development is explored in this paper, specifically how the conditions and characteristics of a country’s financial system affect entrepreneurial opportunities within a space of sustainability and inclusivity. The study is conducted using a mixed methods approach consisting of both a systematic literature review and econometric modeling, coupled with qualitative analysis of a subsample of countries to analyze these dynamics. At a fundamental level, it seeks to analyze the dynamics of financial systems, including the regulatory frameworks, market structures, and access to finance, and their role in forming an entrepreneurial landscape and contributing to the development of sustainable and inclusive ecosystems. The results show strong patterns and challenges in how financial systems support entrepreneurship. Areas of investigation include the role of financial institutions and markets in organizing access to finance (including the impact of regulatory barriers on entrepreneurial activities) and the integration of sustainability principles in policy and practice. This study stresses the need to align financial system policies with the goals of sustainable entrepreneurship so as to facilitate inclusive economic growth. Additionally, the research points out directions for how to make finance more accessible, foster more innovation, and remove the inefficiencies of regulation. For policymakers, investors, and researchers, the insights are designed to improve the entrepreneurial ecosystems through targeted investments as well as simplifying the financial processes. Through proactive actions, stakeholders have the ability to utilize entrepreneurialism as a tool for economic growth, societal progress, and ecological sustainability. The findings of this research contribute to the current ongoing discourse in sustainable entrepreneurship by furthering the stream of debate proposing how financial systems facilitate or inhibit entrepreneurial outcomes.

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.914
Threshold uncertainty score0.689

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0000.001
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 head0.004
GPT teacher head0.200
Teacher spread0.196 · 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

Citations6
Published2025
Admission routes1
Has abstractyes

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