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Record W4320147231 · doi:10.55365/1923.x2022.20.105

What are the Challenges that SMEs have Faced During the Financial Crisis in Lebanon?

2022· article· en· W4320147231 on OpenAlexvenueno aff
Racha Ghayad, Mohamad Hamdan, Mohammad Hammoud

Bibliographic record

VenueReview of Economics and Finance · 2022
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicInternational Business and FDI
Canadian institutionsnot available
Fundersnot available
KeywordsProfitability indexBusinessOrder (exchange)Face (sociological concept)Financial crisisSmall and medium-sized enterprisesCapital (architecture)FinanceValue (mathematics)Affect (linguistics)MarketingEconomics

Abstract

fetched live from OpenAlex

Small and Medium Size Enterprises have a crucial part in every economy.They account for the majority of businesses worldwide.They provide the main source of employment and are major contributors to value creation across all sectors.Studies have been made to measure the impact of problems that SMEs' performances suffer from.This study is conducted to show the effect of the challenges SMEs face in Lebanon, focusing mainly on their performance.The methodology of this paper includes several previous studies and a survey questionnaire in order to study how Lebanese SMEs' owners perceive the different challenges that they face and their impact on their business.The findings showed that most SMEs lack financial resources due to their inaccessibility to financial capital especially during the last three years.We concluded that employees' salaries have an effect on performance while entrepreneurial skills and business obstacles do not affect profitability.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.013
Threshold uncertainty score0.025

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.027
GPT teacher head0.221
Teacher spread0.194 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
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

Citations2
Published2022
Admission routes1
Has abstractyes

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