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Record W4327790955 · doi:10.5267/j.msl.2023.2.002

Small and medium emprises performance in Dubai: A critical role of technological factor and environmental factor

2023· article· en· W4327790955 on OpenAlexvenueno aff
Nasser Al Darmaki, Hartini binti Jaafar

Bibliographic record

VenueManagement Science Letters · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicSocioeconomic Development in MENA
Canadian institutionsnot available
Fundersnot available
KeywordsGovernment (linguistics)BusinessIndustrial organizationMarketing

Abstract

fetched live from OpenAlex

In Dubai, the government alone cannot bring about economic development and provide jobs to all and sundry. Businesses established by individuals and corporate entities aid the government in the provision of jobs to people and contribute to the economic growth and development of a country. The role of SMEs is crucial in most of the countries of the world and they contribute significantly towards provision of employment opportunities in their local communities and development of their economies. The main objective of this study is to examine the factors influencing the performance of SMEs in the UAE. The findings from the analysis found that technological factors and environmental factors have a positive and significant impact on SMEs performance. This study has a significant contribution to the body of literature as it provides a worthy theoretical framework in it. Besides theoretical contribution, this study also provides practical implications to SMEs, government and policymakers. The future direction of this study would enhance the future body of literature.

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)0.003
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.035
Threshold uncertainty score0.070

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0030.002
Scholarly communication0.0040.001
Open science0.0010.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.022
GPT teacher head0.255
Teacher spread0.233 · 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 designObservational
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
Published2023
Admission routes1
Has abstractyes

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