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Record W4413889118 · doi:10.47467/elmal.v6i9.8721

Analisis Bibliometrik: Strategic Management dan Firms’ Performance di SME

2025· article· en· W4413889118 on OpenAlexaboutno aff
Frisqha Sekar G. C. Lintang, Muhammad Saiful Hakim

Bibliographic record

VenueEl-Mal Jurnal Kajian Ekonomi & Bisnis Islam · 2025
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicFinancial Analysis and Corporate Governance
Canadian institutionsnot available
Fundersnot available
KeywordsBusinessBusiness administrationStrategic managementIndustrial organizationProcess managementMarketing

Abstract

fetched live from OpenAlex

Strategic management is the essential basis for supporting the success of an organisation. Strategi management play its role in making the right decision. Strategic management affects the performance of a company, especially small and medium-sized enterprise (SME). This study conducted a systematic literature review and bibliometric analysis by collecting 104 relevant articles. The bibliometric findings indicate that the trend of strategic management research on small-medium enterprise performance has increased from 1989 to 2022. The results of the regional contributions analysis show that the United Kingdom, United States, and Canada were the dominant countries in this research field. The content analysis identified major themes and research trends in this field, including innovation, dynamic capability, strategic choice, RBV, entrepreneurship, customer orientation, and strategic human resource management. Finally, the findings present research gaps, as well as recommendation to examine the influence of resource-based view on industrial organizations.

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)0.011
metaresearch head score (Gemma)0.030
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesBibliometrics
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.916
Threshold uncertainty score0.056

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.030
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0840.108
Science and technology studies0.0010.001
Scholarly communication0.0050.003
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0070.001

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 head0.017
GPT teacher head0.224
Teacher spread0.207 · 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.

Study designNot applicable
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

Citations0
Published2025
Admission routes1
Has abstractyes

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