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Record W4401727598 · doi:10.5430/afr.v13n3p18

The Impact of Intellectual Capital on Enterprise Performance in Saudi Arabia: Literature Review of Empirical Research

2024· article· en· W4401727598 on OpenAlexvenueno aff
Afnan Alturiqi

Bibliographic record

VenueAccounting and Finance Research · 2024
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicIntellectual Capital and Performance Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsIntellectual capitalEmpirical researchContext (archaeology)Competitive advantageBusinessCapital (architecture)Production (economics)Knowledge managementIndustrial organizationMarketingEconomicsFinanceComputer scienceMicroeconomics

Abstract

fetched live from OpenAlex

Physical assets such as buildings, plants, and so on, are important factors in the production era, but their importance has decreased with increased the importance of intangible assets in the knowledge era. In the knowledge-based economy, intellectual capital (IC) is one of the most important assets in an enterprise for achieving sustainable competitive advantages. As a result, research on the correlation between IC and enterprise performance (EP) and its role in achieving competitive advantage has become one of the most controversial topics in accounting globally. The findings of the empirical research have been inconsistent; there is no consensus on the effect of IC on the enterprise's performance due to the different definitions and methods of measuring IC used among researchers. The paper focuses on reviewing empirical research about the effect of IC on EP in Saudi Arabia, aiming at a presentation of recent developments and a discussion of the direction for future research. This paper is the first study to review empirical research on IC and EP in the Saudi context.

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)0.007
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.465
Threshold uncertainty score0.595

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.005
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
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 head0.053
GPT teacher head0.381
Teacher spread0.329 · 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 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
Published2024
Admission routes1
Has abstractyes

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