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Record W2341894183 · doi:10.5539/ibr.v9n6p143

The Effect of Structural Capital on Enterprise (Qualitative and Quantitative) Performance

2016· article· en· W2341894183 on OpenAlexvenueno aff
Osman Yılmaz, Pinar Comez

Bibliographic record

VenueInternational Business Research · 2016
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicIntellectual Capital and Performance Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsLISRELStructural equation modelingStructural capitalHuman capitalCapital (architecture)Classical economicsBusinessIntellectual capitalQualitative analysisIndustrial organizationEconomicsQualitative researchEconometricsMicroeconomicsEconomic capitalIndividual capitalSociologyMathematicsMarket economyFinanceStatistics

Abstract

fetched live from OpenAlex

<p>Intellectual capital is a new managerial notion that is adaptive to changing environmental conditions and provides advantages in highly competitive marketplace. It is contextualized in the literature with the sub-elements: str<em>uctural capital, human capital and relation capital. </em>Even though this notion found wide interest in academia, the impacts of its sub-elements on business performance haven’t been studied enough. In this study we aim to fill this gap. For this reason, the relationships between structural capital and qualitative and quantitative performance have been investigated. For analysis we preferred Structural Equation Model (SEM) using Lisrel 8.51. According to the findings, structural capital affects the qualitative performance positively and explains 82% of the change in qualitative performances of companies; while explaining 28 % of the positive change.</p>

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)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.433
Threshold uncertainty score0.407

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.039
GPT teacher head0.363
Teacher spread0.324 · 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 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

Citations5
Published2016
Admission routes1
Has abstractyes

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