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Record W3098253665 · doi:10.22215/etd/2013-09978

Tracing social capital within a firm: A relational capital perspective

2013· dissertation· en· W3098253665 on OpenAlexaff
Behrooz Talle

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldBusiness, Management and Accounting
TopicIntellectual Capital and Performance Analysis
Canadian institutionsCarleton University
Fundersnot available
KeywordsExtant taxonPerspective (graphical)Social capitalRelational capitalResource-based viewIndustrial organizationResource (disambiguation)BusinessTracingCapital (architecture)Relational viewKnowledge managementMicroeconomicsEconomicsCompetitive advantageMarketingIntellectual capitalPolitical scienceFinance

Abstract

fetched live from OpenAlex

This study analyzes the effects of relationship capital (RC) on the growth of firms.Social capital (SC) scholars suggest that a firm's relationships drives its growth strategies, but extant literature on SC fails to explain how relational aspect of SC leads to growth of a firm.Built on the resource based theory of the firm and knowledge of SC, this research defines RC as improved capabilities of the firm in combining various resources, and tests whether the existence of RC in the relationships of a firm affects its growth strategy performance.The results from 347 European firms suggest that relational perspective of SC improves firms' capability to achieve growth and plays a positive role in small firms' competitiveness.The study also opens up some research avenues for an investigation of the effects of trust and commitment, as the two constructs of RC, on a firm's capabilities.

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)0.006
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 score0.006
Threshold uncertainty score0.022

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.002
Science and technology studies0.0010.004
Scholarly communication0.0040.005
Open science0.0010.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.016
GPT teacher head0.236
Teacher spread0.220 · 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

Citations0
Published2013
Admission routes1
Has abstractyes

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