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Record W3082743884 · doi:10.5267/j.msl.2020.8.034

The intervening effect of structural capital on the relationship between strategic innovation and manufacturing SMEs’ performance in Yemen

2020· article· en· W3082743884 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueManagement Science Letters · 2020
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicIntellectual Capital and Performance Analysis
Canadian institutionsnot available
FundersUniversiti Tun Hussein Onn Malaysia
KeywordsStructural equation modelingBusinessSample (material)Export performanceIndustrial organizationPartial least squares regressionCapital (architecture)Small and medium-sized enterprisesWork (physics)Field surveyComponent (thermodynamics)Business administrationMarketingKnowledge managementComputer scienceMechanical engineeringEngineering

Abstract

fetched live from OpenAlex

The field of strategic innovation (SI) has been garnering increasing research interest, with studies adopting and employing varying definitions and creating different methods for its measurement. Despite the innumerable studies, few have addressed manufacturing and small and medium-sized enterprises (SMEs), particularly those focused on Middle East countries, in light of the relationship between structural capital (SC) and SI. Hence, the present work is primarily aimed at examining the role of SC in SI and the performance of manufacturing SMEs. It employed the survey method to gather data from the study sample of 284 Yemeni manufacturing SMEs and the hypotheses were tested using Partial Least Squares-Structural Equation Modelling (PLS-SEM). On the basis of the results, there is a significant influence of SI on performance; SC also has a moderating role of on this relationship. The present study is expected to contribute to the creation of a measurement system for SI in SMEs, stressing each component of SI in enhancing the performance of such enterprises.

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.

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)0.000
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 score0.031
Threshold uncertainty score0.394

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
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 head0.035
GPT teacher head0.240
Teacher spread0.205 · 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