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Record W4210356565 · doi:10.5267/j.uscm.2022.2.003

A study on the relationship between supply chain integration and firm performance

2022· article· en· W4210356565 on OpenAlexvenueno aff
Nahla Al-Nazer

Bibliographic record

VenueUncertain Supply Chain Management · 2022
Typearticle
Languageen
FieldComputer Science
TopicOrganizational and Employee Performance
Canadian institutionsnot available
Fundersnot available
KeywordsConfirmatory factor analysisSample (material)Exploratory factor analysisScale (ratio)Supply chainReliability (semiconductor)Discriminant validityBusinessLinear discriminant analysisMarketingStatisticsMathematicsInternal consistency

Abstract

fetched live from OpenAlex

This study aims to develop a measurement scale for Supply Chain Integration (SCI) and Firm Performance (FP) in Jordanian SMEs. The study instrument was developed based on the previous studies and the survey included 284 companies in Jordan. A sample of 263 responses were used for exploratory analysis. Results show that the 46-item instrument was loaded on four factors. During this phase, the measurement scale was purified to 36 items, and characterized with a high degree of reliability. The results were confirmed using confirmatory factor analysis and showed that the 36-item measurement model met the empirical requirements namely, convergent, construct, and discriminant validity. The fitness indicators test for the model shows that it is applicable in SMEs companies’ environment in Jordan. The study presented implications for decision-makers in SMEs companies. The limitation of this study was presented which were relied on to develop directions for future research.

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)0.003
metaresearch head score (Gemma)0.010
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.003
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0000.001
Research integrity0.0000.001
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 head0.037
GPT teacher head0.252
Teacher spread0.215 · 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 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

Citations3
Published2022
Admission routes1
Has abstractyes

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