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Record W4312185335 · doi:10.5267/j.uscm.2022.9.010

The impact of supply chain integration on strategic performance: The mediating role of strategic vigilance

2022· article· en· W4312185335 on OpenAlexvenueno aff
Hussam Thneibat, Mohed Fares N. Al-Mufleh, Gharam Ali Abdelaziz, Kaled Alrawashdeh, Mohammed Abdulhadi D. A. Al-Alqahtani

Bibliographic record

VenueUncertain Supply Chain Management · 2022
Typearticle
Languageen
FieldComputer Science
TopicOrganizational and Employee Performance
Canadian institutionsnot available
Fundersnot available
KeywordsSupply chainBusinessRestructuringIndustrial organizationPopulationSupply chain managementVertical integrationStructural equation modelingStrategic planningMarketingComputer science

Abstract

fetched live from OpenAlex

The study aimed to identify the impact of supply chain integration through strategic performance and the mediating role of strategic vigilance in industrial companies. The Jordanian population is large and medium-sized, and the study population consists of medium and large-sized industrial companies. For hypothesis testing purposes the study and its model validity, Modeling Equation Structural Analysis (SEM) was used through the AMOS16 program. The study indicates that supply chain integration (strategic integration, internal integration, external integration) has an impact on strategic performance and response. The supply chain, as the results of the study indicated, shows that the response of the supply chain affects strategic performance. The study also found that the response of the supply chain mediates the impact of strategic vigilance on strategic performance. The study recommended working to raise the level of trust and honesty, commitment and attention to the interest of each party to the supply chain to maintain a good level of external integration of the supply chain and work to improve the level of supply chain response to markets and any changes that may occur in the market through corporate restructuring and streamlining working procedures.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.459
Threshold uncertainty score0.576

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 communication0.0000.000
Open science0.0020.000
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 head0.019
GPT teacher head0.245
Teacher spread0.226 · 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 designSimulation or modeling
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

Citations13
Published2022
Admission routes1
Has abstractyes

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