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Record W4294636403 · doi:10.5267/j.uscm.2022.8.009

The influence of supply chain partners’ integrations on organizational performance: The moderating role of trust

2022· article· en· W4294636403 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

VenueUncertain Supply Chain Management · 2022
Typearticle
Languageen
FieldComputer Science
TopicOrganizational and Employee Performance
Canadian institutionsnot available
Fundersnot available
KeywordsModerationBusinessSupply chainSupply chain managementWork (physics)Knowledge managementOrganizational performanceConceptual modelOrder (exchange)MarketingIndustrial organizationConceptual frameworkProcess managementPsychologyComputer science

Abstract

fetched live from OpenAlex

Supply chain management and integration have become more important business topics mainly addressed within the different businesses industries in order to influence the organizational performance. The current research study aims to investigate this effect by involving some key of supply chain partners on organizational performance. Also, the moderation role of trust as an influential aspect in the business was also studied in this work. To conduct this research and meet the stated research objective, a quantitative research method was used to collect data from food products manufacturers in Jordan due to the main contribution of this sector to the national economy of Jordan. PLS-SEM approach was selected in the phase of analysis and the findings revealed a significant effect of all hypothesized research assumptions and a significant moderating effect of trust on the relationship between supply chain partners’ integration and organizational performance. The research findings also provided expected implications and supported the relevant evidence and literature in this area, as well it would contribute to cover the existing research knowledge gaps by integrating a new model including sets of new variables that have not been examined together within a single conceptual framework.

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 categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.355
Threshold uncertainty score1.000

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 science0.0020.001
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 head0.009
GPT teacher head0.222
Teacher spread0.214 · 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