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Record W3211612096 · doi:10.5267/j.uscm.2021.9.007

The effect of risk on supply chain cooperation: Evidence from Vietnam agriculture

2021· article· en· W3211612096 on OpenAlexvenueno aff
Quang Bach Tran, Thi Bich Thuy Nguyen, Thi Yen Nguyen, Van Hao Tran, Thi Xuan Loc Nguyen, Thi Cam Thuong Hoang

Bibliographic record

VenueUncertain Supply Chain Management · 2021
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicQuality and Supply Management
Canadian institutionsnot available
Fundersnot available
KeywordsSupply chainAgricultureBusinessStructural equation modelingDependency (UML)Supply chain risk managementCausal chainSupply chain managementWork (physics)Industrial organizationQuestionnaireRisk managementService managementMarketingFinanceComputer scienceSociology

Abstract

fetched live from OpenAlex

The study aims to test the impact of risk on supply chain cooperation in the agriculture sector in Vietnam. The research paper used the quantitative research method through analysing structural equation modelling (SEM), with a dataset of 518 observations. The survey subject is the experienced and knowledgeable manager in supply chain management in the agricultural sector. The result found that risk has impacted not only directly and negatively on the supply chain cooperation but also indirectly through intermediary factors, namely commitment and the participant's opportunistic behaviour. In addition, the study has also proved that in some cases, the participant's dependency mentality in work and opportunistic behaviour lead to the opposite impact of commitment on trust and level of supply chain cooperation in agriculture. Based on this result, the study also makes recommendations to enhance the effectiveness of the supply chain cooperation in the agricultural sector in Vietnam. The findings contributed to both theory and practice. It pointed out the impact of risk on the supply chain cooperation in the agricultural sector, as well as the mediating role of commitment and opportunistic behaviour in this relationship.

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)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.424
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.013
GPT teacher head0.236
Teacher spread0.223 · 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.

Study designNot applicable
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

Citations1
Published2021
Admission routes1
Has abstractyes

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