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Record W3163232041 · doi:10.1108/scm-06-2020-0238

Used vehicle global supply chains: perspectives on a direct-import model

2021· article· en· W3163232041 on OpenAlexaff
Yangyan Shi, Tiru Arthanari, V. G. Venkatesh, Samsul Islam, Venkatesh Mani

Bibliographic record

VenueSupply Chain Management An International Journal · 2021
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicSustainable Supply Chain Management
Canadian institutionsDalhousie University
Fundersnot available
KeywordsOriginalitySupply chainBusinessSupply networkSupply chain managementMarketingProcess managementExploratory researchValue (mathematics)Industrial organizationQualitative researchKnowledge managementComputer scienceSociology

Abstract

fetched live from OpenAlex

Purpose This study aims to provide a comprehensive understanding of the supply chain (SC) operations of importing used vehicles into New Zealand and how such SCs affect business practices and performance. Design/methodology/approach The study uses an exploratory qualitative semi-structured interview approach to interview the different stakeholders involved in the global used vehicle SC. Findings The research identifies the overall network structure of the used import vehicle SC from Japan to New Zealand and characterises key aspects of its operations and network connections. This paper finds that Japanese buying agents have integrated increasing numbers of services to provide a trouble-free trading platform, which has created a direct-import model for used vehicle companies in New Zealand. Practical implications The findings and recommendations are useful in designing and managing the used vehicle SC for all stakeholders and effective real-time management of uncertain factors. Originality/value The paper primarily analyses SC operations by researching the cooperation and coordination between SC components and networks, based on providing the flow of used vehicles from Japan to New Zealand. It constitutes a pioneering practice-perspective research paper in this domain.

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 categoriesMeta-epidemiology (narrow), Scholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.727
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0030.003
Open science0.0020.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.014
GPT teacher head0.260
Teacher spread0.246 · 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 designTheoretical or conceptual
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

Citations5
Published2021
Admission routes1
Has abstractyes

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