MétaCan
Menu
Back to cohort
Record W4400472898 · doi:10.5267/j.uscm.2024.4.024

The influence of religious orientation on supply chain quality management through ethics as an intervening variable in leather jacket SMEs

2024· article· en· W4400472898 on OpenAlexvenueno aff
Robertus Suraji

Bibliographic record

VenueUncertain Supply Chain Management · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicHalal products and consumer behavior
Canadian institutionsnot available
Fundersnot available
KeywordsBusinessQuality (philosophy)Orientation (vector space)Variable (mathematics)Supply chainChain (unit)Intervening variableReligious orientationMarketingPsychologySocial psychologyMathematicsSociology

Abstract

fetched live from OpenAlex

The research location was carried out in Garut, West Java, which is one of the potential regions for the development of leather jackets for small and medium enterprises (SMEs) in Indonesia based on its comparative advantages. Garut Regency is expected to become the home base of national leather jacket SMEs in Indonesia that are competitive and sustainable. The aim of this research was to analyze the influence of Religious Orientation (RO) on supply chain quality management through Ethics (E) as an intervening variable in Leather Jacket SMEs, Garut - West Java. What was interesting in this research and became a novelty was the inclusion of social science variables in maintaining the quality of supply chain management. In the stage of data collection, the study involved 88 entrepreneurs and leather jacket craftsmen as research respondents and processing was carried out using the Generalized Structured Component Analysis (GSCA) method. The results show that the relationship between RO variables can affect supply chain management variables, also through ethics. The implication of this research is that in running a business, to fix the quality of supply chain management, religious orientation is the important aspect.

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)0.007
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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.674
Threshold uncertainty score0.989

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.000
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 science0.0010.000
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 head0.044
GPT teacher head0.379
Teacher spread0.335 · 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 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

Citations1
Published2024
Admission routes1
Has abstractyes

Explore more

Same venueUncertain Supply Chain ManagementSame topicHalal products and consumer behaviorFrench-language works237,207