The impact of supply chain management 4.0 on the performance of the tea manufacturing firms: mediating role of market and entrepreneurial orientation
Bibliographic record
Abstract
Purpose The purpose of this study is to identify the relationships between computing, digitalization and integrating technologies of supply chain management 4.0, market and entrepreneurial orientation, and performance of tea manufacturing firms, relying on the resource-based view and dynamic capability theory. In addition, this study sheds light on the mediating role of the market and entrepreneurial orientation. Design/methodology/approach The results are obtained by analysing survey data from a sample of 410 respondents from Malaysian tea manufacturing firms. A structural equation modelling approach was performed to validate the direct and indirect proposed hypotheses. Findings Drawing on the resource-based view and dynamic capability theory, this study demonstrates the significant and direct relationships between computing, digitalization, integrating technologies, market and entrepreneurial orientation, and the performance of tea manufacturing firms. In addition, market and entrepreneurial orientation fully mediates the relationship between computing, digitalization, integrating technologies, and the performance of manufacturing firms. Originality/value Due to the novelty of the supply chain management 4.0 concept in manufacturing firms, limited existing studies shed light on its theoretical and practical implications. The findings from the present study contribute to the existing literature by suggesting the mediating role of market and entrepreneurial orientation between supply chain management 4.0 and the performance of manufacturing firms.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".