Industry 4.0 Framework for Sustainable Manufacturing Sector in Jordanian Rural Areas
Bibliographic record
Abstract
Developing countries are facing increasing pressure to remain competitive in the global economy and markets.Industry 4.0 provides improved concepts to enhance manufacturing companies' productivity, efficiency, and sustainability.This study investigates how the Industry 4.0 factors influence the sustainability strategies of manufacturing companies in rural areas in Jordan taking into consideration the adoption and barriers of entry to Industry 4.0.Our study modifies the current model factors of technological, organizational, and environmental context by introducing Industry 4.0 adoption as a moderator, and barriers to adopting Industry 4.0 as a mediator to the sustainability outcomes.The results confirm that the three factors, the technological factor, the organizational factor, and the environmental factor, had a positive impact on the sustainability of rural manufactories in Jordan.Results show a negative moderating effect of Industry 4.0 adoption on the relationship between the TOE framework factors and sustainability, it also shows a partial mediating role of barriers for using Industry 4.0 on the relationship between the TOE framework factors and sustainability.This study fills the gap in the scientific literature to better understand how developing countries can take advantage of Industry 4.0 concepts and increase their competitiveness in the domestic and international economies.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".