Sustainable Supply Chain Management as a Strategic Tool for Competitive Advantage in Tea Industry in Kenya
Bibliographic record
Abstract
It is assumed that companies that utilize sustainable supply chain management as a strategic tool in businessmanagement are likely to have a competitive edge over others. However, this is contrary to the Tea Industry inKenya. The main purpose of this research was to establish the role of sustainable supply chain management as astrategic tool for competitive advantage in the tea industry in Kenya. The specific objective was to find out towhat extent the supply chain collaborative strategy as a tool for competitive advantage is used by the companiesin tea industry in Kenya. The mixed research design was used in the study. The target population was the teacompanies in Kenya and the sample of eight Tea Companies were purposively selected for the study. Datacollection was done by use of both structured questionnaires and oral interview to get the primary data while thesecondary data was obtained by documentary analysis. The results finding indicated that sustainable supplychain management as a strategic tool contributes to the competitive advantage of Kenyan tea companies in theglobal market. The results provide information to the tea companies to come up with sustainable strategies intheir supply chain management in order ensure the Kenyan tea remains competitive in the global market.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".