The impact mechanism of digital transformation on the supply chain capabilities of the fresh-cut flower industry in Yunnan province of China
Bibliographic record
Abstract
Given the rapid global economic development and continuous technical advancements, a key strategy for companies trying to improve their competitive edge and accomplish sustainable development is digital transformation. This study's goal was to investigate how the supply chain capabilities of Yunnan Province's fresh-cut flower business are affected by digital transformation. To collect data, the study employed a survey methodology based on a questionnaire. Ultimately, 402 flower businesses in Yunnan Province produced valid du-plicates. PLS-SEM was utilized in the study to evaluate the data, and the results showed that digital transformation greatly improved the enterprises' capacity for both innovation and supply chain management; innovation capabilities positively impacted supply chain capabilities and acted as a mediator in the relationship between supply chain capabilities and digital transformation. Furthermore, organizational readiness largely exhibits a positive moderating effect on the relationship between digital transformation and supply chain capabilities, whereas technology readiness not only fosters but also reinforces the relationship between digital transformation and innovation capabilities. These results offer an effective reference suggestion for fresh-cut flower companies in Yunnan Province and nationwide on how to enhance supply chain capabilities through digital transformation to improve their competitive advantages.
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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 | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| 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".