Impact of knowledge sharing, IT support, and innovation on supply chain sustainability with uncertainty moderation
Bibliographic record
Abstract
This study analyzes the relationships between knowledge sharing culture, information technology support, and process innovation on supply chain sustainability in Indonesia's digital printing SMEs, with market uncertainty as a moderating variable. Employing an explanatory approach, the research utilizes a cross-sectional survey involving 225 SME owners. Data were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM). The findings reveal that knowledge sharing culture has a significant positive impact on both process innovation and supply chain sustainability. Conversely, information technology support negatively affects these two variables. Process innovation positively contributes to supply chain sustainability, albeit with a small effect. Market uncertainty strengthens supply chain sustainability but weakens the relationship between process innovation and sustainability. The mediating role of knowledge sharing culture through process innovation highlights a critical pathway for enhancing supply chain sustainability. This study offers theoretical and practical implications regarding the importance of knowledge sharing culture and process innovation, alongside challenges in technology adoption. The study's limitations include its cross-sectional approach and focus on digital printing SMEs in Indonesia. Future research is recommended to adopt a longitudinal approach to explore dynamic changes in this context. The novelty of this study lies in its integrated understanding of factors influencing supply chain sustainability amid market uncertainty.
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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 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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".