Project-oriented supply chain and innovation strategies for competitive advantage: An empirical study of SMEs in West Java
Bibliographic record
Abstract
This study examines the impact of supply chain management (SCM) practices and innovation strategies on competitive advantage through operational performance in West Java. Using a quantitative approach, the study surveyed 150 SME managers/owners via Google Forms, analyzing the data with Structural Equation Modeling (SEM) and AMOS 20 software. The results reveal that SCM practices positively influence operational performance and competitive advantage, while innovation strategies also enhance operational performance and competitive advantage. Furthermore, the study finds that although SCM practices and innovation strategies improve competitive advantage, operational performance does not mediate the relationship between these factors and competitive advantage. The implications of these findings suggest that SMEs should focus on enhancing SCM practices and fostering innovation strategies to improve competitive advantage directly. Although operational performance is important, it does not play a central mediating role in boosting competitive advantage. Therefore, businesses should prioritize optimizing SCM and innovation independently for more effective outcomes, without relying on operational performance as an intermediary. This insight can guide policy development and strategic planning for SMEs in West Java, fostering more efficient operations and stronger market positioning.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 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".