The role of supply chain integration, management commitment and supply chain challenges on supply chain performance and MSMEs performance
Bibliographic record
Abstract
The aim of writing this research article is to determine the influence of supply chain challenges on MSMEs performance, Supply chain integration on Micro, Small, and Medium Enterprises (MSMEs) performance, Management commitment to MSMEs performance, Supply chain integration on Supply chain performance. This research method is a quantitative survey, research data was obtained by distributing online questionnaires via social media. 700 questionnaires were distributed to MSMEs owners and of the 700 questionnaires distributed, 350 respondents or 50% responded as determined by the simple random sampling method. This research adopted a quantitative method with data analysis using Structural Equation Modeling (SEM) Partial Least Square (PLS) with SmertPLS software data processing tools. The questionnaire was designed using a Likert scale of 1 to 7. The stages of data analysis were validity, reliability and hypothesis testing. or significance. The results of data analysis show that supply chain challenges have a positive and significant influence on MSMEs performance, Supply chain integration has a positive and significant influence on MSMEs performance, Management commitment has a positive and significant influence on MSMEs performance, Supply chain integration has a positive influence and significant to supply chain performance. The novelty of this research is the creation of a relationship model of supply chain integration, management commitment, supply chain performance, supply chain challenges and MSMEs performance. The implication of this research is to encourage improvements in MSMEs performance, MSMEs managers must encourage improvements or implement challenges in the supply chain. Supply chain integration and management commitment. Supply chain management is not just about managing the flow of goods, but also a holistic business strategy that can create a competitive advantage. With a deep understanding of supply chain components, challenges and strategies, companies can ensure smooth operations and meet customer expectations in a dynamic and global business environment. Implementing best practices in supply chain management is the key to building a strong foundation for business success in an era of ever-growing globalization.
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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 | 0.005 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".