The effect of digital supply chain on organizational performance: An empirical study in Malaysia manufacturing industry
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Nowadays, global technologies, especially digital things, have become an important tool for businesses to maintain feasible partnerships and build a great value connection with other companies. New digital technologies that are emerging every day are on their way to affect nearly all business processes and activities. This study investigates the effect of the digital supply chain on the supply chain and organization performance in the Malaysia manufacturing industry. This paper also further assesses the mediating effect of supply chain performance in the relationship between the digital supply chain and the organizational performance in the Malaysia manufacturing industry. The objectives are achieved via quantitative research design. The researchers emailed the online survey questionnaire to 1160 manufacturing companies listed in the Federation of Malaysian Manufacturers (FMM) directory via stratified sampling technique and received 63 responses. 7 incomplete responses have been deleted and 56 usable responses representing 5.43% of the response rate used for data analysis. The data was analyzed by using the Partial Least Square Structural Equation Modeling (PLS-SEM). Three hypotheses are not supported and seven hypotheses are supported, which includes all the hypotheses of moderating effect. The manufacturing companies in Malaysia can consider adopting the DSC in the business process to remain reliable in the competitive market by providing good supply chain performance and best organizational performance as a whole. The implication of the study is given to academics and practitioners, specifically manufacturing companies. The limitations and the recommendation for future study have been highlighted.
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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 | 0.003 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it