The partnerships and logistics leadership in the SMEs: The impact of digital supply chain implementation
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
Digital supply chains play an important role in improving the performance of small and medium enterprises (SMEs) in this digital era. There has been no research that analyzes the relationship between digital leadership, leadership, and partnerships. The aim of this research is to analyze the defect of digital supply chain implementation on logistics leadership and the impact of digital supply chain implementation on partnerships and logistics leadership partnerships. The method of this research is quantitative and data analysis uses structural equation modeling (SEM) partial least squares (PLS) using tools. SmartPLS 3.0 software data is used for processing the data. Research data is obtained by distributing online questionnaires to 589 SME owners in Indonesia determined using a simple random sampling method. The online questionnaire is designed using a Likert scale from 1 to 7 and distributed via social media. The stages of data analysis are validity testing, reliability testing and hypothetical testing. Based on the results of data analysis, it is concluded that digital supply chain implementation has a positive and significant effect on logistics leadership, digital supply chain implementation has a positive and significant effect on partnerships and logistics leadership had a positive and significant effect on partnerships. The novelty of this research is the creation of a correlation model for variable partnerships, logistics leadership and digital supply chain implementation. The managerial implication of this research is to encourage increased partnerships and logistics leadership and we conclude that SMES managers must implement digital supply chain implementation. The theoretical implication of this research is that a new correlation model of partnerships, logistics leadership and digital supply chain implementation in SMEs is created.
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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 | 0.004 | 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 | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 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 it