Sustainability-Related Impacts of Digitalization on Supply Chain Management
Bibliographic record
Abstract
In this era of digitalization, many companies that aim to improve the sustainability of their supply chain utilize digital technologies. Digital technologies have provided the overall supply chain with more transparency, visibility, and real-time data exchange. The purpose of this paper is to provide an overview of early studies related to the impacts of digitalization on supply chain sustainability. The literature review is carried out by using the PRISMA method (the preferred reporting item for systematic reviews and meta-analyses). To carry out the review, 53 English-language publications were analyzed. The data were collected from Web of Science and Science Direct, and the systematic literature review will consider the impacts of digitalization on supply chain sustainability. Based on the literature, the overall impact of digitalization on supply chain sustainability is positive, but it brings some challenges as well. This paper also identifies potential gaps that were not covered in earlier publications and provides suggestions for future studies. The main contribution of this paper is to provide a complete and up-to-date literature review considering the impact of overall digital technologies on sustainability from a global perspective that summarizes the publications related to this topic. Moreover, in this paper, the challenges or risks of digitalization will be considered, which has received less attention in previous papers.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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".