Supply chain sustainability in VUCA: role of BCT-driven SC mapping and ‘Visiceability’
Bibliographic record
Abstract
The study investigates the role of three essential supply chain capabilities: visibility, traceability, and mapping, collectivity termed as 'visiceability', in the relationship between blockchain technology and supply chain sustainability. The study focuses on Malaysia's Electronics Component manufacturing firms, a sub-sector of the electrical and electronics industry. Data were collected from 105 through a close-ended questionnaire. PLS-SEM was employed to examine the modeled relationships. The findings of the study challenge the notion that supply chain (SC) traceability alone is responsible for mediating the impact of blockchain technology (BCT) on SC sustainability. However, findings confirm the significant roles of SC Mapping and Visibility in the association between BCT and SC sustainability. Findings further validate the significant impact of BCT on SC sustainability, highlighting its multifaceted role. The findings suggest that firms can build their intermediary capabilities instead of exclusively focusing on adopting BCT for SC sustainability. These capabilities can further channel the impact of BCT on improving SC Sustainable. Our findings illustrate that BCT can enhance SC visibility by offering a precise and transparent record of the products, inventory, and transactions. Hence, we strongly suggest that managers consider leveraging BCT to improve their SC visibility, thereby uplifting the sustainability of a supply.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".