A Systematic Review of Strategic Supply Chain Challenges and Teaching Strategies
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
Background: This study provides a comprehensive overview of current supply chain challenges and how they are taught within university circles or among supply chain professionals to simulate reality. Methods: The study applied a systematic literature review, using bibliometric co-citation and concept-centered content analysis for a comprehensive review of 118 relevant articles, leading to the identification of critical challenges in modern supply chain management. Results: These challenges include supplier selection and quality, supply chain networks, and sustainable supply chains. Supply chain educators are encouraged to use games that mirror real-world scenarios to teach these challenges. Results from this review underscore that existing games covered supply chain concepts such as the bullwhip effect, collaboration, networks, supplier selection, quality management, humanitarian logistics, sustainability, lean supply chain, Supply Chain 4.0, and perishable goods supply. Conclusions: The study’s contribution is to assist in selecting games tailored to the supply chain specific aspects and to guide developers in creating realistic games that address recent challenges in supply chain management. It recommends a holistic approach to enhance new supply chain game development, drawing from methodologies such as problem-based learning and Lego Serious Play. This multifaceted approach imparts practical knowledge and comprehensive skills for addressing supply chain intricacies in modern business settings.
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.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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