Supply Chain Management Maturity: A Comprehensive Framework Proposal from Literature Review and Case Studies
Bibliographic record
Abstract
Supply chains have an important role in the competition on the current market. The understanding of maturity and its dimensions in terms of supply chain management – SCM can lead companies to better levels of performance. This paper aims to present findings on supply chain management maturity showing a theoretical model developed from the literature review and its application on three case studies. A systematic approach was used to the literature review. Due to the lack in the literature related to the purpose of this paper a long period was considered for the search of references linked to maturity of supply chain management. The approaches for SCM maturity proposed on the literature suggest different e common dimensions which drive a maturity of SCM. These dimensions can be consolidated in eleven key-dimensions of maturity for SCM. Also, it is possible to verify that as the maturity of SCM evolves to an advanced level more integrated and capable a supply chain becomes. The application of this theoretical model through case studies could confirm the framework proposed and generated new directions of research. The theoretical model was applied in three case studies from different segment of industry and with different level of maturity. A qualitative approach was more adequate for this initial step aligned with this exploratory purpose. More qualitative and quantitative studies need to be done to obtain more evidences from the field and from other different segment of industry. This theoretical model is unique taking into consideration that it was developed from various perspectives of maturity proposed on the literature. This same structure can be applied in more field researches seeking better understandings about maturity of SCM. Also, it can be used by practitioners with the purpose to get a better view of SCM maturity dimensions and allow establishing new directions in terms of supply chain decisions.
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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 | 0.001 | 0.001 |
| 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 | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| 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 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".