Risk Profiles of Emerging and Established Value Chains in Dynamic Markets
Bibliographic record
Abstract
That supply chain management and logistics are a determining factor for the long term success of a company was well documented by Forrester over a half century ago (Forester, 1958), with the importance of the statement only growing through the intervening years. Whether consciously factored into the operating mode or not, logistics and distribution channel management plays a critical role in the life, and death, of a firm. From the rudimentary beginnings of the start-up company to the hectic world of the growth company and onto the relatively secure existence in mature markets, the value chain consisting of logistics and distribution channel linkages follows the firm, until it solidifies into immutable form of the mature value chain and begins to exert an inexorable pressure on the survival of the entire chain, and conversely the chain imposes its will on the members. The emergence of mature industry value chains is often driven by the need to monopolistically control logistics and distribution channels which provides a competitive advantage but also introduces a serious exposure to pending shock loadings of the chain.
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 | 0.001 | 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 | 0.000 | 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".