Changes in manufacturing facility-, network-, and strategy-types at the Michelin North America Company from 1950 to 2014
Bibliographic record
Abstract
Large manufacturing firms operate networks of facilities which they design to achieve particular manufacturing strategies. Facilities, networks and strategies are of several distinct types. The facility-, network- and strategy-types used by a firm depend on the competitive environment in which a firm operates. This paper examines the facility-, network- and strategy-types used by the Michelin North America Company during the period from 1950 to 2014. The examination shows how three changes in the competitive environment (changes in tariffs and government industrial policy, the 1964 Canada – United States Automotive Trade Agreement, and the 1996 North American Free Trade Agreement) triggered significant changes in these types. The examination produces insights into categorisations of facility-, network- and strategy-types that are useful for understanding how large firms operate, how we can predict what changes large firms will make to their facilities, network and strategy and how stakeholders such as employees, suppliers and governments can manage the risks of working with large firms.
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 | 0.001 |
| 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".