Impelling innovation at a Canadian automotive plant
Bibliographic record
Abstract
In industrialized countries manufacturing firms are facing significant change resulting from mass customization, shortening product life cycles, increasing technological change, and the entry of international competitors into their markets as witnessed by the automotive and electronics industries. ‘Process Innovation’ is one of the key areas where innovation is exigent.It pertains to finding better or more efficient ways of producing existing products, or delivering existing services. Making innovation a ubiquitous capability in manufacturing is fundamentally a leadership challenge. It needs a tangible organizational infrastructure that makes managers accountable at all levels for driving, facilitating, and embedding the innovation process into every part of the culture.This paper construes the process of ‘impelling and managing innovation’ at an automotive metal stamping plant in Canada, during the 2007-2009 financial crises in North America. The paper discusses the processes, psychological and physical environment, organisational culture, economic climate, and program content; rationale, significance and denouement.The paper concludes that idea management systems don't replace traditional departments and processes involved in new services, products, or strategies.They serve as an adjunct to them and provide a framework that can help organizations turn innovation into an enterprise-wide discipline-and a sustainable process that drives growth in good times and bad. Auto industry is going to remain important, for local, regional and national economies, as well as for the future of the planet if ecologically sustainable transport systems are to be developed; it will, no doubt, remain an important topic in academia.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.030 | 0.006 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 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 source (direct Gemma or distilled Codex), 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".