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
New Product Development - NDP is a major source of competitive advantage to companies. For decades researchers have studied the phenomena and various approaches have emerged over the years. Firstly, NPD was structured in clearly defined phases or stages to enable a quick and risk-free flow from idea to launch. Later, Concurrent engineering - CE, in which critical development phases are performed simultaneously, was successfully introduced by Japanese companies like Toyota. In recent years, CE has become a widely used option world-wide. CE proven benefits include reduced time-to-market; reduced human and capital cost, increased product quality; all factors related to project efficiency. More recently, Lean product development-LPD, validated some aspects of CE (e.g., overlapping of phases), but proposed a more structured way of reducing non-value added activities. The main objective of this study is to discuss the idea that thus far NPD research has mostly focused on efficiency - eliminating waste, reducing time-to-market and costs. This study also discusses the need for an emphasis on creativity in NPD to enhance value creation. In terms of organization, this study contains a literature review on CE, LPD, and group creativity. This study also proposes an abstract model combining concurrent and lean product development aiming at enabling both creativity and efficiency, consequently enhancing value creation. Lastly, limitations and opportunities for future research are proposed.
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 | 0.000 | 0.000 |
| 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) | 0.001 | 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 it