Supplier integration into new product development: coordinating product, process and supply chain design
Bibliographic record
Abstract
Abstract In many industries, firms are seeking to cut concept to customer development time, improve quality, reduce the cost of new products and facilitate the smooth launch of new products. Prior research has indicated that the integration of material suppliers into the new product development (NPD) cycle can provide substantial benefits towards achieving these goals. This involvement may range from simple consultation with suppliers on design ideas to making suppliers fully responsible for the design of components or systems they will supply. Moreover, suppliers may be involved at different stages of the new product development process. Early supplier involvement is a key coordinating process in supply chain design, product design and process design. Several important questions regarding supplier involvement in new product development remain unanswered. Specifically, we look at the issue of what managerial practices affect new product development team effectiveness when suppliers are to be involved. We also consider whether these factors differ depending on when the supplier is to be involved and what level of responsibility is to be given to the supplier. Finally, we examine whether supplier involvement in new product development can produce significant improvements in financial returns and/or product design performance. We test these proposed relationships using survey data collected from a group of global organizations and find support for the relationships based on the results of a multiple regression analysis.
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 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 | 0.020 | 0.044 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".