Threats to New Product Innovativeness and the Effects of Supplier Influence Processes
Bibliographic record
Abstract
<p>Innovation can be best described as the adoption of an idea or behaviour pertaining to a product, service, device, system, policy or programme that is new to an organization. Many companies nowadays develop and pursue innovative new products as a strategic move to gain competitive share in the market, and many do so by launching new products before competitors moving in. However, to produce innovation effectively, they need support from various operating sections and one of the main sections comes from suppliers. Because managers are always confronted with competitive pressures from newly developed products by rivals, collaborative efforts with experienced suppliers can help companies develope new products more efficiently, especially to cut costs and reduce time to develop new product. Innovative new products from major players in the industry can also have a potential detrimental impact on profitability. To deal with this situation, the authors will discuss how the role of supplier influence can minimize this problem. A model and several propositions are introduced to illustrate potential effects between relavant research variables. First, the relationships between all independent variables (threats to innovation and supplier influence) and new product innovativness were examined. Second, the study assesses whether greater supplier influence would positively moderate the domain relationships. The study advocates that supplier influence is an issue of paramount importance for practitioners in most industries and is an essentail element in the marketing mix that impacts directly on revenue. This study contributes to both theoretical and practical perspectives.</p>
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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 | 0.016 | 0.087 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.005 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 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".