Value‐creation in new product development within converging value chains
Bibliographic record
Abstract
Purpose This paper seeks to shed some light on value‐creation in new product development (NPD) projects within the context of industry convergence and to explore alternative types of projects characterised by different buyer‐seller relationships. Design/methodology/approach There has been much research on value‐creation in general, but limited emphasis on value‐creation in NPD projects addressing new industry segments emerging from industry convergence (for example, the segment of nuctraceuticals and functional foods (NFF) products that is positioned between the food and the pharmaceutical industries). Based on a multi‐case study approach, this paper pursues an exploratory research strategy and investigates 54 NPD projects drawn from a Quebec (Canada) NFF foods cluster. Findings In the context of convergence a new value chain is emerging between two formerly separated sectors. Value‐creation networks spread across industries and reinforce trends of convergence. Firms face competence gaps in NPD and seek to close these by choosing alternative forms of collaboration. Different types of NPD projects involve alternative forms of buyer‐seller relationships and their approach of value‐creation is analysed. Research limitations/implications A typology of different approaches to NPD in converging value chains is presented along with type‐specific implications for value‐creation for the required buyer‐seller relationship. Originality/value This paper provides a unique insight into value‐creation in NPD in the emerging NFF sector, in particular, and for converging industries, in general.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".