Democratizing the New Product Development Process: A New Dimension of Value Creation and Marketing Concept
Bibliographic record
Abstract
This paper theoretically examined how key success factors (KSFs) of new product development process, as a new dimension of marketing concept and value creation, could be exploited through learning outside the firm or through customer involvement in key stages of the development process. Such collaborative relationship- though suffers scholarly neglect in Nigeria, costly and perhaps difficult to apply and more profound in B2B than B2C transactions- is benefiting in terms of manipulating the environment to a firm’s advantage through having products that exactly meet the aspirations of the world of customers, though consumers are erratic and rarely verbalize their needs with precision. All things being equal, user involvement reduces large inventories and distribution costs, minimizes product returns, builds strong customer relationships, matches production with consumption patterns, promises customer willingness to pay premium price, makes managerial decisions flexible, and above all achieves the ideals of TQM, and perhaps marketing concept. However, different firms benefit from different forms of user interactions subject to top management idiosyncrasy, market power, and competitive environment. Often the extent of disruption on established behaviour pattern (e.g.; radical and incremental concepts) determines the measure of customer interactions. SMEs follow distinct action rationality, leading to rapid implementation of some user inputs, and defensiveness towards others and larger firms are more exposed to user inputs because of their supposedly huge and better resources, yet less committed to execute it. Therefore, this paper developed a model of designers and users involvement based on literature. It joins other similar papers to raise alertness on facilitating the spread, and actual implementation, of user involvement philosophy in radical and incremental innovations irrespective of the industry and other environmental variables.
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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 | 0.005 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.014 |
| Scholarly communication | 0.010 | 0.015 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".