Eco Product Innovation in Search of Meaning: Incremental and Radical Practice for Sustainability Development
Bibliographic record
Abstract
Purpose: The purpose of this paper is to discuss the role of eco innovation in order to achieve sustainable development in manufacturing industries. The outcomes of this paper attempts to describe the main drivers of eco innovation among companies, core categories of eco innovation practices in manufacturing industry and framework of radical and incremental eco product innovation. The last part of the paper provides the insight of the new paradigm for eco innovation research in new millennium particularly in developing countries. Design/methodology/Approach: The selected papers that have been reviewed were retrieved from Google scholar database with high citation index. Findings: Manufacturing acknowledges eco innovation as a pivotal role to attain sustainability development in ecology, economy and society. There are three main drivers that able to boost the manufacturing sustainability namely regulation, responsibility and competition. Four types of eco innovation practices are product, process, marketing and organizations. However, among of them, eco product innovation is highly discussed among scholars in new millennium. Most of high cited literature describes the dimension of radical and incremental literature in four dimensions: modes of changes, economy values, design changes and eco innovation practices. The new research paradigm should discuss on eco innovation management in manufacturing industry. Originality/value: Most of scholars are confused with the correct concept of eco innovation and its relationship towards sustainability development. Therefore, this paper attempts to provide a clear direction on difference between the incremental and radical eco product innovation implementation in manufacturing industry en route for building the sustainable development echoes to economy, ecology and society.
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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 | 0.007 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.003 | 0.017 |
| Scholarly communication | 0.012 | 0.011 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".