Network-facilitated green innovation capability development in micro-firms
Why this work is in the frame
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Bibliographic record
Abstract
Purpose The purpose of this paper is to evaluate key criteria underpinning network-facilitated green innovation capability development in micro-firms. Design/methodology/approach Micro-firms, those firms with less than ten full-time employees, need to continuously innovate in order to sustain their business in the emerging green economy. This study uses an interpretive multiple case approach to explore micro-firm owner-manager (O/M) green innovation activities, encompassing O/M views on facilitated network engagement in Ireland and Canada over a 12-month period. Findings The findings show that proactive implementation of green innovation is influenced by the O/M’s natural environment orientation and the potential for economic gain, while facilitated networks provide an additional resource that the O/M can draw from that allows the O/M to test new ideas, comprehend new and existing legislation and identify potential supports in pursuit of green innovation capability development within the micro-firm. Research limitations/implications This study offers a contribution to knowledge in the areas of green innovation, micro-firm capabilities and facilitated network engagement. However, the sample size is small and distance was a challenge, yet data and case protocols are in place which allow for replication of the study. As the research is embedded in the resource and capability theories, alternative theoretical frameworks may shed a different light on the research question. Originality/value Prior studies have found that facilitated networks have a positive impact on micro-firm sustainability as these networks enhance the firm’s constrained resource base. The proposed framework can be used as a guideline for support organisations including facilitated networks in assisting micro-firms in reaching their green innovation goals and objectives. It can also be used by micro-firms in the attainment of the green innovation capability.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 it