Exploring sustainability-oriented innovation capabilities in the Indonesian manufacturing firms, 80th Annual Meeting of the Academy of Management (AOM), Vancouver, Canada (2020).
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Although the studies on sustainability-oriented innovation (SOI) have grown significantly in the last decades, to date research on specific SOI capabilities required by the firm to be a more sustainable innovator is still under-explored. Capability-based perspective is revisited to become a foundation for this empirical study. Specifically, capability theories linked to innovation and sustainability fields involved, including innovation management capabilities (IMC), natural resource-based view (NRBV), and social RBV (SRBV) with dynamic capabilities as overarching theory. As the nature of this research is exploratory, a qualitative approach is employed uses semi-structured interviews to 33 owner and manager of manufacturing firms in Indonesia, supplemented by site visit and archival documentation for triangulation. The findings suggested that around half of the firms studied adopting SOI with an operational optimisation approach. It is found from the data that transition is exists between SOI approaches. Firms operating at a higher level of SOI approach have specific dynamics capabilities above baseline ordinary SOI capabilities (production, marketing, environmental and social) that help them become a more sustainable innovator. These SOI dynamics capabilities include capture SOI idea, proactivity to SOI opportunity, mechanism to implement SOI, stakeholder management for SOI, SOI governance, and SOI continual learning.
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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 | 0.000 | 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 | 0.002 | 0.002 |
| 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