Configuring Technology Resources and Organizational Practices for Innovation Success
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
Overview: As novel technologies and organizational practices become available, innovation managers must identify and invest in those best suiting their needs. To ensure their firm’s innovativeness, innovation managers must integrate these new technologies and organizational practices into their resource portfolio and deploy them in combination with existing resources. In this article, we demonstrate the orchestration of technologies and practices that set the most innovative firms apart from less innovative. Using the fsQCA method, we found that high-performing firms configure their technological resources and organizational capabilities in bundles, whereas their less innovative counterparts are preoccupied with investing in technologies alone. Resource orchestration management is therefore a novel innovation management capability, which may accelerate a firm’s innovative capabilities. We offer practitioners managerial implications that emphasize the development of innovation managers’ resource orchestration capabilities.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.009 | 0.011 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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