Employee‐based Innovation in Organizations: <scp>O</scp> vercoming Strategic Risks from Opportunism and Governance
Bibliographic record
Abstract
Research summary E mployees performing everyday tasks frequently acquire valuable new ideas and knowledge. Our formal analysis studies how organizations can benefit from employee‐driven innovation by using incentives to overcome strategic risk from opportunism and governance. We use a game theory framework to analyze the strategic interactions involved and identify incentives under which valuable ideas will be revealed without appropriation (in equilibrium). Our analysis considers both the short run and the long run, where governance can be adjusted to maximize expected future innovation profits. Innovation value, frequency, governance quality, and employee contestation costs are shown to play a salient role in determining the innovation incentives and equilibrium. Overall, our analysis and results provide a number of insights on how organizations can overcome frictions from strategic innovation risks to more fully mobilize their innovation potential and knowledge‐based resources. Managerial summary I dea theft can occur in organizations when employees find it beneficial to present a valuable idea of another employee as theirs. If employees engaged in everyday tasks believe this will likely happen or that they will not be rewarded enough, they may not reveal them. We analyze the design of appropriate innovation rewards that will prevent stealing of innovative ideas and allow organizations to capture value from employee‐driven innovation. We show that governance quality, innovation value, and costs related to contestation play a salient role in determining appropriate innovation rewards and the organization's innovation capacity. “Flatter” organizations can deter idea theft more effectively and need to pay lower innovation rewards. In the long term, we show that all organizations can become more innovative by adjusting their governance quality and reducing employee contestation costs. Further, the ones with higher innovation potential and contestation costs will move toward higher quality governance and seek more entrepreneurial employees, as this raises long‐run innovation profits. Copyright © 2017 Strategic Management 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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".