Propositions for R&D Governance Regimes: A Behavioral Perspective
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
Purpose: Our paper intends to bring systematic attention to the transaction costs and corresponding governance structures in the corporate R&D contexts. Design/methodology/approach: The current conversation on the governance of R&D has addressed topics related to investments, resource allocation, knowledge sharing, or managing intellectual property rights. While these are important aspects of innovation cost and benefit, they do not address an equally important issue of transaction cost arising out of human behavior. We adopt a systematic synthesis of 16 qualitative teaching case studies to validate the existence of human behavior-related transaction cost issues in the context of R&D and identify firms’ governance responses to mitigate or eliminate their effect. Findings: Our findings suggest that transaction costs issues can be mitigated by appropriate governance models ranging from centralized R&D to open innovation. While structure mitigates the transaction cost some ex-ante and ex-post controls may also be required. Practical implications: For management practice, the insights of our study provide evidence-based advice for R&D managers regarding the practical, effective ways of limiting and controlling the transaction costs associated with R&D activity. Originality/value: This paper uses teaching-case studies to analyze a variety of transaction cost dilemmas in the R&D context and brings in a new perspective to R&D governance.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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