Competition and innovation with horizontal R&D spillovers
Bibliographic record
Abstract
Purpose The purpose of this paper is to extend a theoretical framework for analyzing competition and innovation in the presence of horizontal spillovers. Design/methodology/approach A theoretical analysis approach is adopted to drive the paper’s findings. Findings It is shown that when firms behave non-cooperatively in both the R&D and production stages, the degree of spillover has a negative relationship with the effective and respective R&D expenditures of each firm as well as the level of social welfare. An inverted-U relationship between competition and social welfare also holds. When firms behave cooperatively in the R&D stage, and non-cooperatively in the production stage the relationship between the R&D expenditure of the joint research lab and the number of firms in the market is negative. Originality/value In the literature on R&D spillovers and process innovation, efforts are mostly focused on the comparative R&D expenditures and the relative social welfare between non-cooperative and cooperative R&D. The question of the effectiveness of R&D technology on the optimal number of firm, however, is not explicitly addressed. The paper is intended to address this lacuna.
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.
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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.012 | 0.001 |
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".