Bibliographic record
Abstract
This paper examines the incentives of firms to invest in socially responsible product innovations. Our analysis connects the existence of socially responsible innovations to the presence of intrinsic and extrinsic social responsibility preferences. In addition to deriving economic value from the product, consumers have heterogeneous intrinsic needs to consume products that are socially responsible. They also have extrinsic social comparison preferences that are based on their meetings with others in social interactions. The frequency of these meetings are endogenous to the consumption choices of consumers. A consumer enjoys a social comparison benefit if her consumption decision is more socially responsible than the consumer that she meets in a social interaction and a social comparison cost if it is less socially responsible. The analysis reveals a nonmonotonic effect of social comparison effects on innovation incentives. When the economic value of a product is relatively small, the incentive to innovate decreases as social comparison effects increase. By contrast, when the economic value of a product is sufficiently large, increases in social comparison effects increase the incentive to innovate. Social comparison benefits and costs have different effects on competition between firms. In particular, social comparison benefits soften price competition, whereas social comparison costs tend to exacerbate price competition. We also identify market conditions where a monopoly invests more or less compared to a firm facing competition.
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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 | 0.005 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.005 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".