Manufacturer defensive and offensive advertising in competing distribution channels
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
Abstract This paper investigates how two competing manufacturers should invest in defensive and offensive advertising in a two‐segment market and whether they should each adopt a decentralized or an integrated channel if their goal is to maximize total channel profits. We find that manufacturers in decentralized channels can exclusively undertake either of the two types of advertising or combine the two at the equilibrium. In integrated channels, they can either combine the two or exclusively undertake defensive advertising. When multiple equilibria exist, strategies that combine both types of advertising should be preferred to exclusive defensive advertising strategies, which are better than exclusive offensive advertising strategies. Also, total channel profits are higher in decentralized channels than in integrated channels when the brands are moderately or highly substitutable. Conversely, total channel profits of integrated channels are higher than those of decentralized channels in areas where the brands are relatively differentiated and the offensive advertising retaliatory capacity of the rival is stronger. Theoretical and managerial implications of these findings are discussed.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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