Cross-Market Network Effect with Asymmetric Customer Loyalty: Implications for Competitive Advantage
Why this work is in the frame
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Bibliographic record
Abstract
A cross-market network effect exists in many industries (e.g., newspaper publishing, media, software) in which a seller sells both a primary and a secondary product (e.g., a newspaper publisher sells newspapers to readers and advertising space to advertisers), and the value of the secondary product depends on the size of the user base of the primary product. This paper examines the competitive implications of asymmetric customer loyalty in such markets. In traditional markets, an advantage in customer loyalty generates a profit advantage. We show here, however, that in the presence of a cross-market network effect, a midlevel of loyalty advantage in the primary product market can lead to an overall profit disadvantage. This surprising result is derived from the interdependence of the two markets, whereby a profit in one market may be gained at the cost of the other, and by the positive relationship between a larger loyalty segment and a higher opportunity cost of price competition in the product of the primary market. Extending our model to a two-period entry game also shows that under certain conditions, the entrant with disadvantage in customer loyalty can outperform the incumbent in profit and market share. This result suggests that asymmetry in customer loyalty can be a source of “first-mover” advantage or disadvantage.
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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 | 0.007 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.004 |
| 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