On the Diffusion of Subscription-Based Services: The Roles of Price, Advertising, and Customers’ Defection
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
There are a limited number of aggregate service diffusion models that have been analytically analyzed and empirically estimated for subscription-based services. Aggregate diffusion models of this sort are instrumental for decision-making and forecasting the number of subscribers over time. In this article, an aggregate diffusion model of subscription services for a monopoly is developed, incorporating a customer acquisition process, a customer attrition process, and marketing-mix variables. On the empirical side, using Canadian cable TV diffusion data related to several provinces, the inclusion of marketing-mix variables into the aggregate diffusion model for subscription services that incorporate customers’ defection is found to improve its performance. An extended Kalman filter estimator shows that advertising affects the coefficient of innovation, whereas price affects the coefficient of imitation. On the theoretical side, the sensitivity of marketing-mix decisions to a change in customers’ defection at the steady state is operationalized for a long planning horizon together with fixed marketing-mix decisions over time. Upon meeting certain realistic conditions, it is shown for the first time that customers’ defection could enhance a firm's profitability. Managerial implications of the study, together with directions for future research, 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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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