Effects of consumer loyalty and product web compatibility on cooperative advertising and pricing policies in a dual-channel supply chain
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
A common practice for brand manufacturers is to operate dual distribution channels in which they offer an online channel for direct sales to end consumers and an independently-managed retail channel for sales in physical stores. This structure enables the manufacturers to reach multiple segments of consumers with different online and offline shopping preferences, but it may create channel conflicts due to the manufacturers’ competitive position in the end market. Cooperative advertising programs can be implemented in response to the emerging competitive dynamics between the manufacturers and the retailers. We investigate the impact of the consumers’ sales channel preference ( i.e ., “consumer loyalty”) and the product compatibility with online shopping ( i.e ., “product web compatibility or web fit”) on the cooperative advertising and pricing decisions of a manufacturer and a retailer in a dual-channel supply chain. We use game-theoretical models and characterize the firms’ equilibrium behaviors under different power structures in the channel. Our results indicate that the level of the retailer’s advertising investment and the manufacturer’s reimbursement in the cooperative advertising program depend critically on consumer loyalty, product web compatibility, and the power distribution among the channel members. For example, when the channel power is symmetrically distributed or held asymmetrically by the retailer, the retailer’s local advertising level increases as the product web compatibility decreases or the proportion of store-loyal consumers increases; whereas this trend is reversed when the manufacturer is the channel leader. We examine how the introduction of the direct channel affects the profits, and we generate additional managerial insights from numerical experiments.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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