The Dual-Channel Retailer’s Channel Synergy Strategy Decision
Bibliographic record
Abstract
The main research question asked in this paper is whether and when a dual-channel retailer (retailer in short) should adopt the “buy online and pick up in store” (BOPS) strategy. To answer this question, we first derive the optimal price decision using the non-BOPS and BOPS strategies. Subsequently, we compare the performance of retailers under non-BOPS and BOPS scenarios. Our main findings are that under the monopoly scenario, retailers may not always benefit from the BOPS strategy. Retailers will benefit only if the offline operational costs are low and the degree of customer acceptance of the online channel is high. However, the BOPS strategy cannot improve dual-channel retailers’ market share. Furthermore, under a Stackelberg game scenario with e-retailers as leaders, when the value of a product is medium and the transaction costs of the offline channel are high, retailers can use the BOPS strategy to enhance their market share. If the degree of customer acceptance of the online channel is also high, retailers can further improve their profits by using the BOPS strategy. Overall, these findings not only provide decision support for retailers, but also enrich the theories on dual-channel retailing in operations management.
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How this classification was reachedexpand
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 | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".