Horizontal information sharing or not? The choice in information leakage dilemma of the reverse supply chain
Bibliographic record
Abstract
Recyclers can derive benefits from horizontal demand information sharing with competitors under specific conditions. However, these advantages may be compromised by the actions of remanufacturers. Information leakage occurs when a remanufacturer selectively discloses information obtained from one recycler to another. This study aims to support recyclers within the reverse supply chain in effectively engaging in horizontal information sharing while mitigating the risk of remanufacturers disclosing proprietary information to competitors, thereby preventing the dissemination of information contrary to the recyclers' intentions for sharing. The research focuses on analyzing the impact of horizontal information sharing and information leakage on the profitability of both remanufacturers and recyclers. An analytical model has been developed based on partial and asymmetric signals of customer valuation. Three scenarios are explored: no information sharing and no leakage, information sharing only, and scenarios involving both sharing and leakage. The novelty of this study lies in its examination of a demand process characterized by distributional uncertainty, which mirrors the informational challenges faced by recyclers entering new markets or expanding into new recycling categories. Recyclers operate with incomplete information and cannot determine whether they possess superior information compared to their competitors. The findings suggest that information sharing among recyclers can enhance the profits of those experiencing high demand but may adversely affect those with lower demand levels. In the absence of horizontal information sharing between recyclers, remanufacturers tend to leak information about higher-demand recyclers to others. Ultimately, managers of competing firms who face uncertainty regarding their information standing should consider sharing information to gain improved demand forecasts or, at minimum, to prevent remanufacturers from exploiting information leakage for personal gain. This refined analysis provides critical insights for stakeholders in the reverse supply chain, highlighting the complex interplay between information sharing and competitive advantage, as well as the strategic importance of managing information flow to safeguard business interests.
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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 | 0.000 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.004 |
| Open science | 0.001 | 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 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".