Is blockchain technology desirable? When considering power structures and consumer preference for blockchain
Bibliographic record
Abstract
Blockchain technology is very useful for combating counterfeits and verifying the authenticity of products for consumers. This paper studies blockchain adoption in a two-level supply chain consisting of a brand supplier and a retailer. Our contribution using the game-theoretic framework is to consider the various preferences that consumers may have for blockchain-supported products and to investigate the value and effects of blockchain in a traditional wholesale channel with different power structures and a platform-based-agent selling channel. We confirm that consumer aversion to blockchain will lower retailer incentive to adopt blockchain, while the opposite will occur if consumers are interested in blockchain. We find that the market leader with power advantage is more motivated to adopt blockchain while the follower has less motivation. We also find that the brand supplier will be willing to move to the agent selling channel if the unit cost of the blockchain is low and the platform commission rate is medium. Moreover, an interesting finding is that blockchain can achieve a win–win-win outcome for the brand supplier, retailer, and consumers under a certain critical threshold, which may cause unfair distribution of supply chain profit and may also be detrimental to the establishment of agent selling.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 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 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".