Blockchain Adoption for Combating Deceptive Counterfeits
Why is this work in the frame?
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Full frame distilled prediction
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.
- Candidate categories
- none
- Consensus categories
- none
- Domain
- Candidate signal: noneConsensus signal: none
- Study design
- Candidate signal: Theoretical or conceptualConsensus signal: none
- Genre
- Candidate signal: MethodsConsensus signal: none
- Teacher disagreement score
- 0.894
- Threshold uncertainty score
- 0.353
- Validation status
machine_predicted_unvalidated·codex-gemma-dda1882f352a
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)
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
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.
- Teacher spread
- 0.236 · how far apart the two teachers sit on this one work
- Validation status
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
Abstract
Counterfeiting is a severe problem in many sectors. There are two types of counterfeits: non‐deceptive and deceptive. While both types are important business challenge, deceptive counterfeit has an additional negative impact—customers have a post‐purchase regret if they expect to purchase a real product but ended up with a fake. The focus of this study is on the setting that relates to deceptive counterfeits. Our paper is one of the first that examines the effectiveness of blockchain as a solution to a supply chain challenge. Specifically, the unique feature of blockchain that we model, which none of the traditional strategies studied in the literature is capable of, is that blockchain adoption changes the analysis from a deceptive counterfeit setting to a non‐deceptive counterfeit setting. We also consider government being a decision maker and customers' privacy concern from blockchain adoption, two features that are not examined in the existing literature. We consider a market with a manufacturer and a deceptive counterfeiter. The manufacturer can signal product authenticity either with blockchain technology or through pricing. The government can provide subsidy to encourage blockchain adoption. Blockchain should be used when the counterfeit quality is intermediate or when customers have intermediate distrust about products in the market. If government provides subsidy, blockchain can be more effective than differential pricing strategy in eliminating post‐purchase regret. Our results advocate for government providing subsidy because it benefits both customers and the society and could be a better approach than government enforcement efforts.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
The record
- Venue
- Production and Operations Management
- Topic
- Blockchain Technology Applications and Security
- Field
- Computer Science
- Canadian institutions
- Western University
- Funders
- National Natural Science Foundation of China
- Keywords
- CounterfeitBlockchainGovernment (linguistics)Product (mathematics)BusinessEnforcementQuality (philosophy)SubsidyMarketingRegretComputer securityEconomicsComputer scienceLaw
- Has abstract in OpenAlex
- yes