A reputation-aware two-way auction mechanism construction method for a data transaction market
By constructing a reputation-aware two-way auction mechanism (RDAM) in the data trading market, the problems of information asymmetry, adverse selection, and static reputation failure are solved. This enables efficient quality screening and dynamic closed-loop learning, improves market efficiency and quality differentiation, and generates continuous motivation for quality investment.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- NANJING UNIV OF SCI & TECH
- Filing Date
- 2026-04-15
- Publication Date
- 2026-07-17
AI Technical Summary
Traditional two-way auction mechanisms in the data trading market suffer from problems such as information asymmetry, adverse selection and moral hazard, static reputation failure, and a lack of closed-loop evaluation and incentives. This leads to the squeezing out of high-quality sellers, resulting in low market efficiency and difficulty in achieving quality differentiation and long-term sustainability.
We construct a reputation-aware two-way auction mechanism (RDAM) by integrating the bid matrix, ask vector, and reputation score of market participants. By deeply coupling dynamic reputation with two-way auction, we explicitly introduce quality/reputation information to form a closed-loop learning process of transaction feedback, reputation update, price and matching, ensuring the preference of high-quality sellers and the suppression of low-quality sellers.
It improves market efficiency, quality differentiation, and long-term sustainability, enhances social welfare and transaction volume, significantly strengthens the success rate of high-quality sellers, reduces the proportion of buyer-disappointed transactions, and creates an intrinsic motivation for continuous quality investment, while possessing scalability and robustness.
Smart Images
Figure CN122414902A_ABST