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Binyan Pu

dblp:410/3774 · DBLP profile ↗
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1ranked-venue papers
0as first author
1since 2021 · last 2025
0009-0002-6967-3345ORCID · reported

Domains — the database's venue-derived domains; a paper can count in several

Artificial intelligence and machine learning · 1 · 1 since 2021Theory of computation · 1 · 1 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Theoretical computer science
1 paper
Algorithmic game theory and mechanism design · 100%

Topics — the 3 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Algorithmic game theory and mechanism design › mechanism design
information design
0.912025
The Design of Quality Disclosure Policy and the Limits to Competition · EC 2025
Algorithmic game theory and mechanism design › non-cooperative game
duopoly competition
0.312025
The Design of Quality Disclosure Policy and the Limits to Competition · EC 2025
Algorithmic game theory and mechanism design
mechanism design
0.312025
The Design of Quality Disclosure Policy and the Limits to Competition · EC 2025

Methods — techniques the papers use, named apart from their topics

information design · 0.9game theory · 0.9
YearPublicationVenuePosition
2025 The Design of Quality Disclosure Policy and the Limits to Competition
abstract
We study a two-dimensional information design problem in a duopoly with vertical differentiation. A third-party designer, literal or metaphorical, designs a public joint signal structure to reveal product quality before firms compete in prices. The industry-optimal policy only reveals the quality ranking, which amplifies perceived differentiation, mitigates price competition, and yields socially optimal allocation. The consumer-optimal policy, to the contrary, intensifies competition by fully concealing the ranking. We further derive welfare-maximizing signal structures for arbitrary Pareto weights. The optimal policy takes one of the following forms: ranking, no-ranking, full revelation, or a combination of full revelation with either ranking or no-ranking policies. Our analysis illustrates how the optimal quality disclosure rule is shaped by both the relative weight on consumer welfare and industry profits and the price competition in response to the information revealed to consumers.
Ming Li 0024, Binyan Pu, Renkun Yang
EC2