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Combinatorial auction design
David Porter1, Stephen Rassenti, Anil Roopnarine
1Interdisciplinary Center for Economic Science, George Mason University, Fairfax, VA 22030, USA. dporter4@gmu.edu
Summary
This study introduces a novel combinatorial auction design that overcomes computational and cognitive challenges. Laboratory tests show it achieves highly efficient outcomes, making complex auctions more practical.
Area of Science:
- Economics
- Computational Economics
- Auction Theory
Background:
- Combinatorial auctions offer expressive bidding with package bids and logical constraints.
- They are valuable for complementary values or production/financial constraints but are rarely used.
- Existing challenges include computational uncertainty and cognitive complexity leading to inefficient bidding.
Purpose of the Study:
- To present a new type of combinatorial auction.
- To address computational and cognitive complexities in combinatorial auctions.
- To demonstrate improved efficiency through laboratory testing.
Main Methods:
- Development of a novel combinatorial auction mechanism.
- Laboratory experimentation to evaluate auction performance.
- Analysis of bidding strategies and outcome efficiency.
Main Results:
- The proposed combinatorial auction design eliminated computational uncertainty.
- Cognitive complexity was reduced, mitigating perverse bidding strategies.
- Extremely efficient outcomes were achieved in laboratory settings.
Conclusions:
- The novel combinatorial auction design is a viable solution to practical implementation challenges.
- This approach enhances efficiency and bidder participation in complex auctions.
- Further research can explore real-world deployment and scalability.