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Auction design and performance: An agent-based simulation with endogenous participation

conference contribution
posted on 07.08.2018, 00:00 by A Hailu, John RolfeJohn Rolfe, Jill WindleJill Windle, R Greiner
This paper presents results from computational experiments evaluating the impact on performance of different auction design features. The focus of the study is a conservation auction for water quality where auctions are used to allocate contracts for improved land management practices among landholders bidding to provide conservation services. An agent-based model of bidder agents that learn using a combination of direction and reinforcement learning algorithms is used to simulate performance. The auction design features studied include: mix of conservation activities in tendered projects (auction scope effects); auction budget levels relative to bidder population size (auction scale effects); auction pricing rules (uniform versus discriminatory pricing); and endogeneity of bidder participation. Both weak and strong bidder responses to tender failure are explored for the case of endogeneity in participation. The results highlight the importance of a careful consideration of scale and scope issues and that policymakers need to consider alternatives to currently used pay-as-bid or discriminatory pricing fromats. Averaging over scope variations, the uniform auction can deliver substantially higher budgetary efficiency compared to the discriminatory auction. This advantage is especially higher when bidder participation decisions are more sensitive to auction outcomes. © Springer-Verlag Berlin Heidelberg 2011.

History

Volume

CCIS 129

Start Page

214

End Page

226

Number of Pages

13

Start Date

22/01/2010

Finish Date

24/01/2010

ISSN

1865-0929

ISBN-13

9783642198892

Location

Valencia, Spain

Publisher

Springer

Place of Publication

New York, NY

Peer Reviewed

Yes

Open Access

No

Era Eligible

Yes

Name of Conference

2nd International Conference on Agents and Artificial Intelligence (ICAART 2010)