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Bidding and performance in multiple unit combinatorial fishery quota auctions: Role of information feedbacks

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  • Iftekhar, Md Sayed
  • Tisdell, John G.

Abstract

This article explores the role of market information and learning in multiple unit combinatorial markets for fishing quota. Combinatorial auctions allow trading of packages of different types of quotas (for example for different regions or industry) in the same auction market. Bidders can submit package bids which would allow them to enjoy synergy benefits. However, to realize the full benefit bidders require comprehensive understanding of the market. This article focuses on the impact of varying levels of information feedback on performance in multiple unit forward combinatorial auctions using laboratory experiments. In a general context of trade in fishery quota, it was asked whether (a) providing additional market information and (b) learning through time helps in more efficient outcomes. It is found that much of the benefits of information are derived from structural effects, like repeated rounds and package valuations. Providing additional market information does not improve auction performances to a large extent. These results will be useful in designing more efficient combinatorial markets for fisheries quota.

Suggested Citation

  • Iftekhar, Md Sayed & Tisdell, John G., 2015. "Bidding and performance in multiple unit combinatorial fishery quota auctions: Role of information feedbacks," Marine Policy, Elsevier, vol. 62(C), pages 233-243.
    • Handle: RePEc:eee:marpol:v:62:y:2015:i:c:p:233-243
    DOI: 10.1016/j.marpol.2015.09.014
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    Cited by:

    1. Iftekhar, M. S. & Tisdell, J. G., 2018. "Learning in repeated multiple unit combinatorial auctions: An experimental study," Working Papers 267301, University of Western Australia, School of Agricultural and Resource Economics.
    2. Chia-Nan Wang & Ming-Hsun Lin & Chung-Jen Huang & Ching-Chiu Huang & Ruei-Yuan Liao, 2017. "Using TRIZ to Improve the Procurement Process of Spare Parts in the Taiwan Navy," Sustainability, MDPI, vol. 9(10), pages 1-12, October.

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    More about this item

    Keywords

    Experience weighted attraction learning; Fishery quota market; Information feedback; Intelligent agent bidders (robots); Laboratory experiments; Multiple unit forward combinatorial auctions;
    All these keywords.

    JEL classification:

    • Q2 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Renewable Resources and Conservation
    • D44 - Microeconomics - - Market Structure, Pricing, and Design - - - Auctions
    • D47 - Microeconomics - - Market Structure, Pricing, and Design - - - Market Design

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