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Approximations to auctions of digital goods with share-averse bidders

Affiliation:	1. Department of Veterinary Clinical Studies, Faculty of Veterinary Medicine, Universiti Malaysia Kelantan, Pengkalan Chepa, 16100 Kota Bharu, Kelantan, Malaysia;2. Department of Veterinary Clinical Studies, Faculty of Veterinary Medicine, Universiti Putra Malaysia, 43400 Serdang, Selangor, Malaysia;3. Department of Preclinical Studies, Faculty of Veterinary Medicine, Universiti Putra Malaysia, 43400 Serdang, Selangor, Malaysia;1. School of Information Systems, Singapore Management University, 80 Stamford Road, Singapore 178902, Singapore;2. School of Electrical and Electronic Engineering, Nanyang Technological University, Nanyang Avenue, Singapore 639798, Singapore;3. Manufacturing Execution and Control Group, Singapore Institute of Manufacturing Technology, Nanyang Drive, Singapore 638075, Singapore;1. Princeton University, Dept. of Computer Science, 35 Olden Street, Princeton, NJ 08540-5233, United States;2. Uppsala University, Dept. of Information Technology, Box 337, 751 05 Uppsala, Sweden

Abstract:	We consider the case of a digital product for share-averse bidders, where the product can be sold to multiple buyers who experience some disutility from other firms or consumers owning the same product. We model the problem of selling a digital product to share-averse bidders as an auction and apply a Bayesian optimal mechanism design. We also design constant-approximation algorithms in the prior-free setting including both average- and worst-case analyses.

Keywords:	Auction Share-averse bidders Constant-approximation algorithms Prior-free algorithms
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