@inproceedings{c3481f796d0c437fa8e54600f90a7531,
title = "Reputation in repeated pay-to-bid auctions",
abstract = "This study primarily focuses on pay-to-bid auctions in which bidders pay a fixed fee for each bid to increase the price and explores the reputation of bidders within the auctions. The reputation effects can be discovered from sample observations in pay-to-bid auction websites. Pay-to-bid auctions are highly susceptible to manipulative behaviors by an aggressive bidder. To explain the phenomenon, a basic model in which two bidders take part in a series of pay-to-bid auctions is developed and an extension of a multiplayer model builds on the basic model. The question of an optimal auction from the auctioneer's standpoint, in an asymmetric setting, is addressed. It is expected to theoretically show that the results from previous symmetric pay-to-bid auction models do not carry over to repeated auctions when one of the bidders is endowed with a reputation for bidding aggressively.",
keywords = "Aggressive bidding behaviors, Game theory, Incomplete information, Pay-to-bid auctions, Reputation",
author = "Anqi Wu and Kwon, {H. Dharma} and Kim, {Sung Won}",
note = "Publisher Copyright: {\textcopyright} 2018 Association for Information Systems. All rights reserved.; 24th Americas Conference on Information Systems 2018: Digital Disruption, AMCIS 2018 ; Conference date: 16-08-2018 Through 18-08-2018",
year = "2018",
language = "English (US)",
isbn = "9780996683166",
series = "Americas Conference on Information Systems 2018: Digital Disruption, AMCIS 2018",
publisher = "Association for Information Systems",
booktitle = "Americas Conference on Information Systems 2018",
}