Privacy in a Multi-Stage Game – An Evolutionary Programming Approach

Abstract

The second chance offer is a common seller practice on eBay. It consists of price discrimination against the losing bidder, who is offered an identical item at the value of his or her highest bid. This paper approaches this as a privacy problem, which is posed as one of information revelation in a multi-stage game. [7] has shown that, if bidders are rational, they change their bidding strategies to compensate for the price discrimination so that the seller is not motivated to violate privacy in this manner. [8] has shown this is true even if the seller price discriminates with a probability α, when there are as many items as there are bidders. In this paper, we examine the cases when the items are insufficient for all bidders-to determine whether privacy violation is more acceptable to the bidder, in the presence of scarcity. Using both Bayesian techniques and evolutionary programming simulations, we determine optimal strategies for bidders and sellers. We present the Nash equilibria obtained, and determine that there is at least one case when sellers are motivated to perform randomized price discrimination because of the second mover advantage. Our use of evolutionary programming simulations is unique in the privacy literature.