Incentives for Sharing in Peer-to-Peer Networks
WELCOM '01 Proceedings of the Second International Workshop on Electronic Commerce
eNcentive: a framework for intelligent marketing in mobile peer-to-peer environments
ICEC '03 Proceedings of the 5th international conference on Electronic commerce
An anonymous bonus point system for mobile commerce based on word-of-mouth recommendation
Proceedings of the 2004 ACM symposium on Applied computing
Coupon Based Incentive Systems and the Implications of Equilibrium Theory
CEC '04 Proceedings of the IEEE International Conference on E-Commerce Technology
The human side of sharing in peer-to-peer networks
Proceedings of the 2nd European Union symposium on Ambient intelligence
Modelling incentives for collaboration in mobile ad hoc networks
Performance Evaluation - Selected papers from the first workshop on modeling and optimization in mobile, ad hoc and wireless networks (WiOpt'2003)
Secure incentives for commercial ad dissemination in vehicular networks
Proceedings of the 8th ACM international symposium on Mobile ad hoc networking and computing
Vehicular networks and the future of the mobile internet
Computer Networks: The International Journal of Computer and Telecommunications Networking
Hi-index | 0.00 |
Ad hoc networks and peer-to-peer systems typically require many users to participate, in order to leverage the full benefits of the system. In this paper we examine an electronic coupon system, where providers send out coupons, which are passed from user to user. The incentive for users to participate is that they receive bonus points for each redemption of the coupon. The contributions of this paper are two-fold. First, we define a general model for such bonus point -based coupon schemes and derive an optimal strategy which allows each user to determine how many bonus points she should ask for when passing the coupon. Second, we show that our optimal strategy is extremely robust against all other user strategies, and that there is a strong incentive for users to follow our optimal strategy.