Peer-to-Peer and scientific networks, often require those that use the system (i.e. users) to utilize other nodes (i.e. resources) that are unknown. Users are unable to identify whether a resource will be honest, selfish, or malicious. In order for users to reduce the risk of using a malicious resource and to motivate nodes from being selfish, we propose an adaptive reputation-based trust framework for distributed system applications. In this framework, users are able to appraise a resource by using price and a quantifiable metric of trust that is gathered from its own view and the views of other peers (i.e. references) regarding the reputation of the resource. The appraisal process provides the user with a reliable metric that can be used in the process of resource scheduling and selection. In response, economic resources will compete with each other using a variety of strategies that attempt to maximize their profit. The simulation results show that the framework is user friendly by providing long-term high satisfaction, filters out malicious nodes, and encourages resources to provide reliable and high-quality service.