This paper is focused on the coordination of order and production policy between buyers and suppliers in supply chains. When a buyer and a supplier of an item work independently, the buyer will place orders based on his economic order quantity (EOQ). However, the buyer’s EOQ may not lead to an optimal policy for the supplier. It can be shown that a cooperative batching policy can reduce total c...

BACKGROUND The dearth of health workers in rural settings in Lao People's Democratic Republic (PDR) and other developing countries limits healthcare access and outcomes. In evaluating non-wage financial incentive packages as a potential policy option to attract health workers to rural settings, understanding the expected costs and effects of the various programs ex ante can assist policy-makers...

abstract this article aims to provide theoretical model for analyzing challenge of asymmetric information in the third sector of economy (which is the most important challenge, preventing the growth and development of third sector), using the theoretical foundation of contract theory and incentive theory with regard to the special characteristics of third sector derived by its special structure...

This article is devoted to adverse selection problems in which individual private information is a whole utility function and cannot be reduced to some nite-dimensional parameter. In this case, incentive compatibility conditions can be conveniently expressed using some abstract convexity notions arising in Mass Transfer Theory 8]. After this characterization is provided, an existence result of ...

We study mechanisms for an allocation of goods among agents, where agents have no incentive to lie about their true values (incentive compatible) and for which no agent will seek to exchange outcomes with another (envy-free). Mechanisms satisfying each requirement separately have been studied extensively, but there are few results on mechanisms achieving both. We are interested in those allocat...

In the on-line Explore & Exploit literature, central to Machine Learning, a central planner is faced with a set of alternatives, each yielding some unknown reward. The planner’s goal is to learn the optimal alternative as soon as possible, via experimentation. A typical assumption in this model is that the planner has full control over the experiment design and implementation. When experiments ...