Markov Decision Processes (MDPs) have been widely used as invaluable tools in dynamic decision-making, which is a central concern for economic agents operating at both the micro and macro levels.
Many companies have jumped on the “big data” bandwagon. They’re hiring data scientists, mining employee and customer data for insights, and creating algorithms to optimize their recommendations.
When making decisions under uncertainty, it is important to distinguish between the probability that a judgment is true and the confidence analysts possess in drawing their conclusions.
Improving the performance of the healthcare sector requires an understanding of the efficiency and effectiveness of care delivered by providers.
We develop an 18-item self-report measure of receptiveness to opposing views. Studies 1a and 1b present the scale and report measures of internal, convergent, and discriminant validity.
In a variety of applications, decisions needs to be made dynamically after receiving imperfect observations about the state of an underlying system.
Few people have sat across from the Iranians and the North Koreans at the negotiating table. Wendy Sherman has done both.
It is common for organizations to offer awards to motivate individual behavior, yet few empirical studies evaluate their effectiveness in the field.
While in recent decades the social and business sectors have evolved on fairly separate tracks, today companies are increasingly expected to generate social value in addition to profit.
To examine how hybrid organizations make decisions that enable them to sustain the joint pursuit social and commercial goals, and how these decision-making processes unfold over time as tensions betwe
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