Either in the form of nature’s wrath or a pandemic, catastrophes cause major destructions in societies, thus requiring policy and decision makers to take urgent action by evaluating a host of interdependent parameters, and possible scenarios. The primary purpose of this pa-per is to propose a...

This paper extends decision making under risk and uncertainty to group theory via representations of invariant behavioural space for prospect theory. First, we predict that canonical specifications for value functions, probability weighting functions, and stochastic choice maps are homomorphic....

We consider a standard one-agent decision-making problem under risk and we address the following question: under what conditions is utility maximization equivalent to 'risk' minimization, where the measure of risk used by the decision-maker is a conservative coherent risk measure?

Neural networks are tackled through probabilities for neurons to be activated by other neurons. They are represented by doubly stochastic matrices, named brain matrices, the polytope of which is the convex hull of the permutation matrices which are vertices of this Birkhoff polytope. Each...

Administration in organizations emerged as a specific field of inquiry for social sciences in the middle of the twentieth century. Herbert Simon has defined a program that allows social sciences to move from principles to concepts about action and action taking. Four main perspectives of...

Moore & Shannon's theorem is the cornerstone in reliability theory, but cannot be applied to human systems in its original form. A generalization to human systems would therefore be of considerable interest because the choice of organization structure can remedy reliability problems that...

This study is among the first to uncover specific concepts and skills critical to the general corporate real estate executive. The research targeted a broad range of U.S. and international corporate real estate executives in positions to know the requirements for their assignment. The results...

We consider an agent who has to repeatedly make choices in an uncertain and changing environment, who has full information of the past, who discounts future payoffs, but who has no prior. We provide a learning algorithm that performs almost as well as the best of a given finite number of experts...

The predictive power of Cumulative Prospect Theory (CPT) and Expected Utility Theory (EUT) is typically compared using decisions from description (DfD), wherein lotteries' outcome values and probabilities are explicitly stated. In decisions from experience (DfE), individuals sample (without...

In this paper a comprehensive framework that maximizes advertising revenues of a company in a personalized advertisement setting is presented. The research was motivated from a real life problem faced by a company that develops a web based 3-D virtual reality social platform. The objective of...