It is difficult to motivate advisors to acquire information through standard performancecontracts when for instance outcomes are uncertain and/or only observed in the distant future. Decision-makers may however exploit advisors’ desire to influence the outcome. To investigate this, I build a model in which a decision-maker and an advisor both intrinsically care about the decision’s consequences...

This paper considers a decision-making process under ambiguity in which the decision-maker is supposed to split outcomes between familiar and unfamiliar ones. She is assumed to behave differently with respect to unfamiliar gains, unfamiliar losses and customary (familiar) outcomes. In particular, she is supposed to be pessimistic on gains, optimistic on losses and ambiguity neutral on the famil...

This paper proposes a new multi-attribute ranking procedure based on distance from decision-maker preferences. This method has two phases. In the first phase, the decision maker is asked to define the preferred performance for each attribute. In the second phase, Weighted Sum method and new distance-based normalization procedure are used to determine the overall performance rating of alternatives.

In multiobjective optimization problems, the identified Pareto Frontiers and Sets often contain too many solutions, which make it difficult for the decision maker to select a preferred alternative. To facilitate the selection task, decision making support tools can be used in different instances of the multiobjective optimization search to introduce preferences on the objectives or to give a co...

This paper proposes an integrated approach to determine attribute weights in the multiple attribute decision making problems. The approach makes use of the subjective information provided by a decision maker and the objective information to form a two-objective programming model. Thus the resultant attribute weights and rankings of alternatives reflect both the subjective considerations of a de...

We study the dual problems associated with the robust counterparts of uncertain convex programs. We show that while the primal robust problem corresponds to a decision maker operating under the worst possible data, the dual problem corresponds to a decision maker operating under the best possible data. © 2008 Elsevier B.V. All rights reserved.

Three different strategies are identified for organizational adaptation, including dynamic process selection. An executable organizational model composed of individual models of a five stage interacting decision maker is used to evaluate the effectiveness of the different adaptation strategies on organizational performance. The concept of entropy is used to calculate the total activity value, a...

Today, organizations rely on decision makers to produce “mission critical” decisions that are based on inputs from multiple domains. The ideal decision maker has a profound understanding of specific domains, coupled with the experience that allows them to act quickly and decisively on the information. Daily they face problems and failures that are too difficult for any individual person to solv...

We analyze a sequential decision making process, in which at each stepthe decision is made in two stages. In the rst stage a partially optimalaction is chosen, which allows the decision maker to learn how to improveit under the new environment. We show how inertia (cost of changing)may lead the process to converge to a routine where no further changesare made. We illustrate our scheme with some...

We give a representation of analogical reasoning in choice under uncertainty. A decision maker is faced with two decision problems, a familiar and a novel one. It is shown that, under assumptions that capture the salience of alignable differences in choice, the decision maker can be construed as choosing between acts in the novel decision problem as if drawing all likelihood information from a ...