Commercial AI solutions provide analysts and managers with data-driven business intelligence for a wide range of decisions, such as demand forecasting and pricing. However, human analysts may have their own insights and experiences about the decision-making that is at odds with the algorithmic...

Prior research suggests that those who rely on intuition rather than effortful reasoning when making decisions are less averse to risk and ambiguity. The evidence is largely correlational, however, leaving open the question of the direction of causality. In this paper, we present experimental...

We present a preference foundation for Chance Theory (CT), a model of decision making under uncertainty where the evaluation of an act depends distinctively on its lowest outcome. This outcome is evaluated with the riskless value function u and the potential increments over it are evaluated by...

A choice problem is risky (respectively ambiguous) if the decision maker is choosing between probability distributions (respectively sets of probability distributions) over utility relevant consequences. We provide an axiomatic foundation for and a representation of continuous linear preferences...

I analyze optimal natural resource use in an intergenerational model with the risk of a catastrophe. Each generation maximizes a weighted sum of discounted utility (positive) and the probability that a catastrophe will occur at any point in the future (negative). The model generates time-...

In this paper, I seek to establish a framework in which solutions to imperfect recall decision problems can be suitably examined. I introduce a strategy concept which is an extension of the standard concept employed since von Neumann and Morgenstern, and show how it may provide optimal solutions...

In this paper, I study decision theory in the presence of imperfect recall. I use an extension of the standard strategy concept for the analysis of extensive form games in order to examine the range of imperfect recall problems for which there exists an optimal solution. Optimality is assessed...

In this study we introduce a new stochastic choice rule that categorizes objects in order to simplify the choice procedure. At any given trial, the decision maker deliberately randomizes over mental categories and chooses the best item according to her utility function within the realized...

Nudge is a concept of policy intervention that originates in Thaler and Sunstein's (2008) popular eponymous book. Following their own hints, we distinguish three properties of nudge interventions: they redirect individual choices by only slightly altering choice conditions (here nudge 1), they...