Uncertain future development presents a significant challenge during the distribution strategy planning process. Traditional planning approaches, reliant on creating potential scenarios and assigning probabilities, often struggle due to future developments' inherent unpredictability, which can...

We can overcome uncertainty with uncertainty. Using randomness in our choices and in what we control, and hence in the decision making process, could potentially offset the uncertainty inherent in the environment and yield better outcomes. The example we develop in greater detail is the...

We can overcome uncertainty with uncertainty. Using randomness in our choices and in what we control and hence in the decision making process, could potentially offset the uncertainty inherent in the environment and yield better outcomes. This methodology is suitable for the social sciences...

Heterogeneous beliefs among market participants can lead to questionable speculative trading that goes beyond any risk-sharing motives. We demonstrate that such unwarranted betting behavior in market equilibrium can be mitigated by introducing nonlinear pricing for ambiguous contracts, without...

Economists often estimate a subset of their model parameters outside the model and let the decision-makers inside the model treat these point estimates as-if they are correct. This practice ignores model ambiguity, opens the door for misspecification of the decision problem, and leads to...

Economists often estimate economic models on data and use the point estimates as a stand-in for the truth when studying the model’s implications for optimal decision-making. This practice ignores model ambiguity, exposes the decision problem to misspecification, and ultimately leads to...

In typical robust portfolio selection problems, one mainly finds portfolios with the worst-case return under a given uncertainty set, in which asset returns can be realized. A too large uncertainty set will lead to a too conservative robust portfolio. However, if the given uncertainty set is not...

We propose a new model formulation for a three-echelon supply network design problem incorporating the concept of relocatable modular capacities. A robust supply network configuration must be determined based on uncertain demand. Furthermore, by incorporating the conditional value at risk...

Probabilistic preference models predict that a subject makes different choices with different probabilities in repeatedly experiments with the same stimuli. This paper explains why. First, we prove that a gamble is a statistical ensemble or sample function of a random field with canonical...