This study responds to the call by some scholars to establish a framework for ignorance. It challenges the myth that ignorance is all bad and an utterly undesirable state in organizations and proposes a new framework for the application of ignorance analytics in organizations. It includes a...

Over the last decades, dynamic pricing has become increasingly popular. To solve pricing problems, however, is particularly challenging if the customers' and competitors' behavior are both strategic and unknown. Reinforcement Learning (RL) methods are promising for solving such dynamic problems...

This paper develops a novel gradient-based reinforcement learning algorithm for solving dynamic quantile models with uncertainty. Unlike traditional approaches that rely on expected utility maximization, we focus on agents who evaluate outcomes based on specific quantiles of the utility...

This paper develops a novel gradient-based reinforcement learning algorithm for solving dynamic quantile models with uncertainty. Unlike traditional approaches that rely on expected utility maximization, we focus on agents who evaluate outcomes based on specific quantiles of the utility...