Editorial Statement—Stochastic Models and Simulation

Stochastic Models and Simulation

Baris Ata, University of Chicago

The Stochastic Models and Simulation department seeks to publish work that contributes to the modeling, analysis, or simulation of stochastic systems, broadly construed, through advances in methodology or applications. These advances may stem from the development of new methods and models or creative applications of existing ones. The department seeks to attract papers that contribute to the science or practice of management through stochastic modeling.

In terms of methodological areas, the department is interested in a broad range of topics that pertain to the management of stochastic systems and more broadly address decision making under uncertainty. Examples of relevant problem areas include manufacturing, inventory and production management, delivery of healthcare services, service operations, revenue management, and financial engineering. Methodological contributions to these areas may take the form of novel analytical, computational, simulation-based, or statistical methods.

We welcome papers that apply emerging deep learning/artificial intelligence tools and other computational methods to tackle address managerial problems with a strong stochastic modeling content. We are also interested in contributions that emphasize new applications such as sharing economy markets, management of online matching platforms, and social sector operations.

The department places particular emphasis on the originality and breadth of the approach and the quality of the results. Ideally, these should transcend the specifics of the motivating problem but at the same time should remain grounded in practice and avoid focusing on abstract theory per se. Although rigor plays an important role in assessing submissions, it is by no means sufficient, and a greater premium is placed on the novelty of the problem being studied and its overall importance and value to management science theory and/or practice.