Abstract
Abstract In the field of system dynamics (SD), there has been a missing set of theoretically sound techniques for explicitly modeling dynamics during discrete decision‐making processes across varying levels and types of decision pressures. Purchasing a property, filing a divorce, approving a merger, imposing a tariff, and launching a war are examples of actions that have broader ramifications; in these cases, the decisions and timing of those decisions are crucial in understanding and predicting the interactions between the decision‐makers and their environments. Sequential Sampling Models (SSMs) have remained commonplace in cognitive psychology (CP) for decades because of their utility in simultaneously capturing individual decisions and decision‐time distributions. This article reviews existing SSM literature and proposes a generalized, elementary mechanism distilled from existing SSMs, which establishes a connection between SD and CP in the hope of benefiting both fields. © 2022 System Dynamics Society.