A Quantifiable Risky Decision Model: Incorporating Individual Memory into Informational Cascade

People memory system plays a key role in the decision‐making process (DMP). In order to examine its influence on decision‐making, an individual's memory‐based decision‐making system is developed, and then, we integrate the multi‐agent decision systems and construct a sequential risky decision model on the basis of an informational cascade. This study aims at exploring the public's decisions on whether or not to take protective actions under risk. The findings indicate that people with different strength of ties to friends and relatives make huge differences on decision‐making. In the group with weak ties, the agent's total size of decision information and the level of risk perception are reducing in the sequential decision process. We further prove that people with weak ties are more prone to take no protective action, and the probability is also decreasing with the decision turn. The sequence of people with strong ties makes decisions dynamically with the intensity of released information. Finally, the influences of forgetting rate and memory capacity on people's decision‐making are examined. The model provides a new line of thought about building a multi‐agent system of DMP, which is also very helpful for the design of an information management system during emergencies. Copyright © 2014 John Wiley & Sons, Ltd.