Explaining the phenomenon of surprise using foundational data processing

Document Type : research Artichel

Authors

boos

Abstract

Surprise is a phenomenon that all systems face with different natures and levels, and in many cases it can endanger its survival. Surprise is a cognitive state that occurs as a result of unexpected events, and due to having characteristics such as high acceleration and cognitive inconsistency, it can disrupt the decision-making mechanism. The aim of this research is to provide a model to understand the phenomenon of surprise. The current research is a type of basic research with a qualitative approach and using foundation data theory. Based on this, 35 in-depth interviews with specialists and experts in different fields were conducted in the field of how surprises occur and after analyzing the data; The number of 6215 open codes, 200 components and 30 subcategories were identified and finally modeled using the foundation's data theorizing paradigm model. The results show that three categories of capability-oriented, intention-oriented and environment-oriented components are among the causal conditions that explain the phenomenon of surprise. The components of space-time and substrate-speed are among the background conditions, and the components of the outer layer and uncertainty are also among the intervening conditions. Based on this, the main strategies for understanding surprise include the use of systemic thinking in regard to causal conditions and the use of strategic intelligence, which can lead to consequences such as identifying weak signs and processing scenarios related to system behavior, and as a result, reducing surprise from rare events. .

Keywords