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Intuitive decision-making is based on implicit knowledge relayed to the conscious mind at the point of decision through affect or unconscious cognition. Some studies also suggest that intuitive decision-making relies more on the mind's parallel processing functions, while deliberative decision-making relies more on sequential processing.
Intuition was assessed by a sample of 11 Australian business leaders as a gut feeling based on experience, which they considered useful for making judgments about people, culture, and strategy. [45] Such an example likens intuition to "gut feelings", which — when viable [ clarification needed ] — illustrate preconscious activity.
Malcolm Gladwell described intuition, not as an emotional reaction, but a very quick thinking. [5] He said that if an individual realized that a truck is about to hit him, there would be no time to think through all of his options and, to survive, he must rely on this kind of decision-making apparatus, which is capable of making very quick judgments based on little information. [6]
Mental models affect the way that people work with information, and also how they determine the final decision. The decision itself changes, but the mental models remain the same. It is the predominant method of learning, because it is very convenient.
Dual process theory within moral psychology is an influential theory of human moral judgement that posits that human beings possess two distinct cognitive subsystems that compete in moral reasoning processes: one fast, intuitive and emotionally-driven, the other slow, requiring conscious deliberation and a higher cognitive load.
The recognition heuristic, originally termed the recognition principle, has been used as a model in the psychology of judgment and decision making and as a heuristic in artificial intelligence. The goal is to make inferences about a criterion that is not directly accessible to the decision maker, based on recognition retrieved from memory.
The naturalistic decision making (NDM) framework emerged as a means of studying how people make decisions and perform cognitively complex functions in demanding, real-world situations. These include situations marked by limited time, uncertainty, high stakes, team and organizational constraints, unstable conditions, and varying amounts of ...
Data-informed decision-making (DIDM) gives reference to the collection and analysis of data to guide decisions that improve success. [1] Another form of this process is referred to as data-driven decision-making, "which is defined similarly as making decisions based on hard data as opposed to intuition, observation, or guesswork."