You have to make big and small decisions every day of your life. What would you like for breakfast? When should you meet your friends for dinner? Which university should you go to? How many children do you want?
When faced with certain decisions, you may be inclined to toss a coin and let the opportunity determine your destiny. In most cases, we will follow a certain strategy or a series of strategies to make a decision.
For many of the relatively small decisions we make every day, tossing a coin is not a bad method. For some complex and important decisions, we are more likely to invest a lot of time, research, effort and mental energy to come to the correct conclusion.
So how does this process work? Here are some of the main decision strategies you might use.
Single feature model
This approach involves making your decision entirely dependent on a single function. For example, suppose you are buying soap. Faced with multiple choices in local supermarkets, you decide to make a decision based on the price and buy the cheapest soap. In this case, you ignore other variables (such as smell, brand, reputation, and effectiveness) and focus on only one feature.
When the decision is relatively simple and time is tight, the single feature method may be effective. However, it is usually not the best strategy when dealing with more complex decisions.
Additional feature model
This approach involves considering all the important features of possible options, and then systematically evaluating each option. This method is often a better method when making more complex decisions.
For example, suppose you are interested in buying a new camera. You create a list of the important functions you want the camera to have, and then score each possible option on a scale of -5 to +5.
Cameras with important advantages may receive a +5 rating on this factor, and cameras with significant disadvantages may receive a -5 rating on this factor. After reviewing each option, you can summarize the results to determine which option has the highest rating.
Additive feature models are a good way to determine the best options for various options. However, as you can imagine, it can be very time-consuming, and if you are pressed for time, it may not be the best decision-making strategy.
Eliminate the model by aspect
The aspect elimination model was first proposed by psychologist Amos Tversky in 1972. In this method, you evaluate each option one feature at a time, starting with any feature that you consider most important. When an item does not meet the criteria you established, you cross out the item from your list of options. When you delete an item from the list, your list of possible choices will get smaller and smaller until you finally find only one choice.
Make a decision
The first three processes are usually used in situations where decision-making is very simple, but what happens when a certain degree of risk, ambiguity, or uncertainty is involved? For example, imagine your psychology class is about to be late.
In order to arrive on time, should you exceed the speed limit, but risk being fined for a speeding ticket? Or should you limit your speed, risk being late, and be deducted points for missing scheduled popular quizzes? In this case, you must weigh the possibility of being late for the appointment and the possibility of getting a speeding ticket.
When making decisions in this situation, people tend to adopt two different decision-making strategies: usability heuristics and representative heuristics. Remember, heuristics are a rule of thumb that allows people to make quick decisions and judgments.
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When we are trying to determine how likely something is, we usually make such estimates based on how easy it is for us to remember similar events that happened in the past. For example, if you are trying to determine whether you should be speeding and risk getting a ticket, you might think about how many times have you seen someone stopped by the police on a particular highway section.
If you can’t think of any examples right away, you may decide to continue taking the risk because the usability heuristic makes you judge that few people are stopped for speeding on your particular route. If you can think of many people being stopped, you might decide to drive safely and follow the recommended speed limit.
This psychological shortcut involves comparing our current situation with the prototype of a particular event or behavior. For example, when trying to determine whether you should speed up to arrive in class on time, you might compare yourself to the image of the person most likely to get a speeding ticket.
If your prototype is a careless teenager driving a hot car, and you are a young businesswoman driving a car, you might estimate that the probability of getting a speeding ticket is very low.
Very good sentence
The decision-making process can be simple (for example, randomly selecting from our available options) or very complicated (for example, systematically rating different aspects of existing choices). The strategy we use depends on a variety of factors, including the time it takes us to make a decision, the overall complexity of the decision, and the degree of ambiguity involved.