[SOUND] The question we need to find clear answers to is if rational decision making is so straight forward, if we follow the process identified earlier, why do we make mistakes? So the literature and the research on this ad domain provide us two possible answers. And when we explore these alternative models, we see that these two models can be dealing, or defined as dealing with the problem of uncertainty. In other words, we really have difficulty identifying the cause effect relationships. The first model is called prescriptive models. And the other is called descriptive models. We will go one by one and describe what each of them are prescribing for us let say about decision making. So when we say prescriptive models this is what we mean. We study how people would behave if they follow certain requirements of rational decision making. In other words we study people to understand where they made a mistake and we develop the models and show them this is the right way of making decision. We prescribe to them what the right way of rational decision-making is. So in order to deal with this we develop methods for making complex optimal decisions. You take, for instance, different courses in statistics. You learn different algorithms on Excel spreadsheets to calculate future value of investments, or you think about future impact of decisions. And, we have to develop methods for making these complex decisions. And most of on BA classes, actually, spend the time to deal with these issues. But there are also descriptive models of decision making. Descriptive models say we need to investigate how people actually behave and make decisions. We learn their strategies of making decisions. As a result, we can develop methods to avoid predictable errors and make better decisions in organizations. We need to understand why people deviate from these rational decision making systems. So let's start with the prescriptive models. These are sometimes called expected utility theory and they are based on fundamental assumptions. And if you have taken a statistics or math course you will see were easily these fundamental assumptions of rationality are based on those principles. One basic assumption of rational decision making is ordering of alternatives in the sense that decision maker, once he or she defines a decision and comes up with alternatives, can choose between those two alternatives. because if you're not capable of choosing, there is no way of making decisions. So this is a very simple straight forward assumption. You also assume that there is dominance in the sense that the decision maker will never select a worse case when there is a better alternative. The third assumption is cancellation. If you are making decisions where there are multiple factors you need to take into account, if both alternatives have the same attribute on one dimensions, you will not use that to make decisions. Let me give you an example. Imagine you are in the market to buy a car. You identified three different cars that fit to your needs and expectations. And you also discover all those three cards have the same color, red. Well, the color of the card then should not be a factor that can be used to make the decision that's why we call it cancellation. And then finally, we believe that there is this major rational element assumption which is called transitivity which means if A is better than B and B is better than C, A has to be better than C. These are straight forward as I said, expected utility theory of fundamental assumptions of math. Of course finally we can also should be able to say that decision maker should not be affected whether we first present the decision maker alternative A And then C, and then B or vice-versa, because there should be invariance in terms of evaluation of these alternatives. And in video question for you. Imagine I give you two choices. A choice one says you have alternative A that says here you have $1 million put on this table, and you can pick that up and the other alternative is you have 10% chance of getting $2,500,000, 89% chance of getting one million and 1% chance of getting nothing. Which one would you choose, A or B? Please write your answer and then go to the next question. Next question gives you again two alternatives, and wants you to make a choice. The alternative A says you have 11% chance of getting $1 million, and 89% chance of getting zero. And alternative B says you have a 10% chance of getting $2.5 million and a 90% chance of getting zero. The question is, which one would you choose? And please write your answer on that question, as well. Now this creates what we call the paradox of rationality. Which method did you use to make these decisions? I'm thinking not about which one you choose, but how you make that decision. For decision one, most people choose alternative A. They say, give me my million, I'm fine. When you look at decision two, most people choose alternative B. So, what is the method that that alternative B and A are using? So what is the paradox? The paradox is that we use different methods of decision making in each case. In decision one, we actually choose of the safest alternative even though if you apply expected decision to your methods. In other words, you multiply the probability of an event with the amount you're going to get, everyone should actually select alternative B, but we don't. We want the sure thing. When we are faced on the other hand with decision two, where we have, again, two alternatives, we use the expected calculation method. We take the probabilities and multiply it with the amount we will gain and then compare these two results. So why do we choose in one case, one method, and choose another method for the second case? This is the paradox of rationality, because if we are rational, we should be using the same method in both cases. So the models based on bounded rationality, people said well, the reason we make these kinds of mistakes is because we are not 100% rational. And they explained it by calling satisfies. They said we don't search for all alternatives when we are buying a car. We don't look at all the cars in the neighborhood or all the dealers. We go to a couple of dealers and then we pick one and then they say, we're satisfied with that decision. That's what I call satisficing. And that makes us to be bounded to rational, not 100% rational. Some people argue that the reason we are bounded in terms of our rationality is because we have limited willpower. People give more weight to present concerns rather than future concerns or needs. We save less money for our retirement, but we're willing to spend the money for, let's say, a big dinner tonight. That is about our willpower. And the other argument is we have bounded self interest. People are interested about not only their outcomes, but other people's outcomes. That is why there is so much competition in organizations about the salaries, about the increases, and we actually do not sometimes make rational decisions when we faced with these issues. So these were the arguments presented for why we are not 100% rational in our decision making. But there is more to managerial cognition than simple bounded rationality. In our next video we will focus on this topic in more detail.