Every day we face numerous decisions. Many decisions involve an element of risk, where it is essential to compare possible benefits with potential costs to help us choose the best course of action. In this experiment, I intend to investigate risk taking behaviour. The first theory which was put forward to explain decision making was utility theory. It puts forward the idea that when people make decisions, they think about the probability of a given outcome and the utility of that outcome. Expected utility is calculated using the following equation:-
Expected Utility = (probability of a given outcome) x (utility of that outcome) Tversky and Kahneman (1987) carried out the Asian Disease Study to investigate decision making. They gave participants a scenario, in which a rare disease was to kill 600 people. Participants were given two programmes to combat the disease. Programme A would save 200 lives, while programme B had a third probability that all 600 lives would be saved and a two third probability that no one would be saved. The expected utility of Programme A is 1 x 200 = 200 people saved and the expected utility of Programme B is 0.33 x 600 = 200.
Therefore the two programmes are equally useful. In the investigation, 72% of participants chose programme A, suggesting that their decision was not made on a purely rational basis and suggests that participants are more likely to choose a safe option rather than taking a risk. This was further supported when Tversky and Kahneman gave other participants the same problem presented differently. In Programme A, 400 people would die, in Programme B there was a third probability that nobody would die and a two third probability that 600 people would die. Even though this is the same problem, only 22% of the participants chose programme A.
This study demonstrates the framing effect. This means that a persons decision is influenced by the phrasing or frame in which the situation is presented. In the first account, Programme A is framed in a positive way, emphasising the number of lives that saved. In the second version, the emphasis is on the number of deaths. It seems when faced with a loss, people opt for the risky option. This experiment also demonstrates loss Aversion, in which individuals are more susceptible to losses, rather than gains. This explains the decrease in the number of participants who chose Programme A in the second condition. A study which supports this is another study by Tversky and Kanneman. Participants were given the following two choices and had to choose the choice they favoured:
Logically, both choices are identical (i.e. utilities are the same). There is no correct or incorrect answer as the option chosen by the participant reflects their willingness to take a risk. One would expect, that people opting for the first option in choice one, would also opt for the first one in choice two. However, the experiment found that most participants, who chose the first option in choice one, chose the second option in choice two. Therefore, they contradicted themselves by preferring the sure thing in choice one and the risk in choice two. Tversky and Kahneman explain this in terms of framing the question.
In this investigation, participants were influenced by the use of the negative word ‘loss’ in choice 2 against the positive word ‘gain’ in choice one. When they were offered a sure gain, they seemed to be unfavourable to taking a risk and prefer to hold onto what they have. When faced with a loss, participants tend to be more willing to take a risk, presumably with the intention of trying to avoid or reduce the loss. Primarily, this experiment shows that the same people differ in their risk taking strategy, depending on the language in which a risk is expressed.
Other factors have been looked at in relation to the framing effect. Farthing (2005) surveyed 48 young men and 52 women on their attitudes towards risky scenarios. He found out that men thought that women would be impressed by pointless gambles, but women in fact preferred cautious men.