Introduction

The theory of bounded rationality is one that been a cause for discussion in economist circles around the world for many years. The theory, originally coined by Hebert Simon surrounded the limitation of humans to process the amount of information available to make a logical, economic decision and the consumer would therefore, settle for something that satisfyingly sufficient, or ‘satisfice’(Simon 1955). Furthermore, the theory expanded over time to also include mans use of heuristics to simplify cognitive effort in the decision making process (Simon and Newell 1972) and it was argued that ‘logical and economic’ decisions were never reached by humans due to emotions and judgement controlling the decision making process and causing a range of biases and errors (Tversky and Kahneman 1986). The theory identified that humans would use these heuristics, such as rule of thumb or an estimation, to find something that is satisfactory to their needs rather than making the ideal economic decision. I agree with the notion that the world is ‘too complex for people to solve problems by employing strict logical rules and comprehensive thought processes’ (Simon 1955) and am also of the belief that humans will rely on heuristics to make the cognitive process more straightforward.

Rational Consumer Choice

Rational consumer choice theory has been around for many years and stems from the ideal that consumers act in a ‘rational’ fashion when making economic decisions. Not as complex as strict rationality, rational consumer choice considers some of the objections to the aforementioned theory and alters them accordingly to a more evidence driven and therefore viable, theory. One such objection is through observing most transactions introspectively, the conclusion can be drawn that most economic agents are not maximizers and that even if maximization were possible, it would be difficult to obtain in practice (as they cannot compute all possible information relating to the purchase). Rationality in reference to the rational consumer choice theory is not defined the same as the colloquial definition of ‘sanity’, rather is termed on a much narrower spectrum; a rational act is one whereby the individual acts to benefit their personal advantage or utility by weighing up potential costs and the associated utility.

However, rational choice theory has had its fair share of criticisms. One such criticism is that rational choice theory operates in a static environment. That is, decisions are made with only one consideration taking place; which option will maximise utility? In reality, this notion is considered to be untrue. For example, in the consideration of a consumer transaction, the marketplace is operating in a constant state of change and uncertainty as new competition enters and information is available to the purchaser.

A second criticism of the rational consumer model is that the analysis of human behaviour occurs in the form of mathematical models and in the simplification of real-world contexts (Snidal 2002). The first issue surrounding this criticism is through the manipulation of results obtained through mathematical models enabling them to employ ‘tricks’ to control the data to prove support their argument (Stein 1999). Along similar lines, also considered is the easiness that predictions made by rational choice theory are often of little valued and are considered vague to the questions they are actually answering. It is however, considered easier to note that the manipulation of of mathematical models could be easier to identify than that of verbal arguments and discussions (Snidal 2002).

Another criticism surrounds the notion of rationality. Critics contend that people are often irrational in their decision making and rarely have a clear set of preferred goals and will not always follow a ‘pursuit of maximum utility or benefit’ (McCubbins 1996). In everyday society, it can be seen that people make decisions that are not the best for them examples including the consumption of alcohol or cigarettes of which are degenerative to their health. Furthermore, it can be seen that individuals rarely make decisions with all the facts and accurate knowledge that of the resulting utility gained from such decisions. However, this is where the benefits of bounded rationality can be discovered, of which are discussed below.

Bounded Rationality

Like rational choice theory, bounded rationality stems from the ideal that reason underlies every individuals decision making process. However, unlike the previously described rational choice theory, bounded rationality tends to observe that consumers will opt for the satisficing purchase rather than the utility maximizer. This is due to the lack of information available to the individual at the time of the decisions. There is no unified theory of bounded rationality (Aumann 1997), rather, a collection of ideals shared by a number of learned economists. Bounded rationality acts as a bridge between rational consumer choice and abstract choice, considering that whilst consumers do search for a ‘utility maximising’ option, they are often willing to settle for something in the middle, the aforementioned term of satisficing; sufficiently satisfying (Simon 1955). Through the individuals adoption of the satisficing option, they are able to maintain adequate utility whilst still obtaining the item wanted, however, have still not reached their maximum possible utility available had they made a completely rational decision.

With the consumer arriving at a point of satisfice, it asks the question of how the individual managed to achieve this notion whilst still maintaining a rational decision making process. This has been described through Simon and Newell’s discussion of the individuals use of heuristics in the decision making process. It was discussed previously that humans don’t have the cognitive ability to process all data present in the decision making process (Simon 1955). Rather than attempt to complete this action, it was recognised that humans develop heuristics to help them with the process (Simon and Newell 1972), including the use of rule of thumb measurements and estimations. These have been developed over time to help reduce cognitive stress during the decision making process. These heuristics are aimed at achieving the satisficing result and not the utility maximizer that could otherwise been achieved had we had the ability to process the extent of the information available. Rather than focussing on the somewhat unrealistic picture of rational human decision making, bounded rationality has the ability to achieve adequate data whilst maintaining a more realistic and probable scenario.

In a differing aspect to the previously mentioned point, bounded rationality, whilst arriving at a point of satisficing point, does not maximise utility potential. This can be found through the examination of Loewenstein and Lerner’s discussion surrounding the role of emotions and personal judgement in the decision making process. Until recently, the role of emotion had rarely been included as a consideration when determining the processes of the economic decision maker. However, recent research has shown that incidental affect, that is, affect unrelated to the decision at hand, can impact on the judgement and decision made by the individual (Loewenstein et al 2003). Contemporary decision making research is now considering the role of emotions in the decision making process and whether emotion can act to further improve or degrade the decision making process. Evidence shows that emotions do serve as an essential role in the decision making process, however, they are also a potential source of biased judgement (Averill 1983).

RATIONAL CHOICE MODEL PREDICTIONS ARE NOT BORNE OUT IN THE EVIDENCE

The concept of bounded rationality does not aim to cover the whole area of cognitive psychology, rather, focus its emphasis upon the decision making process. Below I will examine illustrative examples of how particular scenarios can have the same answer and probability, however, through changing how the question is framed to the individual can end up with a differing response. The first example was from a study of preferences between particular medical treatments (McNeil et al. 1982). For the example listed, respondents were given statistical data about the outcomes of two treatments. Half of the party were given the data phrased towards the mortality rate, whilst others were given data phrased towards the survival rate. The below is phrased as it was to the respondents.

Problem 1 (Survival Frame)
Surgery: Of 100 people having surgery, 90 live through the post operative period, 68 are alive at the end of the first year and 34 are alive at the end of five years.
Radiation Therapy: Of 100 people having radiation therapy, all live through the treatment, 77 are alive at the end of one year and 22 are alive at the end of five years.

Problem 2 (Mortality Frame)
Surgery:Surgery: Of 100 people having surgery 10 die during surgery or the post-operative period, 32 die by the end of the first year and 66 die by the end of five years.
Radiation Therapy: Of 100 people having radiation therapy, none die during treatment, 23 die by the end of one year and 78 die by the end of five years.

The results of the tests show that the particular framing of the words (between mortality or survival frameworks) accounted for a 26% increase in the popularity of a surgery, with figures rising from 18% (survival) to 44% (mortality). This empirical data depicts that rational choice theory does not apply, as if it did both responses would be the same as they are stating identical statistical ratings. If rational choice theory were to apply, simply changing the way that a question is phrased should not alter the response. This makes a further case for bounded rationality which helps to cement that both heuristics and emotions will be employed by individuals in the decision making process. In the aforementioned data, it is evident that through considering that people are more likely to alter their decisions when considering the emotive notion of death rather than survival.

Another example considers the difference in decisions when monetary value is considered, both of which involve risky options. This test was outlined in a Tversky and Kahneman article published in 1981. The test revealed, without going into distinctive detail of the questions asked, that individuals would choose a risk averse option when considering gains, and choices involving losses are often more risk seeking. This article also outlined evidence that supported the notion of bounded rationality, in that individuals would use heuristics to determine which option they selected rather than processing all the logical data held in front of them; that is they would use rule of thumb of estimate which option they believed calculated the higher return, rather than using relative cognitive processes to develop a logical and mathematically correct formulation. This indicates that they are indifferent about receiving a satisficing result or the utility maximizing result as it is too difficult a figure to calculate.

CONCLUSION

The theory of bounded rationality is one that I believe, is more relevant and indeed statistically accurate, in todays society. It doesn’t have the same issues experienced by consumer choice theory in that the data is expected to be collected at a static point and no other considerations will be given; that is, that individuals are completely economically rational beings. This point is often disproved by statistical data as detailed above and the data rather, supports the theory of bounded rationality to the extent that individuals will employ the use of emotions and judgements when making a decision. Along similar lines, it is depicted that due to the lack of cognitive ability to process every possible response in the decision making process, individuals will employ the use of heuristics to simplify the process and come to an adequately satisficing decision.

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