What support is in place to assist those people that do not conform to normative theories? The prescriptive approach introduces ways to help people make better decisions, such as ‘decision analysis’. Decision analysis uses several techniques, such as decision trees, to assist in the destructuring of complex decisions into more manageable components, draw out values and beliefs for the elements and apply normative principles to their reinstatement.
One of the most common theories in the field of is the . According to this theory, people usually make their decisions by weighing the severity and of the possible outcomes of different alternatives. The integration of this information is made through some type of , based calculus ( activity) which enables us to make a decision. In this theory, psychological processes and the decision maker’s emotional state were ignored and not taken into account as inputs to the based calculus. In ‘Risk as Feelings’, Loewenstein, Weber and Hsee argue that these processes of decision making include: ‘anticipatory emotions, which are immediate visceral reactions (fear, anxiety, dread) to risk and uncertainties’ and ‘anticipated emotions, which are typically not experienced in the immediate present but are expected to be experienced in the future’ (disappointment or regret). Research shows that happy decision-makers are reluctant to gamble. The fact that a person is happy would make him or her decide against gambling, since he or she would not want to undermine his or her happy feeling. This can be looked upon as ‘mood maintenance’. According to the information hypothesis, feelings during the decision process affect people's choices, in cases where feelings are experienced as reactions to the imminent decision. Mellers and McGraw (2001) proposed that anticipated pleasure is an emotion that is formed during the decision making process and is taken into account as an additional information source. They argued that the decision maker guess’s how they will feel when they are right or wrong as a result of choosing one of the alternatives. These estimated feelings are averaged and compared between the different alternatives. It seems that this theory is the same as the but both can result in different choices. In a study from 2001, Isen suggests that tasks which are meaningful, interesting, or important to the decision maker; and if he or she is in a good mood, the decision making process will be more efficient and thorough. People will usually integrate material for decision making and be less confused by a large set of variables, if the conditions are of positive effect. This allows the decision makers to work faster and they will either finish the task at hand quicker, or will turn attention to other important tasks.
Risk is an unavoidable fact of life where it comes to decision making; risky decisions based on uncertainty of the outcome can be metaphorically referred to as a ‘gamble’. The most common applied normative model of risky choice is called ‘subjective expected utility theory’; this is an extension by Savage (1954) of the EU theory by Von Neumann and Morgenstern (1944). EU theory, as previously mentioned, was applied to games of chance with known probabilities, and SEU theory elaborated on this by allowing for ‘subjective probabilities’ also. This generalisation of the theory allowed it to be applied to decision scenarios where no objective mathematical probabilities are available and where judgements may be no more than estimates of likelihoods. So let us now look at how SEU can benefit decision making, based on normative theory and the prescriptive application of decision analysis. The classic analytic framework of numerical probabilities assigned to different events and symbolised by a ‘decision tree’, was created by von Winterfeldt and Edwards in 1986. It is a means of representing all aspects of a decision, the best alternative is then chosen by combining probabilities and utilities which correspond to the possible outcomes associated with each possible alternative. The decision tree can help people to clarify the relevant events and structure of a decision while the computations based on their stated values will follow normative theory. Therefore I would comment that there is no normative technique for extracting the ‘correct structure’ of decisions from individuals, decision trees can act as facilitators of thought, and not representatives of complex decisions. Following on from this criticism, modern research has moved on from this and decision trees are now used as tools to aid thinking, not as resolutions.
The theory of requisite decision modelling (Phillips, 1984) states that models of decision making need only be sufficient in structure and content to resolve the issues at hand. The aim of this model is to capture only essential elements of a decision process for the purpose of the decision to be made; an iterative procedure is then followed involving the construction of: model, analysis, model refinement and re-analysis until the model is confirmed as requisite. This procedure assists in developing a shared understanding and fosters commitment to progression through social purposes. Creating representations of decisions and values cannot be achieved by mechanical computations; they involve deep thought. In my opinion the best advantage of design analysis is perhaps the ability for decision makers to open up all the assets of a decision.
Conforming to SEU is equivalent to adhering to certain axioms (comparability, transitivity, dominance, independence and invariance). Human decision making has been shown to violate these axioms, meaning that decision making is not adequately portrayed by SEU. In support of this criticism of SEU ‘preference reversals’ also illustrates failure in predicting aspects of human decision making, in that the evaluability and prominence of attributes, and whether a task involves choosing or rejecting, have been shown to influence peoples choices (effects not predicted by SEU). Prospect Theory (Kahneman and Tversky (1979)) is a descriptive model which clarifies many of the phenomena that cannot be accounted for by SEU. It does not define ideal choices, but accounts for a huge range of observed anomalies in choice both in lab and field data representing real-life decisions.
And so in conclusion I shall say this: normative theorists appreciated from an early point in history that people do not make decisions as they should, however psychologists and economists think very differently about behavioural research on decision making. To psychologists it is clear that people cannot possibly represent all the relevant information that normative models need for judgement and decision, in the words of Bernstein: ‘Who could design a brain that could perform the way this model mandates? Every single one of us would have to know and understand everything completely and at once’ (Daniel Kahneman quoted by Bernstein, 1996). Psychology has however since the 1950’s made huge progress in establishing that human decision making cannot be characterised in the idealized mathematical/economic way assumed. Modern descriptive theories are now emerging to tackle the discrepancies in normative theories, and even though some normative theories may seem rejectable, such restricted rationality does not imply irrationality. The issues between the different approaches to the evaluation of human judgement and decision making are intense and will not be solved overnight; all that can remain to be done is further robust psychological studies to stand against normative research. People perform so efficiently using non-normative strategies with such limited information at their disposal, so future research needs to focus on how this is possible and how we might improve our decision making ability.
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References
Emotions in Decision Making. (2008, April 30). In Wikipedia, The Free Encyclopedia. Retrieved 10:51, July 17, 2008, from
Mackintosh, B. and Yiend, J. ‘Cognition and Emotion’, in Braisby, N. and Gellatly, A. Cognitive Psychology, The Open University, Milton Keynes.
Ayton, P. ‘Judgement and decision making’, in Braisby, N. and Gellatly, A. Cognitive Psychology, The Open University, Milton Keynes.
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