Decision Making, Risk, and Ambiguity
Some people are averse to risk, while others are aderse to ambiguity. Researchers at Duke University have now demonstrated that different brain mechanisms are at work in these two tendencies, as reported in a paper published in the March 2, 2006 edition of Neuron. There’s a nice summary of the work in a Duke press release.
The researchers gave subjects a set of gamble-type choices which could be considered certain, risky, or ambiguous. Risky gambles had longer odds, while ambiguous ones didn’t disclose the odds. They measured the brain activity of the subjects while presented with these choices and also determined whether subjects preferred risk or ambiguity by the choices they made. They found that subjects who preferred risk had more activity in their posterior parietal cortex while those who preferred ambiguity lit up part of their lateral prefrontal cortex.
Scott Huettel, Ph.D., the lead author, thinks the work will have a bearing on neuroeconomics:
The results provide important data for the emerging field of “neuroeconomics” … By understanding these mechanisms, we may be able to make better predictions about how people will behave or interact in different circumstances.
Jill Stowe, Ph.D., a decision scientist with Duke’s Fuqua School of Business and study co-author, also comments,
The results are exciting because they suggest that people evaluate risky and ambiguous options in different ways. That element is not currently embedded in current economic models of decision making under risk or ambiguity, so this may very well lead to better economic models in the future, as well as hold implications for future economic policy.
Marketers would do well to understand the difference between risk and ambiguity, and how different people make decisions. While we think of impulse buying as, say, a pack of gum in a supermarket checkout line, many other kinds of buying decision can be impulsive. Although it would be nice to know which customers are risk-averse and which don’t like ambiguity, the best approach may be to reduce BOTH variables to maximize sales – particularly where the time to make a buying decision is brief, and some degree of impulsivity is involved.