Through the years, the Duncan Anderson Design Lecture Series has invited top professionals to share their knowledge and experience with design students at CSULB. This coming year marks the expansion of that series to a bi-monthly event. Thanks to Cecelia Anderson-Malcolm and the Duncan Anderson Endowment, CSULB now has an ongoing design lecture series to rival those at private design schools. The CSULB Industrial Design Program is working closely with IDSA-LA, and its student chapters, to schedule an exciting line-up of speakers. Please let your chapter officers know of professionals you want to meet and hear at future events.
In this lecture, I introduced why designers have to adopt behavioral science to understand customer experience deeply. For instance, prospect theory neatly elucidates why once people have a single extraordinary experience, they can no longer revert to previously satisfactory mundane experiences. It is because the extraordinary experience can become a reference point, while the mundane experiences transform into sources of negative affect. Since loss looms larger than gain, people avoid mundane experiences.
This paper presents a critique of expected utility theory as a descriptive model of decision making under risk, and develops an alternative model, called prospect theory. Choices among risky prospects exhibit several pervasive effects that are inconsistent with the basic tenets of utility theory. In particular, people underweight outcomes that are merely probable in comparison with outcomes that are obtained with certainty. This tendency, called the certainty effect, contributes to risk aversion in choices involving sure gains and to risk seeking in choices involving sure losses. In addition, people generally discard components that are shared by all prospects under consideration. This tendency, called the isolation effect, leads to inconsistent preferences when the same choice is presented in different forms. An alternative theory of choice is developed, in which value is assigned to gains and losses rather than to final assets and in which probabilities are replaced by decision weights. The value function is normally concave for gains, commonly convex for losses, and is generally steeper for losses than for gains. Decision weights are generally lower than the corresponding probabilities, except in the range of low probabilities. Overweighting of low probabilities may contribute to the attractiveness of both insurance and gambling.
