the “certainty that it happens.” In agreement with the principle diminishing sensitivity,
increases close to the extreme points of the scale of probabilities have larger effects than
increases in the intermediate points of the scale. The sensitivity to alterations in the
probabilities decreases as the probabilities stand back of the reference point, what
suggests that function is an inverse-S-shape. The “step function” shows smaller
sensitivity to alterations of the probabilities than the quasi-linear function, except close to
the extreme points 0 and 1. The concept of diminishing sensitivity supplies an incomplete
explanation of the representation of probability weighting function. Even if this concept
permits to explain the curvature of the probability function, it does not says anything on
overweighting and underweighting relatively to the non-transformed probabilities (45°
line). The probability weighting function can be completely below or completely above
the identity line or it can cut the identity line in any point. The higher is the function the
greater is attractiveness of the game. Gonzalez and Wu refers this concept can be
applied to the assessment of a game by two individuals in that one attributes a larger
consideration than other for finding the game more attractive, as to interpersonal
comparisons in that an individual attributes a larger consideration to a choice domain
than the other.
A discrete sequential stochastic programming model is developed to study the decision
making process in the Alentejo dryland region. This model that describes the risk
behavior of the farmers in the Alentejo dryland region has five states of nature, developed
in agreement with the expected value of crop production. The objective function
describes the risk behavior of the farmers in agreement with the Cumulative Prospect
Theory. This model is constituted by a set of functions (the value function and