fit separate models for rounds with good recommendations
and poor recommendations using winner agreement as
the dependent variable. Figure 3 visualizes these models.
When receiving good recommendations, the difficulty of the
decision had almost no influence on the probability of agreeing
with the DSS in either condition. When receiving a poor
recommendation, subjects were slightly more likely to agree
with the DSS when the decision was more difficult, and this
was true in both conditions. Because the estimates for customization
and non-customization are effectively parallel for
both types of recommendations, it does not appear that the
difficulty of the decision moderates customization bias, although
it does seem that when receiving poor recommendations,
users of any type of DSS will be more likely to trust it
when the decision is difficult than when they have an easier
decision.