3, I fit separate models for rounds with good recommenda- tions 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 agree- ing 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 cus- tomization and non-customization are effectively parallel for both types of recommendations, it does not appear that the difficulty of the decision moderates customization bias, al- though it does seem that when receiving poor recommenda- tions, 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.