There are a few layers to this question, from the quick-and-easy answer to deeper statistical issues. I doubt you want to hear the deep issues, but I'll post a few comments in case others are tuning in.
Easy answer: just take the average across the respondents who are males. That's the segment summary utility for males.
More complete answers...
1. The "scale factor" is a thorny issue involving CBC data and can make it hard to compare one respondent or group of respondents to another. If respondents have high error, their utilities are uniformly squished somewhat closer toward zero. If respondents have low error, their utilities are uniformly expanded larger. So, if you try to compare a utility from one respondent group to another respondent group (and if their response error differs substantially) then what you think you see as a utility difference may just owe to the scale factor expansion/contraction.
So, to help reduce the possibility of running into these troubles, we'd recommend you compare respondents using the normalized utilities (the zero-centered diffs) as can be exported from our SMRT simulator package (under Analysis + Run Manager + Export). The normalized utilities put all respondents on the same scale (or at least the scale that is assumed if we make sure that the sum of the differences between best and worst levels across respondents are constant).
2. Some academics would prefer that if you plan to compare respondent groups that you include those respondent groups as covariates in the HB run. This is an advanced option.
