Pia, you have several questions which I'll address in turn.
Utilities are calculated using a hierarchical Bayesian (HB) version of the conditional multinomial logit model. You can google conditional multinomial logit to find more about it (not a bad place to start if you read the conditional logit section: https://en.wikipedia.org/wiki/Discrete_choice
The reason you can see the same importance for different utility ranges is because you're looking at the utility range of the average utilities but importances are calculated at the respondent level and then averaged. let me give you an example. Say we have a study with several attributes, among them color (orange or blue) and price. It turns out that both color and price have an importance of 30%. As you might imagine, everyone wants lower prices, and the range of the average importances for the highest and lowest prices is 17 utility points. But when you look at the average utilities for color, the range is 0 because orange and blue have the same average utility, 0.00. But respondents are heterogeneous with respect to color. Exactly half of them LOVE orange (utility +17) and hate blue (utility -17). The other half LOVE blue ( +17 utility) and hate orange (-17 utility). So the average utility cancels out all this heterogeneity and shows two average utilities of 0.00. The importances, on the other hand, were calculated at the respondent level, and they're as large at the respondent level as the importances for price, namely 30%. Something like this mismatch in heterogeneity is what's causing what you're seeing. this is common, because I find myself explaining this at least a couple of times a month, and I'm one of several folks here at Sawtooth Software who ends up explaining this to folks.